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Breast cancer, Deformable models, Image segmentation, Shape,
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1901
Lesions, Feature extraction, Ultrasonic imaging,
Image edge detection, Breast cancer,
convolutional neural networks
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1903
Training, Cancer, Ultrasonic imaging, Machine learning, Breast,
Image segmentation, Lesions, Breast ultrasound,
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1907
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2004
Cancer, Sensitivity, Breast, Ultrasonic imaging, Lesions,
Biomedical imaging, threshold loss
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Weijers, G.,
Groenhuis, V.,
Mann, R.M.,
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2104
Breast, Ultrasonic imaging, Lesions, Magnetic resonance imaging,
Imaging, Biomedical imaging, Breast,
3D US
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IEEE DOI
2109
Videos, Solid modeling, Tumors, Brightness, Deep learning,
Feature extraction, Breast cancer, 3D convolution,
domain knowledge
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SMU-Net: Saliency-Guided Morphology-Aware U-Net for Breast Lesion
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IEEE DOI
2202
Lesions, Image segmentation, Streaming media, Breast,
Ultrasonic imaging, Image edge detection, Shape,
deep learning
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2203
Computer-aided diagnosis, Breast ultrasound,
Deep convolution neural network, Feature combination
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Real-Time Ultrasound Detection of Breast Microcalcifications Using
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MedImg(41), No. 5, May 2022, pp. 1300-1308.
IEEE DOI
2205
Wires, Imaging, Acoustics, Surface roughness, Rough surfaces,
Real-time systems, Doppler effect, Breast microcalcification,
biopsy guidance
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Zhang, H.J.[Hui-Juan],
Bo, W.[Wei],
Wang, D.[Depeng],
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Huang, C.[Chuqin],
Nyayapathi, N.[Nikhila],
Zheng, E.[Emily],
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Gong, Y.Y.[Yi-Yang],
Yao, J.J.[Jun-Jie],
Xu, W.Y.[Wen-Yao],
Xia, J.[Jun],
Deep-E: A Fully-Dense Neural Network for Improving the Elevation
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MedImg(41), No. 5, May 2022, pp. 1279-1288.
IEEE DOI
2205
Image resolution, Transducers, Imaging,
Convolution, Training, Image reconstruction, Breast imaging,
resolution enhancement
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Mishra, A.K.[Arnab Kumar],
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Bandyopadhyay, S.[Sivaji],
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CR-SSL: A closely related self-supervised learning based approach for
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IJIST(32), No. 4, 2022, pp. 1209-1220.
DOI Link
2207
breast cancer, breast ultrasound, deep learning, self-supervised learning
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Singh, B.K.[Bikesh Kumar],
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Real-time automated segmentation of breast lesions using CNN-based
deep learning paradigm: Investigation on mammogram and ultrasound,
IJIST(32), No. 4, 2022, pp. 1084-1100.
DOI Link
2207
computer-aided segmentation, convolutional neural network,
deep learning, mammogram, ultrasound
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Fei, X.Y.[Xiao-Yan],
Zhou, S.C.[Shi-Chong],
Han, X.M.[Xiang-Min],
Wang, J.[Jun],
Ying, S.H.[Shi-Hui],
Chang, C.[Cai],
Zhou, W.J.[Wei-Jun],
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Doubly supervised parameter transfer classifier for diagnosis of
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PR(120), 2021, pp. 108139.
Elsevier DOI
2109
Doubly supervised parameter transfer classifier,
Support vector machine plus, Breast cancer
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Han, X.M.[Xiang-Min],
Fei, X.Y.[Xiao-Yan],
Wang, J.[Jun],
Zhou, T.[Tao],
Ying, S.H.[Shi-Hui],
Shi, J.[Jun],
Shen, D.G.[Ding-Gang],
Doubly Supervised Transfer Classifier for Computer-Aided Diagnosis
With Imbalanced Modalities,
MedImg(41), No. 8, August 2022, pp. 2009-2020.
