Guidance Image-Based Enhanced Matched Filter with Modified Thresholding for Blood Vessel Extraction

被引:57
作者
Dash, Sonali [1 ]
Verma, Sahil [2 ,3 ]
Kavita [2 ,4 ]
Bevinakoppa, Savitri [5 ]
Wozniak, Marcin [6 ]
Shafi, Jana [7 ]
Ijaz, Muhammad Fazal [8 ]
机构
[1] Raghu Inst Technol A, Dept Elect & Commun Engn, Visakhapatnam 531162, Andhra Pradesh, India
[2] Chandigarh Univ, Dept Comp Sci & Engn, Mohali 140413, India
[3] Chandigarh Univ, Bio & Hlth Informat Res Lab, Mohali 140413, India
[4] Chandigarh Univ, Machine Learning & Data Sci Res Lab, Mohali 140413, India
[5] Melbourne Inst Technol, Sch IT & Engn, Melbourne, Vic 3000, Australia
[6] Silesian Tech Univ, Fac Appl Math, PL-44100 Gliwice, Poland
[7] Prince Sattam Bin Abdul Aziz Univ, Coll Arts & Sci, Dept Comp Sci, Wadi Ad Dwasir 11991, Saudi Arabia
[8] Sejong Univ, Dept Intelligent Mechatron Engn, Seoul 05006, South Korea
来源
SYMMETRY-BASEL | 2022年 / 14卷 / 02期
关键词
fast guided filter; matched filter; modified thresholding; vessel segmentation; DIABETIC-RETINOPATHY; RETINAL IMAGES; SEGMENTATION; TORTUOSITY; DIAMETER;
D O I
10.3390/sym14020194
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Fundus images have been established as an important factor in analyzing and recognizing many cardiovascular and ophthalmological diseases. Consequently, precise segmentation of blood using computer vision is vital in the recognition of ailments. Although clinicians have adopted computer-aided diagnostics (CAD) in day-to-day diagnosis, it is still quite difficult to conduct fully automated analysis based exclusively on information contained in fundus images. In fundus image applications, one of the methods for conducting an automatic analysis is to ascertain symmetry/asymmetry details from corresponding areas of the retina and investigate their association with positive clinical findings. In the field of diabetic retinopathy, matched filters have been shown to be an established technique for vessel extraction. However, there is reduced efficiency in matched filters due to noisy images. In this work, a joint model of a fast guided filter and a matched filter is suggested for enhancing abnormal retinal images containing low vessel contrasts. Extracting all information from an image correctly is one of the important factors in the process of image enhancement. A guided filter has an excellent property in edge-preserving, but still tends to suffer from halo artifacts near the edges. Fast guided filtering is a technique that subsamples the filtering input image and the guidance image and calculates the local linear coefficients for upsampling. In short, the proposed technique applies a fast guided filter and a matched filter for attaining improved performance measures for vessel extraction. The recommended technique was assessed on DRIVE and CHASE_DB1 datasets and achieved accuracies of 0.9613 and 0.960, respectively, both of which are higher than the accuracy of the original matched filter and other suggested vessel segmentation algorithms.
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页数:19
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