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License: MIT License
Medical image augmentation tool that can be integrated with Pytorch & MONAI.
License: MIT License
Riscrivere test unitari
Extend the dataloader for cases where there are two images associated with the mask, for example CT,MRI and mask
Controllare che tutte le immagini del blocco vengano salvate e non sovrascritte
Al momento le trasformazioni vengono fatte solo su data[0] che è l'immagine, trascurando le segmentazioni.
Aggiungere nuovo attributo J per far decidere all'utente la grandezza del subset
Prima di rilasciare il batch, se richiesto dall'utente, salvare per ogni immagine del batch la fetta centrale nel path specificato dall'utente
Sviluppare 3 benchmark con 0, 5, 10 trasformazioni in augmentation sia per gpu che cpu
Assicurarsi di restituire tutto in float32
Hi,
I am encountering an issue with the ImageToImageDataset
class in the MONAI library, specifically regarding the shape of loaded images.
__len__
Method:__len__
method to:Second, Issue with Image Loading:
The main concern arises with the loading of images in the getitem method. The class uses the LoadImage transformer to load the images, and I added print statements to check the shape of the loaded images. However, instead of getting a 3D tensor shape, which I expected for medical images (like MRI or CT scans), the loaded images are in 2D shape.
Here is the output I observed:
Loaded MR Image Shape: torch.Size([244, 204])
Loaded CT Image Shape: torch.Size([244, 204])
Loaded Mask Image Shape: torch.Size([244, 204])
I am trying to load and process 3D medical images, but the dataset seems to be returning 2D slices or incorrectly shaped tensors.
Could you please advise on how to resolve this issue? Is there a specific parameter or method I should use to ensure the images are correctly loaded as 3D tensors?
Thank you for your assistance.
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