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Title: Automated segmentation of tumour changes in temporal PET-CT data
Authors: Nyirenda, G
Kim, J
Wen, L
Feng, D
Keywords: Adaptive region growing
PET-CT segmentation
Treatment response
Tumour changes
Issue Date: 2012
Publisher: IEEE
Source: 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2-5 May 2012, Barcelona, p. 1699-1702 How to cite?
Abstract: Positron emission tomography and computed tomography (PET-CT) is widely accepted as the best imaging in the management of cancer. To assess response to treatment, multiple scans of a patient are usually acquired and tumour changes are analysed at different stages during the treatment. However, it is difficult to assimilate these changes, especially where a patient has in excess of e.g. four temporal scans. We aimed to advance current single-time PET tumour segmentation algorithms to multiple-time PET studies. We therefore proposed a new treatment response confidence connected region growing (TRCCRG) algorithm. Our algorithm is interactive and includes a combined function of Radial profile plot and Rodbard curve fitting as a measure of tumour likelihood for the morphologically expanded volume in successive scans. Evaluation with 10 simulated PET data and 6 clinical lymphoma PET-CT patients (each with 4 studies) demonstrated that the proposed method was successful in detecting and delineating tumours.
ISBN: 978-1-4577-1857-1
ISSN: 1945-7928
DOI: 10.1109/ISBI.2012.6235906
Appears in Collections:Conference Paper

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