20.7.1 Breast Cancer, Mammograms, Analysis, Mammography

Computer Vision Systems Laboratories,
2011.
WWW Version. Vendor, Medical Image Analysis. Various techniques and products. Infrared systems.

Highnam, R.[Ralph], Brady, M.[Michael],
Mammographic Image Analysis,
KluwerFebruary 1999, ISBN 0-7923-5620-9.
WWW Version. BibRef 9902

MiniMammographic Database,
1995
WWW Version. Dataset, Mammography.

DDSM: Digital Database for Screening Mammography,
2000, USF.
HTML Version. Dataset, Mammography.

Bowyer, K.W., Astley, S., (Eds.)
Special Issue: State of the Art in Digital Mammographic Image Analysis,
PRAI(7), No. 6, December 1993, pp. 1309-1503. BibRef 9312

Goin, J.E.[James E.], Haberman, J.D.[JoAnn D.],
Automated Breast Cancer Detection by Thermography: Performance Goal and Diagnostic Feature Identification,
PR(16), No. 2, 1983, pp. 125-129.
WWW Version. 0309
BibRef
Earlier: PR(15), No. 5, 1982, pp. 425.
WWW Version. 0309
BibRef

Goin, J.E.[James E.],
ROC Curve Estimation and Hypothesis Testing: Applications to Breast Cancer Detection,
PR(15), No. 3, 1982, pp. 263-269.
WWW Version. 0309
BibRef

Karssemeijer, N.,
Stochastic model for automated detection of calcifications in digital mammograms,
IVC(10), No. 6, July-August 1992, pp. 369-375.
WWW Version. 0401
BibRef

te Brake, G.M., Karssemeijer, N.,
Single and multiscale detection of masses in digital mammograms,
MedImg(18), No. 7, July 1999, pp. 628-639.
IEEE Top Reference. 0110
BibRef

Karssemeijer, N., te Brake, G.M.,
Detection of stellate distortions in mammograms,
MedImg(15), No. 5, October 1996, pp. 611-619.
IEEE Top Reference. 0203
BibRef

Hupse, R., Karssemeijer, N.,
Use of Normal Tissue Context in Computer-Aided Detection of Masses in Mammograms,
MedImg(28), No. 12, December 2009, pp. 2033-2041.
IEEE DOI Link 0912
BibRef

Timp, S., Varela, C., Karssemeijer, N.,
Temporal Change Analysis for Characterization of Mass Lesions in Mammography,
MedImg(26), No. 7, July 2007, pp. 945-953.
IEEE DOI Link 0707
BibRef

Zheng, B.Y.[Bao-Yu], Qian, W.[Wei], Clarke, L.P.,
Digital mammography: mixed feature neural network with spectral entropy decision for detection of microcalcifications,
MedImg(15), No. 5, October 1996, pp. 589-597.
IEEE Top Reference. 0203
BibRef

Kobatake, H., Yoshinaga, Y.,
Detection of spicules on mammogram based on skeleton analysis,
MedImg(15), No. 3, June 1996, pp. 235-245.
IEEE Top Reference. 0203
BibRef

Dhawan, A.P., Chitre, Y., Kaiser-Bonasso, C.,
Analysis of mammographic microcalcifications using gray-level image structure features,
MedImg(15), No. 3, June 1996, pp. 246-259.
IEEE Top Reference. 0203
BibRef

Rangayyan, R.M., Elfaramawy, N.M., Desautels, J.E.L., Alim, O.A.,
Measures of Acutance and Shape for Classification of Breast-Tumors,
MedImg(16), No. 6, December 1997, pp. 799-810.
IEEE Top Reference. 9803
BibRef

Polakowski, W.E., Cournoyer, D.A., Rogers, S.K., Desimio, M.P., Ruck, D.W., Hoffmeister, J.W., Raines, R.A.,
Computer-Aided Breast-Cancer Detection and Diagnosis of Masses Using Difference of Gaussians and Derivative-Based Feature Saliency,
MedImg(16), No. 6, December 1997, pp. 811-819.
IEEE Top Reference. 9803
BibRef

Marchette, D.J., Lorey, R.A., Priebe, C.E.,
An Analysis of Local Feature-Extraction in Digital Mammography,
PR(30), No. 9, September 1997, pp. 1547-1554.
WWW Version. 9708
BibRef

Heine, J.J., Deans, S.R., Cullers, D.K., Stauduhar, R., Clarke, L.P.,
Multiresolution statistical analysis of high-resolution digital mammograms,
MedImg(16), No. 5, October 1997, pp. 503-515.
IEEE Top Reference. 0205
BibRef

