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Hello, I have gone through your paper 'End-to-End Cascade Network for 3D Brain Tumor Segmentation in MICCAI 2018 BraTS Challenge'. As you claimed focal loss implementation in the architecture, can you…
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Hi, I have read your paper "TransBTS: Multimodal Brain Tumor Segmentation Using Transformer", which implements transformer module in 3D medical image segmentation task. This task is absorbing, and I h…
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Hi,
I'm trying to finetune nnUNet for a brain tumor segmentation task using pretrained weights from Task082_BraTS2020. My data consists of brain MRI images with 4 input modalities, and the labels m…
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Hi there,
Thanks for providing such an interesting tool for the research community.
I am testing the pipeline on scATAC-seq tumor samples only. How to work around "Step2. Unbiased segmentation ba…
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## Issue description
This issue has for goal to document inference on images with dimensions different from the ones used during training.
## 2D UNet
The 2D model trained for spinal cord segmenta…
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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
4 months ago
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Dear Zhou,
Thank you for your contribution to this paper. As the title indicates I am having an issue with running the test on your model. Up until the following output the program seems to be work…
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UNETR的原文是这样描述的:“For the brain tumor segmentation task, the entire training set of 484 multi-modal multi-site MRI data (FLAIR, T1w, T1gd, T2w) with ground truth labels of gliomas segmentation necrotic/…
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As far as I know, using Dice, PPV and Sensitivity to evaluate the segmentation image must have the ground truth of the testing dataset. I cannot get the 'more' that the type of it is .nii of the testi…
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Hi all,
First of all thank you so much and congrats for your great job.
I have a 3D dataset with very small size of tumor in each image.
I do not have any ROI mask, I only have the images and the g…