Automatic detection of PET lesions

Authors:
Zhe Chen;David Dagan Feng;Weidong Cai
Affiliations:
Biomedical & Multimedia Information Technology (BMIT) Group, School of Information technology, The University of Sydney;Biomedical & Multimedia Information Technology (BMIT) Group, School of Information technology, The University of Sydney and Center for Multimedia Signal Processing (CMSP), Department of Electronic ...;Biomedical & Multimedia Information Technology (BMIT) Group, School of Information technology, The University of Sydney
Venue:
VIP '02 Selected papers from the 2002 Pan-Sydney workshop on Visualisation - Volume 22
Year:
2003

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Abstract

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.