The value of artificial intelligence in the detection of early cerebral changes in acute stroke using non-contrast CT scans | ||
| Benha Medical Journal | ||
| Article 5, Volume 42, Issue 6, June 2025, Pages 41-49 PDF (859.04 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/bmfj.2024.329095.2234 | ||
| Authors | ||
| Hesham El-Sayed El-Sheikh1; Hamada Mohammed Khater2; Jehan Ibrahim Al -Tohamy3; Khaled El Sayed Ahmed4; Heba Ahmed Hassan* 5 | ||
| 1Professor of Diagnostic Radiology Faculty of Medicine - Benha University | ||
| 2Assistant Professor of Diagnostic Radiology Faculty of Medicine - Benha University | ||
| 3Fellow of radiology, General Organization for Teaching Hospitals and Institutes | ||
| 4Assistant professor of biomedical engineering Faculty of Engineering - Benha University | ||
| 5M.Sc. in Diagnostic Radiology- Benha University Assistant lecturer of Diagnostic Radiology- Benha University | ||
| Abstract | ||
| Background: Over the last few years, there has been increasing interest in the use of deep learning algorithms to assist with abnormality detection on medical images. Aim and Objective: was to assess the value of artificial intelligence in the detection of early cerebral changes in acute stroke using non-contrast CT scans. Patient & Methods: this cross sectional study included 1095 patients distributed across both training and validation, as well as a separate test set. Using 48 hours follow up non contrast CT images as the main reference standard to diagnose the acute ischemic stroke at the initial CT images & AI. Axial scanning extending from base of the skull up to the vertex with coronal & sagittal reformate images. Results: There were no statistically significant differences found among the diagnosis results of the first and second radiologist’s diagnosis and the AI system diagnosis (p > 0.05). Conclusion: In spite CAD system has established fair accuracy, the need of more accurate algorithm is necessary to determine if it can replicate non contrast CT and radiologist observations. | ||
| Keywords | ||
| Artificial Intelligence; non contrast computed tomography scan; acute ischemic stroke | ||
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