IEEE DOI
2208
Solid modeling, Imaging, Classification algorithms, Diseases,
Magnetic resonance imaging, Knowledge transfer,
block-diagonal low-rank
BibRef
Karunanayake, N.[Nalan],
Lohitvisate, W.[Wanrudee],
Makhanov, S.S.[Stanislav S.],
Artificial life for segmentation of fusion ultrasound images of
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PR(131), 2022, pp. 108838.
Elsevier DOI
2208
Artificial life, Fusion image, Medical image segmentation,
Genetic algorithm, Ultrasound images, Breast cancer
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Li, X.F.[Xiao-Feng],
Sang, Y.P.[Yu-Peng],
Ma, X.[Xianmin],
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Quantitative feature classification for breast ultrasound images
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IET-IPR(17), No. 5, 2023, pp. 1417-1426.
DOI Link
2304
breast ultrasound images, feature classification,
image reconstruction, improved naive bayes, texture feature
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Li, Y.F.[Yan-Feng],
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Cheng, Z.Y.[Zhan-Yi],
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Semi-Supervised Learning for ABUS Tumor Detection Using Deep Learning
Methodxo,
IET-IPR(17), No. 7, 2023, pp. 2113-2126.
DOI Link
2305
automated breast ultrasound, copy-paste strategy,
semi-supervised learning, tumor detection
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Chen, G.P.[Gong-Ping],
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Dai, Y.[Yu],
Zhang, J.X.[Jian-Xun],
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AAU-Net: An Adaptive Attention U-Net for Breast Lesions Segmentation
in Ultrasound Images,
MedImg(42), No. 5, May 2023, pp. 1289-1300.
IEEE DOI
2305
Image segmentation, Convolution, Breast, Lesions, Ultrasonic imaging,
Kernel, Breast tumors, Ultrasound images,
deep learning
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Chen, Y.X.[Yi-Xiong],
Zhang, C.H.[Chun-Hui],
Ding, C.H.Q.[Chris H. Q.],
Liu, L.[Li],
Generating and Weighting Semantically Consistent Sample Pairs for
Ultrasound Contrastive Learning,
MedImg(42), No. 5, May 2023, pp. 1388-1400.
IEEE DOI
2305
Videos, Medical diagnostic imaging, Semantics, Training,
Visualization, Representation learning, Ultrasonic imaging, breast tumor
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Wu, H.[Huisi],
Huang, X.T.[Xiao-Ting],
Guo, X.R.[Xin-Rong],
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Qin, J.[Jing],
Cross-Image Dependency Modeling for Breast Ultrasound Segmentation,
MedImg(42), No. 6, June 2023, pp. 1619-1631.
IEEE DOI
2306
Lesions, Image segmentation, Semantics, Context modeling,
Task analysis, Feature extraction, Ultrasonic imaging,
deep learning
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Mo, Y.H.[Yu-Hao],
Han, C.[Chu],
Liu, Y.[Yu],
Liu, M.[Min],
Shi, Z.W.[Zhen-Wei],
Lin, J.[Jiatai],
Zhao, B.C.[Bing-Chao],
Huang, C.W.[Chun-Wang],
Qiu, B.J.[Bing-Jiang],
Cui, Y.[Yanfen],
Wu, L.[Lei],
Pan, X.P.[Xi-Peng],
Xu, Z.[Zeyan],
Huang, X.M.[Xiao-Mei],
Li, Z.H.[Zhen-Hui],
Liu, Z.Y.[Zai-Yi],
Wang, Y.[Ying],
Liang, C.H.[Chang-Hong],
HoVer-Trans: Anatomy-Aware HoVer-Transformer for ROI-Free Breast
Cancer Diagnosis in Ultrasound Images,
MedImg(42), No. 6, June 2023, pp. 1696-1706.
IEEE DOI
2306
Breast cancer, Breast, Solid modeling, Transformers, Lesions,
Hospitals, Computational modeling, Breast cancer diagnosis,
anatomical structure
BibRef
Luo, Y.Z.[Yao-Zhong],
Huang, Q.H.[Qing-Hua],
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Classification of tumor in one single ultrasound image via a novel
multi-view learning strategy,
PR(143), 2023, pp. 109776.
