brain lesion segmentation,
Online
WWW Link.
1605
Code, Brain Lesion Segmentation. multi-scale 3D Deep Convolutional Neural Network coupled with a 3D
fully connected Conditional Random Field.
BibRef
Kyriacou, S.K.,
Davatzikos, C.,
Zinreich, S.J.,
Bryan, R.N.,
Nonlinear elastic registration of brain images with tumor pathology
using a biomechanical model [MRI],
MedImg(18), No. 7, July 1999, pp. 580-592.
IEEE Top Reference.
0110
BibRef
Iftekharuddin, K.M.[Khan M.],
Jia, W.[Wei],
Marsh, R.[Ronald],
Fractal analysis of tumor in brain MR images,
MVA(13), No. 5-6, 2003, pp. 352-362.
WWW Link.
0304
See also FractalNet: A biologically inspired neural network approach to fractal geometry.
BibRef
Corso, J.J.,
Sharon, E.,
Dube, S.,
El-Saden, S.,
Sinha, U.,
Yuille, A.L.,
Efficient Multilevel Brain Tumor Segmentation With Integrated Bayesian
Model Classification,
MedImg(27), No. 5, May 2008, pp. 629-640.
IEEE DOI
0711
BibRef
Al-Kadi, O.S.[Omar S.],
Texture measures combination for improved meningioma classification of
histopathological images,
PR(43), No. 6, June 2010, pp. 2043-2053.
Elsevier DOI
1003
BibRef
Earlier:
A fractal dimension based optimal wavelet packet analysis technique for
classification of meningioma brain tumours,
ICIP09(4177-4180).
IEEE DOI
0911
Coloured texture analysis; Feature extraction; Histopathological
images; Meningioma; Naive Bayesian classifier; Bhattacharyya distance
BibRef
Zhang, N.[Nan],
Ruan, S.[Su],
Lebonvallet, S.[Stephane],
Liao, Q.M.[Qing-Min],
Zhu, Y.M.[Yue-Min],
Kernel feature selection to fuse multi-spectral MRI images for brain
tumor segmentation,
CVIU(115), No. 2, February 2011, pp. 256-269.
Elsevier DOI
1102
BibRef
Earlier:
Multi-kernel SVM based classification for brain tumor segmentation of
MRI multi-sequence,
ICIP09(3373-3376).
IEEE DOI
0911
SVM; Segmentation; Feature selection; Fusion; Follow-up system; Brain
tumor; MRI
BibRef
Boughattas, N.[Naouel],
Berar, M.[Maxime],
Hamrouni, K.[Kamel],
Ruan, S.[Su],
Brain tumor segmentation from multiple MRI sequences using multiple
kernel learning,
ICIP14(1887-1891)
IEEE DOI
1502
Feature extraction
BibRef
Hamamci, A.,
Kucuk, N.,
Karaman, K.,
Engin, K.,
Unal, G.,
Tumor-Cut: Segmentation of Brain Tumors on Contrast Enhanced MR Images
for Radiosurgery Applications,
MedImg(31), No. 3, March 2012, pp. 790-804.
IEEE DOI
1203
BibRef
Jayachandran, A.,
Dhanasekaran, R.,
Automatic detection of brain tumor in magnetic resonance images
using multi-texton histogram and support vector machine,
IJIST(23), No. 2, 2013, pp. 97-103.
DOI Link
1307
support vector machine, radial basis function, binarized image
BibRef
Jayachandran, A.,
Dhanasekaran, R.,
Brain tumor severity analysis using modified multi-texton histogram
and hybrid kernel SVM,
IJIST(24), No. 1, 2014, pp. 72-82.
DOI Link
1403
tumor
BibRef
El-Melegy, M.[Moumen],
Mokhtar, H.[Hashim],
Tumor segmentation in brain MRI using a fuzzy approach with class
center priors,
JIVP(2014), No. 1, 2014, pp. 21.
DOI Link
1404
BibRef
Earlier:
Incorporating prior information in the fuzzy C-mean algorithm with
application to brain tissues segmentation in MRI,
ICIP09(3393-3396).
