105 Machine learning and carotid artery CT radiomics identify significant differences between culprit and non-culprit lesions in patients with stroke and transient ischaemic attack
IntroductionCarotid atherosclerosis is the main cause of ischaemic stroke. Texture analysis is a radiomic approach used to quantify image heterogeneity which can predict tumour aggression in oncology. We investigated whether this method could be applied to carotid artery disease to differentiate sym...
Saved in:
Published in | Heart (British Cardiac Society) Vol. 106; no. Suppl 2; pp. A82 - A84 |
---|---|
Main Authors | , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
BMJ Publishing Group LTD
01.07.2020
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Be the first to leave a comment!