The following information was submitted:
Transactions: INTERNATIONAL JOURNAL of BIOLOGY and BIOMEDICAL ENGINEERING
Transactions ID Number: 19-443
Full Name: Nader Riyahi Alam
Position: Associate Professor
Age: ON
Sex: Male
Address: Keshavarz blvd., 16 azar st, poursina ave.,
Country: IRAN
Tel: 0098-21-66466383
Tel prefix: 0098-21
Fax: 0098-21-66466383
E-mail address: riahinad@sina.tums.ac.ir
Other E-mails: riahinader66@yahoo.com
Title of the Paper: Computer-Aided Mass Detection on Digitized Mammograms using a Novel Hybrid Segmentation System
Authors as they appear in the Paper: Farzad Younesi
Email addresses of all the authors: fyounesi@razi.tums.ac.ir
Number of paper pages: 8
Abstract: A Novel hybrid segmentation method has been developed for detection of masses in digitized mammograms using three parallel approaches: adaptive thresholding method, Gabor filtering and fuzzy entropy feature as a computer-aided detection(CAD) scheme. The algorithm consists of the following steps: a) Preprocessing of the digitized mammograms including identification of region of interest (ROI) as candidate for massive lesion through breast region extraction, b) Image enhancement using linear transformation and subtracting enhanced from the original image, c) Characterization of the ROI by extracting the fuzzy entropy feature, d) Local adaptive thresholding for segmentation of mass areas, e) Filtering the input images using Gabor functions, f) Combine expert of the last three parallel approaches for mass detection. The proposed method was tested on 78 mammograms (30 normal & 48 cancerous) from the BIRADS and local databases. The detected regions validated by comparing!
them with the radiologists' hand-sketched boundaries of real masses. The current algorithm can achieve a sensitivity of 90.73% and specificity of 89.17%. This approach showed that the behavior of local adaptive thresholding, Gabor filters and fuzzy entropy technique could be useful for mass detection on digitized mammograms. Our results suggest that the proposed method could help radiologists as a second reader in mammographic screening of masses.
Keywords: Digitized Mammograms,Detection of Masses, Hybrid System
EXTENSION of the file: .doc
Special (Invited) Session: Hybrid System for Detection of Masses in Digitized Mammograms
Organizer of the Session: 647-315.pdf
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