IEEE DOI
0911
BibRef
Chih-Feng, C.[Chen],
Ling-Wei, H.[Hsu],
Chun-Chung, L.[Lui],
Chen-Chang, L.[Lee],
Hsu-Huei, W.[Weng],
Yuan-Hsiung, T.[Tsai],
Ho-Ling, L.[Liu],
In vivo correlation between semi-quantitative hemodynamic parameters
and Ktrans derived from DCE-MRI of brain tumors,
IJIST(22), No. 2, June 2012, pp. 132-136.
DOI Link
1202
BibRef
Angoth, V.[Vivek],
Dwith, C.Y.N.,
Singh, A.[Amarjot],
A Novel Wavelet Based Image Fusion for Brain Tumor Detection,
IJCVSP(2), No. 1, 2013, pp. xx-yy.
WWW Link.
1303
BibRef
Bauer, S.[Stefan],
Lu, H.X.[Huan-Xiang],
May, C.P.[Christian P.],
Nolte, L.P.[Lutz P.],
Büchler, P.[Philippe],
Reyes, M.[Mauricio],
Integrated segmentation of brain tumor images for radiotherapy and
neurosurgery,
IJIST(23), No. 1, March 2013, pp. 59-63.
DOI Link
1303
BibRef
Dhanalakshmi, K.,
Rajamani, V.,
An intelligent mining system for diagnosing medical images
using combined texture-histogram features,
IJIST(23), No. 2, 2013, pp. 194-203.
DOI Link brain tumor, image processing, association rule mining, associative classifier
1307
BibRef
Arakeri, M.P.[Megha P.],
Reddy, G.R.M.[G. Ram Mohana],
An intelligent content-based image retrieval system for clinical
decision support in brain tumor diagnosis,
MultInfoRetr(2), No. 3, September 2013, pp. 175-188.
WWW Link.
1307
BibRef
Arakeri, M.P.[Megha P.],
Reddy, G.R.M.[G. Ram Mohana],
Computer-aided diagnosis system for tissue characterization of brain
tumor on magnetic resonance images,
SIViP(9), No. 2, February 2015, pp. 409-425.
WWW Link.
1503
BibRef
Vilamala, A.[Albert],
Lisboa, P.J.G.[Paulo J.G.],
Ortega-Martorell, S.[Sandra],
Vellido, A.[Alfredo],
Discriminant Convex Non-negative Matrix Factorization for the
classification of human brain tumours,
PRL(34), No. 14, 2013, pp. 1734-1747.
Elsevier DOI
1308
Discriminant Convex Non-negative Matrix Factorization
BibRef
Beno, M.M.[M. Marsaline],
Valarmathi, I.R.,
Swamy, S.M.,
Rajakumar, B.R.,
Threshold prediction for segmenting tumour from brain MRI scans,
IJIST(24), No. 2, 2014, pp. 129-137.
DOI Link
1405
bilateral filter
BibRef
Kwon, D.J.[Dong-Jin],
Niethammer, M.,
Akbari, H.,
Bilello, M.,
Davatzikos, C.,
Pohl, K.M.,
PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration,
MedImg(33), No. 3, March 2014, pp. 651-667.
IEEE DOI
1404
biomedical MRI
BibRef
Govindaraj, V.[Vishnuvarthanan],
Murugan, P.R.[Pallikonda Rajasekaran],
A complete automated algorithm for segmentation of tissues and
identification of tumor region in T1, T2, and FLAIR brain images
using optimization and clustering techniques,
IJIST(24), No. 4, 2014, pp. 313-325.
DOI Link
1411
image segmentation
BibRef
Balasubramani, P.[Perumal],
Murugan, P.R.[Pallikonda Rajasekaran],
Efficient image compression techniques for compressing multimodal
medical images using neural network radial basis function approach,
IJIST(25), No. 2, 2015, pp. 115-122.
DOI Link
1506
MRI images
BibRef
Militello, C.[Carmelo],
Rundo, L.[Leonardo],
Vitabile, S.[Salvatore],
Russo, G.[Giorgio],
Pisciotta, P.[Pietro],
Marletta, F.[Francesco],
Ippolito, M.[Massimo],
D'Arrigo, C.[Corrado],
Midiri, M.[Massimo],
Gilardi, M.C.[Maria Carla],
Gamma Knife treatment planning: MR brain tumor segmentation and
volume measurement based on unsupervised Fuzzy C-Means clustering,
IJIST(25), No. 3, 2015, pp. 213-225.
