Coupling Deformable Model & Pixel Affinity Methods For Medical Image Segmentation & 3D Organ Reconstruction

Abstract IIS-9820794 Metaxas, Dimitris University of Pennsylvania $150,658 - 12 mos. Coupling Deformable Model and Pixel Affinity Methods for Medical Image Segmentation and 3D Organ Reconstruction This is the first year funding of a three year continuing award. This research develops new and efficient methods for segmenting radiological data of internal organs and reconstructing their 3D shape, to improve clinical practice and medical education. These new methods allow the inclusion of image features such as patterns, textures and contours, to the storage and retrieval of data from the patient databases of the future. The methods we develop do not depend on the imaging modality used and can be used for any type of internal organ. However, given the focus of our current research, we segment primarily the lungs and the heart and secondarily the brain. Such data are routinely used at the University of Pennsylvania. In particular we develop 1) methods for detecting and segmenting the boundaries of internal organs, 2) methods for detecting abnormalities in the form of lesions, such as cancers and infections, 3) appropriate user interfaces so that the segmentation results can be superimposed on the radiological image, 4) 3D reconstructions of the shape of the internal organs using deformable models and splines, 5) the necessary evaluation procedures to test the accuracy of the segmentation methods and the efficacy of the user interface.