APP for Monitoring Skin Spots,
2019.
WWW Link.
Code, Skin Spots.
1906
he app allows you to:
take and organise photos of spots;
compare two images of a spot side by side;
email those images to someone (eg. doctor).
That's all!
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Dermoscopic images; Pattern classification; Markov random field
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Segmentation; Evaluation; NPRI; Melanoma
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IJIST(20), No. 4, December 2010, pp. 316-322.
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Earlier: A3, A1, A2:
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See also Discriminative cue integration for medical image annotation.
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Melanoma; Dermoscopy; Pigmented skin lesion classification; Adaptive
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Skin detection; Skin classification; Color spaces and skin detection;
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ICIAR12(II: 268-277).
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Pereyra, M.,
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Segmentation of Skin Lesions in 2-D and 3-D Ultrasound Images Using a
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MVA(23), No. 5, September 2012, pp. 1029-1045.
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Shepherd, T.,
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Interactive Lesion Segmentation with Shape Priors From Offline and
Online Learning,
MedImg(31), No. 9, September 2012, pp. 1698-1712.
IEEE DOI
1209
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Ma, L.[Li],
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Analysis of the contour structural irregularity of skin lesions using
wavelet decomposition,
PR(46), No. 1, January 2013, pp. 98-106.
Elsevier DOI
1209
Melanoma detection; Structural irregularity of contours; Wavelet
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Abbas, Q.[Qaisar],
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Dermoscopy; Pattern classification; Steerable pyramid transform; Human
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Lu, C.[Cheng],
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PR(46), No. 2, February 2013, pp. 509-518.
Elsevier DOI
1210
Histopathological image analysis; Object detection; Image analysis;
Melanocytes
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Lu, C.[Cheng],
Mandal, M.[Mrinal],
Automated analysis and diagnosis of skin melanoma on whole slide
histopathological images,
PR(48), No. 8, 2015, pp. 2738-2750.
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1505
Histopathological image analysis
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Hani, A.F.M.,
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Arshad, L.,
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Jamil, A.,
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Wound model reconstruction from three-dimensional skin surface imaging
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IET-IPR(6), No. 5, 2012, pp. 521-533.
DOI Link
1210
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d'Alessandro, B.,
Dhawan, A.P.,
3-D Volume Reconstruction of Skin Lesions for Melanin and Blood Volume
Estimation and Lesion Severity Analysis,
MedImg(31), No. 11, November 2012, pp. 2083-2092.
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Xie, F.Y.[Feng-Ying],
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Automatic segmentation of dermoscopy images using self-generating
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Dermoscopy images; Self-generating neural network; Image clustering;
Automatic segmentation; Generic algorithms
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Deng, Z.L.[Zi-Lin],
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ICIP17(1732-1736)
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1803
Convolutional neural networks, Feature extraction,
Image analysis, Image segmentation, Lesions, Robustness, Skin,
Lesion segmentation
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Lu, J.,
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Automatic Segmentation of Scaling in 2-D Psoriasis Skin Images,
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Vionnet, L.,
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24-MHz Scanner for Optoacoustic Imaging of Skin and Burn,
MedImg(33), No. 2, February 2014, pp. 535-545.
IEEE DOI
1403
biomedical optical imaging
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Scharcanski, J.[Jacob],
Celebi, M.E.[M. Emre], (Eds.),
Computer Vision Techniques for the Diagnosis of Skin Cancer,
Saez, A.,
Serrano, C.,
Acha, B.,
Model-Based Classification Methods of Global Patterns in Dermoscopic
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MedImg(33), No. 5, May 2014, pp. 1137-1147.
IEEE DOI
1405
Classification
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Serna, A.[Andrés],
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Segmentation of elongated objects using attribute profiles and area
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Elsevier DOI
1408
Mathematical morphology
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Lu, Y.,
Xie, F.,
Wu, Y.,
Jiang, Z.,
Meng, R.,
No Reference Uneven Illumination Assessment for Dermoscopy Images,
SPLetters(22), No. 5, May 2015, pp. 534-538.
IEEE DOI
1411
Algorithm design and analysis
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Schwarz, M.,
Omar, M.,
Buehler, A.,
Aguirre, J.,
Ntziachristos, V.,
Implications of Ultrasound Frequency in Optoacoustic Mesoscopy of the
Skin,
MedImg(34), No. 2, February 2015, pp. 672-677.
IEEE DOI
1502
Dermis
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Korotkov, K.,
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Garcia, R.,
A New Total Body Scanning System for Automatic Change Detection in
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1502
biomedical optical imaging
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Jiji, G.W.[Gnanasigamony Wiselin],
Raj, P.S.J.D.[Peter Savariraj Johnson Durai],
Content-based image retrieval in dermatology using intelligent
technique,
IET-IPR(9), No. 4, 2015, pp. 306-317.
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content-based retrieval
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Application to dermatological image processing,
SIViP(9), No. 5, July 2015, pp. 1081-1091.
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Epidermis segmentation in skin histopathological images based on
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Lu, C.[Cheng],
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Automated segmentation of the epidermis area in skin whole slide
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DOI Link
1509
biomedical optical imaging
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Kruk, M.[Michal],
Swiderski, B.[Bartosz],
Osowski, S.[Stanislaw],
Kurek, J.[Jaroslaw],
Slowinska, M.[Monika],
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Melanoma recognition using extended set of descriptors and
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JIVP(2015), No. 1, 2015, pp. 43.
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Sáez, A.,
Sánchez-Monedero, J.,
Gutiérrez, P.A.,
Hervás-Martínez, C.,
Machine Learning Methods for Binary and Multiclass Classification of
Melanoma Thickness From Dermoscopic Images,
MedImg(35), No. 4, April 2016, pp. 1036-1045.
IEEE DOI
1604
Color
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Kasmi, R.,
Mokrani, K.,
Classification of malignant melanoma and benign skin lesions:
implementation of automatic ABCD rule,
IET-IPR(10), No. 6, 2016, pp. 448-455.
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biomedical optical imaging
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Bae, J.S.[Ji-Sang],
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Lee, J.Y.[Jae-Young],
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Skin Condition Estimation Using Mobile Handheld Camera,
ETRI(38), No. 4, August 2016, pp. 776-786.
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Noroozi, N.[Navid],
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Computer assisted diagnosis of basal cell carcinoma using Z-transform
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JVCIR(40, Part A), No. 1, 2016, pp. 128-148.
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1609
Skin cancer
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Barata, C.[Catarina],
Celebi, M.E.[M. Emre],
Marques, J.S.[Jorge S.],
Rozeira, J.[Jorge],
Clinically inspired analysis of dermoscopy images using a generative
model,
CVIU(151), No. 1, 2016, pp. 124-137.
Elsevier DOI
1610
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Earlier: A1, A3, A2, Only:
Improving dermoscopy image analysis using color constancy,
ICIP14(3527-3531)
IEEE DOI
1502
Melanoma.
Design automation
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Ghanta, S.,
Jordan, M.I.,
Kose, K.,
Brooks, D.H.,
Rajadhyaksha, M.,
Dy, J.G.,
A Marked Poisson Process Driven Latent Shape Model for 3D
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IP(26), No. 1, January 2017, pp. 172-184.