DOI Link
1509
semi-automatic segmentation
BibRef
Stefano, A.[Alessandro],
Vitabile, S.[Salvatore],
Russo, G.[Giorgio],
Ippolito, M.[Massimo],
Marletta, F.[Franco],
D'Arrigo, C.[Corrado],
D'Urso, D.[Davide],
Sabini, M.G.[Maria Gabriella],
Gambino, O.[Orazio],
Pirrone, R.[Roberto],
Ardizzone, E.[Edoardo],
Gilardi, M.C.[Maria Carla],
An Automatic Method for Metabolic Evaluation of Gamma Knife Treatments,
CIAP15(I:579-589).
Springer DOI
1511
BibRef
Menze, B.H.,
Jakab, A.,
Bauer, S.,
Kalpathy-Cramer, J.,
Farahani, K.,
Kirby, J.,
Burren, Y.,
Porz, N.,
Slotboom, J.,
Wiest, R.,
Lanczi, L.,
Gerstner, E.,
Weber, M.A.,
Arbel, T.,
Avants, B.B.,
Ayache, N.,
Buendia, P.,
Collins, D.L.,
Cordier, N.,
Corso, J.J.,
Criminisi, A.,
Das, T.,
Delingette, H.,
Demiralp, C.,
Durst, C.R.,
Dojat, M.,
Doyle, S.,
Festa, J.,
Forbes, F.,
Geremia, E.,
Glocker, B.,
Golland, P.,
Guo, X.[Xiaotao],
Hamamci, A.,
Iftekharuddin, K.M.,
Jena, R.,
John, N.M.,
Konukoglu, E.,
Lashkari, D.,
Mariz, J.A.,
Meier, R.,
Pereira, S.,
Precup, D.,
Price, S.J.,
Raviv, T.R.[T. Riklin],
Reza, S.M.S.,
Ryan, M.,
Sarikaya, D.,
Schwartz, L.,
Shin, H.C.[Hoo-Chang],
Shotton, J.,
Silva, C.A.,
Sousa, N.,
Subbanna, N.K.,
Szekely, G.,
Taylor, T.J.,
Thomas, O.M.,
Tustison, N.J.,
Unal, G.,
Vasseur, F.,
Wintermark, M.,
Ye, D.H.[Dong Hye],
Zhao, L.[Liang],
Zhao, B.[Binsheng],
Zikic, D.,
Prastawa, M.,
Reyes, M.,
Van Leemput, K.,
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS),
MedImg(34), No. 10, October 2015, pp. 1993-2024.
IEEE DOI
1511
benchmark testing
BibRef
Shanthakumar, P.,
Kumar, P.G.[P. Ganesh],
Computer aided brain tumor detection system using watershed
segmentation techniques,
IJIST(25), No. 4, 2015, pp. 297-301.
DOI Link
1512
enhancement
BibRef
Ai, Y.[Ye],
Miao, F.[Feng],
Hu, Q.M.[Qing-Mao],
Li, W.F.[Wei-Feng],
Multi-Feature Guided Brain Tumor Segmentation Based on Magnetic
Resonance Images,
IEICE(E98-D), No. 12, December 2015, pp. 2250-2256.
WWW Link.
1601
BibRef
Anitha, V.,
Murugavalli, S.,
Brain tumour classification using two-tier classifier with adaptive
segmentation technique,
IET-CV(10), No. 1, 2016, pp. 9-17.
DOI Link
1601
biomedical MRI
BibRef
Jui, S.L.,
Zhang, S.,
Xiong, W.,
Yu, F.,
Fu, M.,
Wang, D.,
Hassanien, A.E.[Aboul Ella],
Xiao, K.[Kai],
Brain MRI Tumor Segmentation with 3D Intracranial Structure
Deformation Features,
IEEE_Int_Sys(31), No. 2, March 2016, pp. 66-76.
IEEE DOI
1604
Biomedical image processing
BibRef
Xiao, K.[Kai],
Hassanien, A.E.[Aboul Ella],
Sun, Y.[Yan],
Ng, E.K.K.[Edwin Kit Keong],
Brain MR Image Tumor Segmentation with Ventricular Deformation,
ICIG11(297-302).
