In this paper we present a hierarchical, learning-based approach for automatic and accurate liver segmentation from 3D CT volumes. We target CT volumes that come from largely dive...
Haibin Ling, Shaohua Kevin Zhou, Yefeng Zheng, Bog...
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
Abstract— This paper presents a robust algorithm for segmentation and line detection in 2D range scans. The described method exploits the multimodal probability density function ...
Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in...
Albert Murtha, Dana Cobzas, Mark Schmidt, Martin J...
Abstract. Interaction increases flexibility of segmentation but it leads to undesirable behaviour of an algorithm if knowledge being requested is inappropriate. In region growing, ...