Image analysis of radiographic cranial examinations using analog grid and AI-based grid
Cranial radiography is a critical diagnostic procedure that demands high-quality imaging to accurately visualize complex anatomical structures within the skull. Traditionally, manual grids have been employed to reduce scattered radiation and enhance image contrast, thereby improving overall image qu...
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| Main Authors: | , |
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| Format: | Article |
| Language: | en |
| Published: |
Faculty of Medicine
2026
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/132585/1/132585.pdf https://doi.org/10.24191/jchs.v11i1.10839 https://ir.uitm.edu.my/id/eprint/132585/ https://jchs-medicine.uitm.edu.my/ |
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| Summary: | Cranial radiography is a critical diagnostic procedure that demands high-quality imaging to accurately visualize complex anatomical structures within the skull. Traditionally, manual grids have been employed to reduce scattered radiation and enhance image contrast, thereby improving overall image quality. However, these physical grids often present limitations in clinical settings due to their cumbersome nature, increased radiation dose requirements, and reduced workflow efficiency. In response to these challenges, digital radiography systems have introduced software-based virtual grids, such as AI-enhanced grids, which aim to replicate the benefits of physical grids while improving dose efficiency and workflow flexibility. |
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