IEEE DOI
1109
BibRef
Stefano, A.[Alessandro],
Vitabile, S.[Salvatore],
Russo, G.[Giorgio],
Ippolito, M.[Massimo],
Marletta, F.[Franco],
d'Arrigo, C.[Corrado],
d'Urso, D.[Davide],
Gambino, O.[Orazio],
Pirrone, R.[Roberto],
Ardizzone, E.[Edoardo],
Gilardi, M.C.[Maria Carla],
A fully automatic method for biological target volume segmentation of
brain metastases,
IJIST(26), No. 1, 2016, pp. 29-37.
DOI Link
1604
random walk
BibRef
Pereira, S.,
Pinto, A.,
Alves, V.,
Silva, C.A.,
Brain Tumor Segmentation Using Convolutional Neural Networks in MRI
Images,
MedImg(35), No. 5, May 2016, pp. 1240-1251.
IEEE DOI
1605
Brain modeling
BibRef
Thirumurugan, P.,
Ramkumar, D.,
Batri, K.,
Raja, D.S.[D. Sundhara],
Automated detection of glioblastoma tumor in brain magnetic imaging
using ANFIS classifier,
IJIST(26), No. 2, 2016, pp. 151-156.
DOI Link
1606
contourlet transform
BibRef
Kathirvel, R.,
Batri, K.,
A computer-aided approach for meningioma brain tumor detection using
CANFIS classifier,
IJIST(27), No. 3, 2017, pp. 193-200.
DOI Link
1708
accuracy, brain tumor, classifier, contourlet transform, , features
BibRef
Kathirvel, R.,
Batri, K.,
Detection and diagnosis of meningioma brain tumor using ANFIS
classifier,
IJIST(27), No. 3, 2017, pp. 187-192.
DOI Link
1708
brain tumors, detection, diagnosis, features, , tissues
BibRef
Thirumurugan, P.,
Shanthakumar, P.,
Brain tumor detection and diagnosis using ANFIS classifier,
IJIST(26), No. 2, 2016, pp. 157-162.
DOI Link
1606
gray matter, white matter, CSF, brain tumor, brain tissue
BibRef
Kumarganesh, S.,
Suganthi, M.,
An efficient approach for brain image (tissue) compression based on
the position of the brain tumor,
IJIST(26), No. 4, 2016, pp. 237-242.
DOI Link
1701
brain tumor
BibRef
Thiruvenkadam, K.[Kalaiselvi],
Perumal, N.[Nagaraja],
Fully automatic method for segmentation of brain tumor from
multimodal magnetic resonance images using wavelet transformation and
clustering technique,
IJIST(26), No. 4, 2016, pp. 305-314.
DOI Link
1701
clustering, fuzzy c-means, segmentation, tumor, wavelet
BibRef
Vishnuvarthanan, G.,
Rajasekaran, M.P.[M. Pallikonda],
Vishnuvarthanan, N.A.[N. Anitha],
Prasath, T.A.[T. Arun],
Kannan, M.,
Tumor detection in T1, T2, FLAIR and MPR brain images using a
combination of optimization and fuzzy clustering improved by
seed-based region growing algorithm,
IJIST(27), No. 1, 2017, pp. 33-45.
DOI Link
1704
MPSO-based FCM
BibRef
Angulakshmi, M.,
Priya, G.G.L.[G.G. Lakshmi],
Automated brain tumour segmentation techniques: A review,
IJIST(27), No. 1, 2017, pp. 66-77.
DOI Link
1704
review
BibRef
Sivakumar, P.,
Ganeshkumar, P.,
CANFIS based glioma brain tumor classification and retrieval system
for tumor diagnosis,
IJIST(27), No. 2, 2017, pp. 109-117.
DOI Link
1706
brain tumor, CANFIS, classification, retrieval, segmentation
BibRef
Farhi, L.[Lubna],
Yusuf, A.[Adeel],
Raza, R.H.[Rana Hammad],
Adaptive stochastic segmentation via energy-convergence for brain
tumor in MR images,
JVCIR(46), No. 1, 2017, pp. 303-311.
Elsevier DOI
1706
Active, contours
BibRef
Kaur, T.[Taranjit],
Saini, B.S.[Barjinder Singh],
Gupta, S.[Savita],
Quantitative metric for MR brain tumour grade classification using
sample space density measure of analytic intrinsic mode function
representation,
IET-IPR(11), No. 8, August 2017, pp. 620-632.