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Markov processes
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Zortea, M.[Maciel],
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A simple weighted thresholding method for the segmentation of
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1701
Segmentation
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Ferri, M.[Massimo],
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A Feasibility Study for a Persistent Homology-Based k-Nearest Neighbor
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JMIV(57), No. 3, March 2017, pp. 324-339.
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1702
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Xie, F.,
Fan, H.,
Li, Y.,
Jiang, Z.,
Meng, R.,
Bovik, A.,
Melanoma Classification on Dermoscopy Images Using a Neural Network
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MedImg(36), No. 3, March 2017, pp. 849-858.
IEEE DOI
1703
Cancer
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Yu, L.,
Chen, H.,
Dou, Q.,
Qin, J.,
Heng, P.A.,
Automated Melanoma Recognition in Dermoscopy Images via Very Deep
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MedImg(36), No. 4, April 2017, pp. 994-1004.
IEEE DOI
1704
Biomedical imaging
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Roy, A.[Anandarup],
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JCLMM: A finite mixture model for clustering of circular-linear data
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PR(66), No. 1, 2017, pp. 160-173.
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1802
Mixture model
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Barata, C.[Catarina],
Celebi, M.E.[M. Emre],
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Development of a clinically oriented system for melanoma diagnosis,
PR(69), No. 1, 2017, pp. 270-285.
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1706
Melanoma, diagnosis
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Ohki, K.[Keiichi],
Celebi, M.E.[M. Emre],
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Schwarz, M.,
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Omar, M.,
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Ovsepian, S.V.,
Aguirre, J.,
Ntziachristos, V.,
Optoacoustic Dermoscopy of the Human Skin: Tuning Excitation Energy
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MedImg(36), No. 6, June 2017, pp. 1287-1296.
IEEE DOI
1706
Attenuation, Bandwidth, Detectors, Frequency response, Phantoms, Skin,
Angiographic imaging, evaluation and performance,
image quality assessment, optimization,
optoacoustic/photo-acoustic imaging, skin, tissue modelling,
vessels, visualization
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Bae, J.S.[Ji-Sang],
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Robust skin-roughness estimation based on co-occurrence matrix,
JVCIR(46), No. 1, 2017, pp. 13-22.
Elsevier DOI
1706
Skin, roughness
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Sadri, A.R.[Amir Reza],
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Zekri, M.[Maryam],
Celebi, M.E.[Mehmet Emre],
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WN-based approach to melanoma diagnosis from dermoscopy images,
IET-IPR(11), No. 7, July 2017, pp. 475-482.
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Yuan, Y.,
Chao, M.,
Lo, Y.C.,
Automatic Skin Lesion Segmentation Using Deep Fully Convolutional
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MedImg(36), No. 9, September 2017, pp. 1876-1886.
IEEE DOI
1709
cancer, endoscopes, neural nets, skin, tumours, Jaccard distance,
automatic skin lesion segmentation, melanoma detection challenge,
Malignant tumors,
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Shrivastava, S.[Shubhangi],
Raj, A.N.J.[Alex Noel Joseph],
A vision-based non-contact area and volume estimation of irregular
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IJCVR(7), No. 5, 2017, pp. 489-501.
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1709
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Pezeshk, A.,
Petrick, N.,
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Seamless Lesion Insertion for Data Augmentation in CAD Training,
MedImg(36), No. 4, April 2017, pp. 1005-1015.
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1704
Biomedical imaging
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Adjed, F.[Faouzi],
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Fusion of structural and textural features for melanoma recognition,
IET-CV(12), No. 2, March 2018, pp. 185-195.
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Biomedical imaging, Feature extraction, Training, Skin, Diseases,
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Lesions, Skin, Malignant tumors, Feature extraction, Smart phones,
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Skin, Diseases, Visualization, Training, Hospitals, Feature extraction,
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biomedical ultrasonics, image segmentation,
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Lesions, Skin, Melanoma, Learning systems, Task analysis,
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Imaging, Skin cancer, Surgery, Tumors, Millimeter wave technology,
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Skin cancer, Contrast stretching, Lesion localization,
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2002
Lesions, Skin, Image segmentation, Melanoma, Bidirectional control,
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2002
Skin, Imaging, Image segmentation, surface segmentation
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Cells, Principle component analysis (PCA), Melanoma, Alexnet, VGG-16
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Photoacoustic imaging, OCT, skin, multi-modality fusion, integration of multiscale information
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3D Image mosaicing, Structure-from-Motion (SfM),
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Lesions, Image segmentation, Skin, Task analysis, Feature extraction,
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Skin lesion, Transfer learning, CNN, Internet of things
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2008
Classification, Melanoma, Convolutional neural networks (cnns)
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2008
canny edge detection, color segmentation, Gaussian filter,
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Fitness adaptive deer hunting-based region growing and recurrent
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dermoscopic image, melanoma skin cancer,
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biomedical images, brain tumor detection, CAD of malaria,
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2010
Skin, Optical imaging, Biomedical optical imaging,
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Skin lesion classification, Dermoscopy image analysis,
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Hierarchical deep learning, Explainability, Channel attention,
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2012
Microscopy, segmentation, skin, quantification and estimation, optical imaging
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Wu, H.,
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2012
Lesions, Skin, Image segmentation, Feature extraction, Melanoma,
Task analysis, Shape, Skin lesion segmentation,
deep learning
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Xie, Y.,
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2012
Image segmentation, Lesions, Medical diagnostic imaging, Skin,
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Cai, J.,
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2012
Lesions, Proposals,
Computed tomography, Training, Detectors, Biomedical imaging,
pseudo 3D IoU
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Khan, M.A.[Muhammad Attique],
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Skin cancer, Mask RCNN, Transfer learning, Optimal features, ELM
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Jiji, G.W.[G. Wiselin],
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Melanoma and Nevi Classification using Convolution Neural Networks,
IVCNZ20(1-6)
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2012
Training, Convolution, Neural networks, Focusing, Melanoma, Lesions,
Testing, melanoma, ResNet50, identification, classification
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Sabri, M.A.,
Filali, Y.,
El Khoukhi, H.,
Aarab, A.,
Skin Cancer Diagnosis Using an Improved Ensemble Machine Learning
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ISCV20(1-5)
IEEE DOI
2011
cancer, feature extraction, image classification,
learning (artificial intelligence), medical image processing,
ensemble learning.
