In this paper, a supervised pixel-based classifier approach for segmenting different anatomical regions in abdominal Computed Tomography (CT) studies is presented. The approach co...
Mikhail Kalinin, Daniela Stan Raicu, Jacob D. Furs...
Abstract--We aim at improving quantitative measures of emphysema in computed tomography (CT) images of the lungs. Current standard measures, such as the relative area of emphysema ...
We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsu...
Pancreas segmentation in 3-D computed tomography (CT) data is of high clinical relevance, but extremely difficult since the pancreas is often not visibly distinguishable from the...
Marius Erdt, Matthias Kirschner, Klaus Drechsler, ...
In this paper, we propose a hybrid approach for automatic single-organ segmentation in Computed Tomography (CT) data. The approach consists of three stages: first, a probability i...
Ruchaneewan Susomboon, Daniela Stan Raicu, Jacob D...