Browse Menu >>

Browse Subjects >>

Biomedical & Life Sciences

Business & Economics

Chemistry & Materials Science

Computer Science & Communications

Earth & Environmental Sciences

Engineering

Medicine & Healthcare

Physics & Mathematics

Social Sciences & Humanities

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

 

Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
   
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations

More>>

D-Y. Tsai, and Y. Lee, (2004) Improved adaptive neigh- borhood pre-processing for medical image enhancement, LNCS-3314, 576–581.

has been cited by the following article:

  • TITLE: A novel vague set approach for selective contrast enhancement of mammograms using multiresolution

    AUTHORS: Arpita Das, Mahua Bhattacharya

    KEYWORDS: Multiresolution; Vague Set Approach; True- membership Functions; False-Membership Functions

    JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.2 No.8, December 15, 2009

    ABSTRACT: The proposed algorithm introduces a novel vague set approach to develop a selective but robust, flexible and intelligent contrast enhancement technique for mammograms. Wavelet based filtering analysis can produce Low Frequency (LF) and High Frequency (HF) subbands of the original input images. The extremely small size microcalcifications become visible under multiresolution techniques. LF subband is then fuzzified by conventional fuzzy c-means clustering (FCM) algorithm with justified number of clusters. HF components, representing the narrow protrusions and other fine details are also fuzzified by FCM with justified number of clusters. Vague set approach captures the hesitancies and uncertainties of truly affected masses/other breast abnormalities with normal glandular tissues. After highlighting the masses/microcalcifications accurately, both LF and HF subbands are transformed back to the original resolution by inverse wavelet transform. The results show that the proposed method can successfully enhance the selected regions of mammograms and provide better contrast images for visual interpretation.