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Bakkouri, I.[Ibtissam],
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Kumar, A.,
Hamarneh, G.,
Drew, M.S.,
Illumination-based Transformations Improve Skin Lesion Segmentation
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ISIC20(3132-3141)
IEEE DOI
2008
Skin, Lesions, Image color analysis, Image segmentation, Gray-scale,
Lighting, Semantics
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Bagchi, S.,
Banerjee, A.,
Bathula, D.R.,
Learning A Meta-Ensemble Technique For Skin Lesion Classification And
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ISIC20(3221-3228)
IEEE DOI
2008
Stacking, Training, Skin, Task analysis, Lesions, Image color analysis, Melanoma
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Coppola, D.,
Lee, H.K.,
Guan, C.,
Interpreting mechanisms of prediction for skin cancer diagnosis using
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ISIC20(3162-3171)
IEEE DOI
2008
Task analysis, Lesions, Logic gates, Skin, Machine learning, Melanoma
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Singh, N.,
Lee, K.,
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Angermueller, C.,
Huang, S.,
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Agreement Between Saliency Maps and Human-Labeled Regions of
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ISIC20(3172-3181)
IEEE DOI
2008
Skin, Diseases, Google, Analytical models, Dermatology, Data models, Image segmentation
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Ribeiro, V.,
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Valle, E.,
Less is More: Sample Selection and Label Conditioning Improve Skin
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ISIC20(3182-3191)
IEEE DOI
2008
Image segmentation, Lesions, Training, Machine learning, Skin,
Task analysis, Data models
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Bissoto, A.,
Valle, E.,
Avila, S.,
Debiasing Skin Lesion Datasets and Models? Not So Fast,
ISIC20(3192-3201)
IEEE DOI
2008
Lesions, Correlation, Skin, Task analysis, Training,
Feature extraction, Data models
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Barata, C.,
Santiago, C.,
How Important Is Each Dermoscopy Image?,
ISIC20(3202-3210)
IEEE DOI
2008
Training, Lesions, Skin, Task analysis, Neural networks,
Computer architecture, Image analysis
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Combalia, M.,
Hueto, F.,
Puig, S.,
Malvehy, J.,
Vilaplana, V.,
Uncertainty Estimation in Deep Neural Networks for Dermoscopic Image
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ISIC20(3211-3220)
IEEE DOI
2008
Uncertainty, Lesions, Skin, Neural networks, Monte Carlo methods,
Training, Task analysis
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Pacheco, A.G.C.,
Sastry, C.S.,
Trappenberg, T.,
Oore, S.,
Krohling, R.A.,
On Out-of-Distribution Detection Algorithms with Deep Neural Skin
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ISIC20(3152-3161)
IEEE DOI
2008
Training, Melanoma, Neural networks, Detection algorithms, Dogs, Skin
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Mahajan, K.,
Sharma, M.,
Vig, L.,
Meta-DermDiagnosis: Few-Shot Skin Disease Identification using
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ISIC20(3142-3151)
IEEE DOI
2008
Skin, Diseases, Lesions, Task analysis, Training, Biomedical imaging,
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Andrade, C.[Catarina],
Teixeira, L.F.[Luís F.],
Vasconcelos, M.J.M.[Maria João M.],
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2007
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Bekmirzaev, S.,
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RethNet: Object-by-Object Learning for Detecting Facial Skin Problems,
VRMI19(425-433)
IEEE DOI
2004
computer vision, face recognition, feature extraction,
image segmentation, learning (artificial intelligence),
fine grained object categorization
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Wu, X.,
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ICCV19(10641-10650)
IEEE DOI
2004
Code, Dermatology.
WWW Link. diseases, learning (artificial intelligence),
medical image processing, skin, joint acne image grading, Training
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Adegun, A.[Adekanmi],
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Dogvanich, A.,
Mamaev, N.,
Krylov, A.,
Makhneva, N.,
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Gavrilov, D.A.,
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Peng, J.,
Gao, R.,
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Lin, Z.,
Classification of Non-Tumorous Facial Pigmentation Disorders Using
Improved Smote and Transfer Learning,
ICIP19(220-224)
IEEE DOI
1910
improved SMOTE, facial pigmentation disorders,
biomedical images analysis and classification, transfer learning
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Tu, W.,
Liu, X.,
Hu, W.,
Pan, Z.,
Xu, X.,
Li, B.,
Segmentation of Lesion in Dermoscopy Images Using Dense-Residual
Network with Adversarial Learning,
ICIP19(1430-1434)
IEEE DOI
1910
dermoscopic image, skin lesion, convolutional neural networks,
adversarial learning, Dense-Residual block
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Wang, X.,
Ding, H.,
Jiang, X.,
Dermoscopic Image Segmentation Through the Enhanced High-Level
Parsing and Class Weighted Loss,
ICIP19(245-249)
IEEE DOI
1910
Skin lesion segmentation, fully convolutional neural network,
enhanced high-level parsing, class weighed loss
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Ferreira, B.[Bárbara],
Barata, C.[Catarina],
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What Is the Role of Annotations in the Detection of Dermoscopic
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Springer DOI
1910
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Franco-Ceballos, R.[Ricardo],
Torres-Madronero, M.C.[Maria C.],
Galeano-Zea, J.[July],
Murillo, J.[Javier],
Zarzycki, A.[Artur],
Garzon, J.[Johnson],
Robledo, S.M.[Sara M.],
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1910
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Carcagnì, P.[Pierluigi],
Leo, M.[Marco],
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Distante, C.[Cosimo],
Classification of Skin Lesions by Combining Multilevel Learnings in a
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Springer DOI
1909
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Bonechi, S.[Simone],
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Rosai, R.[Riccardo],
Tognetti, L.[Linda],
Rossi, A.[Alberto],
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Fusion of Visual and Anamnestic Data for the Classification of Skin
Lesions with Deep Learning,
NTIAP19(211-219).
Springer DOI
1909
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Piantadosi, G.[Gabriele],
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Parmeggiani, D.[Domenico],
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Sansone, C.[Carlo],
Skin Lesions Classification: A Radiomics Approach with Deep CNN,
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1909
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Adegun, A.[Adekanmi],
Viriri, S.[Serestina],
Deep Learning Model for Skin Lesion Segmentation: Fully Convolutional
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1909
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Neher, H.[Helmut],
Arlette, J.[John],
Wong, A.[Alexander],
Discovery Radiomics for Detection of Severely Atypical Melanocytic
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Springer DOI
1909
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Canalini, L.[Laura],
Pollastri, F.[Federico],
Bolelli, F.[Federico],
Cancilla, M.[Michele],
Allegretti, S.[Stefano],
Grana, C.[Costantino],
Skin Lesion Segmentation Ensemble with Diverse Training Strategies,
CAIP19(I:89-101).
Springer DOI
1909
BibRef
Czovny, R.K.,
Bellon, O.R.P.,
Silva, L.,
Costa, H.S.G.,
Minutia Matching using 3D Pore Clouds,
ICPR18(3138-3143)
IEEE DOI
1812
Dermis, Epidermis,
Databases, Biomedical imaging, Measurement uncertainty
BibRef
Yang, J.,
Sun, X.,
Liang, J.,
Rosin, P.L.,
Clinical Skin Lesion Diagnosis Using Representations Inspired by
Dermatologist Criteria,
CVPR18(1258-1266)
IEEE DOI
1812
Skin, Lesions, Diseases, Image color analysis,
Medical diagnostic imaging, Shape
BibRef
Li, H.,
He, X.,
Yu, Z.,
Zhou, F.,
Cheng, J.,
Huang, L.,
Wang, T.,
Lei, B.,
Skin Lesion Segmentation via Dense Connected Deconvolutional Network,
ICPR18(671-675)
IEEE DOI
1812
Lesions, Skin, Decoding, Training, Convolution, Imaging,
Image restoration, Skin lesion segmentation, Dermoscopy image,
Chained residual pooling
BibRef
Luo, W.,
Yang, M.,
Fast Skin Lesion Segmentation via Fully Convolutional Network with
Residual Architecture and CRF,
ICPR18(1438-1443)
IEEE DOI
1812
Lesions, Image segmentation, Convolution, Skin, Kernel, Pipelines,
Training, Melanoma, Fully Convolutional Network,
Conditional Random Field
BibRef
Salih, O.[Omran],
Viriri, S.[Serestina],
Skin Cancer Segmentation Using a Unified Markov Random Field,
ISVC18(25-33).
