Computer-Aided Design on Image Detection: A Chronology Review
In order to conduct research and diagnose diseases, image processing is essential. Medical professionals frequently segment images for pre-and post-surgery decisions, which are necessary for treatment planning. In the medical research field, segmentation is the core subject of several studies. Compu...
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2-s2.0-85168109537 Mahmud M.; Mustafa W.A.; Wahab A.F. Computer-Aided Design on Image Detection: A Chronology Review 2023 Journal of Advanced Research in Applied Sciences and Engineering Technology 31 2 10.37934/araset.31.2.5161 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168109537&doi=10.37934%2faraset.31.2.5161&partnerID=40&md5=fd4807c54e0c404a690bf33c271cd25b In order to conduct research and diagnose diseases, image processing is essential. Medical professionals frequently segment images for pre-and post-surgery decisions, which are necessary for treatment planning. In the medical research field, segmentation is the core subject of several studies. Computer-aided detection (CAD) is utilised to achieve the highest level of classification accuracy and may be used to identify tissues growing abnormally. For the purpose of finding abnormalities, magnetic resonance imaging (MRI) is an effective approach, but it takes time and requires a fair amount of human resources. This approach, however, was problematic for slicing data related to the interior surfaces of cavity structures, for instance, the human skull. As a result, a ray casting algorithm was used to create a software programme. The most significant problem with segmentation techniques for x-ray images is seed point selection. An object's surface structure is described by a three-dimensional (3D) surface structure graph (SSG) that was created during segmentation. Ultrasound image detection is critical today. The model can be further modified using this CAD software so that it can be reproduced on a rapid prototyping device in the STL file format. The suggested deep learning method is exceptionally effective in accurately detecting faults in each layer, according to experimental data. © 2023, Penerbit Akademia Baru. All rights reserved. Semarak Ilmu Publishing 24621943 English Article All Open Access; Hybrid Gold Open Access |
author |
Mahmud M.; Mustafa W.A.; Wahab A.F. |
spellingShingle |
Mahmud M.; Mustafa W.A.; Wahab A.F. Computer-Aided Design on Image Detection: A Chronology Review |
author_facet |
Mahmud M.; Mustafa W.A.; Wahab A.F. |
author_sort |
Mahmud M.; Mustafa W.A.; Wahab A.F. |
title |
Computer-Aided Design on Image Detection: A Chronology Review |
title_short |
Computer-Aided Design on Image Detection: A Chronology Review |
title_full |
Computer-Aided Design on Image Detection: A Chronology Review |
title_fullStr |
Computer-Aided Design on Image Detection: A Chronology Review |
title_full_unstemmed |
Computer-Aided Design on Image Detection: A Chronology Review |
title_sort |
Computer-Aided Design on Image Detection: A Chronology Review |
publishDate |
2023 |
container_title |
Journal of Advanced Research in Applied Sciences and Engineering Technology |
container_volume |
31 |
container_issue |
2 |
doi_str_mv |
10.37934/araset.31.2.5161 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168109537&doi=10.37934%2faraset.31.2.5161&partnerID=40&md5=fd4807c54e0c404a690bf33c271cd25b |
description |
In order to conduct research and diagnose diseases, image processing is essential. Medical professionals frequently segment images for pre-and post-surgery decisions, which are necessary for treatment planning. In the medical research field, segmentation is the core subject of several studies. Computer-aided detection (CAD) is utilised to achieve the highest level of classification accuracy and may be used to identify tissues growing abnormally. For the purpose of finding abnormalities, magnetic resonance imaging (MRI) is an effective approach, but it takes time and requires a fair amount of human resources. This approach, however, was problematic for slicing data related to the interior surfaces of cavity structures, for instance, the human skull. As a result, a ray casting algorithm was used to create a software programme. The most significant problem with segmentation techniques for x-ray images is seed point selection. An object's surface structure is described by a three-dimensional (3D) surface structure graph (SSG) that was created during segmentation. Ultrasound image detection is critical today. The model can be further modified using this CAD software so that it can be reproduced on a rapid prototyping device in the STL file format. The suggested deep learning method is exceptionally effective in accurately detecting faults in each layer, according to experimental data. © 2023, Penerbit Akademia Baru. All rights reserved. |
publisher |
Semarak Ilmu Publishing |
issn |
24621943 |
language |
English |
format |
Article |
accesstype |
All Open Access; Hybrid Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1809677681336254464 |