Hello, May I ask if there is any paper or material that can support the "Medical image data volume may be too large to fit into GPU memory. A widely-used approach is to randomly draw small size data samples during training and run a ‘sliding window’ routine for inference." mentioned in "4. Randomly crop out batch images based on positive/negative ratio"
For example, if I use the RandCropByPosNegLabel transform, How can I make sure that every place containing the target area is collected? If not, does that mean I can't make the best use of my data?
Hello, May I ask if there is any paper or material that can support the "Medical image data volume may be too large to fit into GPU memory. A widely-used approach is to randomly draw small size data samples during training and run a ‘sliding window’ routine for inference." mentioned in "4. Randomly crop out batch images based on positive/negative ratio"
For example, if I use the RandCropByPosNegLabel transform, How can I make sure that every place containing the target area is collected? If not, does that mean I can't make the best use of my data?
