21.7.2.2 Mammography, Microcalcifications, Detection, Analysis

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

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

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

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.
Elsevier DOI 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

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.
Elsevier DOI 0105
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

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.
DOI Link 0208
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 DOI 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.[Issam], Yang, D.S.[De-Shan], Deasy, J.O.[Joseph O.],
Automated Estimation of the Biophysical Target for Radiotherapy Treatment Planning using Multimodality Image Analysis,
ICIP07(V: 533-536).
IEEE DOI 0709
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 DOI 0210
BibRef
Earlier: A1, A4, A2, A3:
Image Retrieval Based on Similarity Learning,
ICIP00(Vol III: 722-725).
IEEE DOI 0008
BibRef

El Naqa, I.[Issam],
Variational methods for image-guided adaptive radiotherapy,
Southwest10(13-16).
IEEE DOI 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 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 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 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.
Elsevier DOI 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 9909
BibRef

Cheng, H.D., Cai, X.P.[Xiao-Peng], Chen, X.W.[Xiao-Wei], Hu, L.M.[Li-Ming], Lou, X.L.[Xue-Ling],
Computer-aided detection and classification of microcalcifications in mammograms: a survey,
PR(36), No. 12, December 2003, pp. 2967-2991.
Elsevier DOI 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.
Elsevier DOI 0311
BibRef

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

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 0902
BibRef
Earlier: A2, A1, A3: ICIP07(V: 1-4).
IEEE DOI 0709
Microcalcification classification; Adaptive support vector machine; Image retrieval BibRef

Cheng, J.Z., Chen, C.M., Cole, E.B., Pisano, E.D., Shen, D.,
Automated Delineation of Calcified Vessels in Mammography by Tracking With Uncertainty and Graphical Linking Techniques,
MedImg(31), No. 11, November 2012, pp. 2143-2155.
IEEE DOI 1211
BibRef

Bekker, A.J., Shalhon, M., Greenspan, H., Goldberger, J.,
Multi-View Probabilistic Classification of Breast Microcalcifications,
MedImg(35), No. 2, February 2016, pp. 645-653.
IEEE DOI 1602
Biological system modeling BibRef

de Cea, M.V.S.[Maria V. Sainz], Nishikawa, R.M., Yang, Y.Y.[Yong-Yi],
Estimating the Accuracy Level Among Individual Detections in Clustered Microcalcifications,
MedImg(36), No. 5, May 2017, pp. 1162-1171.
IEEE DOI 1705
BibRef
Earlier: A1, A3, Only:
Case-based decision strategy using outlier probability in detection of microcalcifications in mammographic lesions,
ICIP16(3409-3413)
IEEE DOI 1610
BibRef
Earlier: A1, A3, Only:
Improving uniformity in detection performance of clustered microcalcifications in mammograms,
ICIP15(842-846)
IEEE DOI 1512
Bayes' risk. Cancer, Detectors, Estimation, Lesions, Mammography, Sensitivity, Solid modeling, Clustered microcalcifications (MCs), computer-aided diagnosis (CAD), false positives (FPs) in detection, mammography, spatial, point, process, (SPP) BibRef

de Cea, M.V.S.[Maria V. Sainz], Yang, Y.Y.[Yong-Yi],
Point process modeling for determining detection accuracy of mammographic microcalcifications,
ICIP17(1357-1361)
IEEE DOI 1803
cancer, diagnostic radiography, mammography, medical image processing, object detection, stochastic processes, microcalcifications BibRef

Muthuvel, M.[Marimuthu], Thangaraju, B.[Balakumaran], Chinnasamy, G.[Gowrishankar],
Microcalcification cluster detection using multiscale products based Hessian matrix via the Tsallis thresholding scheme,
PRL(94), No. 1, 2017, pp. 127-133.
Elsevier DOI 1708
Hessian, matrix BibRef

Zhao, C., Kanicki, J.,
Task-Based Modeling of a 5k Ultra-High-Resolution Medical Imaging System for Digital Breast Tomosynthesis,
MedImg(36), No. 9, September 2017, pp. 1820-1831.
IEEE DOI 1709
CMOS image sensors, cancer, tumours, microcalcification detection, tomosynthesis BibRef