Lo, S.C.B., Chan, H.P., Lin, J.S., Li, H., Freedman, M.T., Mun, S.K.,
Artificial Convolution Neural-Network for Medical Image Pattern-Recognition,
NeurNet(8), No. 7-8, 1995, pp. 1201-1214. BibRef 9500

Lo, S.C.B., Lin, J.S.J., Freedman, M.T., Mun, S.K.,
Application of Artificial Neural Networks to Medical Image Pattern-Recognition: Detection of Clustered Microcalcifications on Mammograms and Lung-Cancer on Chest Radiographs,
VLSIVideo(18), No. 3, April 1998, pp. 263-274. 9806
BibRef

Lo, S.C.B.[Shih-Chung B.], Li, H.[Huai], Wang, Y.[Yue], Kinnard, L., Freedman, M.T.,
A multiple circular path convolution neural network system for detection of mammographic masses,
MedImg(21), No. 2, February 2002, pp. 150-158.
IEEE Top Reference. 0204
BibRef

Li, H., Liu, K., Lo, S.C., and Wang, Y.,
Stochastic Model and Probabilistic Decision-Based Classifier for Mass Detection in Digital Mammography,
ICIP97(III: 539-542).
IEEE DOI Link BibRef 9700

Tsujii, O.[Osamu], Freedman, M.T.[Matthew T.], Mun, S.K.[Seong K.],
Classification of microcalcifications in digital mammograms using trend-oriented radial basis function neural network,
PR(32), No. 5, May 1999, pp. 891-903.
WWW Version. BibRef 9905

Bottema, M.J.[Murk J.], Slavotinek, J.P.[John P.],
Detection and classification of lobular and DCIS (small cell) microcalcifications in digital mammograms,
PRL(21), No. 13-14, December 2000, pp. 1209-1214. 0011
BibRef
Earlier: SCIA99(Biological Applications II). BibRef

Ma, F.[Fei], Bajger, M.[Mariusz], Slavotinek, J.P.[John P.], Bottema, M.J.[Murk J.],
Two graph theory based methods for identifying the pectoral muscle in mammograms,
PR(40), No. 9, September 2007, pp. 2592-2602.
WWW Version. 0705
Adaptive pyramid; Minimum spanning tree; Segmentation; Pectoral muscle; Computer-aided diagnosis BibRef

Ma, F.[Fei], Bajger, M.[Mariusz], Bottema, M.J.[Murk J.],
Automatic Mass Segmentation Based on Adaptive Pyramid and Sublevel Set Analysis,
DICTA09(236-241).
IEEE DOI Link 0912
BibRef

Bajger, M.[Mariusz], Ma, F.[Fei], Williams, S.[Simon], Bottema, M.J.[Murk J.],
Mammographic Mass Detection with Statistical Region Merging,
DICTA10(27-32).
IEEE DOI Link 1012
BibRef

Bajger, M.[Mariusz], Ma, F.[Fei], Bottema, M.J.[Murk J.],
Automatic Tuning of MST Segmentation of Mammograms for Registration and Mass Detection Algorithms,
DICTA09(400-407).
IEEE DOI Link 0912
BibRef

Constantinidis, A.S., Fairhurst, M.C., Rahman, A.F.R.,
A new multi-expert decision combination algorithm and its application to the detection of circumscribed masses in digital mammograms,
PR(34), No. 8, August 2001, pp. 1527-1537.
WWW Version. 0105
BibRef

Grohman, W.M.[Wojciech M.], Dhawan, A.P.[Atam P.],
Fuzzy convex set-based pattern classification for analysis of mammographic microcalcifications,
PR(34), No. 7, July 2001, pp. 1469-1482.
WWW Version. 0105
BibRef

Liu, S.[Sheng], Babbs, C.F., Delp, E.J.,
Multiresolution detection of spiculated lesions in digital mammograms,
IP(10), No. 6, June 2001, pp. 874-884.
IEEE DOI Link 0106
BibRef
Earlier:
Normal mammogram analysis and recognition,
ICIP98(I: 727-731).
IEEE DOI Link 9810
BibRef

Liu, S., and Delp, E.J.,
Multiresolution Detection of Stellate Lesions in Mammograms,
ICIP97(II: 109-112).
IEEE DOI Link BibRef 9700

Kobatake, H., Murakami, M., Takeo, H., Nawano, S.,
Computerized detection of malignant tumors on digital mammograms,
MedImg(18), No. 5, May 1999, pp. 369-378.
IEEE Top Reference. 0110
BibRef

Kobatake, H., Yoshinaga, Y., Murakami, M.,
Automatic detection of malignant tumors on mammogram,
ICIP94(I: 407-410).
IEEE DOI Link 9411
BibRef

