Fig. 3: Illustration of prediction results in three patients with multiple occlusions. | Nature Communications

Fig. 3: Illustration of prediction results in three patients with multiple occlusions.

From: Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke

Fig. 3

Correctly predicted bounding boxes by the artificial neural network (ANN) are shown in red, whereas false positive bounding boxes are depicted in orange, whereas for false-negative predictions only the ground truth annotations are shown (green circle). A Patient with a correctly ANN- identified occlusion of the left carotid bifurcation (chronic; first slice, coronal), the right middle cerebral artery (MCA) M2-segment (second slice, coronal) and anterior cerebral artery (ACA) A3-segment (third slice, sagittal). In addition, a false positive finding of left MCA M2-segment occlusion was identified by the ANN (second slice, coronal) possibly due to decreased opacification of the vessel due to chronic occlusion of the left internal carotid artery. B Patient with occlusion of the right common carotid artery (CCA) not detected by the ANN (first slice, coronal) however false positive prediction of a right carotid bifurcation occlusion distal from the CCA occlusion (second slice, axial). True positive detection of an additional right proximal M1-segment occlusion and false positive of a more distally located M1 occlusion (third slice, coronal). False positive detection of a left MCA M2-segment occlusion (fourth slice, axial), and false negative detection of a right ACA A2-segment occlusion (fifth slice, sagittal). C Patient with tandem occlusion of the carotid bifurcation and the proximal MCA M1-segment correctly detected by the ANN (first slice, both occlusion visible, sagittal; second slice - ICA M1-segment occlusion visible, axial). Images are depicted using radiological orientation (left image side is the patient’s right side).

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