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This paper presents a novel on-line learning method for automatically detecting anatomic structures in medical images. Conventional off-line learning requires collecting all representative samples before the commencement of training. Our presented approach eliminates the need for storing historical training samples and is capable of continuously enhancing its performance with new samples. We evaluate...
This paper presents a novel online learning method for automatically detecting anatomic structures in medical images. Conventional off-line learning methods require collecting a complete set of representative samples prior to training a detector. Once the detector is trained, its performance is fixed. To improve the performance, the detector must be completely retrained, demanding the maintenance...
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