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When rendering effects such as motion blur and defocus blur, shading can become very expensive if done in a naïve way, i.e. shading each visibility sample. To improve performance, previous work often decouple shading from visibility sampling using shader caching algorithms. We present a novel technique for reusing shading in a stochastic rasterizer. Shading(More)
Active shape models (ASMs) and active appearance models (AAMs) are popular approaches for medical image segmentation that use shape information to drive the segmentation process. Both approaches rely on image derived landmarks (specified either manually or automatically) to define the object's shape, which require accurate triangulation and alignment. An(More)
Screening and detection of prostate cancer (CaP) currently lacks an image-based protocol which is reflected in the high false negative rates currently associated with blinded sextant biopsies. Multi-protocol magnetic resonance imaging (MRI) offers high resolution functional and structural data about internal body structures (such as the prostate). In this(More)
Segmentation of the prostate boundary on clinical images is useful in a large number of applications including calculation of prostate volume pre- and post-treatment, to detect extra-capsular spread, and for creating patient-specific anatomical models. Manual segmentation of the prostate boundary is, however, time consuming and subject to inter- and(More)
PURPOSE Prostate gland segmentation is a critical step in prostate radiotherapy planning, where dose plans are typically formulated on CT. Pretreatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to perform, compared to delineation on CT. In this work, the(More)
Recently, high resolution 3 Tesla (T) Dynamic Contrast-Enhanced MRI (DCE-MRI) of the prostate has emerged as a promising modality for detecting prostate cancer (CaP). Computer-aided diagnosis (CAD) schemes for DCE-MRI data have thus far been primarily developed for breast cancer and typically involve model fitting of dynamic intensity changes as a function(More)
Prostate MRI image segmentation has been an area of intense research due to the increased use of MRI as a modality for the clinical workup of prostate cancer. Segmentation is useful for various tasks, e.g. to accurately localize prostate boundaries for radiotherapy or to initialize multi-modal registration algorithms. In the past, it has been difficult for(More)
Segmentation of the prostate boundary on clinical images is useful in a large number of applications including calculating prostate volume during biopsy, tumor estimation, and treatment planning. Manual segmentation of the prostate boundary is, however, time consuming and subject to inter-and intra-reader variability. Magnetic Resonance (MR) imaging (MRI)(More)
We present a hierarchical traversal algorithm for stochastic rasterization of motion blur, which efficiently reduces the number of inside tests needed to resolve spatio-temporal visibility. Our method is based on novel tile against moving primitive tests that also provide temporal bounds for the overlap. The algorithm works entirely in homogeneous(More)