Utilization of evidence theory in the detection of salient regions in successive CT images.
This study presents an integrated approach to locating and presenting the medical practitioner with salient regions in a computed tomography (CT) scan when focusing on the area of the liver. A number of image processing tasks are performed in successive scans to extract areas with a different features than that of the greater part of the organ. In general, these areas do not always correspond to pathological patterns, but may be the result of noise in the scanned image or related to veins passing through the tissue. The result of the algorithm is the original image with a mask indicating these regions, so the attention of the medical practitioner is drawn to them for further examination. The algorithm also calculates a measure of confidence of the system, with respect to the extraction of the salient region, based on the fact that a region with a similar pattern is also located in successive scans. This essentially represents the hypothesis that the volume of both pathological patterns and blood vessels, but not noise patterns, is large enough to be captured in successive scans.
Athanasiadis
Thanos
T
Image, Video and Multimedia Systems Laboratory, National Technical University of Athens, GR-157 80 Athens, Greece. thanos@image.ntua.gr
Wallace
Manolis
M
Karpouzis
Kostas
K
Kollias
Stefanos
S
D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008113:Liver Neoplasms / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed