Matching 3D face scans using interest points and local histogram descriptors

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Early Diagnosis and Staging of Prostate Cancer Using Magnetic Resonance Imaging: State of the Art and Perspectives

Prostate cancer is the second most common cancer among men in the United States after skin cancer. Although it can be a serious disease, early diagnosis of prostate cancer can significantly prevent the growth of cancerous cells. The feature extraction is the process of defining and deriving from the prostate region computational entities that form a sort of prostate cancer signature. Full computer-aided diagnosis (CAD) systems presented in several studies have reported the use of engineered features obtained from multimodal magnetic resonance imaging (MRI) to detect prostate cancer. Similar to other medical imaging CAD systems, the computer-aided diagnosis of prostate cancer using MRI framework encompasses four stages, namely: pre-processing, prostate region extraction, features extraction, and classification. Identifying the region of interest in the MR images is essential to reduce the complexity of the next stages and enhance the performance of the overall CAD system

Fitting of Constrained Models to Poor 3D Data

Proceedings of Adaptive Computing in Design and Manufacture (ACDM 2000)In this work we have addressed the question of whether it is possible to extract parametric models of features from poor quality 3D data. In doing this we have examined the applicability of an evolutionary strategy to the problem of fitting constrained parametric models. In the first phase, a background surface is fitted and removed leaving points of discontinuity associated with the artifacts. Then the discontinuities are classified, using the RANSAC algorithm, into drilled hole artifacts or blade edges suggesting drilled slots. This information, as well as the set of discontinuity points is passed to the Genocop III algorithm proposed by Michalewicz for optimization using a priori geometric constraints. Results, example times for convergence and comparisons with known ground truths are given