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We present a computer vision system that automatically de- tects pulmonary nodules in computed tomography (CT) scans of oncol- ogy patients, performs size analysis andassesses for change in volume over time. Thresholding, backtracking, and smoothing algorithms have been devel- opedto recognize the thorax andtrace the lung bord er. The regions within the lung that potentially contain nodules are evaluated for their shape, size, and position. These candidate regions are then characterized as nodules versus other structures by comparing consecutive CT slices in the same study. A preliminary system for the registration of studies has also been developed. It estimates nodule volume in each study and evaluates the volumetric change over time. Our system has been testedon initial andfollow-up stud ies of four pa- tients. Preliminary results were detection of 284 nodules ranging between 1 and32 mm at various locations andassessment of their volumetric change over time. Our techniques have future applications for determining disease progres- sion, remission, and stability in oncologic patients in addition to coreg- istration of different modalities within the thorax.

Detection of Pulmonary Nodules on CT and Volumetric Assessment of Change over Time