Springer DOI
1811
BibRef
Elmogy, M.[Mohammed],
García-Zapirain, B.[Begoña],
Elmaghraby, A.S.[Adel S.],
Ei-Baz, A.[Ayman],
An Automated Classification Framework for Pressure Ulcer Tissues
Based on 3D Convolutional Neural Network,
ICPR18(2356-2361)
IEEE DOI
1812
Image segmentation,
Image color analysis, Solid modeling, Skin, Kernel, Feature extraction
BibRef
Elmogy, M.[Mohammed],
García-Zapirain, B.[Begoña],
Burns, C.[Connor],
Elmaghraby, A.S.[Adel S.],
Ei-Baz, A.[Ayman],
Tissues Classification for Pressure Ulcer Images Based on 3D
Convolutional Neural Network,
ICIP18(3139-3143)
IEEE DOI
1809
Image segmentation, Kernel,
Image color analysis, Biological system modeling, Solid modeling,
Linear Combinations of Discrete Gaussians (LCDG)
BibRef
Filali, Y.,
Ennouni, A.,
Sabri, M.A.,
Aarab, A.,
A study of lesion skin segmentation, features selection and
classification approaches,
ISCV18(1-7)
IEEE DOI
1807
cancer, feature extraction, feature selection,
image classification, image colour analysis, image segmentation,
machine-learning
BibRef
Zeng, G.D.[Guo-Dong],
Zheng, G.[Guoyan],
Multi-scale Fully Convolutional DenseNets for Automated Skin Lesion
Segmentation in Dermoscopy Images,
ICIAR18(513-521).
Springer DOI
1807
BibRef
Coronado, R.[Ricardo],
Ocsa, A.[Alexander],
Quispe, O.[Oscar],
Non-dermatoscopic Image Analysis for the Recognition of Malignant Skin
Diseases with Convolutional Neural Network and Autoencoders,
CIARP17(160-167).
Springer DOI
1802
BibRef
Mahdiraji, S.A.,
Baleghi, Y.,
Sakhaei, S.M.,
Skin lesion images classification using new color pigmented boundary
descriptors,
IPRIA17(102-107)
IEEE DOI
1712
cameras, cancer, feature extraction, image classification,
image colour analysis, image texture, medical image processing,
Skin lesion
BibRef
Rundo, F.[Francesco],
Conoci, S.[Sabrina],
Banna, G.L.[Giuseppe L.],
Stanco, F.[Filippo],
Battiato, S.[Sebastiano],
Bio-Inspired Feed-Forward System for Skin Lesion Analysis, Screening
and Follow-Up,
CIAP17(II:399-409).
Springer DOI
1711
BibRef
Balducci, F.[Fabrizio],
Grana, C.[Costantino],
Pixel Classification Methods to Detect Skin Lesions on Dermoscopic
Medical Images,
CIAP17(II:444-455).
Springer DOI
1711
BibRef
Al-abayechi, A.A.A.[Alaa Ahmed Abbas],
Jalab, H.A.[Hamid A.],
Ibrahim, R.W.[Rabha W.],
Hasan, A.M.[Ali M.],
Image Enhancement Based on Fractional Poisson for Segmentation of Skin
Lesions Using the Watershed Transform,
IVIC17(249-259).
Springer DOI
1711
BibRef
Bozkurt, A.,
Gale, T.,
Kose, K.,
Alessi-Fox, C.,
Brooks, D.H.,
Rajadhyaksha, M.,
Dy, J.G.,
Delineation of Skin Strata in Reflectance Confocal Microscopy Images
with Recurrent Convolutional Networks,
Microscopy17(777-785)
IEEE DOI
1709
Dermis, Epidermis, Feature extraction, Imaging, Training
BibRef
Gu, Y.,
Zhou, J.,
Qian, B.,
Melanoma Detection Based on Mahalanobis Distance Learning and
Constrained Graph Regularized Nonnegative Matrix Factorization,
WACV17(797-805)
IEEE DOI
1609
Feature extraction, Linear programming, Malignant tumors,
Manifolds, Matrix decomposition, Skin, Skin, cancer
BibRef
Barata, C.[Catarina],
Figueiredo, M.A.T.[Mário A. T.],
Celebi, M.E.[M. Emre],
Marques, J.S.[Jorge S.],
Local Features Applied to Dermoscopy Images:
Bag-of-Features versus Sparse Coding,
IbPRIA17(528-536).
Springer DOI
1706
BibRef
Alarifi, J.S.[Jhan S.],
Goyal, M.[Manu],
Davison, A.K.[Adrian K.],
Dancey, D.[Darren],
Khan, R.[Rabia],
Yap, M.H.[Moi Hoon],
Facial Skin Classification Using Convolutional Neural Networks,
ICIAR17(479-485).
Springer DOI
1706
BibRef
Cho, D.S.[Daniel S.],
Khalvati, F.[Farzad],
Clausi, D.A.[David A.],
Wong, A.[Alexander],
A Machine Learning-Driven Approach to Computational Physiological
Modeling of Skin Cancer,
ICIAR17(79-86).
Springer DOI
1706
BibRef
Hajdu, A.,
Harangi, B.,
Besenczi, R.,
Lázár, I.,
Emri, G.,
Hajdu, L.,
Tijdeman, R.,
Measuring regularity of network patterns by grid approximations using
the LLL algorithm,
ICPR16(1524-1529)
IEEE DOI
1705
Approximation algorithms, Lesions, Measurement uncertainty,
Noise level, Pattern recognition, Pigments, Skin
BibRef
Kaur, P.,
Dana, K.J.,
Cula, G.O.,
Mack, M.C.,
Hybrid deep learning for Reflectance Confocal Microscopy skin images,
ICPR16(1466-1471)
IEEE DOI
1705
Epidermis, Histograms, Image recognition, Libraries,
Machine learning, Neural, networks
BibRef
Pal, A.,
Chaturvedi, A.,
Garain, U.,
Chandra, A.,
Chatterjee, R.,
Severity grading of psoriatic plaques using deep CNN based multi-task
learning,
ICPR16(1478-1483)
IEEE DOI
1705
Computer architecture, Convolution, Diseases, Drugs, Estimation,
Kernel, Skin
BibRef
Liao, H.[Haofu],
Li, Y.[Yuncheng],
Luo, J.B.[Jie-Bo],
Skin disease classification versus skin lesion characterization:
Achieving robust diagnosis using multi-label deep neural networks,
ICPR16(355-360)
IEEE DOI
1705
Dermatology, Diseases, Lesions, Malignant tumors, Skin, Training,
Visualization, convolutional neural networks,
skin disease classification, skin, lesion, characterization
BibRef
Jafari, M.H.,
Karimi, N.,
Nasr-Esfahani, E.,
Samavi, S.,
Soroushmehr, S.M.R.,
Ward, K.,
Najarian, K.,
Skin lesion segmentation in clinical images using deep learning,
ICPR16(337-342)
IEEE DOI
1705
Feature extraction, Image segmentation, Lesions, Lighting,
Machine learning, Malignant tumors, Skin, Melanoma,
convolutional neural network, deep learning,
medical image segmentation, skin, cancer
BibRef
Faraz, K.[Khuram],
Blondel, W.[Walter],
Amouroux, M.[Marine],
Daul, C.[Christian],
Towards skin image mosaicing,
IPTA16(1-6)
IEEE DOI
1703
Tele-dermatology.
