A computer aided detection system for cerebral microbleeds in brain MRI

TY - GEN

T1 - A computer aided detection system for cerebral microbleeds in brain MRI

AU - Ghafaryasl, Babak

AU - van der Lijn, Fedde

AU - Poels, Mariëlle

AU - Vrooman, Henri

AU - Ikram, Mohammad Arfan

AU - Niessen, Wiro J.

AU - van der Lugt, Aad

AU - Vernooij, Meike

AU - de Bruijne, Marleen

N1 - Conference code: 9

PY - 2012

Y1 - 2012

N2 - Advances in MR technology have improved the potential for visualization of small lesions in brain images. This has resulted in the opportunity to detect cerebral microbleeds (CMBs), small hemorrhages in the brain that are known to be associated with risk of ischemic stroke and intracerebral bleeding. In this paper, we propose a computer aided detection (CAD) system for the detection of CMBs to speed up visual analysis. Our method consists of three steps: (i) skull-stripping (ii) initial candidate selection and (iii) reduction of false-positives (FPs) using a two layer classification. Geometrical, intensity-based and local image descriptor features were used in the classification steps. The training and test set consist of 156 subjects (448 CMBs) and 81 subjects (183 CMBs), respectively. The sensitivity for CMB detection was 91% with, on average, 4.1 false-positives per subject.

AB - Advances in MR technology have improved the potential for visualization of small lesions in brain images. This has resulted in the opportunity to detect cerebral microbleeds (CMBs), small hemorrhages in the brain that are known to be associated with risk of ischemic stroke and intracerebral bleeding. In this paper, we propose a computer aided detection (CAD) system for the detection of CMBs to speed up visual analysis. Our method consists of three steps: (i) skull-stripping (ii) initial candidate selection and (iii) reduction of false-positives (FPs) using a two layer classification. Geometrical, intensity-based and local image descriptor features were used in the classification steps. The training and test set consist of 156 subjects (448 CMBs) and 81 subjects (183 CMBs), respectively. The sensitivity for CMB detection was 91% with, on average, 4.1 false-positives per subject.

U2 - 10.1109/ISBI.2012.6235503

DO - 10.1109/ISBI.2012.6235503

M3 - Article in proceedings

SN - 978-1-4577-1858-8

SP - 138

EP - 141

BT - 2012 9th IEEE International Symposium on Biomedical Imaging:

PB - IEEE

T2 - 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro

Y2 - 2 May 2012 through 5 May 2012

ER -