Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
The nature of statistical learning theory
The nature of statistical learning theory
Neural Edge Enhancer for Supervised Edge Enhancement from Noisy Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
MLMI'10 Proceedings of the First international conference on Machine learning in medical imaging
Efficient approximation of neural filters for removing quantumnoise from images
IEEE Transactions on Signal Processing
Hi-index | 0.00 |
One of the major challenges in computer-aided detection (CADe) of polyps in CT colonography (CTC) is the reduction of false-positive detections (FPs) without a concomitant reduction in sensitivity. Major sources of FPs generated by CADe schemes include haustral folds, residual stool, rectal tubes, the ileocecal valve, and extra-colonic structures such as the small bowel and stomach. A large number of FPs is likely to confound the radiologist's task of image interpretation, lower the radiologist's efficiency, and cause radiologists to lose their confidence in CADe as a useful tool. Therefore, it is important to reduce the number of FPs as much as possible while maintaining a high sensitivity. In this paper, FP reduction techniques used in CADe schemes for detection of polyps in CTC are reviewed.