This BIDS App provides the utility of creating a nnU-Net anatomical MRI segmentation and mask with a infant brain trained model. It can easily be included in other processing pipelines and for circumventing JLF within Nibabies.
these updates perform chirality correction in an iterative fashion. the first correction uses a crude LR mask created from splitting the image into left and right from the center of the image in the coronal plain. the second correction uses the more refined LR mask generated with registration to templates (the current method)
This won't impact the midline chirality issues in any way, but it does catch any superficial brain regions outside of the midline. It's a simple update that shouldn't negatively impact anything and also requires an inconsequential amount of additional computing resources/time
I've tested the container and it works as expected
these updates perform chirality correction in an iterative fashion. the first correction uses a crude LR mask created from splitting the image into left and right from the center of the image in the coronal plain. the second correction uses the more refined LR mask generated with registration to templates (the current method)
This won't impact the midline chirality issues in any way, but it does catch any superficial brain regions outside of the midline. It's a simple update that shouldn't negatively impact anything and also requires an inconsequential amount of additional computing resources/time
I've tested the container and it works as expected