Netsch, T., Peitgen, H.O.,
Scale-space signatures for the detection of clustered microcalcifications in digital mammograms,
MedImg(18), No. 9, September 1999, pp. 774-786.
IEEE Top Reference. 0110
BibRef

Zhen, L.[Lei], Chan, A.K.,
An artificial intelligent algorithm for tumor detection in screening mammogram,
MedImg(20), No. 7, July 2001, pp. 559-567.
IEEE Top Reference. 0110
BibRef

Saha, P.K., Udupa, J.K., Conant, E.F., Chakraborty, D.P., Sullivan, D.,
Breast tissue density quantification via digitized mammograms,
MedImg(20), No. 8, August 2001, pp. 792-803.
IEEE Top Reference. 0110
BibRef

Tosteson, T.D., Pogue, B.W., Demidenko, E., McBride, T.O., Paulsen, K.D.,
Confidence maps and confidence intervals for near infrared images in breast cancer,
MedImg(18), No. 12, December 1999, pp. 1188-1193.
IEEE Top Reference. 0110
BibRef

Sahiner, B., Petrick, N., Chan, H.P.[Heang-Ping], Hadjiiski, L.M., Paramagul, C., Helvie, M.A., Gurcan, M.N.,
Computer-aided characterization of mammographic masses: Accuracy of mass segmentation and its effects on characterization,
MedImg(20), No. 12, December 2001, pp. 1275-1284.
IEEE Top Reference. 0201
BibRef

Hadjiiski, L.M., Sahiner, B., Chan, H.P.[Heang-Ping], Petrick, N., Helvie, M.A.,
Classification of malignant and benign masses based on hybrid ART2LDA approach,
MedImg(18), No. 12, December 1999, pp. 1178-1187.
IEEE Top Reference. 0110
BibRef

Hatanaka, Y., Hara, T., Fujita, H., Kasai, S., Endo, T.[Tokiko], Iwase, T.,
Development of an automated method for detecting mammographic masses with a partial loss of region,
MedImg(20), No. 12, December 2001, pp. 1209-1214.
IEEE Top Reference. 0201
BibRef

Sajda, P., Spence, C.D.[Clay Douglas], Pearson, J.,
Learning contextual relationships in mammograms using a hierarchical pyramid neural network,
MedImg(21), No. 3, March 2002, pp. 239-250.
IEEE Top Reference. 0205
BibRef

Spence, C.D.[Clay Douglas], Parra, L.C.[Lucas C.], Sajda, P.,
Detection, Synthesis and Compression in Mammographic Image Analysis with a Hierarchical Image Probability Model,
MMBIA01(xx-yy). 0110
BibRef
Earlier:
Hierarchical Image Probability (HIP) Models,
ICIP00(Vol III: 320-323).
IEEE Abstract. 0008
BibRef

Scholz, B.,
Towards virtual electrical breast biopsy: Space-frequency music for trans-admittance data,
MedImg(21), No. 6, June 2002, pp. 588-595.
IEEE Top Reference. 0208
BibRef

Kerner, T.E., Paulsen, K.D., Hartov, A., Soho, S.K., Poplack, S.P.,
Electrical impedance spectroscopy of the breast: Clinical imaging results in 26 subjects,
MedImg(21), No. 6, June 2002, pp. 638-645.
IEEE Top Reference. 0208
BibRef

Baeg, S.[Soon], Kehtarnavaz, N.[Nasser],
Classification of breast mass abnormalities using denseness and architectural distortion,
ELCVIA(1), No. 1, August 2002, pp. 1-20.
WWW Version. 0208
BibRef

Sentelle, S., Sentelle, C., Sutton, M.A.,
Multiresolution-Based Segmentation of Calcifications for the Early Detection of Breast Cancer,
RealTimeImg(8), No. 3, June 2002, pp. 237-252.
WWW Version. 0208
BibRef

Bagui, S.C.[Subhash C.], Bagui, S.[Sikha], Pal, K.[Kuhu], Pal, N.R.[Nikhil R.],
Breast cancer detection using rank nearest neighbor classification rules,
PR(36), No. 1, January 2003, pp. 25-34.
WWW Version. 0210
BibRef

El Naqa, I., Yang, Y.Y.[Yong-Yi], Wernick, M.N., Galatsanos, N.P., Nishikawa, R.M.,
A support vector machine approach for detection of microcalcifications,
MedImg(21), No. 12, December 2002, pp. 1552-1563.
IEEE Top Reference. 0301
BibRef
Earlier:
A support vector machine approach for detection of microcalcifications in mammograms,
ICIP02(II: 953-956).
IEEE Abstract. 0210
BibRef

