Retinal blood vessel segmentation using morphological structuring element and entropy thresholding

Sumathy, B.; Poornachandra, S.

doi:10.1109/icccnt.2012.6396076

Cited by 6 publications

(2 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Filtering and morphological operations play a significant role in preprocessing of retinal image to enhance the blood vessel regions. 2 The artifacts issue in unsupervised method based on Gabor filter is addressed by the optimized Gabor filter 3 to reduce the false positives. Optimum value of frequency and orientation is obtained for Gabor filter to segment blood vessels of different widths.…”

Section: Related Workmentioning

confidence: 99%

Improvement of thin retinal vessel extraction using mean matting method

Sathananthavathi¹,

Indumathi²,

Mahiya³

et al. 2021

Int J Imaging Syst Tech

View full text Add to dashboard Cite

In this paper, a new mean matting method based on mean correlation is proposed to extract thin blood vessels precisely. The proposed algorithm is the combination of both supervised and unsupervised method. The supervised methodology performs well in extracting thick blood vessels; however, thin vessels are not precisely extracted. Even the capability of unsupervised method is better in extracting thin vessels; it has some artifacts in the output. The proposed method combines the advantages of both supervised and unsupervised method to extract vessel regions more precisely irrespective of their thickness.Using supervised methodology, thick blood vessels are extracted by training the classifier with the significant features describing the vessel regions. Trimap is generated on the unsupervised output and mean correlation is computed for all unknown pixels in the trimap to classify those pixels into vessels or background. The proposed matting method has less computational complexity compared to other existing matting methods. The performance of the proposed method is evaluated in detail on DRIVE and STARE datasets.

show abstract

Section: Related Workmentioning

confidence: 99%

Improvement of thin retinal vessel extraction using mean matting method

Sathananthavathi¹,

Indumathi²,

Mahiya³

et al. 2021

Int J Imaging Syst Tech

View full text Add to dashboard Cite

show abstract

“…An automatic segmentation of the vasculature might save workload of the ophthalmologists plus could contribute to portray the discovered injuries [9 -10]. Moreover, blood vessels are used as benchmarks for registration of retinal images of the same patient that had been collected from different sources [11][12][13][14][15]. In addition, the segmentation of the vascular tree appears to be the best suitable demonstration of the image registration applications caused by this explanation which are mapping the entire retina [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%