Chun-Jung Juan1, Yi-Jui Liu2, Shao-Chieh Lin3, and Yi-Hung Jeng4
1Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, 2Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, 3Ph.D. program in Electrical and Communication Engineering, Feng Chia University, Taichung, Taiwan, 4Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan, Hsinchu, Taiwan
1Department of Medical Imaging, China Medical University Hsinchu Hospital, Hsinchu, Taiwan, 2Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, 3Ph.D. program in Electrical and Communication Engineering, Feng Chia University, Taichung, Taiwan, 4Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu, Taiwan, Hsinchu, Taiwan
Verifies
the value of ADC threshold on the performance of the deep learning models in segmenting
acute ischemic infarction with increasing the Dice similarity coefficient (DSC).
(a)Stroke
images and labeling region; (b) GT, Prediction and Overlap in each
mask.
The DSCs between the GT and the prediction in different ADC thresholds
and different stroke sizes.