El Naqa, I., Yang, Y., Galatsanos, N.P., Nishikawa, R.M., Wernick, M.N.,
A Similarity Learning Approach to Content-Based Image Retrieval: Application to Digital Mammography,
MedImg(23), No. 10, October 2004, pp. 1233-1244.
IEEE Abstract. 0410
BibRef

El Naqa, I., Yang, Y.Y.[Yong-Yi], Galatsanos, N.P., Wernick, M.N.,
Content-based image retrieval for digital mammography,
ICIP02(III: 141-144).
IEEE Abstract. 0210
BibRef
Earlier: A1, A4, A2, A3:
Image Retrieval Based on Similarity Learning,
ICIP00(Vol III: 722-725).
IEEE Abstract. 0008
BibRef

El Naqa, I.[Issam],
Variational methods for image-guided adaptive radiotherapy,
Southwest10(13-16).
IEEE DOI Link 1005
BibRef

Wei, L., Yang, Y., Nishikawa, R.M., Jiang, Y.,
A Study on Several Machine-Learning Methods for Classification of Malignant and Benign Clustered Microcalcifications,
MedImg(24), No. 3, March 2005, pp. 371-380.
IEEE Abstract. 0501
BibRef

Wei, L., Yang, Y., Nishikawa, R.M., Wernick, M.N., Edwards, A.,
Relevance Vector Machine for Automatic Detection of Clustered Microcalcifications,
MedImg(24), No. 10, October 2005, pp. 1278-1285.
IEEE DOI Link 0510
BibRef

Wei, L.Y.[Li-Yang], Yang, Y.Y.[Yong-Yi], Nishikawa, R.M.,
Relevance Vector Machine Learning for Detection of Microcalcifications in Mammograms,
ICIP05(I: 9-12).
IEEE DOI Link 0512
BibRef

Wei, L.Y.[Li-Yang], Yang, Y.Y.[Yong-Yi], Nishikawa, R.M., Wernick, M.N.,
Mammogram Retrieval by Similarity Learning from Experts,
ICIP06(2517-2520).
IEEE DOI Link 0610
BibRef

de Santo, M.[Massimo], Molinara, M.[Mario], Tortorella, F.[Francesco], Vento, M.[Mario],
Automatic classification of clustered microcalcifications by a multiple expert system,
PR(36), No. 7, July 2003, pp. 1467-1477.
WWW Version. 0304
BibRef

de Vito, S., Tortorella, F., Vento, M.,
C: Automatic classification of clustered microcalcifications by a multiple expert system,
CIAP99(464-469).
IEEE DOI Link 9909
BibRef

Duchesnay, E.[Edouard], Montois, J.J.[Jean-Jacques], Jacquelet, Y.[Yann],
Cooperative agents society organized as an irregular pyramid: A mammography segmentation application,
PRL(24), No. 14, October 2003, pp. 2435-2445.
WWW Version. 0307
BibRef

Cheng, H.D., Cai, X.P.[Xiao-Peng], Chen, X.W.[Xiao-Wei], Hu, L.M.[Li-Ming], Lou, X.[Xueling],
Computer-aided detection and classification of microcalcifications in mammograms: a survey,
PR(36), No. 12, December 2003, pp. 2967-2991.
WWW Version. 0310
Survey, Mammograms. BibRef

Cheng, H.D., Wang, J.L.[Jing-Li], Shi, X.J.[Xiang-Jun],
Microcalcification detection using fuzzy logic and scale space approaches,
PR(37), No. 2, February 2004, pp. 363-375.
WWW Version. 0311
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

Raimondo, F., Gavrielides, M.A., Karayannopoulou, G., Lyroudia, K., Pitas, I., Kostopoulos, I.,
Automated Evaluation of Her-2/neu Status in Breast Tissue From Fluorescent In Situ Hybridization Images,
IP(14), No. 9, September 2005, pp. 1288-1299.
IEEE DOI Link 0508
BibRef

Richard, F.J.P.[Frédéric J.P.],
A comparative study of markovian and variational image-matching techniques in application to mammograms,
PRL(26), No. 12, September 2005, pp. 1819-1829.
WWW Version. 0508
BibRef

Sheshadri, H.S., Kandaswamy, A.,
Detection of Breast Cancer Tumor Based on Morphological Watershed Algorithm,
GVIP(05), No. V5, 2005, pp. 17-21
HTML Version. BibRef 0500

Thangavel, K., Karnan, M., Sivakumar, R., Mohideen, A.K.[A. Kaja],
Automatic Detection of Microcalcification in Mammograms: A Review,
GVIP(05), No. V5, 2005, pp. 31-61
HTML Version. BibRef 0500