Wang, J.[Juan], Yang, Y.Y.[Yong-Yi],
A context-sensitive deep learning approach for microcalcification detection in mammograms,
PR(78), 2018, pp. 12-22.
Elsevier DOI 1804
BibRef
Earlier:
Feature saliency analysis for perceptual similarity of clustered microcalcifications,
ICIP15(775-778)
IEEE DOI 1512
BibRef
Earlier:
Adaboost with dummy-variable modeling for reduction of false positives in detection of clustered microcalcifications,
ICIP14(2295-2298)
IEEE DOI 1502
Computer-aided diagnosis (CAD), Clustered microcalcifications (MCs), Deep learning. Perceptual similarity. Adaptation models BibRef

Wang, J.[Juan], Yang, Y.Y.[Yong-Yi], Nishikawa, R.M.[Robert M.],
Quantitative study of image features of clustered microcalcifications in for-presentation mammograms,
ICIP16(3404-3408)
IEEE DOI 1610
BibRef
Earlier:
Reduction of false positive detection in clustered microcalcifications,
ICIP13(1433-1437)
IEEE DOI 1402
Design automation. Computer-aided diagnosis (CAD) BibRef

Yang, Y.[Yan], Wang, J.[Juan], Yang, Y.Y.[Yong-Yi],
Improving SVM classifier with prior knowledge in microcalcification detection1,
ICIP12(2837-2840).
IEEE DOI 1302
BibRef

Bria, A., Marrocco, C., Borges, L.R., Molinara, M., Marchesi, A., Mordang, J., Karssemeijer, N., Tortorella, F.,
Improving the Automated Detection of Calcifications Using Adaptive Variance Stabilization,
MedImg(37), No. 8, August 2018, pp. 1857-1864.
IEEE DOI 1808
Mammography, Standards, Solid modeling, Adaptation models, Transforms, Cancer, Digital mammography, quantum noise, microcalcification detection BibRef

Chakravarthy, S.R.S.[S. R. Sannasi], Rajaguru, H.[Harikumar],
Detection and classification of microcalcification from digital mammograms with firefly algorithm, extreme learning machine and non-linear regression models: A comparison,
IJIST(30), No. 1, 2020, pp. 126-146.
DOI Link 2002
benign, breast cancer, extreme learning machine, firefly classifier, malignant, mammogram, regression model, wavelet BibRef

AlGhamdi, M., Abdel-Mottaleb, M., Collado-Mesa, F.,
DU-Net: Convolutional Network for the Detection of Arterial Calcifications in Mammograms,
MedImg(39), No. 10, October 2020, pp. 3240-3249.
IEEE DOI 2010
Mammography, Task analysis, Image segmentation, Feature extraction, Solid modeling, Biological system modeling, segmentation U-Net BibRef

Liu, W.M.[Wei-Min], Long, M.J.[Mei-Jun], Peng, L.R.[Ling-Rong], Qu, C.H.[Cai-Hong], Guo, R.[Ruomi], Kang, Z.[Zhuang], Wang, J.[Jin], Wu, J.[Juekun], Wang, X.H.[Xiao-Hong],
Digital breast tomosynthesis improves diagnostic accuracy of breast microcalcifications,
IJIST(31), No. 2, 2021, pp. 555-561.
DOI Link 2105
breast imaging, breast imaging report and data system, diagnosis, digital breast tomosynthesis, microcalcification BibRef

Aminzadeh, A., Arhatari, B.D., Maksimenko, A., Hall, C.J., Hausermann, D., Peele, A.G., Fox, J., Kumar, B., Prodanovic, Z., Dimmock, M., Lockie, D., Pavlov, K.M., Nesterets, Y.I., Thompson, D., Mayo, S.C., Paganin, D.M., Taba, S.T., Lewis, S., Brennan, P.C., Quiney, H.M., Gureyev, T.E.,
Imaging Breast Microcalcifications Using Dark-Field Signal in Propagation-Based Phase-Contrast Tomography,
MedImg(41), No. 11, November 2022, pp. 2980-2990.
IEEE DOI 2211
Breast, X-ray imaging, Computed tomography, Australia, Imaging, Breast cancer, Detectors, Breast cancer, dark-field imaging, X-ray imaging BibRef

