International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 11, Issue 11 (November 2024), Pages: 92-98

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 Original Research Paper

Statistical edge detection with an application to intraventricular hemorrhage

 Author(s): 

 Sameer A. H. Al-Subh *, Kamal A. Al-Banawi

 Affiliation(s):

 Department of Mathematics and Statistics, Mutah University, Al-Karak, Jordan

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0009-0006-2973-6929

 Digital Object Identifier (DOI)

 https://doi.org/10.21833/ijaas.2024.11.010

 Abstract

The goal of edge detection is to determine whether a point in an image is an edge point. This is done by applying first and second derivative operators to detect the greatest change in image intensity. In this paper, we propose a new method where the threshold, represented by the average a̅, is calculated within a neighborhood of I(x1,x2). This approach not only reduces processing time but also ensures that no pixels are missed. Pixels below the threshold are replaced after enhancement. We extend this work by applying the Canny edge detector (CED) to detect boundaries in MRI images of abnormal brains affected by intraventricular hemorrhage (IVH). Two thresholds are used: the hysteresis threshold in the CED and our proposed statistical threshold, which works alongside traditional edge operators like Sobel, Prewitt, and Laplacian.

 © 2024 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Edge detection, Derivative operators, Threshold, Canny edge detector, Intraventricular hemorrhage

 Article history

 Received 21 May 2024, Received in revised form 14 September 2024, Accepted 28 October 2024

 Acknowledgment

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Al-Subh SAH and Al-Banawi KA (2024). Statistical edge detection with an application to intraventricular hemorrhage. International Journal of Advanced and Applied Sciences, 11(11): 92-98

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 Figures

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 Tables

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