20.7.1.6 Mammograms, Ultrasound

Chapter Contents (Back)
Mammograms. Ultrasound. Medical, Applications.

Goldberg, V.[Victor],
Method and apparatus for diagnosis of breast tumors,
US_Patent5,260,871, Nov 9, 1993
WWW Link. BibRef 9311

Fatemi, M., Wold, L.E., Alizad, A., Greenleaf, J.F.,
Vibro-acoustic tissue mammography,
MedImg(21), No. 1, January 2002, pp. 1-8.
IEEE Top Reference. 0202
BibRef

Urban, M.W., Silva, G.T., Fatemi, M., Greenleaf, J.F.,
Multifrequency Vibro-Acoustography,
MedImg(25), No. 10, October 2006, pp. 1284-1295.
IEEE DOI 0609
BibRef

Joo, S., Yang, Y.S., Moon, W.K., Kim, H.C.,
Computer-Aided Diagnosis of Solid Breast Nodules: Use of an Artificial Neural Network Based on Multiple Sonographic Features,
MedImg(23), No. 10, October 2004, pp. 1292-1300.
IEEE Abstract. 0410
BibRef

Alizad, A., Fatemi, M., Wold, L.E., Greenleaf, J.F.,
Performance of Vibro-Acoustography in Detecting Microcalcifications in Excised Human Breast Tissue: A Study of 74 Tissue Samples,
MedImg(23), No. 3, March 2004, pp. 307-312.
IEEE Abstract. 0403
BibRef

Aguilo, M.A., Aquino, W., Brigham, J.C., Fatemi, M.,
An Inverse Problem Approach for Elasticity Imaging through Vibroacoustics,
MedImg(29), No. 4, April 2010, pp. 1012-1021.
IEEE DOI 1003
BibRef
And: Corrections: MedImg(29), No. 6, June 2010, pp. 1331-1331.
IEEE DOI 1007
BibRef

Madabhushi, A., Metaxas, D.N.,
Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions,
MedImg(22), No. 2, February 2003, pp. 155-169.
IEEE Top Reference. 0304
BibRef

Gefen, S., Tretiak, O.J., Piccoli, C.W., Donohue, K.D., Petropulu, A.P., Shankar, P.M., Dumane, V.A., Huang, L., Kutay, M.A., Genis, V., Forsberg, F., Reid, J.M., Goldberg, B.B.,
ROC analysis of ultrasound tissue characterization classifiers for breast cancer diagnosis,
MedImg(22), No. 2, February 2003, pp. 170-177.
IEEE Top Reference. 0304
BibRef

Oelze, M.L., O'Brien, W.D., Blue, J.P., Zachary, J.F.,
Differentiation and Characterization of Rat Mammary Fibroadenomas and 4T1 Mouse Carcinomas Using Quantitative Ultrasound Imaging,
MedImg(23), No. 6, June 2004, pp. 764-771.
IEEE Abstract. 0406
BibRef

Abbey, C.K., Zemp, R.J., Liu, J., Lindfors, K.K., Insana, M.F.,
Observer Efficiency in Discrimination Tasks Simulating Malignant and Benign Breast Lesions Imaged With Ultrasound,
MedImg(25), No. 2, February 2006, pp. 198-209.
IEEE DOI 0602
BibRef

Alemán-Flores, M.[Miguel], Álvarez-León, L.[Luis], Caselles, V.[Vicent],
Texture-Oriented Anisotropic Filtering and Geodesic Active Contours in Breast Tumor Ultrasound Segmentation,
JMIV(28), No. 1, May 2007, pp. 81-97.
Springer DOI 0710
BibRef

Alemán-Flores, M.[Miguel], Álvarez-León, L.[Luis],
Video Segmentation Through Multiscale Texture Analysis,
ICIAR04(II: 339-346).
Springer DOI 0409
BibRef
Earlier:
Texture Classification through Multiscale Orientation Histogram Analysis,
ScaleSpace03(479-493).
Springer DOI 0310
BibRef

Tang, A.M., Kacher, D.F., Lam, E.Y., Wong, K.K., Jolesz, F.A., Yang, E.S.,
Simultaneous Ultrasound and MRI System for Breast Biopsy: Compatibility Assessment and Demonstration in a Dual Modality Phantom,
MedImg(27), No. 2, February 2008, pp. 247-254.
IEEE DOI 0802
BibRef

