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 propose an automatic procedure for the correct segmentation of grey and white matter in MR data sets of the human brain. Our method exploits general anatomical knowledg...
Christian Wasserthal, Karin Engel, Karsten Rink, A...
An algorithm for improved automatic segmentation of gross anatomical structures of the human brain is presented that merges the output of a tissue classification process with gross...
D. Louis Collins, Alex P. Zijdenbos, Wim F. C. Baa...
Abstract. This study presents a novel automatic approach for the identification of anatomical brain structures in magnetic resonance images (MRI). The method combines a fast multis...
Ayelet Akselrod-Ballin, Meirav Galun, Moshe John G...
In this paper, a hybrid discriminative/generative model for brain anatomical structure segmentation is proposed. The learning aspect of the approach is emphasized. In the discrimin...