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» Fast Automatic Segmentation of the Esophagus from 3D CT Data...
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MICCAI
2009
Springer
10 years 10 months ago
Fast Automatic Segmentation of the Esophagus from 3D CT Data Using a Probabilistic Model
Automated segmentation of the esophagus in CT images is of high value to radiologists for oncological examinations of the mediastinum. It can serve as a guideline and prevent confu...
Johannes Feulner, Shaohua Kevin Zhou, Alexander Ca...
ICCV
2007
IEEE
10 years 7 months ago
Fast Automatic Heart Chamber Segmentation from 3D CT Data Using Marginal Space Learning and Steerable Features
Multi-chamber heart segmentation is a prerequisite for global quantification of the cardiac function. The complexity of cardiac anatomy, poor contrast, noise or motion artifacts ...
Yefeng Zheng, Adrian Barbu, Bogdan Georgescu, Mich...
MICCAI
2010
Springer
9 years 11 months ago
Model-Based Esophagus Segmentation from CT Scans Using a Spatial Probability Map
Automatic segmentation of the esophagus from CT data is a challenging problem. Its wall consists of muscle tissue, which has low contrast in CT. Sometimes it is filled with air or...
Johannes Feulner, Shaohua Kevin Zhou, Martin Huber...
ISVC
2009
Springer
10 years 5 months ago
A Novel 3D Segmentation of Vertebral Bones from Volumetric CT Images Using Graph Cuts
Bone mineral density (BMD) measurements and fracture analysis of the spine bones are restricted to the Vertebral bodies (VBs). In this paper, we present a novel and fast 3D segment...
Melih S. Aslan, Asem M. Ali, Ham M. Rara, Ben Arno...
CVPR
2011
IEEE
9 years 5 months ago
Effective 3D Object Detection and Regression Using Probabilistic Segmentation Features in CT Images
3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose ...
Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff
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