Replace RadIO with TorchIO for patch-based inference

[fepegar]

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[fepegar]

I "fixed" some mypy errors by explicitly ignoring them. I'm not sure this is the best solution.

[ant0nsc]

Looking GREAT! Lots of ugly code replaced by uncle tio ;-)

[javier-alvarez]

#665 Lets address this one before merging and run manual regression test on prostate and H&N

[fepegar]

Comparison RadIO vs TorchIO

I suspect the tiny differences might be due to implementation details. For example, if an image needs to be 3 voxels larger along a specific dimensions, we could add 2 voxels at the beginning and 1 at the end, or vice versa.

Quantitative

RadIO

Structure	25%	50%	75%	count	max	mean	min	std
external	0.992	0.996	0.997	109.0	0.998	0.994706	0.969	0.003560
femur_l	0.978	0.980	0.982	109.0	0.988	0.979541	0.962	0.003938
femur_r	0.978	0.980	0.981	109.0	0.987	0.979486	0.967	0.003760
bladder	0.960	0.971	0.979	109.0	0.990	0.965761	0.840	0.023162
rectum	0.856	0.899	0.921	109.0	0.961	0.886587	0.636	0.048407
prostate	0.823	0.867	0.903	109.0	0.954	0.853202	0.629	0.068248
seminalvesicles	0.758	0.799	0.841	109.0	0.909	0.785954	0.189	0.089569

TorchIO

Structure	25%	50%	75%	count	max	mean	min	std
external	0.992	0.996	0.997	109.0	0.998	0.994642	0.969	0.003591
femur_l	0.978	0.980	0.982	109.0	0.988	0.979596	0.962	0.003923
femur_r	0.978	0.980	0.982	109.0	0.988	0.979596	0.966	0.003847
bladder	0.960	0.972	0.978	109.0	0.990	0.965532	0.824	0.024132
rectum	0.857	0.899	0.916	109.0	0.963	0.884596	0.630	0.050930
prostate	0.822	0.864	0.905	109.0	0.953	0.853560	0.612	0.067435
seminalvesicles	0.758	0.800	0.840	109.0	0.913	0.786560	0.155	0.089954

Qualitative

[fepegar]

I can run H&N too, but I suspect results will be very similar again.