Elsevier DOI
2310
Image classification, Deep learning, Multi-view learning,
Breast cancer recognition
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Qi, W.B.[Wen-Bo],
Wu, H.C.,
Chan, S.C.,
MDF-Net: A Multi-Scale Dynamic Fusion Network for Breast Tumor
Segmentation of Ultrasound Images,
IP(32), 2023, pp. 4842-4855.
IEEE DOI
2310
BibRef
Özcan, H.[Hakan],
BUS-CAD: A computer-aided diagnosis system for breast tumor
classification in ultrasound images using grid-search-optimized
machine learning algorithms with extended and Boruta-selected
features,
IJIST(33), No. 5, 2023, pp. 1480-1493.
DOI Link
2310
all-feature selection, breast cancer, classification,
iterative correlation analysis, ultrasound
BibRef
Rautela, K.[Kamakshi],
Kumar, D.[Dinesh],
Kumar, V.[Vijay],
Active contour and texture features hybrid model for breast cancer
detection from ultrasonic images,
IJIST(33), No. 6, 2023, pp. 2061-2072.
DOI Link
2311
active contour, breast cancer, feature extraction,
texture feature, ultrasound
BibRef
Rengarajan, R.[Rajeshwari],
Devasena, M.S.G.[M. S. Geetha],
Gopu, G.,
Enhanced grasshopper optimization-based selection of ultrasound and
elastography features for breast lesion classification,
IJIST(33), No. 6, 2023, pp. 2142-2156.
DOI Link
2311
breast cancer, computer-aided diagnosis, elastography,
enhanced grasshopper optimization algorithm, image segmentation
BibRef
Li, H.Y.[Hai-Yan],
Wang, X.[Xu],
Tang, Y.[Yiyin],
Ye, S.H.[Shu-Hua],
BCUIS-Net: A breast cancer ultrasound image segmentation network via
boundary-aware and shape feature fusion,
IJIST(34), No. 1, 2024, pp. e23011.
DOI Link
2401
boundary aware module, breast lesion segmentation,
shape feature fusion module, shape fusion loss
BibRef
You, G.[Guizeng],
Yang, X.[Xinwu],
Lee, X.[Xuanbo],
Zhu, K.Q.[Kong-Qiang],
EfficientUNet: An efficient solution for breast tumour segmentation
in ultrasound images,
IET-IPR(18), No. 2, 2024, pp. 523-534.
DOI Link
2402
cancer, convolutional neural networks, image segmentation, ultrasonic imaging
BibRef
Atrey, K.[Kushangi],
Singh, B.K.[Bikesh Kumar],
Bodhey, N.K.[Narendra Kuber],
Integration of ultrasound and mammogram for multimodal classification
of breast cancer using hybrid residual neural network and machine
learning,
IVC(145), 2024, pp. 104987.
Elsevier DOI
2405
Breast cancer, Feature fusion, Multimodal classification,
Transfer learning, Machine learning
BibRef
Dar, M.F.[Mohsin Furkh],
Ganivada, A.[Avatharam],
Deep learning and genetic algorithm-based ensemble model for feature
selection and classification of breast ultrasound images,
IVC(146), 2024, pp. 105018.
Elsevier DOI
2405
Deep learning, Feature selection, Ultrasound imaging,
Breast cancer, Genetic algorithm
BibRef
Yao, R.[Ruihan],
He, B.B.[Bing-Bing],
Zhang, Y.F.[Yu-Feng],
Li, Z.Y.[Zhi-Yao],
Zhu, J.Y.[Jing-Ying],
Lang, X.[Xun],
Optimal fusion of features from decomposed ultrasound RF data with
adaptive weighted ensemble classifier to improve breast lesion
classification,
IVC(146), 2024, pp. 105045.
Elsevier DOI
2405
BibRef
Wang, J.[Jian],
Qiao, L.[Liang],
Zhou, S.[Shichong],
Zhou, J.[Jin],
Wang, J.[Jun],
Li, J.C.[Jun-Cheng],
Ying, S.H.[Shi-Hui],
Chang, C.[Cai],
Shi, J.[Jun],
Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers
With Partially Annotated Ultrasound Images,
MedImg(43), No. 7, July 2024, pp. 2509-2521.
