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Pathological lesion detection in 3D dynamic PET images using asymmetry

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3 Author(s)
Zhe Chen ; Sch. of Inf. technologies, Sydney Univ., NSW, Australia ; Dagan Feng ; Weidong Cai

This paper describes a segment-based asymmetry feature detection approach for three-dimensional positron emission tomography (PET) brain images to automatically extract pathological lesions. The method consists of three stages: preprocessing, segmentation, and asymmetry detection. The method was tested on simulation and clinical data sets and a per-pixel asymmetry feature detection is experimentally compared with our per-segment approach and the per-segment method is shown to produce fewer false positives and better demarcation in the PET data examples presented.

Published in:

Image Analysis and Processing, 2003.Proceedings. 12th International Conference on

Date of Conference:

17-19 Sept. 2003