feature extraction
BibRef
Majtner, T.,
Yildirim-Yayilgan, S.,
Hardeberg, J.Y.,
Combining deep learning and hand-crafted features for skin lesion
classification,
IPTA16(1-6)
IEEE DOI
1703
biomedical optical imaging
BibRef
Haji Rassouliha, A.,
Kmiecik, B.,
Taberner, A.J.,
Nash, M.P.,
Nielsen, P.M.F.,
A Low-cost, hand-held stereoscopic device for measuring dynamic
deformations of skin in vivo,
ICVNZ15(1-6)
IEEE DOI
1701
deformation
BibRef
Yao, T.T.[Ting-Ting],
Wang, Z.Y.[Zhi-Yong],
Xie, Z.[Zhao],
Gao, J.[Jun],
Feng, D.D.[David Dagan],
A Multiview Joint Sparse Representation with Discriminative
Dictionary for Melanoma Detection,
DICTA16(1-6)
IEEE DOI
1701
Dictionaries
BibRef
Kawahara, J.[Jeremy],
Hamarneh, G.[Ghassan],
Multi-resolution-Tract CNN with Hybrid Pretrained and Skin-Lesion
Trained Layers,
MLMI16(164-171).
Springer DOI
1611
BibRef
Bozorgtabar, B.[Behzad],
Abedini, M.[Mani],
Garnavi, R.[Rahil],
Sparse Coding Based Skin Lesion Segmentation Using Dynamic Rule-Based
Refinement,
MLMI16(254-261).
Springer DOI
1611
BibRef
Kropidlowski, K.[Karol],
Kociolek, M.[Marcin],
Strzelecki, M.[Michal],
Czubinski, D.[Dariusz],
Blue Whitish Veil, Atypical Vascular Pattern and Regression Structures
Detection in Skin Lesions Images,
ICCVG16(418-428).
Springer DOI
1611
BibRef
Sun, X.X.[Xiao-Xiao],
Yang, J.F.[Ju-Feng],
Sun, M.[Ming],
Wang, K.[Kai],
A Benchmark for Automatic Visual Classification of Clinical Skin
Disease Images,
ECCV16(VI: 206-222).
Springer DOI
1611
BibRef
Bulan, O.,
Artan, Y.,
Wheal detection from skin prick test images using normalized-cuts and
region selection,
ICIP16(1250-1253)
IEEE DOI
1610
Calibration
BibRef
Schneider, D.,
Hecht, A.,
Photogrammetric 3d Acquisition And Analysis Of Medicamentous Induced
Pilomotor Reflex (goose Bumps),
ISPRS16(B5: 903-908).
DOI Link
1610
BibRef
Bernart, E.,
Scharcanski, J.,
Bampi, S.,
Segmentation and classification of melanocytic skin lesions using
local and contextual features,
ICIP16(2633-2637)
IEEE DOI
1610
Cancer
BibRef
Mete, M.,
Sirakov, N.M.,
Griffin, J.,
Menter, A.,
A novel classification system for dysplastic nevus and malignant
melanoma,
ICIP16(3414-3418)
IEEE DOI
1610
Lesions
BibRef
Majtner, T.[Tomáš],
Yildirim-Yayilgan, S.[Sule],
Hardeberg, J.Y.[Jon Yngve],
Efficient Melanoma Detection Using Texture-Based RSurf Features,
ICIAR16(30-37).
Springer DOI
1608
BibRef
Akaho, R.[Rina],
Hirose, M.[Misa],
Tsumura, N.[Norimichi],
Nonlinear Estimation of Chromophore Concentrations and Shading from
Hyperspectral Images,
ICISP16(101-108).
WWW Link.
1606
melanin, oxy-hemoglobin, deoxy-hemoglobin and shading.
BibRef
Afifi, S.[Shereen],
Gholam Hosseini, H.[Hamid],
Sinha, R.[Roopak],
Hardware Acceleration of SVM-Based Classifier for Melanoma Images,
MCBMIIA15(235-245).
Springer DOI
1603
BibRef
Saleh, F.S.,
Azmi, R.,
Automated lesion border detection of dermoscopy images using spectral
clustering,
IPRIA15(1-6)
IEEE DOI
1603
cancer
BibRef
Hames, S.C.,
Ardigo, M.,
Soyer, H.P.,
Bradley, A.P.,
Prow, T.W.,
Anatomical Skin Segmentation in Reflectance Confocal Microscopy with
Weak Labels,
DICTA15(1-8)
IEEE DOI
1603
feature extraction
BibRef
Madooei, A.[Ali],
Drew, M.S.[Mark S.],
Detecting specular highlights in dermatological images,
ICIP15(4357-4360)
IEEE DOI
1512
DRM
BibRef
Gonzalez-Castro, V.,
Debayle, J.,
Wazaefi, Y.,
Rahim, M.,
Gaudy, C.,
Grob, J.J.,
Fertil, B.,
Automatic classification of skin lesions using geometrical
measurements of adaptive neighborhoods and local binary patterns,
ICIP15(1722-1726)
IEEE DOI
1512
General adaptive neighborhoods
BibRef
Santos, A.[Anderson],
Pedrini, H.[Helio],
Human Skin Segmentation Improved by Saliency Detection,
CAIP15(II:146-157).
Springer DOI
1511
BibRef
Codella, N.[Noel],
Cai, J.J.[Jun-Jie],
Abedini, M.[Mani],
Garnavi, R.[Rahil],
Halpern, A.[Alan],
Smith, J.R.[John R.],
Deep Learning, Sparse Coding, and SVM for Melanoma Recognition in
Dermoscopy Images,
MLMI15(118-126).
Springer DOI
1511
BibRef
Rizzi, M.[Maria],
d'Aloia, M.[Matteo],
Cice, G.[Gianpaolo],
Computer Aided Evaluation (CAE) of Morphologic Changes in Pigmented
Skin Lesions,
ISCA15(250-257).
Springer DOI
1511
BibRef
Santos, A.[Anderson],
Pedrini, H.[Helio],
Human Skin Segmentation Improved by Texture Energy Under Superpixels,
CIARP15(35-42).
Springer DOI
1511
BibRef
Kaur, P.[Parneet],
Dana, K.J.[Kristin J.],
Cula, G.O.[Gabriela Oana],
From photography to microbiology:
Eigenbiome models for skin appearance,
BioImage15(1-10)
IEEE DOI
1510
Artificial neural networks
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Gupta, M.D.[Mithun Das],
Srinivasa, S.[Srinidhi],
Madhukara, J.,
Antony, M.[Meryl],
KL divergence based agglomerative clustering for automated Vitiligo
grading,
CVPR15(2700-2709)
IEEE DOI
1510
BibRef
Koehoorn, J.[Joost],
Sobiecki, A.C.[André C.],
Boda, D.[Daniel],
Diaconeasa, A.[Adriana],
Doshi, S.[Susan],
Paisey, S.[Stephen],
Jalba, A.[Andrei],
Telea, A.[Alexandru],
Automated Digital Hair Removal by Threshold Decomposition and
Morphological Analysis,
ISMM15(15-26).
