Feature extraction and classification for rectal bleeding in prostate cancer radiotherapy: A PCA based method
Abstract
In this work, we studied the efficiency of principal component analysis for feature extraction and classification of prostate cancer patients suffering from rectal bleeding. We fully exploited the three-dimensional planned dose distribution by considering the voxels as observations. We compared different possibilities for selecting the most relevant features (sequential and combinatory). The receiving operator characteristics were used as performance criterion. The obtained results demonstrate the ability of the method to classify two groups of patients, namely rectal bleeding and non-rectal bleeding. They also suggest that local dose/toxicity relationships exist.
Keywords
This work was supported by "Region Bretagne" and has received a French government support granted to the CominLabs excellence laboratory and managed by the National Research Agency in the "Investing for the Future" program under reference ANR-10-LABX-07-01.
This work was supported by "Region Bretagne" and has received a French government support granted to the CominLabs excellence laboratory and managed by the National Research Agency in the "Investing for the Future" program under reference ANR-10-LABX-07-01
Domains
Medical Imaging
Origin : Files produced by the author(s)
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