Sun, H.T.[Hao-Tian], Wu, S.[Shandong], Chen, X.J.[Xin-Jian], Li, M.[Ming], Kong, L.[Lingji], Yang, X.D.[Xiao-Dong], Meng, Y.[You], Chen, S.[Shuangqing], Zheng, J.[Jian],
SAH-NET: Structure-Aware Hierarchical Network for Clustered Microcalcification Classification in Digital Breast Tomosynthesis,
Cyber(54), No. 4, April 2024, pp. 2345-2357.
IEEE DOI Code:
WWW Link. 2403
Feature extraction, Convolution, Cancer, Transformers, Medical diagnostic imaging, Image resolution, Breast, microcalcification (MC) BibRef


Loizidou, K.[Kosmia], Skouroumouni, G.[Galateia], Savvidou, G.[Gabriella], Constantinidou, A.[Anastasia], Nikolaou, C.[Christos], Pitris, C.[Costas],
Classification of Breast Micro-calcifications as Benign or Malignant Using Subtraction of Temporally Sequential Digital Mammograms and Machine Learning,
CAIP23(II:109-118).
Springer DOI 2312
BibRef

Wang, K.[Kaier], Hill, M.[Melissa], Knowles-Barley, S.[Seymour], Tikhonov, A.[Aristarkh], Litchfield, L.[Lester], Bare, J.C.[James Christopher],
Improving Segmentation of Breast Arterial Calcifications from Digital Mammography: Good Annotation is All You Need,
ACCVWS22(134-150).
Springer DOI 2307
BibRef

Wang, K., Khan, N., Highnam, R.,
Automated Segmentation of Breast Arterial Calcifications from Digital Mammography,
IVCNZ19(1-6)
IEEE DOI 2004
blood vessels, diagnostic radiography, diseases, feature extraction, image classification, image filtering, deep learning BibRef

Zhang, F.[Fandong], Luo, L.[Ling], Sun, X.W.[Xin-Wei], Zhou, Z.[Zhen], Li, X.L.[Xiu-Li], Yu, Y.Z.[Yi-Zhou], Wang, Y.Z.[Yi-Zhou],
Cascaded Generative and Discriminative Learning for Microcalcification Detection in Breast Mammograms,
CVPR19(12570-12578).
IEEE DOI 2002
BibRef

Wang, J., Yang, Y.,
A Hierarchical Learning Approach for Detection of Clustered Microcalcifications in Mammograms,
ICIP19(804-808)
IEEE DOI 1910
Computer-aided detection (CADe), clustered microcalcifications (MCs), fully-convolutional neural network BibRef

Savelli, B.[Benedetta], Marrocco, C.[Claudio], Bria, A.[Alessandro], Molinara, M.[Mario], Tortorella, F.[Francesco],
Combining Convolutional Neural Networks for Multi-context Microcalcification Detection in Mammograms,
CAIPWS19(36-44).
Springer DOI 1909
BibRef

Wang, J., Fu, Z., Sadeghradehyazdi, N., Kipnis, J., Acton, S.T.,
Nonlinear Shape Regression for Filtering Segmentation Results from Calcium Imaging,
ICIP18(738-742)
IEEE DOI 1809
Shape, Neurons, Image segmentation, Calcium, Imaging, Manifolds, Splines (mathematics), Calcium imaging, shape analysis, cell segmentation BibRef

Khalaf, A.F.[Aya F.], Yassine, I.A.[Inas A.],
Novel features for microcalcification detection in digital mammogram images based on wavelet and statistical analysis,
ICIP15(1825-1829)
IEEE DOI 1512
Computer Aided Diagnosis BibRef

