We present an automated algorithm for tissue segmentation of noisy, low contrast magnetic resonance (MR) images of the brain. We use a mixture model composed of a large number of G...
We consider approaches for exact similarity search in a high dimensional space of correlated features representing image datasets, based on principles of clustering and vector qua...
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
A fully learning-based framework has been presented for deformable registration of MR brain images. In this framework, the entire brain is first adaptively partitioned into a numbe...
The attentive region extraction is a challenging issue for semantic interpretation of image and video content. The successful attentive region extraction greatly facilitates image...