Thangavel, K., Karnan, M.,
Meta-Heuristic Algorithms for Automatic Detection of Microcalcifications In Digital Mammograms,
GVIP(05), No. V7, 2005, pp. xx-yy
HTML Version. BibRef 0500

Wirth, M.A., Nikitenko, D., Lyon, J.,
Segmentation of the Breast Region in Mammograms Using a Rule-Based Fuzzy Reasoning Algorithm,
GVIP(05), No. V2, January 2005, pp. 45-54
HTML Version. BibRef 0501

Wirth, M.A.[Michael A.], Nikitenko, D.[Dennis],
Suppression of Stripe Artifacts in Mammograms Using Weighted Median Filtering,
ICIAR05(966-973).
Springer DOI Link 0509
BibRef

Wirth, M.A., Stapinski, A.,
Segmentation of the breast region in mammograms using snakes,
CRV04(385-392).
IEEE Abstract. 0408
BibRef

Thangavel, K., Karnan, M., Pethalakshmi, A.,
Performance Analysis of Rough Reduct Algorithms in Mammogram,
GVIP(05), No. V8, 2005, pp. 13-21.
HTML Version. BibRef 0500

Guo, H.[Hong], Nandi, A.K.[Asoke K.],
Breast cancer diagnosis using genetic programming generated feature,
PR(39), No. 5, May 2006, pp. 980-987.
WWW Version. 0604
Feature extraction; Genetic programming; Fisher discriminant analysis; Pattern recognition See also Feature generation using genetic programming with application to fault classification. BibRef

Dominguez, A.R.[Alfonso Rojas], Nandi, A.K.[Asoke K.],
Toward breast cancer diagnosis based on automated segmentation of masses in mammograms,
PR(42), No. 6, June 2009, pp. 1138-1148.
Elsevier DOI Link
WWW Version. 0902
Breast cancer; Breast masses; Mammography; Image analysis BibRef

Adiga, U., Malladi, R., Fernandez-Gonzalez, R., Ortiz de Solorzano, C.,
High-Throughput Analysis of Multispectral Images of Breast Cancer Tissue,
IP(15), No. 8, August 2006, pp. 2259-2268.
IEEE DOI Link 0606
BibRef

Hassanien, A.E.[Aboul Ella],
Fuzzy rough sets hybrid scheme for breast cancer detection,
IVC(25), No. 2, February 2007, pp. 172-183.
WWW Version. 0701
Rough sets; Fuzzy image processing; Mammograms; Classification; Feature extraction; Rule and reduct generation; Similarity measure; Gray-level co-occurrence matrices BibRef

Eltonsy, N.H., Tourassi, G.D., Elmaghraby, A.S.,
A Concentric Morphology Model for the Detection of Masses in Mammography,
MedImg(26), No. 6, June 2007, pp. 880-889.
IEEE DOI Link 0706
BibRef

Cao, A.[Aize], Song, Q.[Qing], Yang, X.[Xulei],
Robust information clustering incorporating spatial information for breast mass detection in digitized mammograms,
CVIU(109), No. 1, January 2008, pp. 86-96.
WWW Version. 0801
Robust information clustering; Minimax optimization of mutual information; Spatial information BibRef

Cao, A.[Aize], Song, Q.[Qing], Yang, X.[Xulei], Wang, L.[Lei],
Breast mass segmentation based on information theory,
ICPR04(III: 758-761).
IEEE DOI Link 0409
BibRef

Castella, C.[Cyril], Abbey, C.K.[Craig K.], Eckstein, M.P.[Miguel P.], Verdun, F.R.[Francis R.], Kinkel, K.[Karen], Bochud, F.O.[François O.],
Human linear template with mammographic backgrounds estimated with a genetic algorithm,
JOSA-A(24), No. 12, December 2007, pp. B1-B12.
WWW Version. 0801
BibRef

Castella, C.[Cyril], Eckstein, M.P.[Miguel P.], Abbey, C.K.[Craig K.], Kinkel, K.[Karen], Verdun, F.R.[Francis R.], Saunders, R.S., Samei, E., Bochud, F.O.[François O.],
Mass detection on mammograms: influence of signal shape uncertainty on human and model observers,
JOSA-A(26), No. 2, February 2009, pp. 425-436.
WWW Version. 0902
BibRef

Perconti, P.[Philip], Loew, M.H.[Murray H.],
Salience measure for assessing scale-based features in mammograms,
JOSA-A(24), No. 12, December 2007, pp. B81-B90.
WWW Version. 0801
BibRef

