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Author
Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio
Title
A computational framework for cancer response assessment based on oncological PET-CT scans
Type
Journal Article
Year
2014
Publication
Computers in Biology and Medicine
Abbreviated Journal
CBM
Volume
55
Issue
Pages
92–99
Keywords
Computer aided diagnosis; Nuclear medicine; Machine learning; Image processing; Quantitative analysis
Abstract
In this work we present a comprehensive computational framework to help in the clinical assessment of cancer response from a pair of time consecutive oncological PET-CT scans. In this scenario, the design and implementation of a supervised machine learning system to predict and quantify cancer progression or response conditions by introducing a novel feature set that models the underlying clinical context is described. Performance results in 100 clinical cases (corresponding to 200 whole body PET-CT scans) in comparing expert-based visual analysis and classifier decision making show up to 70% accuracy within a completely automatic pipeline and 90% accuracy when providing the system with expert-guided PET tumor segmentation masks.
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HuPBA;MILAB
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no
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Admin @ si @ SED2014
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2606
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