6533b861fe1ef96bd12c5545
RESEARCH PRODUCT
A Machine Learning Approach for Computer-Aided Detection of Cerebral Microbleed Using High-order Shape Features
Amir Fazlollahi Fabrice Meriaudeau Luca Giancardo Christopher Rowe Victor L Villemagne Paul Yates Olivier Salvado Pierrick Bourgeatsubject
[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processingdescription
International audience; This paper presents a novel machine learning approach for computer-aided detection of microbleeds in SWI. The major contributions are: identifying microbleed extent in order to extract proper cubic regions-of-interest (ROI) containing the structure, (2) extracting a set of robust 3- dimensional (3D) Radon- and Hessian-based shape descriptors within the ROIs as well as 2D Radon features computed on intensity-projection images of the corresponding ROIs, and (3) incorporating a cascade of random forests (RF) classifiers to iteratively reduce false detection rates while maintaining a high sensitivity.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-05-10 |