Mustra, M.[Mario], Grgic, M.[Mislav],
Detection of areas containing microcalcifications in digital mammograms,
WSSIP14(51-54) 1406
Biomedical imaging BibRef

Diaz-Huerta, C.C.[Claudia C.], Felipe-Riverón, E.M.[Edgardo M.], Montaño-Zetina, L.M.[Luis M.],
Evaluation and Selection of Morphological Procedures for Automatic Detection of Micro-calcifications in Mammography Images,
CIARP12(575-582).
Springer DOI 1209
BibRef

Chatterjee, S., Ray, A.K., Karim, R., Biswas, A.,
Detection of Micro-calcification to Characterize Malignant Breast Lesion,
NCVPRIPG11(251-254).
IEEE DOI 1205
BibRef

Ma, Y.M.[Yi-Ming], Tay, P.C.[Peter C.], Adams, R.D.[Robert D.], Zhang, J.Z.[James Z.],
A novel shape feature to classify microcalcifications,
ICIP10(2265-2268).
IEEE DOI 1009
BibRef

Torrent, A.[Albert], Oliver, A.[Arnau], Llado, X.[Xavier], Marti, R.[Robert], Freixenet, J.[Jordi],
A supervised micro-calcification detection approach in digitised mammograms,
ICIP10(4345-4348).
IEEE DOI 1009

See also Segmenting extended structures in radio astronomical images by filtering bright compact sources and using wavelets decomposition. BibRef

Tay, P.C.[Peter C.], Ma, Y.M.[Yi-Ming],
A novel microcalcification shape metric to classify regions of interests,
Southwest10(201-204).
IEEE DOI 1005
BibRef

Jing, H.[Hao], Yang, Y.Y.[Yong-Yi],
Regularized adaptive classification based on image retrieval for clustered microcalcifications,
ICIP12(1169-1172).
IEEE DOI 1302
BibRef
Earlier:
Case-Adaptive Classification Based on Image Retrieval for Computer-Aided Diagnosis,
ICIP10(4333-4336).
IEEE DOI 1009
BibRef
And:
Image retrieval for computer-aided diagnosis of breast cancer,
Southwest10(9-12).
IEEE DOI 1005
BibRef
Earlier:
Spatial distribution modeling for detection of clustered microcalcifications,
ICIP09(657-660).
IEEE DOI 0911
BibRef

Siong, T.S.[Ting Shyue], Isa, N.A.M.[Nor Ashidi Mat], Nordin, Z.M.[Zailani Mohammed], Ngah, U.K.[Umi Kalthum],
The Determination of the Number of Suspicious Clustered Micro Calcifications on ROI of Mammogram Images,
IVIC09(232-242).
Springer DOI 0911
BibRef

Chang, T.T.[Tian-Tian], Feng, J.[Jun], Liu, H.W.[Hong-Wei], Ip, H.H.S.[Horace H. S.],
Clustered Microcalcification detection based on a Multiple Kernel Support Vector Machine with Grouped Features (GF-SVM),
ICPR08(1-4).
IEEE DOI 0812
BibRef

Wu, Z.Q., Jiang, J., Peng, Y.H.,
Effective features based on normal linear structures for detecting microcalcifications in mammograms,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Veni, G., Regentova, E.E., Zhang, L.,
Detection of Clustered Microcalcifications with SUSAN Edge Detector, Adaptive Contrast Thresholding and Spatial Filters,
ICIAR08(xx-yy).
Springer DOI 0806

See also Susan: A New Approach to Low-Level Image-Processing. BibRef

Hernández-Cisneros, R.R.[Rolando R.], Terashima-Marín, H.[Hugo], Conant-Pablos, S.E.[Santiago E.],
Comparison of Class Separability, Forward Sequential Search and Genetic Algorithms for Feature Selection in the Classification of Individual and Clustered Microcalcifications in Digital Mammograms,
ICIAR07(911-922).
Springer DOI 0708
BibRef

Oporto-Díaz, S.[Samuel], Hernández-Cisneros, R.R.[Rolando R.], Terashima-Marín, H.[Hugo],
Detection of Microcalcification Clusters in Mammograms Using a Difference of Optimized Gaussian Filters,
ICIAR05(998-1005).
Springer DOI 0509
BibRef