DOI Link
1708
BibRef
Ramakrishnan, T.,
Sankaragomathi, B.,
A professional estimate on the computed tomography brain tumor images
using SVM-SMO for classification and MRG-GWO for segmentation,
PRL(94), No. 1, 2017, pp. 163-171.
Elsevier DOI
1708
Feature, extraction
BibRef
Rajinikanth, V.,
Satapathy, S.C.[Suresh Chandra],
Fernandes, S.L.[Steven Lawrence],
Nachiappan, S.,
Entropy based segmentation of tumor from brain MR images:
A study with teaching learning based optimization,
PRL(94), No. 1, 2017, pp. 87-95.
Elsevier DOI
1708
BibRef
Arunachalam, M.[Murugan],
Savarimuthu, S.R.[Sabeenian Royappan],
An efficient and automatic glioblastoma brain tumor detection using
shift-invariant shearlet transform and neural networks,
IJIST(27), No. 3, 2017, pp. 216-226.
DOI Link
1708
brain image, NSCT multiresolution, SIST enhancement,
texture features, , classification
BibRef
Rufus, N.H.A.[N. Herald Anantha],
Selvathi, D.,
Performance analysis of computer aided brain tumor detection system
using ANFIS classifier,
IJIST(27), No. 3, 2017, pp. 273-280.
DOI Link
1708
brain image, classifier, features, GLCM, , tumor
BibRef
Gupta, M.[Manu],
Rajagopalan, V.[Venkateswaran],
Pioro, E.P.[Erik P.],
Prabhakar Rao, B.V.V.S.N.,
Volumetric analysis of MR images for glioma classification and their
effect on brain tissues,
SIViP(11), No. 7, October 2017, pp. 1337-1345.
Springer DOI
1708
BibRef
Urien, H.[Hélène],
Buvat, I.[Irène],
Rougon, N.[Nicolas],
Soussan, M.[Michaël],
Bloch, I.[Isabelle],
Brain Lesion Detection in 3D PET Images Using Max-Trees and a New
Spatial Context Criterion,
ISMM17(455-466).
Springer DOI
1706
BibRef
Bento, M.[Mariana],
Sym, Y.[Yan],
Frayne, R.[Richard],
Lotufo, R.[Roberto],
Rittner, L.[Letícia],
Probabilistic Segmentation of Brain White Matter Lesions Using
Texture-Based Classification,
ICIAR17(71-78).
Springer DOI
1706
BibRef
Salvador, R.,
Fabelo, H.,
Lazcano, R.,
Ortega, S.,
Madroñal, D.,
Callicó, G.M.,
Juárez, E.,
Sanz, C.,
Demo: HELICoiD tool demonstrator for real-time brain cancer detection,
DASIP16(237-238)
IEEE DOI
1704
biological tissues
BibRef
Mukherjee, S.[Sabyasachi],
Bandyopadhyay, O.[Oishila],
Biswas, A.[Arindam],
Automated Brain Tumor Diagnosis and Severity Analysis from Brain MRI,
CompIMAGE16(194-207).
Springer DOI
1704
BibRef
Réjichi, S.,
Chaabane, F.,
Brain tumor extraction using graph based classification of MRI time
series for diagnostic assistance,
ISIVC16(320-324)
IEEE DOI
1704
Feature extraction
BibRef
Jaroudi, R.[Rym],
Baravdish, G.[George],
Åström, F.[Freddie],
Johansson, B.T.[B. Tomas],
Source Localization of Reaction-Diffusion Models for Brain Tumors,
GCPR16(414-425).
Springer DOI
1611
BibRef
Dvorák, P.[Pavel],
Menze, B.[Bjoern],
Local Structure Prediction with Convolutional Neural Networks for
Multimodal Brain Tumor Segmentation,
MCV15(59-71).
Springer DOI
1608
BibRef
Swiderska, Z.[Zaneta],
Markiewicz, T.[Tomasz],
Grala, B.[Bartlomiej],
Kozlowski, W.[Wojciech],
Texture and Mathematical Morphology for Hot-Spot Detection in Whole
Slide Images of Meningiomas and Oligodendrogliomas,
CAIP15(II:1-12).
Springer DOI
1511
BibRef
De Marsico, M.[Maria],
Nappi, M.[Michele],
Riccio, D.[Daniel],
Entropy-Based Automatic Segmentation and Extraction of Tumors from
Brain MRI Images,
CAIP15(II:195-206).