Raundahl, J., Loog, M., Pettersen, P., Tanko, L.B., Nielsen, M.,
Automated Effect-Specific Mammographic Pattern Measures,
MedImg(27), No. 8, August 2008, pp. 1054-1060.
IEEE DOI Link 0808
BibRef

Egorov, V., Sarvazyan, A.P.,
Mechanical Imaging of the Breast,
MedImg(27), No. 9, September 2008, pp. 1275-1287.
IEEE DOI Link 0809
See also Prostate Mechanical Imaging: 3-D Image Composition and Feature Calculations. BibRef

Kao, T.J., Boverman, G., Kim, B.S., Isaacson, D., Saulnier, G.J., Newell, J.C., Choi, M.H., Moore, R.H., Kopans, D.B.,
Regional Admittivity Spectra With Tomosynthesis Images for Breast Cancer Detection: Preliminary Patient Study,
MedImg(27), No. 12, December 2008, pp. 1762-1768.
IEEE DOI Link 0812
BibRef

Schaefer, G.[Gerald], Zavisek, M.[Michal], Nakashima, T.[Tomoharu],
Thermography based breast cancer analysis using statistical features and fuzzy classification,
PR(42), No. 6, June 2009, pp. 1133-1137.
Elsevier DOI Link
WWW Version. 0902
BibRef
Earlier: A1, A3, A2:
Analysis of Breast Thermograms Based on Statistical Image Features and Hybrid Fuzzy Classification,
ISVC08(I: 753-762).
Springer DOI Link 0812
Cancer diagnosis; Breast cancer; Medical thermography; Image analysis; Pattern classification BibRef

Wei, L.Y.[Li-Yang], Yang, Y.Y.[Yong-Yi], Nishikawa, R.M.[Robert M.],
Microcalcification Classification Assisted by Content-Based Image Retrieval for Breast Cancer Diagnosis,
PR(42), No. 6, June 2009, pp. 1126-1132.
Elsevier DOI Link
WWW Version. 0902
BibRef
Earlier: A2, A1, A3: ICIP07(V: 1-4).
IEEE DOI Link 0709
Microcalcification classification; Adaptive support vector machine; Image retrieval BibRef

Verma, B.[Brijesh], McLeod, P.[Peter], Klevansky, A.[Alan],
A novel soft cluster neural network for the classification of suspicious areas in digital mammograms,
PR(42), No. 9, September 2009, pp. 1845-1852.
Elsevier DOI Link
WWW Version. 0905
Pattern classification; Neural networks; Clustering algorithms BibRef

Cao, M., Liang, Y., Shen, C., Miller, K.D., Stantz, K.M.,
Developing DCE-CT to Quantify Intra-Tumor Heterogeneity in Breast Tumors With Differing Angiogenic Phenotype,
MedImg(28), No. 6, June 2009, pp. 861-871.
IEEE DOI Link 0906
See comment: and Response BibRef

Cao, M., Liang, Y., Stantz, K.M.,
Response to Letter Regarding Article: 'Developing DCE-CT to Quantify Intra-Tumor Heterogeneity in Breast Tumors With Differing Angiogenic Phenotype',
MedImg(29), No. 4, April 2010, pp. 1089-1092.
IEEE DOI Link 1003
See also Comment on Developing DCE-CT to Quantify Intra-Tumor Heterogeneity in Breast Tumors With Differing Angiogenic Phenotype. BibRef

Abramyuk, A., Wolf, G., Hietschold, V., Haberland, U., van den Hoff, J., Abolmaali, N.,
Comment on 'Developing DCE-CT to Quantify Intra-Tumor Heterogeneity in Breast Tumors With Differing Angiogenic Phenotype',
MedImg(29), No. 4, April 2010, pp. 1088-1089.
IEEE DOI Link 1003
See also Developing DCE-CT to Quantify Intra-Tumor Heterogeneity in Breast Tumors With Differing Angiogenic Phenotype. BibRef

Masmoudi, H., Hewitt, S.M., Petrick, N., Myers, K.J., Gavrielides, M.A.,
Automated Quantitative Assessment of HER-2/neu Immunohistochemical Expression in Breast Cancer,
MedImg(28), No. 6, June 2009, pp. 916-925.
IEEE DOI Link 0906
BibRef

Subashini, T.S., Ramalingam, V., Palanivel, S.,
Automated assessment of breast tissue density in digital mammograms,
CVIU(114), No. 1, January 2010, pp. 33-43.
Elsevier DOI Link
WWW Version. 1001
Mammograms; Breast tissue density; Segmentation; Pectoral muscles; Artifact removal; Statistical features; Support vector machines BibRef

