Abstract
Computerized medical image examination (CMIE) plays a significant role in modern hospitals to achieve the necessary tasks, like segmentation and classification. By segmenting an image, we can extract a particular section for examination. A two-dimensional computed tomography (CT) slice was used for liver-vessel examination (LiVE). A simple automatic technique for supporting LiVE is being developed in this research. A CT slice is collected, a 3D to 2D conversion is done, (ii) Kapur's tri-level thresholding and Hummingbird-Optimizer is used to enhance the CT slice, (iii) the watershed algorithm (WA) is used to extract the vessel, and (iv) the WA is compared and verified against the segmentation methods chosen. WA provides better segmentation results than other methods because it is an automatic approach. Using the chosen image database, the proposed technique achieves an overall segmentation accuracy of >97%. Other segmentation problems can be used in the future to verify the merit of this scheme.
| Original language | English |
|---|---|
| Pages (from-to) | 1824-1831 |
| Number of pages | 8 |
| Journal | Procedia Computer Science |
| Volume | 235 |
| DOIs | |
| State | Published - 2024 |
| Event | 2nd International Conference on Machine Learning and Data Engineering, ICMLDE 2023 - Dehradun, India Duration: 23 Nov 2023 → 24 Nov 2023 |
Keywords
- Kapur's thresholding
- hummingbird-optimizer
- liver CT
- liver-vessel
- watershed-algorithm
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