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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 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 To identify and evaluate textural quantitative imaging signatures (QISes) for tumors occurring within the central gland (CG) and peripheral zone (PZ) of the prostate, respectively, as seen on in vivo 3 Tesla (T) endorectal T2-weighted (T2w) MRI. MATERIALS AND METHODS This study used 22 preoperative prostate MRI data sets (16 PZ, 6 CG) acquired(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)
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)
RATIONALE AND OBJECTIVES Accurate prostate volume estimation is useful for calculating prostate-specific antigen density and in evaluating posttreatment response. In the clinic, prostate volume estimation involves modeling the prostate as an ellipsoid or a spheroid from transrectal ultrasound, or T2-weighted magnetic resonance imaging (MRI). However, this(More)
Prostate segmentation is a necessary step for computer aided diagnosis systems, volume estimation, and treatment planning. The use of standard datasets is vital for comparing different segmentation algorithms, and 100 datasets from 4 institutions were gather to test different algorithms on T2-weighted MR imagery. In this paper, a landmark-free Active(More)
We present a novel anisotropic sampling algorithm for image space shading which builds upon recent advancements in decoupled sampling for stochastic rasterization pipelines. First, we analyze the frequency content of a pixel in the presence of motion and defocus blur. We use this analysis to derive bounds for the spectrum of a surface defined over a(More)
Sphaerospores were found among three species of fish examined from waters known to be enzootic for proliferative kidney disease (PKD) of salmonids. They were detected in the renal tubules of both hatchery-reared rainbow trout (Salmo gairdneri) exposed to the infectious stage of PKD and in chubs (Gila bicolor) in the headwaters of a hatchery where PKD is(More)
CONTEXT Co-registration of ex-vivo histologic images with pre-operative imaging (e.g., magnetic resonance imaging [MRI]) can be used to align and map disease extent, and to identify quantitative imaging signatures. However, ex-vivo histology images are frequently sectioned into quarters prior to imaging. AIMS This work presents Histostitcher™, a software(More)