Tsui, P.H., Liao, Y.Y., Chang, C.C., Kuo, W.H., Chang, K.J., Yeh, C.K.,
Classification of Benign and Malignant Breast Tumors by 2-D Analysis Based on Contour Description and Scatterer Characterization,
MedImg(29), No. 2, February 2010, pp. 513-522.
IEEE DOI Link 1002
BibRef

de Oliveira Martins, L.[Leonardo], Junior, G.B.[Geraldo Braz], Correa Silva, A.[Aristófanes], de Paiva, A.C.[Anselmo Cardoso], Gattass, M.[Marcelo],
Detection of Masses in Digital Mammograms using K-Means and Support Vector Machine,
ELCVIA(8), No. 2, July 2009, pp. xx-yy.
WWW Version. 1002
BibRef

Muralidhar, G.S., Bovik, A.C., Giese, J.D., Sampat, M.P., Whitman, G.J., Haygood, T.M., Stephens, T.W., Markey, M.K.,
Snakules: A Model-Based Active Contour Algorithm for the Annotation of Spicules on Mammography,
MedImg(29), No. 10, October 2010, pp. 1768-1780.
IEEE DOI Link 1011
BibRef

Muralidhar, G.S.[Gautam S.], Markey, M.K.[Mia K.], Bovik, A.C.[Alan C.],
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Wang, Y.[Ying], Tao, D.C.[Da-Cheng], Gao, X.[Xinbo], Li, X.L.[Xue-Long], Wang, B.[Bin],
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PR(44), No. 9, September 2011, pp. 1903-1915.
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Mass segmentation; Computer-aided diagnose; Vector-valued level set; Relaxed shape constraint; Mammograms See also Relay Level Set Method for Automatic Image Segmentation, A. BibRef

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Chaudhury, A.R.[Amrita Ray], Iyer, R.[Ranjani], Iychettira, K.K.[Kaveri K.], Sreedevi, A.,
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Vani, G., Savitha, R., Sundararajan, N.,
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Fusco, R.[Roberta], Sansone, M.[Mario], Sansone, C.[Carlo], Petrillo, A.[Antonella],
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Wang, J.Y.[Jing-Yan], Li, Y.P.[Yong-Ping], Zhang, Y.[Ying], Xie, H.[Honglan], Wang, C.[Chao],
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Vállez, N.[Noelia], Bueno, G.[Gloria], Déniz-Suárez, O.[Oscar], Seone, J.A.[José A.], Dorado, J.[Julián], Pazos, A.[Alejandro],
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Yousef, W.A.[Waleed A.], Mustafa, W.A.[Waleed A.], Ali, A.A.[Ali A.], Abdelrazek, N.A.[Naglaa A.], Farrag, A.M.[Ahmed M.],
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Not mammogram, but analysis of tissue samples. BibRef

