Brain MRI segmentation using adversarial training approach
55 T1 weighted brain MR images (35 adults and 20 elders) with respective label maps.
1. The authors suggest an adversarial loss in addition to the traditional loss.
2. The authors compare 2 Generator (Segmentor) models - Fully convolutional and dilated networks.
Using conv layers, allows for larger receptive field with fewer trainable weights (compared to the FCN option).
However, the authors claim the adversarial loss contributes more when applying the FCN model