Statistical Edge Detection and Circular Hough Transform for Optic Disk Localization

Ünver, Halil Murat; Kökver, Yunus; Duman, Elvan; Erdem, O. Ayhan

doi:10.3390/app9020350

Cited by 30 publications

(14 citation statements)

References 37 publications

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“…Many vessel tracking algorithms use the ONH center as the starting point, since the vessels diverge from the ONH center. The ONH localization is carried out by detecting its center or by drawing a circle around the ONH region [152][153][154][155][156]. ONH segmentation is introduced by specifying the boundary of ONH.…”

Section: Localization and Segmentation Of Optic Nerve Headmentioning

confidence: 99%

A comprehensive survey on computer-aided diagnostic systems in diabetic retinopathy screening

Tavakoli¹,

Kelley²

2021

Photo Acoustic and Optical Coherence Tomography Imaging, Volume 3

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Diabetes Mellitus (DM) can lead to significant microvasculature disruptions that eventually causes diabetic retinopathy (DR), or complications in the eye due to diabetes. If left unchecked, this disease can increase over time and eventually cause complete vision loss. The general method to detect such optical developments is through examining the vessels, optic nerve head, microaneurysms, haemorrhage, exudates, etc. from retinal images. Ultimately this is limited by the number of experienced ophthalmologists and the vastly growing number of DM cases. To enable earlier and efficient DR diagnosis, the field of ophthalmology requires robust computer aided diagnosis (CAD) systems. Our review is intended for anyone, from student to established researcher, who wants to understand what can be accomplished with CAD systems and their algorithms to modeling and where the field of retinal image processing in computer vision and pattern recognition is headed. For someone just getting started, we place a special emphasis on the logic, strengths and shortcomings of different databases and algorithms frameworks with a focus on very recent approaches.

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Section: Localization and Segmentation Of Optic Nerve Headmentioning

confidence: 99%

A comprehensive survey on computer-aided diagnostic systems in diabetic retinopathy screening

Tavakoli¹,

Kelley²

2021

Photo Acoustic and Optical Coherence Tomography Imaging, Volume 3

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show abstract

“…The Hough transform is a feature extraction technique used in image analysis, computer vision, and digital image processing [23][24][25][26][27]. The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure for the possible geometric shapes of edges.…”

Section: Extracting Lbo Features By Hough Transformmentioning

confidence: 99%

Automatic segmentation of large bowl obstruction area with hough transform from erect abdominal radiograph images

Kim

Song

Woo

2021

IJECE

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Large bowel obstruction is less frewuent but often appears acute and needs emergent treatment. Erect abdominal radiograph is usually the first imaging study performed in patients suspected of having large bowel obstruction. However, that mordality suffers from operator subjectivity thus a fully automatic computer aied tool is necessary. In this paper, we peopose an automatic large bowel feature (air-fluid region) segmentation method based on Canny edge detection and Hough transform. In experiment, the proposed method was successful in finding target region from large bowel obstruction patients’ radiographic images in all 30 cases provided. Whilie limited only applicable to the large bowel obstruction cases, the proposed method is practically feasible in application.

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“…al. [9], where their studies were directed to the Optic Disk Localization detection. The team used the Hough Transform to detect optic disk (OD) in retinal images for diagnosis diseases, such as diabetic retinopathy, papilledema, and glaucoma.…”

Section: Related Workmentioning

confidence: 99%

Circular Hough Transform to improve viable Saccharomyces cerevisiae identification

Borges¹,

Silva

Quinta³

et al. 2021

Anais Do XVII Workshop De Visão Computacional (WVC 2021)

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Yeast counting is an important step in monitoring the fermentation process in sugarcane mills to optimize ethanol production. There is a need for a faster method to count viable cells in place of the fastidious and operator-dependent traditional method. In this paper, the application of a slightly modified version of the standard Circular Hough Transforms to automate the inoculated fermentation process of Saccharomyces cerevisae is reported. The results of several experiments with different preprocessing algorithms and parameter adjustments are presented. The resulting system will be part of a microbiological control procedure that is being developed to respond to Brazilian ethanol sugarcane mill's demands.

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Statistical Edge Detection and Circular Hough Transform for Optic Disk Localization

Cited by 30 publications

References 37 publications

A comprehensive survey on computer-aided diagnostic systems in diabetic retinopathy screening

A comprehensive survey on computer-aided diagnostic systems in diabetic retinopathy screening

Automatic segmentation of large bowl obstruction area with hough transform from erect abdominal radiograph images

Circular Hough Transform to improve viable Saccharomyces cerevisiae identification

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