Computer Aided Diagnosis of Mammographic Tissue Using Shapelets in Quaternionic Representation

被引：3
作者：
Apostolopoulos, G. [1 ]
Koutras, A. [1 ,2 ]
Christoyianni, I. [1 ]
Dermatas, E. [1 ]
机构：
[1] Univ Patras, Elect & Comp Engn Dept, Wired Commun Lab, Patras 26500, Greece
[2] Tech Educ Inst Western Greece, Informat & Mass Media Dept, Patras, Greece
来源：
XIV MEDITERRANEAN CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING 2016 | 2016年 / 57卷
关键词：
Shapelets; quaternion; breast cancer; computer-aided diagnosis (CAD); feature extraction; BREAST-CANCER; MASSES;
D O I：
10.1007/978-3-319-32703-7_45
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
In this paper a robust regions-of-suspicion (ROS) diagnosis system on mammograms, recognizing all types of abnormalities is presented and evaluated. A new type of descriptors, based on Shapelet decomposition, estimate the source images that generate the observed ROS in mammograms. The Shapelet decomposition coefficients can be used to efficiently detect ROS areas using a new classifier base on quaternionic representation. Extensive experiments using the Mammographic Image Analysis Society (MIAS) database have shown high recognition accuracy over 86% for all kinds of breast, with less computational cost.
引用
收藏
页码：222 / 227
页数：6
相关论文
共 50 条
  • [31] Computer Aided Breast Cancer Diagnosis Techniques in Ultrasound: A Survey
    Prabusankarl, K. M.
    Thirumoorthy, P.
    Manavalan, R.
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2014, 4 (03) : 331 - 349
  • [32] Computer aided diagnosis (CAD) of breast mass on ultrasonography and scintimammography
    Hwang, KH
    Lee, JG
    Kim, JH
    Lee, HJ
    Om, KS
    Yoon, M
    Choe, W
    Healthcom 2005: 7th International Workshop on Enterprise Networking and Computing in Healthcare Industry, Proceedings, 2005, : 187 - 190
  • [33] A Cervical Histopathology Dataset for Computer Aided Diagnosis of Precancerous Lesions
    Meng, Zhu
    Zhao, Zhicheng
    Li, Bingyang
    Su, Fei
    Guo, Limei
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021, 40 (06) : 1531 - 1541
  • [34] Computer-Aided Diagnosis of Breast Tumors Using Textures from Intensity Transformed Sonographic Images
    Lo, C. M.
    Chang, R. F.
    Huang, C. S.
    Moon, W. K.
    1ST GLOBAL CONFERENCE ON BIOMEDICAL ENGINEERING & 9TH ASIAN-PACIFIC CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING, 2015, 47 : 124 - +
  • [35] Computer-aided diagnosis of breast cancer from mammogram images using deep learning algorithms
    Emmanuel Gbenga Dada
    David Opeoluwa Oyewola
    Sanjay Misra
    Journal of Electrical Systems and Information Technology, 11 (1)
  • [36] Deep Learning in Computer-Aided Diagnosis Incorporating Mammographic Characteristics of both Tumor and Parenchyma Stroma
    Li, Hui
    Sheth, Deepa
    Mendel, Kayla R.
    Lan, Li
    Giger, Maryellen L.
    14TH INTERNATIONAL WORKSHOP ON BREAST IMAGING (IWBI 2018), 2018, 10718
  • [37] Computer-Aided Diagnosis of Malignant Mammograms using Zernike Moments and SVM
    Sharma, Shubhi
    Khanna, Pritee
    JOURNAL OF DIGITAL IMAGING, 2015, 28 (01) : 77 - 90
  • [38] Computer-aided diagnosis of breast lesions using a multifeature analysis procedure
    Alam, SK
    Lizzi, FL
    Feleppa, EJ
    Liu, T
    Kalisz, A
    MEDICAL IMAGE 2002: ULTRASONIC IMAGING AND SIGNAL PROCESSING, 2002, 4687 : 296 - 303
  • [39] Computer-aided diagnosis of breast cancer
    Lo, JY
    Floyd, CE
    COMPUTER-AIDED DIAGNOSIS IN MEDICAL IMAGING, 1999, 1182 : 221 - 225
  • [40] Computer aided diagnosis of breast cancer on mammograms
    Kunio Doi
    Maryellen L. Giger
    Robert M. Nishikawa
    Robert A. Schmidt
    Breast Cancer, 1997, 4 (4) : 228 - 233
12345