Publicação: A Parallel Framework for HCC Detection in DCE-MRI Sequences with Wavelet-Based Description and SVM classification
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Assoc Computing Machinery
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Acesso aberto
Resumo
In this article, we propose a complete framework devoted to detect liver HCC (Hepato-Cellular Carcinoma) tumors within DCE-MRI (Dynamic Contrast Enhanced-MRI) sequences. Our system employs different phases of these hepatic image sequences (depending on time after contrast agent injection) to describe local patches with wavelet-based descriptors. By using a SVM (Support Vector Machine)-based classification, we are able to distinguish healthy patches from pathological ones. Moreover, thanks to a parallel image processing strategy, we are able to reduce significantly the running time so that our system may be utilized as a computer aided diagnosis tool in the future. Our experiments show that our contribution is an accurate system for HCC detection, with a small cohort of patients, but representing a high volume of image data to be processed. This work encourages us to conduct deeper researches for detecting complex HCC cases for larger patients cohorts.
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Medical image analysis, machine learning, DCE-MRI, liver, HCC, tumor detection, parallelization, wavelet image description
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Inglês
Como citar
33rd Annual Acm Symposium On Applied Computing. New York: Assoc Computing Machinery, p. 14-21, 2018.
