Article
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Preserved in Portico This version is not peer-reviewed
Image Segmentation Using 2D Discrete Wavelet Transform for Medical Image
Version 1
: Received: 23 May 2024 / Approved: 23 May 2024 / Online: 23 May 2024 (08:07:52 CEST)
A peer-reviewed article of this Preprint also exists.
Jarrar, H. Image Segmentation Using 2D Discrete Wavelet Transform for Medical Image. IJARCCE 2024, 13, doi:10.17148/ijarcce.2024.13601. Jarrar, H. Image Segmentation Using 2D Discrete Wavelet Transform for Medical Image. IJARCCE 2024, 13, doi:10.17148/ijarcce.2024.13601.
Abstract
Medical image segmentation is a critical step in various healthcare applications, aiding in diagnosis, treatment planning, and disease monitoring. In this study, we investigate the efficacy of a segmentation approach based on the 2D wavelet transform. Leveraging a dataset comprising 10 diverse medical images, we evaluate the performance of our segmentation method using three key metrics: accuracy, precision, and recall. Our findings demonstrate that the proposed approach enhances segmentation accuracy, offering promising results compared to existing methods. By harnessing the multi-resolution feature extraction capabilities of the 2D wavelet transform, our method achieves improved delineation of medical image structures, paving the way for more accurate and efficient healthcare interventions.
Keywords
image segmentation; medical image analysis; 2D wavelet transform; healthcare applications
Subject
Computer Science and Mathematics, Computer Vision and Graphics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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