Springer DOI
1511
BibRef
Pedoia, V.[Valentina],
Balbi, S.[Sergio],
Binaghi, E.[Elisabetta],
Fully Automatic Brain Tumor Segmentation by Using Competitive EM and
Graph Cut,
CIAP15(I:568-578).
Springer DOI
1511
BibRef
Roy, S.[Shaswati],
Maji, P.[Pradipta],
A New Post-processing Method to Detect Brain Tumor Using Rough-Fuzzy
Clustering,
PReMI15(407-417).
Springer DOI
1511
BibRef
Oh, K.H.[Kang Han],
Kim, S.H.[Soo Hyung],
Lee, M.[Myungeun],
Tumor detection on brain MR images using regional features: Method
and preliminary results,
FCV15(1-4)
IEEE DOI
1506
biomedical MRI
BibRef
Martinez-Cortes, T.[Tomas],
Fernandez-Torres, M.A.[Miguel Angel],
Jimenez-Moreno, A.[Amaya],
Gonzalez-Diaz, I.[Ivan],
Diaz-de-Maria, F.[Fernando],
Guzman-De-Villoria, J.A.[Juan Adan],
Fernandez, P.[Pilar],
A Bayesian model for brain tumor classification using clinical-based
features,
ICIP14(2779-2783)
IEEE DOI
1502
Bayes methods
BibRef
Al-Shaikhli, S.D.S.[Saif Dawood Salman],
Yang, M.Y.[Michael Ying],
Rosenhahn, B.[Bodo],
Brain tumor classification using sparse coding and dictionary
learning,
ICIP14(2774-2778)
IEEE DOI
1502
Brain
BibRef
And:
Coupled Dictionary Learning for Automatic Multi-Label Brain Tumor
Segmentation in Flair MRI images,
ISVC14(I: 489-500).
Springer DOI
1501
BibRef
Havaei, M.[Mohammad],
Jodoin, P.M.[Pierre-Marc],
Larochelle, H.[Hugo],
Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN
Classification,
ICPR14(556-561)
IEEE DOI
1412
Brain
BibRef
Zhou, M.[Mu],
Hall, L.O.[Lawrence O.],
Goldgof, D.B.[Dmitry B.],
Exploring Brain Tumor Heterogeneity for Survival Time Prediction,
ICPR14(580-585)
IEEE DOI
1412
Accuracy
BibRef
Subbanna, N.[Nagesh],
Precup, D.[Doina],
Arbel, T.[Tal],
Iterative Multilevel MRF Leveraging Context and Voxel Information for
Brain Tumour Segmentation in MRI,
CVPR14(400-405)
IEEE DOI
1409
BibRef
Drakopoulos, F.[Fotis],
Chrisochoides, N.P.[Nikos P.],
A Parallel Adaptive Physics-Based Non-rigid Registration Framework for
Brain Tumor Resection,
CompIMAGE14(57-68).
Springer DOI
1407
BibRef
Nasir, M.[Muhammad],
Baig, A.[Asim],
Khanum, A.[Aasia],
Brain Tumor Classification in MRI Scans Using Sparse Representation,
ICISP14(629-637).
Springer DOI
1406
BibRef
Kvet, M.[Michal],
Kvet, M.[Marek],
Matiasko, K.[Karol],
Application for brain tumour imaging,
WSSIP14(47-50)
1406
Atmospheric measurements
BibRef
Parisot, S.[Sarah],
Wells, W.[William],
Chemouny, S.[Stephane],
Duffau, H.[Hugues],
Paragios, N.[Nikos],
Uncertainty-Driven Efficiently-Sampled Sparse Graphical Models for
Concurrent Tumor Segmentation and Atlas Registration,
ICCV13(641-648)
IEEE DOI
1403
BibRef
Parisot, S.[Sarah],
Duffau, H.[Hugues],
Chemouny, S.[Stephane],
Paragios, N.[Nikos],
Graph-based detection, segmentation and characterization
of brain tumors,
CVPR12(988-995).
IEEE DOI
1208
BibRef
Salah, M.B.[Mohamed Ben],
Diaz, I.[Idanis],
Greiner, R.[Russell],
Boulanger, P.[Pierre],
Hoehn, B.[Bret],
Fully Automated Brain Tumor Segmentation Using Two MRI Modalities,
ISVC13(I:30-39).
