Prediction of functional outcome after mechanical thrombectomy using radiomics and deep learning features derived from intra-thrombus and peri-thrombus regions
Purpose Although mechanical thrombectomy (MT) achieves high recanalization rates in acute ischemic stroke (AIS), functional outcomes remain highly inconsistent. We aimed to evaluate the effectiveness of radiomics and deep learning features (DLFs) extracted from both intra-thrombus and peri-thrombus regions on baseline...