Morphological operations with iterative rotation of structuring elements for segmentation of retinal vessel structures

被引:24
|
作者
Pal, Soumyadeep [1 ]
Chatterjee, Saptarshi [1 ]
Dey, Debangshu [1 ]
Munshi, Sugata [1 ]
机构
[1] Jadavpur Univ, Elect Engn Dept, Kolkata, India
关键词
Computer aided diagnosis; Diabetic retinopathy; Hit-or-miss transform; Segmentation; Wavelet transform; BLOOD-VESSELS; MATHEMATICAL MORPHOLOGY; IMAGES; EXTRACTION; LEVEL;
D O I
10.1007/s11045-018-0561-9
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The development of computer aided diagnosis system has a great impact on early and accurate disease diagnosis. The segmentation of retinal blood vessels aids in identifying the alteration in vessel structure and hence helps to diagnose many diseases such as diabetic retinopathy, glaucoma, hypertension along with some cardiovascular diseases. In this research work, a method is presented for the segmentation of retinal vessel structure from retinal fundus images.2D wavelet transform assisted morphological gradient operation based Contrast Limited Adaptive Histogram Equalization' technique has been introduced for the preprocessing of the low contrast fundus images. Morphological gray level hit-or-miss transform with multi-structuring element with varying orientation has been proposed for the separation of blood vessel from its background. Finally a hysteresis thresholding, guided by some morphological operations has been employed to obtain the binary image excluding other unwanted areas. The proposed methodology has been tested on DRIVE database and a maximum accuracy and an average accuracy of 95.65 and 94.31% respectively have been achieved.
引用
收藏
页码:373 / 389
页数:17
相关论文
共 44 条
  • [1] Morphological operations with iterative rotation of structuring elements for segmentation of retinal vessel structures
    Soumyadeep Pal
    Saptarshi Chatterjee
    Debangshu Dey
    Sugata Munshi
    Multidimensional Systems and Signal Processing, 2019, 30 : 373 - 389
  • [2] An Efficient Retinal Blood Vessel Segmentation using Morphological Operations
    Ozkaya, U.
    Ozturk, S.
    Akdemir, B.
    Seyfi, L.
    2018 2ND INTERNATIONAL SYMPOSIUM ON MULTIDISCIPLINARY STUDIES AND INNOVATIVE TECHNOLOGIES (ISMSIT), 2018, : 32 - 38
  • [3] Retinal Blood Vessel Segmentation using Morphological Structuring Element and Entropy Thresholding
    Sumathy, B.
    Poornachandra, S.
    2012 THIRD INTERNATIONAL CONFERENCE ON COMPUTING COMMUNICATION & NETWORKING TECHNOLOGIES (ICCCNT), 2012,
  • [4] BLOOD VESSEL SEGMENTATION IN RETINAL IMAGES BY MORPHOLOGICAL OPERATIONS AND BY A NOVEL PIXEL TRACKING ALGORITHM
    Hameed, Isam S.
    Ocbagabir, Helen
    Barkana, Buket D.
    Yildirim, Burak
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2015, 11 (01): : 189 - 201
  • [5] Fast computation of morphological operations with arbitrary structuring elements
    VanDroogenbroeck, M
    Talbot, H
    PATTERN RECOGNITION LETTERS, 1996, 17 (14) : 1451 - 1460
  • [6] Unsupervised Morphological Approach for Retinal Vessel Segmentation
    Krishna, B. V. Santhosh
    Gnanasekaran, T.
    Aswini, S.
    PROGRESS IN COMPUTING, ANALYTICS AND NETWORKING, ICCAN 2017, 2018, 710 : 743 - 752
  • [7] Retinal Vessel Segmentation via Adversarial Learning and Iterative Refinement
    Gu W.
    Xu Y.
    Journal of Shanghai Jiaotong University (Science), 2024, 29 (1) : 73 - 80
  • [8] Retinal Vessel Segmentation via Adversarial Learning and Iterative Refinement
    Gu, Wen
    Xu, Yi
    Journal of Shanghai Jiaotong University (Science), 2024, 29 (01) : 73 - 80
  • [9] Retinal Vessel Segmentation Via Iterative Geodesic Time Transform
    Dai, Baisheng
    Bu, Wei
    Wu, Xiangqian
    Teng, Yan
    2012 21ST INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR 2012), 2012, : 561 - 564
  • [10] Retinal Vessel Segmentation Based on Frangi Filter and Morphological Reconstruction
    Nugroho, Hanung Adi
    Aras, Rezty Amalia
    Lestari, Tri
    Ardiyanto, Igi
    2017 INTERNATIONAL CONFERENCE ON CONTROL, ELECTRONICS, RENEWABLE ENERGY AND COMMUNICATIONS (ICCREC), 2017, : 181 - 184