Springer DOI
1506
BibRef
Wazaefi, Y.,
Paris, S.,
Fertil, B.,
Contribution of a classifier of skin lesions to the dermatologist's
decision,
IPTA12(207-211)
IEEE DOI
1503
cancer
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Toth, J.[Janos],
Szakacs, L.[Laszlo],
Hajdu, A.[Andras],
Finding the optimal parameter setting for an ensemble-based lesion
detector,
ICIP14(3532-3536)
IEEE DOI
1502
Databases
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Kechichian, R.,
Gong, H.,
Revenu, M.,
Lezoray, O.,
Desvignes, M.,
New data model for graph-cut segmentation:
Application to automatic melanoma delineation,
ICIP14(892-896)
IEEE DOI
1502
Image color analysis
BibRef
Lezoray, O.,
Revenu, M.,
Desvignes, M.,
Graph-based skin lesion segmentation of multispectral dermoscopic
images,
ICIP14(897-901)
IEEE DOI
1502
Clustering algorithms
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Mete, M.[Mutlu],
Sirakov, N.M.[Nikolay Metodiev],
Optimal set of features for accurate skin cancer diagnosis,
ICIP14(2256-2260)
IEEE DOI
1502
Accuracy
BibRef
Vasconcelos, M.J.M.[Maria João M.],
Rosado, L.[Luís],
Ferreira, M.[Márcia],
Principal Axes-Based Asymmetry Assessment Methodology for Skin Lesion
Image Analysis,
ISVC14(II: 21-31).
Springer DOI
1501
BibRef
Satat, G.,
Barsi, C.,
Raskar, R.,
Skin perfusion photography,
ICCP14(1-8)
IEEE DOI
1411
biomedical optical imaging
BibRef
Kropidlowski, K.[Karol],
Kociolek, M.[Marcin],
Strzelecki, M.[Michal],
Czubinski, D.[Dariusz],
Model Based Approach for Melanoma Segmentation,
ICCVG14(347-355).
Springer DOI
1410
BibRef
Nasonova, A.[Alexandra],
Nasonov, A.[Andrey],
Krylov, A.[Andrey],
Pechenko, I.[Ivan],
Umnov, A.[Alexey],
Makhneva, N.[Natalia],
Image Warping in Dermatological Image Hair Removal,
ICIAR14(II: 159-166).
Springer DOI
1410
BibRef
Somoza, E.[Eduardo],
Cula, G.O.[Gabriela Oana],
Correa, C.[Catherine],
Hirsch, J.B.[Julie B.],
Automatic Localization of Skin Layers in Reflectance Confocal
Microscopy,
ICIAR14(II: 141-150).
Springer DOI
1410
BibRef
Abbas, Q.[Qaisar],
Fondón, I.[Irene],
Sarmiento, A.[Auxiliadora],
Celebi, M.E.[M. Emre],
An Improved Segmentation Method for Non-melanoma Skin Lesions Using
Active Contour Model,
ICIAR14(II: 193-200).
Springer DOI
1410
BibRef
Liu, Z.[Zhao],
Zerubia, J.B.[Josiane B.],
Melanin and Hemoglobin Identification for Skin Disease Analysis,
ACPR13(145-149)
IEEE DOI
1408
diseases
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Ma, Z.[Zhen],
Tavares, J.M.R.S.[João Manuel R. S.],
Segmentation of Skin Lesions Using Level Set Method,
CompIMAGE14(228-233).
Springer DOI
1407
BibRef
Abuzaghleh, O.,
Barkana, B.D.,
Faezipour, M.,
SKINcure: A real time image analysis system to aid in the malignant
melanoma prevention and early detection,
Southwest14(85-88)
IEEE DOI
1406
cancer
BibRef
Hirose, M.[Misa],
Toyota, S.[Saori],
Tatsuzawa, Y.[Yuri],
Tsumura, N.[Norimichi],
Evaluating Visibility of Age Spot and Freckle Based on Simulated
Spectral Reflectance of Skin,
ICISP14(9-17).
Springer DOI
1406
BibRef
Vasconcelos, M.J.M.[Maria João M.],
Rosado, L.[Luís],
No-reference Blur Assessment of Dermatological Images Acquired via
Mobile Devices,
ICISP14(350-357).
Springer DOI
1406
BibRef
Jaworek-Korjakowska, J.[Joanna],
Tadeusiewicz, R.[Ryszard],
Assessment of dots and globules in dermoscopic color images as one of
the 7-point check list criteria,
ICIP13(1456-1460)
IEEE DOI
1402
dots and globules;feature extraction;hair removal;melanoma;skin lesion
BibRef
Seck, A.[Alassane],
Dee, H.[Hannah],
Tiddeman, B.[Bernard],
3D Facial Skin Texture Analysis Using Geometric Descriptors,
ICPR14(1126-1131)
IEEE DOI
1412
BibRef
Earlier:
Local Orientation Patterns for 3D Surface Texture Analysis of Normal
Maps: Application to Facial Skin Condition Classification,
ISVC13(I:572-581).
Springer DOI
1310
Feature extraction
BibRef
Barata, C.[Catarina],
Celebi, M.E.[M. Emre],
Marques, J.S.[Jorge S.],
Color Detection in Dermoscopy Images Based on Scarce Annotations,
IbPRIA15(309-316).
Springer DOI
1506
BibRef
Ruela, M.[Margarida],
Barata, C.[Catarina],
Marques, J.S.[Jorge S.],
What Is the Role of Color Symmetry in the Detection of Melanomas?,
ISVC13(I:1-10).
Springer DOI
1310
BibRef
Ruela, M.[Margarida],
Barata, C.[Catarina],
Mendonça, T.[Teresa],
Marques, J.S.[Jorge S.],
What Is the Role of Color in Dermoscopy Analysis?,
IbPRIA13(819-826).
Springer DOI
1307
BibRef
Ferreira, P.M.[Pedro M.],
Mendonça, T.[Teresa],
Rocha, P.[Paula],
A Wide Spread of Algorithms for Automatic Segmentation of Dermoscopic
Images,
IbPRIA13(592-599).
Springer DOI
1307
BibRef
Pereira, C.[Carla],
Veiga, D.[Diana],
Mahdjoub, J.[Jason],
Guessoum, Z.[Zahia],
Gonçalves, L.[Luís],
Small Red Lesions Detection Using a MAS Approach,
ICIAR13(521-529).
Springer DOI
1307
BibRef
Barata, C.[Catarina],
Marques, J.S.[Jorge S.],
Mendonça, T.[Teresa],
Bag-of-Features Classification Model for the Diagnose of Melanoma in
Dermoscopy Images Using Color and Texture Descriptors,
ICIAR13(547-555).
Springer DOI
1307
BibRef
Barata, C.[Catarina],
Marques, J.S.[Jorge S.],
Rozeira, J.[Jorge],
Evaluation of Color Based Keypoints and Features for the Classification
of Melanomas Using the Bag-of-Features Model,
ISVC13(I:40-49).
Springer DOI
1310
BibRef
Earlier:
The Role of Keypoint Sampling on the Classification of Melanomas in
Dermoscopy Images Using Bag-of-Features,
IbPRIA13(715-723).
Springer DOI
1307
BibRef
He, Y.D.[Ying-Ding],
Xie, F.Y.[Feng-Ying],
Automatic Skin Lesion Segmentation Based on Texture Analysis and
Supervised Learning,
ACCV12(II:330-341).