IEEE DOI
2407
Training, Solid modeling, Lesions, Annotations, Task analysis,
Ultrasonic imaging, Tumors, Ultrasound image, region of interest,
weakly supervised learning
BibRef
Zhang, W.T.[Wan-Ting],
Wu, H.[Huisi],
Qin, J.[Jing],
Domesticating SAM for Breast Ultrasound Image Segmentation via
Spatial-frequency Fusion and Uncertainty Correction,
ECCV24(XXIII: 20-37).
Springer DOI
2412
BibRef
Ellis, J.[Jack],
Appiah, K.[Kofi],
Amankwaa-Frempong, E.[Emmanuel],
Kwok, S.C.[Sze Chai],
Classification of 2D Ultrasound Breast Cancer Images with Deep
Learning,
DEF-AI-MIA24(5167-5173)
IEEE DOI
2410
Deep learning, Ultrasonic imaging, Accuracy,
Computational modeling, Transfer learning, Breast cancer,
Deep Learning
BibRef
Tagnamas, J.[Jaouad],
Ramadan, H.[Hiba],
Yahyaouy, A.[Ali],
Tairi, H.[Hamid],
Joining CNNs and Transformer networks for enhanced breast ultrasound
image segmentation,
ISCV24(1-6)
IEEE DOI
2408
Image segmentation, Ultrasonic imaging, Accuracy,
Computer architecture, Feature extraction, Transformers, Decoding,
Swin-Transformer
BibRef
Adityan, M.K.L.[M. K. Laksath],
Sharma, H.[Himanchal],
Paul, A.[Angshuman],
Segmentation and Classification-Based Diagnosis of Tumors From Breast
Ultrasound Images Using Multibranch Unet,
ICIP23(2505-2509)
IEEE DOI
2312
BibRef
Zhang, H.Y.[Heng-Yu],
Xu, J.X.[Jing-Xuan],
Wang, M.Y.[Meng-Yu],
Li, Y.F.[Yan-Feng],
DenseATT-Net: Densely-Connected Neural Network with Intensive
Attention Modules for 3D ABUS Mass Segmentation,
ICIVC22(348-353)
IEEE DOI
2301
3D automated breast ultrasound.
Training, Image segmentation, Solid modeling, Ultrasonic imaging,
Shape, Computational modeling, Deep Learning, ABUS Images, Attention Module
BibRef
Zhuang, X.W.[Xian-Wei],
Zhu, X.[Xiner],
Hu, H.J.[Hao-Ji],
Yao, J.[Jincao],
Li, W.[Wei],
Yang, C.[Chen],
Wang, L.P.[Li-Ping],
Feng, N.[Na],
Xu, D.[Dong],
Residual Swin Transformer Unet with Consistency Regularization for
Automatic Breast Ultrasound Tumor Segmentation,
ICIP22(3071-3075)
IEEE DOI
2211
Image segmentation, Ultrasonic imaging, Semantics,
Self-supervised learning, Transformers, Decoding, Task analysis,
Convolutional Neural Networks
BibRef
Jin, S.B.[Song-Bai],
Lu, W.K.[Wen-Kai],
Monkam, P.[Patrice],
Deep Neural Network-Based Noisy Pixel Estimation for Breast
Ultrasound Segmentation,
ICIP22(1776-1780)
IEEE DOI
2211
Deep learning, Training, Image segmentation, Ultrasonic imaging,
Breast tumors, Annotations, Neural networks, Image segmentation,
breast tumor segmentation
BibRef
Wijata, A.M.[Agata M.],
Nalepa, J.[Jakub],
Unbiased Validation of the Algorithms for Automatic Needle
Localization in Ultrasound-Guided Breast Biopsies,
ICIP22(3571-3575)
IEEE DOI
2211
Location awareness, Ultrasonic imaging, Image analysis, Biopsy,
Breast biopsy, Needles, Lesions, Biopsy needle localization.
