Paper Info
Title
A Novel Classification Method for Prediction of Rectal Bleeding in Prostate Cancer Radiotherapy Based on a Semi-Nonnegative ICA of 3D Planned Dose Distributions
Abstract
The understanding of dose/side-effects relationships in prostate cancer radiotherapy is crucial to define appropriate individual's constraints for the therapy planning. Most of the existing methods to predict side-effects do not fully exploit the rich spatial information conveyed by the three-dimensional planned dose distributions. We propose a new classification method for three-dimensional individuals' doses, based on a new semi-nonnegative ICA algorithm to identify patients at risk of presenting rectal bleeding from a population treated for prostate cancer. The method first determines two bases of vectors from the population data: the two bases span vector subspaces, which characterize patients with and without rectal bleeding, respectively. The classification is then achieved by calculating the distance of a given patient to the two subspaces. The results, obtained on a cohort of 87 patients (at two year follow-up) treated with radiotherapy, showed high performance in terms of sensitivity and specificity.
Year
DOI
Venue
2015
10.1109/JBHI.2014.2328315
IEEE J. Biomedical and Health Informatics
Keywords
Field
DocType
Classification,feature extraction,prostate cancer,radiotherapy,rectal bleeding,semi-nonnegative ICA algorithm,side effects
Population,Planned Dose,Pattern recognition,Radiation therapy,Prostate cancer,Artificial intelligence,Radiology,Surgery,Therapy planning,Cohort,Medicine
Journal
Volume
Issue
ISSN
19
3
2168-2194
Citations 
PageRank 
References 
1
0.39
15
Authors
10
Name
Order
Citations
PageRank
Julie Coloigner141.50
Aureline Fargeas210.39
Amar Kachenoura330.77
Lu Wang4132.82
Gaël Dréan551.61
Caroline Lafond620.76
Lotfi Senhadji724231.96
Renaud de Crevoisier820.87
Oscar Acosta9297.17
Laurent Albera1025024.44