Automatic extraction of blood vessels and veins using laplace operator in fundus image

The paper proposes a novel method for extraction of blood vessels and veins from medical image of human eye - retinal fundus images that can be used in ophthalmology for detecting various eyes' diseases such glaucoma, diabetic retinopathy or macula oedema. The method utilizes an approach of preprocessing of image by using adaptive histogram equalization by CLAHE algorithm of green channel of fundus retinal image. Subsequently, using Laplace operator as key point of proposed algorithm and subsequently is applied the operation erosion processed image and removed small segments from image to enhance extraction of blood vessels from fundus image. The proposed technique analyzes detection and evaluates precision of the method on dataset from public fundus image libraries DRIVE, and HRF and compare with reference training results provided by these libraries.

[1]  Radim Burget,et al.  Novel method for localization of common carotid artery transverse section in ultrasound images using modified Viola-Jones detector. , 2013, Ultrasound in medicine & biology.

[2]  Wenhua Xu,et al.  Segmentation of blood vessels in color fundus images based on optimal multi-threshold method , 2012, 2012 International Conference on Machine Learning and Cybernetics.

[3]  Malay Kishore Dutta,et al.  An adaptive threshold based algorithm for detection of red lesions of diabetic retinopathy in a fundus image , 2014, 2014 International Conference on Medical Imaging, m-Health and Emerging Communication Systems (MedCom).

[4]  G. Lang Laser treatment of diabetic retinopathy. , 2007, Developments in ophthalmology.

[5]  Andrew Hunter,et al.  Optic nerve head segmentation , 2004, IEEE Transactions on Medical Imaging.

[6]  Chikkannan Eswaran,et al.  An automated blood vessel extraction algorithm in fundus images , 2012, 2012 IEEE International Conference on Bioinformatics and Biomedicine.

[7]  T. Sano,et al.  [Diabetic retinopathy]. , 2001, Nihon rinsho. Japanese journal of clinical medicine.

[8]  Kamil Riha,et al.  Automatic detection of the macula in retinal fundus images using multilevel thresholding , 2014 .

[9]  Max A. Viergever,et al.  Ridge-based vessel segmentation in color images of the retina , 2004, IEEE Transactions on Medical Imaging.

[10]  C. Thanapong,et al.  Extraction Blood Vessels from Retinal Fundus Image Based on Fuzzy C-Median Clustering Algorithm , 2007, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007).

[11]  Hideki Kuga,et al.  A computer method of understanding ocular fundus images , 1982, Pattern Recognit..