Proceedings Article | 24 March 2016
KEYWORDS: 3D modeling, Lung, 3D image processing, Computing systems, Mesothelioma, Computed tomography, Image processing, Tumor growth modeling, Feature extraction, Image registration, Data modeling, Tissues, Computer aided diagnosis and therapy, Image segmentation
Pleural thickenings are caused by asbestos exposure and may evolve into malignant pleural mesothelioma. An early diagnosis plays a key role towards an early treatment and an increased survival rate. Today, pleural thickenings are detected by visual inspection of CT data, which is time-consuming and underlies the physician's subjective judgment. A computer-assisted diagnosis system to automatically assess pleural thickenings has been developed, which includes not only a quantitative assessment with respect to size and location, but also enhances this information with an anatomical description, i.e. lung side (left, right), part of pleura (pars costalis, mediastinalis, diaphragmatica, spinalis), as well as vertical (upper, middle, lower) and horizontal (ventral, dorsal) position. For this purpose, a 3D anatomical model of the lung surface has been manually constructed as a 3D atlas. Three registration sub-steps including rigid, affine, and nonrigid registration align the input patient lung to the 3D anatomical atlas model of the lung surface. Finally, each detected pleural thickening is assigned a set of labels describing its anatomical properties. Through this added information, an enhancement to the existing computer-assisted diagnosis system is presented in order to assure a higher precision and reproducible assessment of pleural thickenings, aiming at the diagnosis of the pleural mesothelioma in its early stage.
