segmentation

Active Mean Fields for Probabilistic Image Segmentation: Connections with Chan-Vese and Rudin-Osher-Fatemi Models

Segmentation is a fundamental task for extracting semantically meaningful regions from an image. The goal of segmentation algorithms is to accurately assign object labels to each image location. However, image-noise, shortcomings of algorithms, and …

Automatic atlas-based three-label cartilage segmentation from MR knee images

Osteoarthritis (OA) is the most common form of joint disease and often characterized by cartilage changes. Accurate quantitative methods are needed to rapidly screen large image databases to assess changes in cartilage morphology. We therefore …

Longitudinal three-label segmentation of knee cartilage

Automatic accurate segmentation methods are needed to assess longitudinal cartilage changes in osteoarthritis (OA). We propose a novel general spatio-temporal three-label segmentation method to encourage segmentation consistency across time in …

Segmentation with area constraints

Image segmentation approaches typically incorporate weak regularity conditions such as boundary length or curvature terms, or use shape information. High-level information such as a desired area or volume, or a particular topology are only implicitly …

Automatic multi-atlas-based cartilage segmentation from knee MR images

In this paper, we propose a multi-atlas-based method to automatically segment the femoral and tibial cartilage from T1 weighted magnetic resonance (MR) knee images. The segmentation result is a joint decision of the spatial priors from a multi-atlas …

Automatic bone segmentation and alignment from MR knee images

Automatic image analysis of magnetic resonance (MR) images of the knee is simplified by bringing the knee into a reference position. While the knee is typically put into a reference position during image acquisition, this alignment will generally not …

Automatic three-label bone segmentation from knee MR images

We propose a novel fully automatic three-label bone segmentation approach applied to knee segmentation (femur and tibia) from T1 and T2* magnetic resonance (MR) images. The three-label segmentation approach guarantees separate segmentations of femur …

DTI Connectivity by Segmentation

This paper proposes a new method to compute connectivity information from diffusion weighted images. It is inspired by graph-based approaches to connectivity definition, but formulates the estimation problem in the continuum. In particular, it …

Near-tubular fiber bundle segmentation for diffusion weighted imaging: Segmentation through frame reorientation

This paper proposes a methodology to segment near-tubular fiber bundles from diffusion weighted magnetic resonance images (DW-MRI). Segmentation is simplified by locally reorienting diffusion information based on large-scale fiber bundle geometry. …

Knowledge-Based Segmentation for Tracking Through Deep Turbulence

A combined knowledge-based segmentation/active contour algorithm is used for target tracking through turbulence. The algorithm utilizes Bayesian modeling for segmentation of noisy imagery obtained through longrange, laser imaging of a distance …