Das, A.[Arpita], Bhattacharya, M.[Mahua],
GA Based Neuro Fuzzy Techniques for Breast Cancer Identification,
IMVIP08(136-141).
IEEE DOI 0809
BibRef
Earlier: A2, A1:
Fuzzy Logic Based Segmentation of Microcalcification in Breast Using Digital Mammograms Considering Multiresolution,
IMVIP07(98-105).
IEEE DOI 0709
BibRef

Vitulano, S.[Sergio], Casanova, A.[Andrea], Savona, V.[Valentina],
The Spiral Method Applied to the Study of the Microcalcifications in Mammograms,
CIAP05(915-921).
Springer DOI 0509
BibRef

Catanzariti, E., Ciminello, M., Prevete, R.,
Computer aided detection of clustered microcalcifications in digitized mammograms using Gabor functions,
CIAP03(266-270).
IEEE DOI 0310
BibRef

Gulsrud, T.O.[Thor Ole], Husøy, J.H.[John Håkon],
Detection of clustered microcalcifications in compressed mammograms,
SCIA01(P-W3A). 0206
BibRef
Earlier:
Optimal Filter for Detection of Clustered Microcalcifications,
ICPR00(Vol I: 508-511).
IEEE DOI 0009
BibRef

Quadrades, S., Sacristán, A.,
Automated Extraction of Microcalcifications BI-Rads Numbers in Mammograms,
ICIP01(II: 289-292).
IEEE DOI 0108
BibRef

Mata, R., Nava, E., Sendra, F.,
Microcalcifications Detection Using Multiresolution Methods,
ICPR00(Vol IV: 344-347).
IEEE DOI 0009
BibRef

Rodriguez-Sánchez, R., García, J.A., Fdez-Valdivia, J., Fdez-Vidal, X.R.[Xose R.],
How to Define the Notion of Microcalcifications in Digitized Mammograms,
ICPR00(Vol I: 494-499).
IEEE DOI 0009
BibRef

Cordella, L.P., Tortorella, F., Vento, M.,
Combining Experts with Different Features for Classifying Clustered Microcalcifications in Mammograms,
ICPR00(Vol IV: 324-327).
IEEE DOI 0009
BibRef

Bhangale, T., Desai, U., Sharma, U.,
An Unsupervised Scheme for Detection of Microcalcifications on Mammograms,
ICIP00(Vol I: 184-187).
IEEE DOI 0008
BibRef

Caputo, B., and Gigante, G.E.,
Digital Mammography: Gabor Filter for Detection of Microcalcifications,
VMV00(375-381).
PS File. BibRef 0001

Gurcan, M.N.[M. Nafi], Yardimci, Y.[Yasemin], Cetin, A.E.[A. Enis],
Influence function based Gaussianity tests for detection of microcalcifications in mammogram images,
ICIP99(III:407-411).
IEEE DOI BibRef 9900

Dinten, J.M.[Jean Marc], Darboux, M., Nicolas, E.,
Feature Extraction for a Precise Characterization of Microcalcifications in Mammograms,
ICIP96(I: 351-354).
IEEE DOI 9610
BibRef

Lado, M.J., Mendez, A.J., Tahoces, P.G., Souto, M., Correa, J., Vidal, J.J.,
Comparison of real and computer-simulated clustered microcalcifications on digital mammograms. ROC study,
ICIP96(I: 355-358).
IEEE DOI 9610
BibRef

Loew, M.H., Mia, R.S.,
Detection of microcalcifications in mammograms using eyetrack data,
ICIP95(III: 145-148).
IEEE DOI 9510
BibRef

Zhang, W.[Wei], Doi, K.[Kunio],
Method and system for the detection of microcalcifications in digital mammograms,
US_Patent5,491,627, Feb 13, 1996
WWW Link. BibRef 9602

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Breast Mass Detection, Analysis .


Last update:Nov 26, 2024 at 16:40:19