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currently the model is trained only on CT images, but now the need of mri models are growing, how the model can be trained to do universal segmentation on any modalities ?
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HELLO,it is a great job,but i want to know how can I train the model on BTCV &&LiTS &&Spleen &&KiTS.As BTCV contains 14 classes,and when I train the model, it will report an error: assert t
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Hi Havard. I have some MRI images from liver. All of them contain tumors. I wanted to predict the survival functions from these images. for images there was one example with mnist dataset. I wanted to…
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Dear developer:
i ran inferCNV with the liver cancer single-cell-RNA dataset, and the hepatocyte from tumor sample was select as the obsevation, the hepatocyte from non-cancer liver tissue sample a…
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Hi
back with potentially stupid questions
I am helping out a friend who is a radiologist. He has MRI and CT (computer tomography) images that are in dicom format
Ideally, it'd be able to find a…
toli updated
5 months ago
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We are planning to replace our previous text-based image label description format with a new json-based format for better interoperability. NGFF's [`image-label`](https://ngff.openmicroscopy.org/lates…
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Hello, your work is fantastic, but I have a few questions. I hope you can provide me with some advice.
1. How can I transform the dataset saved in the datapreprocessed folder into the dataset insid…
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SNAF is amazing with its integration of a entire workflow of identification of neoantigen. However, I wonder if there is a way to create custom control dataset? It will be super helpful for researcher…
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What are the functions of generate_livertxt, generate_tumortxt and generate_txt in preprocessing.py respectively
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Thanks for your great work, it’s given me a lot of inspiration.
I have a question about multi-organ segmentation, which is training the model using multiple different organ (tumor) datasets.
In …