Gross segmentation of mammograms using a polynomial model

被引:0
|
作者
Chandrasekhar, R [1 ]
Attikiouzel, Y [1 ]
机构
[1] Univ Western Australia, Dept Elect & Elect Engn, Ctr Intelligent Informat Proc Syst, Nedlands, WA 6907, Australia
来源
PROCEEDINGS OF THE 18TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 18, PTS 1-5 | 1997年 / 18卷
关键词
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
The breast and background on a mammogram form complementary, connected sets. Generally, the intensities comprising the background are spatially continuous, low in value and lie within a closed interval. The background may therefore be approximated by a polynomial in a: and y on the basis of the Weierstrass approximation theorem. We include the whole background and a small portion of the breast in the region being modelled. The modelled background is subtracted from the original image, the resulting image thresholded, and the largest low intensity region taken to be the background. Connected regions are identified, labelled and merged. The background is flood-filled, and inclusions removed from the object, to yield a breast-background binary image. The method has been tested on 58 mammograms of two views from two digital mammogram databases. With one exception, it performs well and yields a skin-air interface with sufficient fidelity to preserve a nipple in profile.
引用
收藏
页码:1056 / 1058
页数:3
相关论文
共 50 条
  • [1] Segmentation of vessels from mammograms using a deformable model
    Valverde, FL
    Guil, N
    Muñoz, J
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2004, 73 (03) : 233 - 247
  • [2] Anatomic segmentation of mammograms via breast model
    Bakic, P
    Brzakovic, D
    Zhu, Z
    DIGITAL MAMMOGRAPHY, 1998, 13 : 291 - 294
  • [3] Lesion detection using segmentation and classification of mammograms
    Vibha, L.
    Harshavardhan, G. M.
    Pranaw, K.
    Shenoy, P. Deepa
    Venugopal, K. R.
    Patnaik, L. M.
    PROCEEDINGS OF THE IASTED INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND APPLICATIONS, 2007, : 311 - +
  • [4] Segmentation of the breast region in mammograms using snakes
    Wirth, MA
    Stapinski, A
    1ST CANADIAN CONFERENCE ON COMPUTER AND ROBOT VISION, PROCEEDINGS, 2004, : 385 - 392
  • [5] A model-based algorithm for mass segmentation in mammograms
    Xu, Weidong
    Xia, Shunren
    Xiao, Min
    Duan, Huilong
    2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 2543 - 2546
  • [6] Segmentation of breast tumors in mammograms using fuzzy sets
    Guliato, D
    Rangayyan, RM
    Carnielli, WA
    Zuffo, JA
    Desautels, JEL
    JOURNAL OF ELECTRONIC IMAGING, 2003, 12 (03) : 369 - 378
  • [7] Segmentation of Pectoral Muscle in Mammograms Using Granular Computing
    Divyashree, B., V
    Amarnath, R.
    Naveen, M.
    Kumar, Hemantha G.
    JOURNAL OF INFORMATION TECHNOLOGY RESEARCH, 2022, 15 (01)
  • [8] Segmentation of the breast region in mammograms using watershed transformation
    Kang Wei
    Wang Guangzhi
    Ding Hui
    2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7, 2005, : 6500 - 6503
  • [9] Unsupervised Mammograms Segmentation
    Haindl, Michal
    Mikes, Stanislav
    19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6, 2008, : 676 - 679
  • [10] Segmentation of mass in mammograms using a novel intelligent algorithm
    Xu, WD
    Xia, SR
    Duan, HL
    Xiao, M
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2006, 20 (02) : 255 - 270