Springer DOI
1304
BibRef
Mete, M.[Mutlu],
Ou, Y.L.[Ye-Lin],
Sirakov, N.M.[Nikolay Metodiev],
Skin Lesion Feature Vector Space with a Metric to Model Geometric
Structures of Malignancy for Classification,
IWCIA12(285-297).
Springer DOI
1211
BibRef
Razeghi, O.[Orod],
Qiu, G.P.[Guo-Ping],
Williams, H.[Hywel],
Thomas, K.[Kim],
Computer Aided Skin Lesion Diagnosis with Humans in the Loop,
MLMI12(266-274).
Springer DOI
1211
BibRef
Oyola, J.[Julián],
Arroyo, V.[Virginia],
Ruedin, A.[Ana],
Acevedo, D.[Daniel],
Detection of Chickenpox Vesicles in Digital Images of Skin Lesions,
CIARP12(583-590).
Springer DOI
1209
BibRef
Güçin, M.,
Patias, P.,
Altan, M.O.,
Detection and Evaluation of Skin Disorders By One of Photogrammetric
Image Analysis Methods,
ISPRS12(XXXIX-B3:537-542).
DOI Link
1209
BibRef
Amelard, R.[Robert],
Wong, A.[Alexander],
Clausi, D.A.[David A.],
Extracting High-Level Intuitive Features (HLIF) for Classifying Skin
Lesions Using Standard Camera Images,
CRV12(396-403).
IEEE DOI
1207
BibRef
Gong, H.[Hao],
Desvignes, M.[Michel],
Hemoglobin and Melanin Quantification on Skin Images,
ICIAR12(II: 198-205).
Springer DOI
1206
BibRef
Ramli, R.,
Malik, A.S.,
Hani, A.F.M.,
Yap, F.B.,
Segmentation of Acne Vulgaris Lesions,
DICTA11(335-339).
IEEE DOI
1205
BibRef
Cavalcanti, P.G.,
Yari, Y.,
Scharcanski, J.,
Pigmented skin lesion segmentation on macroscopic images,
IVCNZ10(1-7).
IEEE DOI
1203
BibRef
Sirakov, N.M.[Nikolay Metodiev],
Mete, M.[Mutlu],
Chakrader, N.S.[Nara Surendra],
Automatic boundary detection and symmetry calculation in dermoscopy
images of skin lesions,
ICIP11(1605-1608).
IEEE DOI
1201
BibRef
Prigent, S.[Sylvain],
Zugaj, D.[Didier],
Descombes, X.[Xavier],
Martel, P.[Philippe],
Zerubia, J.B.[Josiane B.],
Estimation of an optimal spectral band combination to evaluate skin
disease treatment efficacy using multi-spectral images,
ICIP11(2801-2804).
IEEE DOI
1201
BibRef
Khak Abi, S.[Sina],
Lee, T.K.[Tim K.],
Atkins, M.S.[M. Stella],
Tree Structured Model of Skin Lesion Growth Pattern via Color Based
Cluster Analysis,
MLMI11(291-299).
Springer DOI
1109
BibRef
Babu, M.N.[M. Naresh],
Madasu, V.K.[Vamsi K.],
Hanmandlu, M.,
Vasikarla, S.,
Histo-pathological image analysis using OS-FCM and level sets,
AIPR10(1-8).
IEEE DOI
1010
Orientation Sensitive Fuzzy C-means algorithm (OS-FCM)
Skin cancer, melanoma, analysis
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Classification of Melanoma Lesions Using Wavelet-Based Texture Analysis,
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OCT: Optical Coherence Tompgraphy.
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ICIP13(626-629)
IEEE DOI
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Diseases
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Prigent, S.[Sylvain],
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Erythema detection in digital skin images,
ICIP10(2545-2548).
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Subramaniam, N.[Nitya],
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ICIP10(3021-3024).
IEEE DOI
1009
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Zacher, A.[Andrzej],
Utilization of Multi-spectral Images in Photodynamic Diagnosis,
ICCVG10(II: 367-375).
Springer DOI
1009
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Zacher, A.[Andrzej],
The Spectral Analysis of Human Skin Tissue Using Multi-spectral Images,
ICCVG10(II: 376-384).
Springer DOI
1009
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Placidi, G.[Giuseppe],
Cifone, M.G.[Maria Grazia],
Cinque, B.[Benedetta],
Franchi, D.[Danilo],
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La Torre, C.[Cristina],
Macchiarelli, G.[Guido],
Maglione, M.[Marta],
Maurizi, A.[Alfredo],
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Numerical Methods for the Semi-automatic Analysis of Multimodal Wound
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CompIMAGE10(151-162).
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George, Y.,
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Garnavi, R.[Rahil],
A Pixel-Based Skin Segmentation in Psoriasis Images Using Committee
of Machine Learning Classifiers,
DICTA17(1-8)
IEEE DOI
1804
diseases, feature extraction, image classification,
image colour analysis, image segmentation,
Training
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George, Y.,
Aldeen, M.[Mohammad],
Garnavi, R.[Rahil],
Skin Hair Removal for 2D Psoriasis Images,
DICTA15(1-8)
IEEE DOI
1603
diseases
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Garnavi, R.[Rahil],
Aldeen, M.[Mohammad],
Finch, S.[Sue],
Varigos, G.[George],
Global versus Hybrid Thresholding for Border Detection in Dermoscopy
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ICISP10(531-540).
Springer DOI
1006
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Jha, A.K.[Abhinav K.],
Kupinski, M.A.[Matthew A.],
Rodriguez, J.J.[Jeffrey J.],
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ADC estimation of lesions in diffusion-weighted MR images:
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Southwest10(209-212).
IEEE DOI
1005
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Fadzil, M.H.A.[M.H. Ahmad],
Fitriyah, H.[Hurriyatul],
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Affandi, A.M.[Azura Mohammed],
Thickness Characterization of 3D Skin Surface Images Using Reference
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IVIC09(448-454).
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0911
3d surface analysis for skin lesions.
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Hani, A.F.M.[Ahmad Fadzil M.],
Eltegani, N.M.[Nejood M.],
Hussein, S.H.[Suraiya H.],
Jamil, A.[Adawiyah],
Gill, P.[Priya],
Assessment of Ulcer Wounds Size Using 3D Skin Surface Imaging,
IVIC09(243-253).
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0911
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Nayak, R.[Rohit],
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Towards a comprehensive assessment of wound-composition using
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IEEE DOI
0911
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Mendoza, C.S.[Carlos S.],
Serrano, C.[Carmen],
Acha, B.[Begona],
Scale invariant descriptors in pattern analysis of melanocytic lesions,
ICIP09(4193-4196).
IEEE DOI
0911
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Clawson, K.M.,
Morrow, P.J.,
Scotney, B.W.,
McKenna, D.J.,
Dolan, O.M.,
Analysis of Pigmented Skin Lesion Border Irregularity Using the
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IMVIP09(18-23).
IEEE DOI
0909
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Celebi, M.E.[M. Emre],
Hwang, S.[Sae],
Iyatomi, H.[Hitoshi],
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Robust border detection in dermoscopy images using threshold fusion,
ICIP10(2541-2544).
IEEE DOI
1009
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Iyatomi, H.[Hitoshi],
Celebi, M.E.[M. Emre],
Schaefer, G.[Gerald],
Tanaka, M.[Masaru],
Automated color normalization for dermoscopy images,
ICIP10(4357-4360).
