3D lung surface analysis towards segmentation of pleural thickenings

Abstract

Pleural thickenings are connective tissue propagations caused also by a long time exposure to asbestos. They can be an early stage indicator of the malignant pleural mesothelioma. Its diagnosis is time-consuming and underlies the physician’s subjective judgment. In order to speed-up the diagnosis and to increase the objectivity of the analysis, three fully automatic methods to detect pleural thickenings from CT data are described and compare in this paper. We apply normal vector analysis, second derivate analysis or curvature scale space computation to analyze the lung surface. In the second step we combine a hysteresis-thresholding with the principle of the convex hull to segment localized thickenings precisely. These new approaches are presented in order to allow precise and robust detection of pleural mesothelioma in early stage.