Automated scene analysis of CT scans.
Since the advent of computed tomography, there has been an increasing realization that CT scans contain quantitative as well as qualitative information useful in the diagnostic process. Often however, the use of this information is impeded by the tedious manual outlining of the areas of interest in the scan. To alleviate this problem, we have developed a scene segmentation algorithm which will automatically delineate areas of interest in a CT scan. This procedure uses known information about the expected objects in the scan in conjuction with an algorithm to label those objects. The resultant scene segmentation divides the scan into four anatomical areas: skull, normal brain, high density lesions and CSF. After an area of interest is interactively selected by the clinician, volume, density or other quantitative measures may be computed. Limitations of the algorithm and its clinical applications are discussed.
D015502:Absorptiometry, Photon; D001932:Brain Neoplasms / Q000000981:diagnostic imaging; D002543:Cerebral Hemorrhage / Q000000981:diagnostic imaging; D003201:Computers; D003626:Data Display; D006801:Humans; D014057:Tomography, X-Ray Computed / Q000379:methods*