Irwin, M.R., Downey, D.B., Gardi, L., Fenster, A.,
Registered 3-D Ultrasound and Digital Stereotactic Mammography for Breast Biopsy Guidance,
MedImg(27), No. 3, March 2008, pp. 391-401.
IEEE DOI 0803
BibRef

Drukker, K., Sennett, C.A., Giger, M.L.,
Automated Method for Improving System Performance of Computer-Aided Diagnosis in Breast Ultrasound,
MedImg(28), No. 1, January 2009, pp. 122-128.
IEEE DOI 0901
BibRef

Yeh, C.K.[Chih-Kuang], Chen, Y.S.[Yung-Sheng], Fan, W.C.[Wei-Che], Liao, Y.Y.[Yin-Yin],
A disk expansion segmentation method for ultrasonic breast lesions,
PR(42), No. 5, May 2009, pp. 596-606.
Elsevier DOI 0902
Speckle noise; Lesion contour; Disk expansion method; Computer-aided diagnosis (CAD) BibRef

Liu, B.[Bo], Cheng, H.D., Huang, J.H.[Jian-Hua], Tian, J.W.[Jia-Wei], Tang, X.L.[Xiang-Long], Liu, J.[Jiafeng],
Fully automatic and segmentation-robust classification of breast tumors based on local texture analysis of ultrasound images,
PR(43), No. 1, January 2010, pp. 280-298.
Elsevier DOI 0909
Texture classification; Support vector machine (SVM); Computer aided diagnosis (CAD); Breast ultrasound (BUS) imaging BibRef

Xian, M.[Min], Cheng, H.D., Zhang, Y.T.[Ying-Tao],
A Fully Automatic Breast Ultrasound Image Segmentation Approach Based on Neutro-Connectedness,
ICPR14(2495-2500)
IEEE DOI 1412
Pattern recognition BibRef

Liu, B.[Bo], Cheng, H.D., Huang, J.H.[Jian-Hua], Tian, J.W.[Jia-Wei], Tang, X.L.[Xiang-Long], Liu, J.F.[Jia-Feng],
Probability density difference-based active contour for ultrasound image segmentation,
PR(43), No. 6, June 2010, pp. 2028-2042.
Elsevier DOI 1003
Image segmentation; Active contour; Probability difference; Level set; Breast ultrasound (bus) imaging BibRef

Cheng, H.D., Shan, J.[Juan], Ju, W.[Wen], Guo, Y.H.[Yan-Hui], Zhang, L.[Ling],
Automated breast cancer detection and classification using ultrasound images: A survey,
PR(43), No. 1, January 2010, pp. 299-317.
Elsevier DOI 0909
computer-aided diagnosis; Automated breast cancer detection and classification; Ultrasound imaging; Feature extraction and selection; Classifiers BibRef

Takemura, A., Shimizu, A., Hamamoto, K.,
Discrimination of Breast Tumors in Ultrasonic Images Using an Ensemble Classifier Based on the AdaBoost Algorithm With Feature Selection,
MedImg(29), No. 3, March 2010, pp. 598-609.
IEEE DOI 1003
BibRef

Rodtook, A.[Annupan], Makhanov, S.S.[Stanislav S.],
Continuous force field analysis for generalized gradient vector flow field,
PR(43), No. 10, October 2010, pp. 3522-3538.
Elsevier DOI 1007
Gradient vector flow; Snakes; Segmentation; Ultrasound image; Breast tumor BibRef

Rodtook, A.[Annupan], Makhanov, S.S.[Stanislav S.],
Multi-feature gradient vector flow snakes for adaptive segmentation of the ultrasound images of breast cancer,
JVCIR(24), No. 8, 2013, pp. 1414-1430.
Elsevier DOI 1312
Active contours BibRef

Chucherd, S.[Sirikan], Rodtook, A.[Annupan], Makhanov, S.S.[Stanislav S.],
Phase Portrait Analysis for Multiresolution Generalized Gradient Vector Flow,
IEICE(E93-D), No. 10, October 2010, pp. 2822-2835.
WWW Link. 1011
BibRef

Tan, T., Platel, B., Huisman, H., Sanchez, C.I., Mus, R., Karssemeijer, N.,
Computer-Aided Lesion Diagnosis in Automated 3-D Breast Ultrasound Using Coronal Spiculation,
MedImg(31), No. 5, May 2012, pp. 1034-1042.
IEEE DOI 1202
BibRef

