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. Author manuscript; available in PMC: 2023 Apr 20.
Published in final edited form as: Comput Med Imaging Graph. 2021 Oct 30;95:102000. doi: 10.1016/j.compmedimag.2021.102000

Figure 1:

Figure 1:

Illustration of our hemisphere-based segmentation pipeline. (a) A sample MRI image. (b) The localization network predicts 12 bounding-box parameters for a given image. (c) The bounding-box parameters include the coordinates of the center voxel and dimensions of each bounding box. (d) Images of both hemispheres are obtained by cropping the original image and image of the right hemisphere is horizontally flipped. (e) The segmentation network segments each hemisphere into 54 structures. (f) The segmentation generated is affixed with left or right label accordingly. (g) The segmentation generated for the right hemisphere is horizontally flipped and fused with the segmentation generated for the left hemisphere.