In: Neurological Research and Practice, 1 (2019), Nr. 23. S. 1-13. ISSN 2524-3489
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Abstract
Tools for medical image analysis have been developed to reduce the time needed to detect abnormalities and to provide more accurate results. Particularly, tools based on artificial intelligence and machine learning techniques have led to significant improvements in medical imaging interpretation in the last decade. Automatic evaluation of acute ischemic stroke in medical imaging is one of the fields that witnessed a major development. Commercially available products so far aim to identify (and quantify) the ischemic core, the ischemic penumbra, the site of arterial occlusion and the collateral flow but they are not (yet) intended as standalone diagnostic tools. Their use can be complementary; they are intended to support physicians’ interpretation of medical images and hence standardise selection of patients for acute treatment. This review provides an introduction into the field of computer-aided diagnosis and focuses on the automatic analysis of non-contrast-enhanced computed tomography, computed tomography angiography and perfusion imaging. Future studies are necessary that allow the evaluation and comparison of different imaging strategies and post-processing algorithms during the diagnosis process in patients with suspected acute ischemic stroke; which may further facilitate the standardisation of treatment and stroke management.
Dokumententyp: | Artikel |
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Titel der Zeitschrift: | Neurological Research and Practice |
Band: | 1 |
Nummer: | 23 |
Verlag: | BioMed Central |
Ort der Veröffentlichung: | London |
Erstellungsdatum: | 23 Aug. 2019 14:43 |
Erscheinungsjahr: | 2019 |
ISSN: | 2524-3489 |
Seitenbereich: | S. 1-13 |
Institute/Einrichtungen: | Medizinische Fakultät Heidelberg und Uniklinikum > Neurologische Universitätsklinik |
DDC-Sachgruppe: | 610 Medizin |
Freie Schlagwörter: | Acute ischemic stroke, Imaging, Computer aided diagnosis, Artificial intelligence |