BibRef
Kim, D.[Daekyung],
Nam, C.M.[Chang-Mo],
Park, H.[Haesol],
Jang, M.J.[Mi-Jung],
Lee, K.J.[Kyong Joon],
Weakly supervised Branch Network with Template Mask for Classifying
Masses in 3D Automated Breast Ultrasound,
WACV22(3212-3219)
IEEE DOI
2202
Training, Image segmentation, Ultrasonic imaging,
Shape, Neural networks, Radiology,
Object Detection/Recognition/Categorization
BibRef
Huang, K.[Kuan],
Zhang, Y.T.[Ying-Tao],
Cheng, H.D.,
Xing, P.[Ping],
Zhang, B.[Boyu],
Semantic Segmentation of Breast Ultrasound Image with Pyramid Fuzzy
Uncertainty Reduction and Direction Connectedness Feature,
ICPR21(3357-3364)
IEEE DOI
2105
Deep learning, Weight measurement, Image segmentation, Uncertainty,
Ultrasonic imaging, Semantics, Breast, fuzzy logic,
direction connectedness
BibRef
Teixeira, J.F.[João F.],
Carreiro, A.M.[António M.],
Santos, R.M.[Rute M.],
Oliveira, H.P.[Hélder P.],
B-mode Ultrasound Breast Anatomy Segmentation,
ICIAR20(II:193-201).
Springer DOI
2007
BibRef
Torres, F.[Fabian],
Escalante-Ramirez, B.[Boris],
Olveres, J.[Jimena],
Yen, P.L.[Ping-Lang],
Lesion Detection in Breast Ultrasound Images Using a Machine Learning
Approach and Genetic Optimization,
IbPRIA19(I:289-301).
Springer DOI
1910
BibRef
Byra, M.[Michal],
Sznajder, T.[Tomasz],
Korzinek, D.[Danijel],
Piotrzkowska-Wroblewska, H.[Hanna],
Dobruch-Sobczak, K.[Katarzyna],
Nowicki, A.[Andrzej],
Marasek, K.[Krzysztof],
Impact of Ultrasound Image Reconstruction Method on Breast Lesion
Classification with Deep Learning,
IbPRIA19(I:41-52).
Springer DOI
1910
BibRef
Huang, K.,
Cheng, H.D.,
Zhang, Y.,
Zhang, B.,
Xing, P.,
Ning, C.,
Medical Knowledge Constrained Semantic Breast Ultrasound Image
Segmentation,
ICPR18(1193-1198)
IEEE DOI
1812
Tumors, Image segmentation, Training, Breast cancer,
Wavelet transforms, Biomedical imaging, Semantics,
conditional random field (CRF)
BibRef
Xu, F.,
Xian, M.,
Zhang, Y.,
Huang, K.,
Cheng, H.D.,
Zhang, B.,
Ding, J.,
Ning, C.,
Wang, Y.,
A Hybrid Framework for Tumor Saliency Estimation,
ICPR18(3935-3940)
IEEE DOI
1812
Tumors, Adaptation models, Estimation, Image segmentation,
Correlation, Visualization, Computer science, Breast ultrasound,
Automatic segmentation
BibRef
Rodríguez-Cristerna, A.[Arturo],
Gómez-Flores, W.[Wilfrido],
de Albuquerque-Pereira, W.C.[Wagner Coelho],
BUSAT: A MATLAB Toolbox for Breast Ultrasound Image Analysis,
MCPR17(268-277).
Springer DOI
1706
BibRef
Luo, Y.,
Han, S.,
Huang, Q.,
A Novel Graph-Based Segmentation Method for Breast Ultrasound Images,
DICTA16(1-6)
IEEE DOI
1701
Breast tumors
BibRef
Elawady, M.[Mohamed],
Sadek, I.[Ibrahim],
Shabayek, A.E.[Abd El_Rahman],
Pons, G.[Gerard],
Ganau, S.[Sergi],
Automatic Nonlinear Filtering and Segmentation for Breast Ultrasound
Images,
ICIAR16(206-213).