Ma, Y.M.[Yi-Ming], Tay, P.C.[Peter C.], Adams, R.D.[Robert D.], Zhang, J.Z.[James Z.],
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Sahba, F.[Farhang], Venetsanopoulos, A.[Anastasios],
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Torrent, A.[Albert], Oliver, A.[Arnau], Llado, X.[Xavier], Marti, R.[Robert], Freixenet, J.[Jordi],
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ICIP10(4345-4348).
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Oliver, A.[Arnau], Lladó, X.[Xavier], Martí, J.[Joan], Martí, R.[Robert], Freixenet, J.[Jordi],
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Diez, Y.[Yago], Oliver, A.[Arnau], Llado, X.[Xavier], Marti, R.[Robert],
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ICIP10(4421-4424).
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Muralidhar, G.S.[Gautam S.], Bovik, A.C.[Alan C.], Markey, M.K.[Mia K.],
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ICIP10(4373-4376).
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Harirchi, F.[Farshad], Radparvar, P.[Parham], Abrishami Moghaddam, H.[Hamid], Dehghan, F.[Faramarz], Giti, M.[Masoumeh],
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ICPR10(269-272).
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Boucher, A., Cloppet, F., Vincent, N., Jouve, P.,
Visual Perception Driven Registration of Mammograms,
ICPR10(2374-2377).
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Veillard, A.[Antoine], Lomenie, N.[Nicolas], Racoceanu, D.[Daniel],
An Exploration Scheme for Large Images: Application to Breast Cancer Grading,
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Cheikhouhou, I.[Imene], Djemal, K.[Khalifa], Maaref, H.[Hichem],
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ICISP10(576-584).
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Tay, P.C.[Peter C.], Ma, Y.M.[Yi-Ming],
A novel microcalcification shape metric to classify regions of interests,
Southwest10(201-204).
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Jing, H.[Hao], Yang, Y.Y.[Yong-Yi],
Case-Adaptive Classification Based on Image Retrieval for Computer-Aided Diagnosis,
ICIP10(4333-4336).
IEEE DOI Link 1009
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And:
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Southwest10(9-12).
IEEE DOI Link 1005
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Siong, T.S.[Ting Shyue], Isa, N.A.M.[Nor Ashidi Mat], Nordin, Z.M.[Zailani Mohammed], Ngah, U.K.[Umi Kalthum],
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Jing, H.[Hao], Yang, Y.Y.[Yong-Yi],
Spatial distribution modeling for detection of clustered microcalcifications,
ICIP09(657-660).
IEEE DOI Link 0911
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Lao, Z.Q.[Zhi-Qiang], Huo, Z.M.[Zhi-Min],
Quantitative assessment of breast dense tissue on mammograms,
ICIP09(2605-2608).
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Alolfe, M.A.[Mohammed A.], Mohamed, W.A.[Wael A.], Youssef, A.B.M.[Abou-Bakr M.], Mohamed, A.S.[Ahmed S.], Kadah, Y.M.[Yasser M.],
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Byrd, K., Zeng, J.C.[Jian-Chao], Chouikha, M.,
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Wu, Z.Q., Jiang, J., Peng, Y.H.,
Effective features based on normal linear structures for detecting microcalcifications in mammograms,
ICPR08(1-4).
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Wang, Y.[Ying], Gao, X.B.[Xin-Bo], Li, J.[Jie],
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Sampaio, W.B., Diniz, E.M., Silva, A.C., de Paiva, A.C.,
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de Oliveira Martins, L.[Leonardo], Junior, G.B.[Geraldo Braz], da Silva, E.C.[Erick Corrêa], Silva, A.C.[Aristófanes Corrêa], de Paiva, A.C.[Anselmo Cardoso],
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Hernández-Cisneros, R.R.[Rolando R.], Terashima-Marín, H.[Hugo], Conant-Pablos, S.E.[Santiago E.],
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Oporto-Díaz, S.[Samuel], Hernández-Cisneros, R.R.[Rolando R.], Terashima-Marín, H.[Hugo],
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Moayedi, F.[Fatemeh], Azimifar, Z.[Zohreh], Boostani, R.[Reza], Katebi, S.[Serajodin],
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Das, A.[Arpita], Bhattacharya, M.[Mahua],
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Earlier: A2, A1:
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Foggia, P.[Pasquale], Percannella, G.[Gennaro], Sansone, C.[Carlo], Vento, M.[Mario],
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Foggia, P., Guerriero, M., Percannella, G., Sansone, C., Tufano, F., Vento, M.,
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Roller, D.[Dieter], Lampasona, C.[Constanza],
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CVPR06(II: 1552-1558).
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Lee, S.[Sarah], Stathaki, T.[Tania],
Mammogram Analysis Using Two-Dimensional Autoregressive Models: Sufficient or Not?,
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d'Elia, C., Marrocco, C., Molinara, M., Poggi, G., Scarpa, G., Tortorella, F.,
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Marrocco, C.[Claudio], Molinara, M.[Mario], Tortorella, F.[Francesco],
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The Role of Entropy: Mammogram Analysis,
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Bornefalk, H.[Hans],
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Mohammed, S., Yang, L.[Lei], Fiaidhi, J.,
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Gulsrud, T.O.[Thor Ole], Husøy, J.H.[John Håkon],
Detection of clustered microcalcifications in compressed mammograms,
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Christoyianni, I., Dermatas, E., Kokkinakis, G.,
Automatic Detection of Abnormal Tissue in Mammography,
ICIP01(II: 877-880).
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Quadrades, S., Sacristán, A.,
Automated Extraction of Microcalcifications BI-Rads Numbers in Mammograms,
ICIP01(II: 289-292).
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Mata, R., Nava, E., Sendra, F.,
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Rodriguez-Sánchez, R., García, J.A., Fdez-Valdivia, J., Fdez-Vidal, X.R.[Xose R.],
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Bhangale, T., Desai, U., Sharma, U.,
An Unsupervised Scheme for Detection of Microcalcifications on Mammograms,
ICIP00(Vol I: 184-187).
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McGarry, G., Deriche, M.,
Mammographic Image Segmentation Using a Tissue-mixture Model and Markov Random Fields,
ICIP00(Vol III: 416-419).
IEEE Abstract. 0008
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Banerjee, A., Chellappa, R.,
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Caputo, B., and Gigante, G.E.,
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Sari-Sarraf, H., and Gleason, S.S.,
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mammography application BibRef

Varga, M.J., de Muynck, P.,
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Mammography, Texture Based Techniques, Wavelets .