Semi-automatic detection and segmentation algorithm of saccular aneurysms in 2D cerebral DSA images
| Autor: | Qosai Kanafani, Moustafa Al-Mawaldi, Nisreen Sulayman |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
lcsh:Medical physics. Medical radiology. Nuclear medicine
medicine.medical_specialty Shape features lcsh:R895-920 0206 medical engineering Digital subtraction angiography Image processing 02 engineering and technology 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine medicine.artery Medicine Radiology Nuclear Medicine and imaging Segmentation cardiovascular diseases Image segmentation Contextual image classification medicine.diagnostic_test business.industry Image enhancement 020601 biomedical engineering Saccular aneurysm Anterior communicating artery Radiology Nuclear Medicine and imaging cardiovascular system Radiology business Algorithm Saccular aneurysms |
| Zdroj: | The Egyptian Journal of Radiology and Nuclear Medicine, Vol 47, Iss 3, Pp 859-865 (2016) |
| Popis: | Objective To detect and segment cerebral saccular aneurysms (CSAs) in 2D Digital Subtraction Angiography (DSA) images. Patients and methods Ten patients underwent Intra-arterial DSA procedures. Patients were injected with Iodine-containing radiopaque material. A scheme for semi-automatic detection and segmentation of intracranial aneurysms is proposed in this study. The algorithm consisted of three major image processing stages: image enhancement, image segmentation and image classification. Applied to the 2D Digital Subtraction Angiography (DSA) images, the algorithm was evaluated in 19 scene files to detect 10 CSAs. Results Aneurysms were identified by the proposed detection and segmentation algorithm with 89.47% sensitivity and 80.95% positive predictive value (PPV) after executing the algorithm on 19 DSA images of 10 aneurysms. Results have been verified by specialized radiologists. However, 4 false positive aneurysms were detected when aneurysms’ location is at Anterior Communicating Artery (ACA). Conclusion The suggested algorithm is a promising method for detection and segmentation of saccular aneurysms; it provides a diagnostic tool for CSAs. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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