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MICCAI
2001
Springer
13 years 12 months ago
Valmet: A New Validation Tool for Assessing and Improving 3D Object Segmentation
Extracting 3D structures from volumetric images like MRI or CT is becoming a routine process for diagnosis based on quantitation, for radiotherapy planning, for surgical planning a...
Guido Gerig, Matthieu Jomier, Miranda Chakos
MICCAI
2007
Springer
14 years 8 months ago
Adaptive Metamorphs Model for 3D Medical Image Segmentation
Abstract. In this paper, we introduce an adaptive model-based segmentation framework, in which edge and region information are integrated and used adaptively while a solid model de...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas,...
CVPR
2009
IEEE
15 years 2 months ago
Constrained Marginal Space Learning for Efficient 3D Anatomical Structure Detection in Medical Images
Recently, we proposed marginal space learning (MSL) as a generic approach for automatic detection of 3D anatom- ical structures in many medical imaging modalities. To accurately...
Yefeng Zheng, Bogdan Georgescu, Haibin Ling, Shaoh...
MICCAI
2005
Springer
14 years 8 months ago
Segmentation and Size Measurement of Polyps in CT Colonography
Abstract. Virtual colonoscopy is a relatively new method for the detection of colonic polyps. Their size, which is measured from reformatted CT images, mainly determines diagnosis....
J. J. Dijkers, Cees van Wijk, Frans Vos, Jasper Fl...
CVPR
2011
IEEE
12 years 11 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