Thank you very much for open-sourcing RadImageNet — it has been incredibly helpful for my current research!
While using the PyTorch pretrained model (ResNet50), I noticed that the input channels are set to 3. However, medical images such as CT scans are typically single-channel. To better utilize RadImageNet, I would like to ask: during pretraining, how did you convert single-channel images into 3-channel inputs? Was it done by repeating the single channel (e.g., stacking)?
Your clarification would be extremely helpful for my work. Thank you again for your excellent contribution and support!
Thank you very much for open-sourcing RadImageNet — it has been incredibly helpful for my current research!
While using the PyTorch pretrained model (ResNet50), I noticed that the input channels are set to 3. However, medical images such as CT scans are typically single-channel. To better utilize RadImageNet, I would like to ask: during pretraining, how did you convert single-channel images into 3-channel inputs? Was it done by repeating the single channel (e.g., stacking)?
Your clarification would be extremely helpful for my work. Thank you again for your excellent contribution and support!