Springer DOI
1310
BibRef
Bauer, S.[Stefan],
Tessier, J.[Jean],
Krieter, O.[Oliver],
Nolte, L.P.[Lutz P.],
Reyes, M.[Mauricio],
Integrated Spatio-Temporal Segmentation of Longitudinal Brain Tumor
Imaging Studies,
MCV13(74-83).
Springer DOI
1405
BibRef
Sridhar, D.,
Krishna, I.M.[IV. Murali],
Brain Tumor Classification using Discrete Cosine Transform and
Probabilistic Neural Network,
ICSIPR13(92-96).
IEEE DOI
1304
BibRef
Geremia, E.[Ezequiel],
Menze, B.H.[Bjoern H.],
Prastawa, M.[Marcel],
Weber, M.A.,
Criminisi, A.[Antonio],
Brain Tumor Cell Density Estimation from Multi-modal MR Images Based on
a Synthetic Tumor Growth Model,
MCVM12(273-282).
Springer DOI
1305
BibRef
Wei, Z.W.[Zhen-Wen],
Zhang, C.M.[Cai-Ming],
Yang, X.Q.[Xing-Qiang],
Zhang, X.F.[Xiao-Feng],
Segmentation of Brain Tumors in CT Images Using Level Sets,
ISVC12(I: 22-31).
Springer DOI
1209
BibRef
Gasmi, K.[Karim],
Kharrat, A.[Ahmed],
Messaoud, M.B.[Mohamed Ben],
Abid, M.[Mohamed],
Automated Segmentation of Brain Tumor Using Optimal Texture Features
and Support Vector Machine Classifier,
ICIAR12(II: 230-239).
Springer DOI
1206
BibRef
Fazlollahi, A.,
Dowson, N.,
Meriaudeau, F.,
Rose, S.,
Fay, M.,
Thomas, P.,
Taylor, Z.,
Gal, Y.,
Coultard, A.,
Winter, C.,
MacFarlane, D.,
Salvado, O.,
Crozier, S.,
Bourgeat, P.,
Automatic Brain Tumour Segmentation in 18F-FDOPA PET Using PET/MRI
Fusion,
DICTA11(325-329).
IEEE DOI
1205
BibRef
Tran, L.[Loc],
Banerjee, D.[Deb],
Sun, X.Y.[Xiao-Yan],
Wang, J.H.[Ji-Hong],
Kumar, A.J.[Ashok J.],
Vinning, D.[David],
McKenzie, F.D.[Frederic D.],
Li, Y.H.[Yao-Hang],
Li, J.[Jiang],
A Large-Scale Manifold Learning Approach for Brain Tumor Progression
Prediction,
MLMI11(265-272).
Springer DOI
1109
BibRef
Zoghbi, J.M.,
Mamede, M.H.,
Jackowski, M.P.,
Computer-assisted segmentation of brain tumor lesions from
multi-sequence Magnetic Resonance Imaging using the Mumford-Shah model,
IVCNZ10(1-6).
IEEE DOI
1203
BibRef
Li, H.M.[Hong-Ming],
Song, M.[Ming],
Fan, Y.[Yong],
Segmentation of Brain Tumors in Multi-parametric MR Images via Robust
Statistic Information Propagation,
ACCV10(IV: 606-617).
Springer DOI
1011
BibRef
Wang, T.[Tao],
Cheng, I.[Irene],
Basu, A.[Anup],
Fully automatic brain tumor segmentation using a normalized Gaussian
Bayesian Classifier and 3D Fluid Vector Flow,
ICIP10(2553-2556).
IEEE DOI
1009
BibRef
Cho, W.[Wanhyun],
Park, J.[Jonghyun],
Park, S.[Soonyoung],
Kim, S.Y.[Sooh-Yung],
Kim, S.[Sunworl],
Ahn, G.[Gukdong],
Lee, M.[Myungeun],
Lee, G.S.[Guee-Sang],
Level-Set Segmentation of Brain Tumors Using a New Hybrid Speed
Function,
ICPR10(1545-1548).
