TY - GEN
T1 - Principal curved based retinal vessel segmentation towards diagnosis of retinal diseases
AU - You, S.
AU - Bas, E.
AU - Erdogmus, D.
AU - Kalpathy-Cramer, J.
PY - 2011
Y1 - 2011
N2 - The extraction of retinal vessels plays an important role in the diagnosis and study of retinal diseases, such as Age-related Macular Degeneration (AMD), Diabetic Retinopathy, Retinopathy of Prematurity (ROP). Vessel diameters, tortuosity, branch lengths, angles, and bifurcations are essential to diagnosing these diseases. However, this is a challenging task due to high noise levels, the low contrast of thin vessels to the background, non-uniform illumination, and the central light reflex. Our goal here is to develop a framework to accurately segment the retinal vessels as a preprocessing step for the feature extraction of the vessels towards the future disease diagnosis. In this paper, we present a principal curve based retinal vessel segmentation approach to achieve this goal. We first use the isotropic Gaussian kernel Frangi filter to enhance the retinal vessels and measure the diameters of them. A multiscale principal curve projection and tracing algorithm is then proposed to identify the centerlines of the vessels in the output image of the Franfi filter using the underlying kernel smoothing interpolation of the intensities. The estimated vessel radius from the Frangi filter are used as the bandwidth of the kernel interpolation in the principal curve projection and tracing step. The vessel features toward diagnosing and analyzing the diseases can be extracted from our segmentation results. The presented approach is implemented on a publicly available DRIVE database [16].
AB - The extraction of retinal vessels plays an important role in the diagnosis and study of retinal diseases, such as Age-related Macular Degeneration (AMD), Diabetic Retinopathy, Retinopathy of Prematurity (ROP). Vessel diameters, tortuosity, branch lengths, angles, and bifurcations are essential to diagnosing these diseases. However, this is a challenging task due to high noise levels, the low contrast of thin vessels to the background, non-uniform illumination, and the central light reflex. Our goal here is to develop a framework to accurately segment the retinal vessels as a preprocessing step for the feature extraction of the vessels towards the future disease diagnosis. In this paper, we present a principal curve based retinal vessel segmentation approach to achieve this goal. We first use the isotropic Gaussian kernel Frangi filter to enhance the retinal vessels and measure the diameters of them. A multiscale principal curve projection and tracing algorithm is then proposed to identify the centerlines of the vessels in the output image of the Franfi filter using the underlying kernel smoothing interpolation of the intensities. The estimated vessel radius from the Frangi filter are used as the bandwidth of the kernel interpolation in the principal curve projection and tracing step. The vessel features toward diagnosing and analyzing the diseases can be extracted from our segmentation results. The presented approach is implemented on a publicly available DRIVE database [16].
KW - Retinal vessels
KW - centerline tracing
KW - principal curves
UR - http://www.scopus.com/inward/record.url?scp=81355136261&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=81355136261&partnerID=8YFLogxK
U2 - 10.1109/HISB.2011.39
DO - 10.1109/HISB.2011.39
M3 - Conference contribution
AN - SCOPUS:81355136261
SN - 9780769544076
T3 - Proceedings - 2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011
SP - 331
EP - 337
BT - Proceedings - 2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011
T2 - 2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011
Y2 - 26 July 2011 through 29 July 2011
ER -