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. 2021 May 17;17(1):32–40. doi: 10.4244/EIJ-D-20-00570

Figure 3.

Figure 3

Result imaging of the segment recognition model and the lesion morphology detection model. A) Segment recognition. First row: input angiograms. Second row: resulting images generated by DeepDiscern segment recognition DNN. Third row: ground-truth labelled images. Different identified areas represent the different coronary segments. B) Lesion morphology detection. First row: input angiograms and ground-truth bounding boxes. There is a TO morphology in the first and second angiograms, and a thrombus morphology in the third angiogram in this row. Second row: bounding boxes and lesion types generated by the DeepDiscern lesion morphology detection model.