Access Restriction

Author Zhang, Yu ♦ Tomuro, Noriko ♦ Furst, Jacob ♦ Raicu, Daniela Stan
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Image Enhancement ♦ Edge-based Mass Segmentation ♦ Energy Texture Image ♦ Edge-based Segmentation Method ♦ Mass Region ♦ Preliminary Result ♦ Mass Contour ♦ Image Noise ♦ Closed-path Edge ♦ Suspicious Mass Region ♦ Haralick Descriptor ♦ Roi-marked Mammogram Image ♦ Roi Marking ♦ Image Contrast ♦ Co-occurrence Matrix ♦ Filtering Function ♦ Segmented Mass ♦ Digital Database ♦ Identified Mass Region ♦ Energy Descriptor
Abstract This paper presents a novel, edge-based segmentation method for identifying the mass contour (boundary) for a suspicious mass region (Region of Interest (ROI)) in a mammogram. The method first applies a contrast stretching function to adjust the image contrast, then uses a filtering function to reduce image noise. Next, for each pixel in a ROI, the energy descriptor (one of the Haralick descriptors) is computed from the co-occurrence matrix of the pixel; and the energy texture image of a ROI is obtained. From the energy texture image, the edges in the image are detected; and the mass region is identified from the closed-path edges. Finally, the boundary of the identified mass region is used as the contour of the segmented mass. We applied our method to ROI-marked mammogram images from the Digital Database for Screening Mammography (DDSM). Preliminary results show that the contours detected by our method outline the shape and boundary of a mass much more closely than the ROI markings made by radiologists.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article