A unified level set framework utilizing parameter priors for medical image segmentation

A multiphase level set framework for image segmentation using

A Level Set Based Hybride Framework for Confocal Image Segmentation

Based on level set approaches, a hybrid framework with quality control for nuclear segmentation of confocal images is presented. To overcome non homogeneous background, nuclei are firstly modeled into circles with some additive noise and Laplacian of Gaussian filter as a blob-detector is applied. Then, nuclei centers are obtained by energy minimization of fast marching towards the boundaries of...

A Unified Framework for Image Set Compression

While the compression of individual images have been studied extensively, there have been fewer studies on the problem of compressing image sets. A number of schemes have been proposed to compress an image set by taking advantage of the inter-image redundancy between pairs of images. In this paper, we present a unified graph-theoretic framework that includes all such previous schemes. A minimum...

An Adaptive Level Set Method for Medical Image Segmentation

An efficient adaptive multigrid level set method for front propagation purposes in three dimensional medical image processing and segmentation is presented. It is able to deal with non sharp segment boundaries. A flexible, interactive modulation of the front speed depending on various boundary and regularization criteria ensure this goal. Efficiency is due to a graded underlying mesh implicitly...

Combinative Multi-scale Level Set Framework for Echocardiographic Image Segmentation

In the automatic segmentation of echocardiographic images, a priori shape knowledge has been used to compensate for poor features in ultrasound images. This shape knowledge is often learned via an off-line training process, which requires tedious human effort and is highly expertise-dependent. More importantly, a learned shape template can only be used to segment a specific class of images with...