brianlee324 / torch-lddmm Goto Github PK

Suppose the template has a corresponding label map (atlas), and our goal is to obtain the label map for the target image. How to apply the warpping map (or resultant displacement field) to the template label map after lddmm registration?

hello,
I am using your code to realize the lddmm, but I am curious about why you X0-np.mean(X0) for the grids instead use the original grids X0 = range(imgsize)?

self.X0 = torch.tensor(X0-np.mean(X0)).type(self.params['dtype']).to(device=self.params['cuda'])
self.X1 = torch.tensor(X1-np.mean(X1)).type(self.params['dtype']).to(device=self.params['cuda'])

Hello!
I am interested in the efficiency of gpu acceleration and I want to compare gpu version with cpu version.
How to use the lddmm registration without gpu？
Look forward to your reply.