Abnormalities Identification in Mammograms

被引：0
|
作者：
Chiorean, L. D. [1 ]
Vaida, M. F. [1 ]
Striletchi, C. [1 ]
机构：
[1] Tech Univ Cluj Napoca, Commun Dept, Cluj Napoca, Romania
来源：
INTERNATIONAL CONFERENCE ON ADVANCEMENTS OF MEDICINE AND HEALTH CARE THROUGH TECHNOLOGY, MEDITECH 2016 | 2017年 / 59卷
关键词：
segmentation; detection; mammography; abnormality; breast cancer;
D O I：
10.1007/978-3-319-52875-5_44
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
This paper proposes a method for detection of abnormalities in mammograms that could be integrated into a computer-aided diagnosis system. The method is based on segmentation using a clustering method, elimination of small regions, blobs and contour detection and a density analysis. The method was tested on images from screening mammography databases and the results are compared with the selections realized by specialists. The tests show that the method offers good results on images that present well defined abnormalities and by adjusting some parameters it can even detect distortions difficult to be noticed by physicians.
引用
收藏
页码：201 / 204
页数：4
相关论文
共 50 条
  • [41] An automatic method for the identification and interpretation of clustered microcalcifications in mammograms
    Schmidt, F
    Sorantin, E
    Szepesvàri, C
    Graif, E
    Becker, M
    Mayer, H
    Hartwagner, K
    PHYSICS IN MEDICINE AND BIOLOGY, 1999, 44 (05): : 1231 - 1243
  • [42] Identification of Masses in Mammograms by Image Sub-segmentation
    Ojeda-Magana, Benjamin
    Ruelas, Ruben
    Quintanilla-Dominguez, Joel
    Adriana Corona-Nakamura, Maria
    Andina, Diego
    SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS, 6TH INTERNATIONAL CONFERENCE SOCO 2011, 2011, 87 : 589 - 598
  • [43] Identification of masses in digital mammograms with MLP and RBF Nets
    Bovis, K
    Singh, S
    Fieldsend, J
    Pinder, C
    IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL I, 2000, : 342 - 347
  • [44] Soft Clustering and Support Vector Machine based Technique for the Classification of Abnormalities in Digital Mammograms
    Mc Leod, Peter
    Verma, Brijesh
    Park, Minyeop
    2009 INTERNATIONAL CONFERENCE ON INTELLIGENT SENSORS, SENSOR NETWORKS AND INFORMATION PROCESSING (ISSNIP 2009), 2009, : 179 - 183
  • [45] Detection and Classification of the Breast Abnormalities in Digital Mammograms via Regional Convolutional Neural Network
    Al-masni, M. A.
    Al-antari, M. A.
    Park, J. M.
    Gi, G.
    Kim, T. Y.
    Rivera, P.
    Valarezo, E.
    Han, S. -M.
    Kim, T. -S.
    2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2017, : 1230 - 1233
  • [46] Soft Clustering and Support Vector Machine based Technique for the Classification of Abnormalities in Digital Mammograms
    Mc Leod, Peter
    Verma, Brijesh
    Park, Minyeop
    PROCEEDINGS OF THE 2009 FIFTH INTERNATIONAL CONFERENCE ON INTELLIGENT SENSORS, SENSOR NETWORKS AND INFORMATION PROCESSING, 2009, : 185 - 189
  • [47] Identification of the breast boundary in mammograms using active contour models
    Ferrari, RJ
    Rangayyan, RM
    Desautels, JEL
    Borges, RA
    Frère, AF
    MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2004, 42 (02) : 201 - 208
  • [48] Computer-Aided Identification of the Pectoral Muscle in Digitized Mammograms
    K. Santle Camilus
    V. K. Govindan
    P. S. Sathidevi
    Journal of Digital Imaging, 2010, 23 : 562 - 580
  • [49] Identification of the breast boundary in mammograms using active contour models
    R. J. Ferrari
    A. F. Frère
    R. M. Rangayyan
    J. E. L. Desautels
    R. A. Borges
    Medical and Biological Engineering and Computing, 2004, 42 : 201 - 208
  • [50] Intensity based Automatic Boundary Identification of Pectoral Muscle in Mammograms
    Vikhe, P. S.
    Thool, V. R.
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMMUNICATION, COMPUTING AND VIRTUALIZATION (ICCCV) 2016, 2016, 79 : 262 - 269
12345