Title :
Efficient machine learning framework for computer-aided detection of cerebral microbleeds using the Radon transform
Author :
Fazlollahi, Amir ; Meriaudeau, Fabrice ; Villemagne, Victor L. ; Rowe, Christopher C. ; Yates, Paul ; Salvado, Olivier ; Bourgeat, Pierrick
Author_Institution :
Preventative Health Flagship, Comput. Inf., CSIRO, Herston, QLD, Australia
fDate :
April 29 2014-May 2 2014
Abstract :
Recent developments of susceptibility weighted MR techniques have improved visualization of venous vasculature and underlying pathologies such as cerebral microbleed (CMB). CMBs are small round hypointense lesions on MRI images that are emerging as a potential biomarker for cerebrovascular disease. CMB manual rating has limited reliability, is time-consuming and is prone to errors as small CMBs can be easily missed or mistaken for venous cross-sections. This paper presents a computer-aided detection technique that utilizes a novel cascade of random forest classifiers which are trained on robust Radon-based features with an unbalanced sample distribution. The training samples and their associated bounding box were acquired from a multi-scale Laplacian of Gaussian technique with respect to their geometric characteristics. Validation results demonstrate that the current approach outperforms state of the art approaches with sensitivity of 92.04% and an average false detection rate of 16.84 per subject.
Keywords :
Gaussian processes; Radon transforms; biomedical MRI; blood vessels; brain; diseases; haemodynamics; image classification; learning (artificial intelligence); medical image processing; CMB manual rating; Gaussian technique; Radon transform; cerebral microbleed; cerebral microbleeds; cerebrovascular disease biomarker; computer-aided detection; hypointense lesions; machine learning framework; magnetic resonance imaging; multiscale Laplacian; random forest classifiers; susceptibility weighted MRI; venous vasculature; Diseases; Feature extraction; Radio frequency; Sensitivity; Shape; Three-dimensional displays; Transforms; Cerebral Microbleeds; Radon transform; Susceptibility Weighted Imaging; multi-scale Laplacian of Gaussian; sphere detection;
Conference_Titel :
Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on
Conference_Location :
Beijing
DOI :
10.1109/ISBI.2014.6867822