IEEE DOI
1009
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Celebi, M.E.[M. Emre],
Iyatomi, H.[Hitoshi],
Schaefer, G.[Gerald],
Contrast enhancement in dermoscopy images by maximizing a histogram
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ICIP09(2601-2604).
IEEE DOI
0911
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Schaefer, G.[Gerald],
Rajab, M.I.[Maher I.],
Celebi, M.E.[M. Emre],
Iyatomi, H.[Hitoshi],
Skin lesion extraction in dermoscopic images based on colour
enhancement and iterative segmentation,
ICIP09(3361-3364).
IEEE DOI
0911
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Schaefer, G.,
Krawczyk, B.,
Celebi, M.E.,
Iyatomi, H.,
Melanoma Classification Using Dermoscopy Imaging and Ensemble
Learning,
ACPR13(386-390)
IEEE DOI
1408
biomedical optical imaging
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Celebi, M.E.[M. Emre],
Iyatomi, H.[Hitoshi],
Schaefer, G.[Gerald],
Stoecker, W.V.[William V.],
Localization of Lesions in Dermoscopy Images Using Ensembles of
Thresholding Methods,
PSIVT09(1094-1103).
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0901
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Madasu, V.K.[Vamsi K.],
Lovell, B.C.[Brian C.],
Blotch Detection in Pigmented Skin Lesions Using Fuzzy Co-clustering
and Texture Segmentation,
DICTA09(25-31).
IEEE DOI
0912
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Capdehourat, G.[Germán],
Corez, A.[Andrés],
Bazzano, A.[Anabella],
Musé, P.[Pablo],
Pigmented Skin Lesions Classification Using Dermatoscopic Images,
CIARP09(537-544).
Springer DOI
0911
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Ma, L.[Li],
Guo, A.Z.[An-Zhe],
Zou, S.F.[Shao-Fang],
Xu, W.D.[Wei-Dong],
Irregularity and Asymmetry Analysis of Skin Lesions Based on
Multi-Scale Local Fractal Distributions,
CISP09(1-5).
IEEE DOI
0910
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Madan, S.K.[Siddharth K.],
Dana, K.J.[Kristin J.],
Cula, O.G.[Oana G.],
Quasiconvex alignment of multimodal skin images for quantitative
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MMBIA09(117-124).
IEEE DOI
0906
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Mirzaalian, H.[Hengameh],
Lee, T.K.[Tim K.],
Hamarneh, G.[Ghassan],
Learning features for streak detection in dermoscopic color images
using localized radial flux of principal intensity curvature,
MMBIA12(97-101).
IEEE DOI
1203
BibRef
Earlier: A1, A3, A2:
A graph-based approach to skin mole matching incorporating
template-normalized coordinates,
CVPR09(2152-2159).
IEEE DOI
0906
BibRef
Bouhlel, N.[Nizar],
Hajjaji, S.[Salwa],
Sevestre, S.[Sylvie],
Laugier, P.[Pascal],
Texture analysis using Nakagami-MRF model: Preliminary results on
ultrasound images of primary choroidal melanomas,
ICIP09(4181-4184).
IEEE DOI
0911
BibRef
Chaudhry, M.A.[M. Ali],
Ashraf, R.[Robina],
Jafri, M.N.,
Akbar, M.,
Computer aided diagnosis of skin carcinomas based on textural
characteristics,
ICMV07(125-128).
IEEE DOI
0712
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Cho, T.S.[Taeg Sang],
Freeman, W.T.[William T],
Tsao, H.[Hensin],
A reliable skin mole localization scheme,
MMBIA07(1-8).
IEEE DOI
0710
BibRef
Situ, N.[Ning],
Yuan, X.J.[Xiao-Jing],
Zouridakis, G.[George],
Mullani, N.[Nizar],
Automatic Segmentation of Skin Lesion Images using Evolutionary
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ICIP07(VI: 277-280).
IEEE DOI
0709
BibRef
Clawson, K.M.,
Morrow, P.J.,
Scotney, B.W.,
McKenna, D.J.,
Dolan, O.M.,
Determination of Optimal Axes for Skin Lesion Asymmetry Quantification,
ICIP07(II: 453-456).
IEEE DOI
0709
BibRef
And:
Computerised Skin Lesion Surface Analysis for Pigment Asymmetry
Quantification,
IMVIP07(75-82).
IEEE DOI
0709
BibRef
Xu, C.Z.[Cheng-Zhe],
Kim, I.[Intaek],
Kim, M.S.[Moon S.],
Poultry Skin Tumor Detection in Hyperspectral Reflectance Images by
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ICIAR07(1289-1296).
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0708
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Odeh, S.M.[Suhail M.],
Ros, E.[Eduardo],
Rojas, I.[Ignacio],
Palomares, J.M.[Jose M.],
Skin Lesion Diagnosis Using Fluorescence Images,
ICIAR06(II: 648-659).
Springer DOI
0610
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Aribisala, B.S.[Benjamin S.],
Claridge, E.[Ela],
A Border Irregularity Measure Using a Modified Conditional Entropy
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ICIAR05(914-921).
Springer DOI
0509
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Kolesnik, M.[Marina],
Fexa, A.[Ales],
Multi-dimensional Color Histograms for Segmentation of Wounds in Images,
ICIAR05(1014-1022).
Springer DOI
0509
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Kontinen, J.[Jukka],
Röning, J.[Juha],
MacKie, R.M.[Rona M.],
Texture features in the classification of melanocytic lesions,
CIAP97(II: 453-460).
Springer DOI
9709
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Schmid, P.[Philippe],
Lesion Detection in Dermatoscopic Images Using Anisotropic Diffusion and
Morphological Flooding,
ICIP99(III:449-453).
IEEE DOI
BibRef
9900
Yamada, T.,
Saito, H.,
Ozawa, S.,
3d Reconstruction of Skin Surface from Image Sequence,
MVA98(xx-yy).
See also 3D Reconstruction of Book Surface Taken from Image Sequence with Handy Camera.
BibRef
9800
Roehrer, R.[Reinhard],
Ganster, H.[Harald],
Pinz, A.[Axel],
Feature Selection in Melanoma Recognition,
ICPR98(Vol II: 1668-1670).
IEEE DOI
9808
BibRef
Riech, M.[Marcel],
Roning, J.[Juha],
Registration of NEVI in Successive Skin Images for
Early Detection of Melanoma,
ICPR98(Vol I: 352-357).
IEEE DOI
9808
BibRef
Fischer, S.[Stefan],
Schmid, P.[Philippe],
Guillod, J.[Joel],
Analysis of Skin Lesions with Pigmented Networks,
ICIP96(I: 323-326).
IEEE DOI
BibRef
9600
Kutics, A.[Andrea],
Date, M.[Munehiro],
A new parallel method based on a genetic approach for determination and
classification of skin spots,
CIAP95(121-126).
Springer DOI
9509
BibRef
Ross, T.,
Handels, H.,
Kreusch, J.,
Busche, H.,
Wolf, H.H.,
Pöppl, S.J.,
Automatic classification of skin tumours with high resolution surface
profiles,
CAIP95(368-375).
Springer DOI
9509
BibRef
Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Medical Applications -- Endoscopy .