Tan, T., Platel, B., Mus, R., Tabar, L., Mann, R.M., Karssemeijer, N.,
Computer-Aided Detection of Cancer in Automated 3-D Breast Ultrasound,
MedImg(32), No. 9, 2013, pp. 1698-1706.
IEEE DOI 1309
Automated 3-D breast ultrasound BibRef

Gomez, W., Pereira, W.C.A., Infantosi, A.F.C.,
Analysis of Co-Occurrence Texture Statistics as a Function of Gray-Level Quantization for Classifying Breast Ultrasound,
MedImg(31), No. 10, October 2012, pp. 1889-1899.
IEEE DOI 1210
BibRef

Mehdizadeh, S., Austeng, A., Johansen, T.F., Holm, S.,
Eigenspace Based Minimum Variance Beamforming Applied to Ultrasound Imaging of Acoustically Hard Tissues,
MedImg(31), No. 10, October 2012, pp. 1912-1921.
IEEE DOI 1210
BibRef

Moon, W.K.[Woo Kyung], Shen, Y.W.[Yi-Wei], Bae, M.S.[Min Sun], Huang, C.S.[Chiun-Sheng], Chen, J.H.[Jeon-Hor], Chang, R.F.[Ruey-Feng],
Computer-Aided Tumor Detection Based on Multi-Scale Blob Detection Algorithm in Automated Breast Ultrasound Images,
MedImg(32), No. 7, 2013, pp. 1191-1200.
IEEE DOI 1307
Hessian matrices BibRef

Yang, M.C., Moon, W.K., Wang, Y.C.F., Bae, M.S., Huang, C.S., Chen, J.H., Chang, R.F.,
Robust Texture Analysis Using Multi-Resolution Gray-Scale Invariant Features for Breast Sonographic Tumor Diagnosis,
MedImg(32), No. 12, 2013, pp. 2262-2273.
IEEE DOI 1312
Databases BibRef

Lo, C.M., Chen, R.T., Chang, Y.C., Yang, Y.W., Hung, M.J., Huang, C.S., Chang, R.F.,
Multi-Dimensional Tumor Detection in Automated Whole Breast Ultrasound Using Topographic Watershed,
MedImg(33), No. 7, July 2014, pp. 1503-1511.
IEEE DOI 1407
Breast BibRef

Xian, M.[Min], Zhang, Y.T.[Ying-Tao], Cheng, H.D.,
Fully automatic segmentation of breast ultrasound images based on breast characteristics in space and frequency domains,
PR(48), No. 2, 2015, pp. 485-497.
Elsevier DOI 1411
Breast ultrasound (BUS) images BibRef

Xian, M.[Min], Huang, J.H.[Jian-Hua], Zhang, Y.T.[Ying-Tao], Tang, X.L.[Xiang-Long],
Multiple-domain knowledge based MRF model for tumor segmentation in breast ultrasound images,
ICIP12(2021-2024).
IEEE DOI 1302
BibRef

Flores, W.G.[Wilfrido Gómez], de Albuquerque Pereira, W.C.[Wagner Coelho], Infantosi, A.F.C.[Antonio Fernando Catelli],
Improving classification performance of breast lesions on ultrasonography,
PR(48), No. 4, 2015, pp. 1125-1136.
Elsevier DOI 1502
Ultrasonography BibRef

Uniyal, N., Eskandari, H., Abolmaesumi, P., Sojoudi, S., Gordon, P., Warren, L., Rohling, R.N., Salcudean, S.E., Moradi, M.,
Ultrasound RF Time Series for Classification of Breast Lesions,
MedImg(34), No. 2, February 2015, pp. 652-661.
IEEE DOI 1502
Biopsy BibRef

Gangeh, M.J., Tadayyon, H., Sannachi, L., Sadeghi-Naini, A., Tran, W.T., Czarnota, G.J.,
Computer Aided Theragnosis Using Quantitative Ultrasound Spectroscopy and Maximum Mean Discrepancy in Locally Advanced Breast Cancer,
MedImg(35), No. 3, March 2016, pp. 778-790.
IEEE DOI 1603
Breast cancer 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

Shao, H.Y.[Hao-Yang], Zhang, Y.T.[Ying-Tao], Xian, M.[Min], Cheng, H.D., Xu, F.[Fei], Ding, J.[Jianrui],
A saliency model for automated tumor detection in breast ultrasound images,
ICIP15(1424-1428)
IEEE DOI 1512
Breast ultrasound (BUS) images 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).
WWW Link. 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,
EvoIASP(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.[Yajie], 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 .


Last update:Nov 11, 2017 at 13:31:57