The Development of the RSU U<sup>2</sup> Net+ Architecture for Brain Tumor Segmentation in 3D Images Article Swipe
YOU?
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· 2024
· Open Access
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· DOI: https://doi.org/10.24203/0ey9jz30
Segmenting brain tumors in medical images plays a crucial role in diagnosis and monitoring of medical conditions. However, the segmentation process is still performed manually, consuming time and exhibiting variability among assessors. This research aims to develop the RSU U2-Net+ architecture for brain tumor multilabel segmentation in 3D images. The RSU U2-Net+ architecture consists of 9 interconnected blocks, employing broader connectivity in each block. The architecture is reinforced with the use of Residual U-blocks (RSU) to enhance image understanding across various scales without significantly increasing computational load. Testing on data reveals that the RSU U2-Net+ architecture performs well, as indicated by a dice coefficient score of 0.779, IoU of 0.6439, recall of 0.7541, and specificity of 0.9911. Evaluation is also conducted for each tumor label. Recall and specificity for edema are 0.8690 and 0.9851, for enhancing tumor are 0.7991 and 0.9956, and for non-enhancing tumor are 0.5942 and 0.9927. This research makes a significant contribution to the development of advanced medical image analysis technology. The achieved results have tangible benefits for medical practitioners and patients, with the potential to enhance the speed and consistency of brain tumor segmentation in 3D medical images.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.24203/0ey9jz30
- https://ijcit.com/index.php/ijcit/article/download/403/103
- OA Status
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- References
- 13
- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4409956999Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.24203/0ey9jz30Digital Object Identifier
- Title
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The Development of the RSU U<sup>2</sup> Net+ Architecture for Brain Tumor Segmentation in 3D ImagesWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-06-30Full publication date if available
- Authors
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ELvaret Elvaret, Habibullah AkbarList of authors in order
- Landing page
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https://doi.org/10.24203/0ey9jz30Publisher landing page
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https://ijcit.com/index.php/ijcit/article/download/403/103Direct link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://ijcit.com/index.php/ijcit/article/download/403/103Direct OA link when available
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Architecture, Segmentation, Net (polyhedron), Computer science, Artificial intelligence, Mathematics, Geography, Archaeology, GeometryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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13Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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