IEEE DOI
1008
BibRef
Gooya, A.[Ali],
Biros, G.[George],
Davatzikos, C.[Christos],
An EM algorithm for brain tumor image registration:
A tumor growth modeling based approach,
MMBIA10(39-46).
IEEE DOI
1006
BibRef
Chen, V.[Victor],
Ruan, S.[Su],
Graph cut segmentation technique for MRI brain tumor extraction,
IPTA10(284-287).
IEEE DOI
1007
BibRef
Khandani, M.K.[Masoumeh Kalantari],
Bajcsy, R.[Ruzena],
Fallah, Y.P.[Yaser P.],
Automated Segmentation of Brain Tumors in MRI Using Force Data
Clustering Algorithm,
ISVC09(I: 317-326).
Springer DOI
0911
BibRef
Verma, N.K.,
Gupta, P.,
Agrawal, P.,
Cui, Y.[Yan],
MRI brain image segmentation for spotting tumors using improved
mountain clustering approach,
AIPR09(1-8).
IEEE DOI
0910
BibRef
Avola, D.[Danilo],
Cinque, L.[Luigi],
Encephalic NMR Tumor Diversification by Textural Interpretation,
CIAP09(394-403).
Springer DOI
0909
BibRef
Cadena, R.M.[Ruben Machucho],
de la Cruz Rodriguez, S.[Sergio],
Bayro-Corrochano, E.[Eduardo],
Rendering of brain tumors using endoneurosonography,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Song, Y.Q.[Yang-Qiu],
Zhang, C.S.[Chang-Shui],
Lee, J.G.[Jian-Guo],
Wang, F.[Fei],
A Discriminative Method For Semi-Automated Tumorous Tissues
Segmentation of MR Brain Images,
MMBIA06(79).
IEEE DOI
0609
BibRef
Saxena, V.,
Nielsen, J.F.,
Gonzalez-Gomez, I.,
Karapetyan, G.,
Khankaldyyan, V.,
Nelson, M.D.,
Laug, W.E.,
A noninvasive, multimodality approach based on MRS and MRI techniques
for monitoring intracranial brain tumor angiogenesis,
AIPR05(127-132).
IEEE DOI
0510
BibRef
Lee, C.H.[Chi-Hoon],
Schmidt, M.[Mark],
Murtha, A.[Albert],
Bistritz, A.[Aalo],
Sander, J.[Jöerg],
Greiner, R.[Russell],
Segmenting Brain Tumors with Conditional Random Fields and Support
Vector Machines,
CVBIA05(469-478).
Springer DOI
0601
BibRef
Dam, E.,
Loog, M.,
Letteboer, M.,
Integrating automatic and interactive brain tumor segmentation,
ICPR04(III: 790-793).
IEEE DOI
0409
BibRef
Leung, C.C.,
Chen, W.F.,
Kwok, P.C.K.,
Chan, F.H.Y.,
Brain tumor boundary detection in MR image with generalized fuzzy
operator,
ICIP03(II: 1057-1060).
IEEE DOI
0312
BibRef
Capelle, A.S.,
Colot, O.,
Fernandez-Maloigne, C.,
Segmentation of multi-modality MR images by means of evidence theory
for 3d reconstruction of brain tumors,
ICIP02(II: 773-776).
IEEE DOI
0210
BibRef
Capelle, A.S.,
Alata, O.,
Fernandez-Maloigne, C.,
Ferrie, J.,
Unsupervised Algorithm for the Segmentation of Three-dimensional
Magnetic Resonance Brain Images,
ICIP01(III: 1047-1050).
IEEE DOI
0108
BibRef
Capelle, A.S.,
Alata, O.,
Fernandez-Maloigne, C.,
Lefevre, S.,
Unsupervised Segmentation for Automatic Detection of Brain Tumors in
MRI,
ICIP00(Vol I: 613-616).
IEEE DOI
0008
BibRef
Ho, S.[Sean],
Bullitt, E.,
Gerig, G.,
Level-set evolution with region competition:
Automatic 3-D segmentation of brain tumors,
ICPR02(I: 532-535).
IEEE DOI
0211
BibRef
Lorenzen, P.,
Joshi, S.,
Gerig, G.,
Bullitt, E.,
Tumor-Induced Structural and Radiometric Asymmetry in Brain Images,
MMBIA01(xx-yy).
0110
BibRef
Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Brain, Cortex, Alzheimer's Disease, Dementia .