Springer DOI
1608
BibRef
Liu, S.B.[Song-Bo],
Cheng, H.D.,
Liu, Y.[Yan],
Huang, J.H.[Jian-Hua],
Zhang, Y.T.[Ying-Tao],
Tang, X.L.[Xiang-Long],
An effective computer aided diagnosis system using B-Mode and color
Doppler flow imaging for breast cancer,
VCIP13(1-4)
IEEE DOI
1402
biomedical ultrasonics
BibRef
Pons, G.[Gerard],
Martí, R.[Robert],
Ganau, S.[Sergi],
Sentís, M.[Melcior],
Martí, J.[Joan],
Feasibility Study of Lesion Detection Using Deformable Part Models in
Breast Ultrasound Images,
IbPRIA13(269-276).
Springer DOI
1307
BibRef
Harary, S.[Sivan],
Walach, E.[Eugene],
Identification of Malignant Breast Tumors Based on Acoustic Attenuation
Mapping of Conventional Ultrasound Images,
MCVM12(233-243).
Springer DOI
1305
BibRef
Rodrigues, R.[Rafael],
Pinheiro, A.[Antonio],
Braz, R.[Rui],
Pereira, M.[Manuela],
Moutinho, J.,
Towards breast ultrasound image segmentation using multi-resolution
pixel descriptors,
ICPR12(2833-2836).
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1302
BibRef
Hao, Z.H.[Zhi-Hui],
Wang, Q.A.[Qi-Ang],
Ren, H.B.[Hai-Bing],
Xu, K.H.[Kuan-Hong],
Seong, Y.K.[Yeong Kyeong],
Kim, J.[Jiyeun],
Multiscale superpixel classification for tumor segmentation in breast
ultrasound images,
ICIP12(2817-2820).
IEEE DOI
1302
BibRef
Pons, G.[Gerard],
Martí, J.[Joan],
Martí, R.[Robert],
Noble, J.A.[J. Alison],
Simultaneous Lesion Segmentation and Bias Correction in Breast
Ultrasound Images,
IbPRIA11(692-699).
Springer DOI
1106
BibRef
Bocchi, L.[Leonardo],
Rogai, F.[Francesco],
A Genetic Fuzzy Rules Learning Approach for Unseeded Segmentation in
Echography,
EvoIASP12(305-314).
Springer DOI
1204
BibRef
Earlier:
Segmentation of Ultrasound Breast Images:
Optimization of Algorithm Parameters,
EvoIASP11(163-172).
Springer DOI
1104
BibRef
Singh, M.S.[M. Suheshkumar],
Rajan, K.,
Vasu, R.M.,
Sijeesh, K.,
A novel two sources ultrasound modulated optical tomographic system for
screening breast cancer through elasticity characterization,
ICIP09(669-672).
IEEE DOI
0911
BibRef
Shan, J.[Juan],
Wang, Y.X.[Yu-Xuan],
Cheng, H.D.,
Completely automatic segmentation for breast ultrasound using
multiple-domain features,
ICIP10(1713-1716).
IEEE DOI
1009
BibRef
Earlier: A1, A3, A2:
A novel automatic seed point selection algorithm for breast ultrasound
images,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Ponomaryov, V.[Volodymyr],
Sanchez-Ramirez, J.L.[Jose Luis],
Juarez-Landin, C.[Cristina],
Optimal Wavelet Filters Selection for Ultrasound and Mammography
Compression,
CIARP08(62-69).
Springer DOI
0809
BibRef
Ye, Z.[Zhen],
Suri, J.[Jasjit],
Sun, Y.J.[Ya-Jie],
Janer, R.,
Four Image Interpolation Techniques for Ultrasound Breast Phantom Data
Acquired Using Fischer's Full Field Digital Mammography and Ultrasound
System (FFDMUS): A Comparative Approach,
ICIP05(II: 1238-1241).
IEEE DOI
0512
BibRef
Huang, Y.L.[Yu-Len],
Chen, D.R.[Dar-Ren],
Liu, Y.K.[Ya-Kuang],
Breast cancer diagnosis using image retrieval for different ultrasonic
systems,
ICIP04(V: 2957-2960).
IEEE DOI
0505
BibRef
Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Mammograms, Density Issues .