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CVPR
2011
IEEE
12 years 8 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
CVPR
2006
IEEE
14 years 6 months ago
Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment
Automatic polyp detection is an increasingly important task in medical imaging with virtual colonoscopy [15] being widely used. In this paper, we present a 3D object detection alg...
Zhuowen Tu, Xiang Sean Zhou, Luca Bogoni, Adrian B...
MICCAI
2001
Springer
13 years 9 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
CVPR
2006
IEEE
13 years 10 months ago
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes
We develop an integrated, probabilistic model for the appearance and three-dimensional geometry of cluttered scenes. Object categories are modeled via distributions over the 3D lo...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
ECCV
2002
Springer
14 years 6 months ago
A Stochastic Algorithm for 3D Scene Segmentation and Reconstruction
In this paper, we present a stochastic algorithm by effective Markov chain Monte Carlo (MCMC) for segmenting and reconstructing 3D scenes. The objective is to segment a range image...
Feng Han, Zhuowen Tu, Song Chun Zhu