We propose a method to handle the automatic detection of PET lesions based on asymmetry feature measurement after segmenting the PET images. It is an essentially initial step in automatic diagnosis and content-based retrieval applications. Our technique includes six steps: Image alignment, segmentation, image reflection & subtraction, thresholding, background removal using morphological filtering and segment back-mapping. Compared with existing per-pixel asymmetry detection methods, our method can provide fewer false positives and more accurate results |
| Cite as: Chen, Z., Feng, D.D. and Cai, T.W. (2003). Automatic Detection of PET Lesions. In Proc. Pan-Sydney Area Workshop on Visual Information Processing (VIP2002), Sydney, Australia. CRPIT, 22. Jin, J. S., Eades, P., Feng, D. D. and Yan, H., Eds. ACS. 21. |
(from crpit.com)
