TY  - JOUR
IS  - 3
N2  - Proposed is a simple yet effective method to reduce noise for ellipse fitting to scattered data on medical images. The method is developed specifically to address the challenge due to variation in the sharpness, magnitude and continuity of edges, when studying the medical images of a large population. The proposed method exploits prior knowledge to eliminate the inhomogeneity within the region of interest, and uses a k-means clustering technique to eliminate background noise. The objective is to create a 'noise-free' edge map for ellipse fitting. The method has been applied to retinal fundus images for optic-disc segmentation. Experiment results demonstrate the benefits of the proposed method. © The Institution of Engineering and Technology 2013.
KW  - Background noise; Ellipse fitting; Inhomogeneities; K-means clustering techniques; Large population; Prior knowledge; Region of interest; Retinal fundus images
KW  -  Noise abatement
KW  -  Image segmentation
ID  - scholars3745
Y1  - 2013///
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84877747931&doi=10.1049%2fel.2012.3432&partnerID=40&md5=516cf2690cf088a66aeeb1643823c418
A1  - Tang, T.B.
A1  - Lu, C.K.
A1  - Laude, A.
A1  - Dhillon, B.
A1  - Murray, A.F.
JF  - Electronics Letters
VL  - 49
AV  - none
N1  - cited By 3
TI  - Noise reduction for ellipse fitting on medical images
SP  - 178
SN  - 00135194
EP  - 179
ER  -