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ICCV
1999
IEEE

Learning-based Object Detection in Cardiac MR Images

10 years 3 months ago
Learning-based Object Detection in Cardiac MR Images
An automated method for left ventricle detection in MR cardiac images is presented. Ventricle detection is the rst step in a fully automated segmentation system used to compute volumetric information about the heart. Our method is based on learning the gray level appearance of the ventricle by maximizing the discrimination between positive and negative examples in a training set. The main di erences from previously reported methods are feature de nition and solution to the optimization problem involved in the learning process. Our method was trained on a set of 1,350 MR cardiac images from which 101,250 positive examples and 123,096 negative examples were generated. The detection results on a test set of 887 di erent images demonstrate an excellent performance: 98 detection rate, a false alarm rate of 0:05 of the number of windows analyzed 10 false alarms per image and a detection time of 2 seconds per 256 256 image on a Sun Ultra 10 for an 8-scale search. The false alarms are eventu...
Nicolae Duta, Anil K. Jain, Marie-Pierre Dubuisson
Added 15 Oct 2009
Updated 15 Oct 2009
Type Conference
Year 1999
Where ICCV
Authors Nicolae Duta, Anil K. Jain, Marie-Pierre Dubuisson-Jolly
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