Application of Morphological Bit Planes in Retinal Blood Vessel Extraction.

Digital Imaging Research Centre, Faculty of Science Engineering and Computing, Kingston University London, Penrhyn Road, Kingston upon Thames, KT12EE, UK, .
Journal of Digital Imaging (Impact Factor: 1.1). 07/2012; DOI: 10.1007/s10278-012-9513-3
Source: PubMed

ABSTRACT The appearance of the retinal blood vessels is an important diagnostic indicator of various clinical disorders of the eye and the body. Retinal blood vessels have been shown to provide evidence in terms of change in diameter, branching angles, or tortuosity, as a result of ophthalmic disease. This paper reports the development for an automated method for segmentation of blood vessels in retinal images. A unique combination of methods for retinal blood vessel skeleton detection and multidirectional morphological bit plane slicing is presented to extract the blood vessels from the color retinal images. The skeleton of main vessels is extracted by the application of directional differential operators and then evaluation of combination of derivative signs and average derivative values. Mathematical morphology has been materialized as a proficient technique for quantifying the retinal vasculature in ocular fundus images. A multidirectional top-hat operator with rotating structuring elements is used to emphasize the vessels in a particular direction, and information is extracted using bit plane slicing. An iterative region growing method is applied to integrate the main skeleton and the images resulting from bit plane slicing of vessel direction-dependent morphological filters. The approach is tested on two publicly available databases DRIVE and STARE. Average accuracy achieved by the proposed method is 0.9423 for both the databases with significant values of sensitivity and specificity also; the algorithm outperforms the second human observer in terms of precision of segmented vessel tree.

1 Bookmark
  • [Show abstract] [Hide abstract]
    ABSTRACT: This study plays a vital role in the significance of the analysis of an image in medical image processing field, is gaining thought of many researchers in modern times. The recognition of faults present in the destroyed portion of an image is imperative for based field. In this paper, we focus at developing an approach for better classification of medical images. Our methodology is based on the concept of a novel fuzzy approach with bit plane (FCMBP) algorithm. The bit plane filtering method is used to slice the given image for classification to find out the destroyed region of the given image. The sliced image should be normalized with the old techniques and compared with the fuzzy technique for better classification and cluster of the spoiled portion. Thereby the control points have been extracted that are needed for further reconstruction of images. The performance of fuzzy approach with bit plane technique is evaluated using simulation and it is proved that our approach yields better results when compared to accessible methods.
    Emerging Trends in Computing, Communication and Nanotechnology (ICE-CCN), 2013 International Conference on; 01/2013
  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents an automated blood vessel detection method from the fundus image. The method first performs some basic image preprocessing tasks on the green channel of the retinal image. A combination of morphological operations like top- hat and bottom-hat transformations are applied on the preprocessed image to highlight the blood vessels. Finally, the Kohonen Clustering Network is applied to cluster the input image into two clusters namely vessel and non-vessel. The performance of the proposed method is tested by applying it on retinal images from Digital Retinal Images for Vessel Extraction (DRIVE)database. The results obtained from the proposed method are compared with three other state of the art methods. The sensitivity, false-positive fraction (FPF) and accuracy of the proposed method is found to be higher than the other methods which imply that the proposed method is more efficient and accurate.
    2014 IEEE International Advance Computing Conference (IACC); 02/2014
  • [Show abstract] [Hide abstract]
    ABSTRACT: A novel algorithm is presented to automatically identify the retinal vessels depicted in color fundus photographs.
    Medical Physics 09/2014; 41(9):092702. · 3.01 Impact Factor