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Opening this issue to discuss the results and the performances of the models trained to segment MS lesions in the spinal cord.
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In this issue, I explore the work done to segment MS lesion in the spinal cord using the STU-Net.
I used the code from this repo: https://github.com/uni-medical/STU-Net
The dataset used is the …
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Some degenerative cervical myelopathy (DCM) patients have T2w/T2*w hyperintense lesions. Similarly to SCI and MS lesions, it would be great to automate their segmentation.
So far, we have available…
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We are working on universal/contrast-agnostic models for lesion or spinal cord segmentation. But it seems like going for a single model/segmentation head for segmenting the lesions of all sites is an …
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![ambiguity_L_FI_score_detection](https://github.com/user-attachments/assets/007b8eae-2db5-4495-846b-e3f10de89326)
Dear @vpchung, @rachitsaluja,
First of all, thank you for sharing lesion-wise e…
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In this issue, I detail the work done:
- to get MS lesion segmentation using the current best model.
- to manually correct those lesion segmentations
I created the file `monai/run_inference.py` …
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In the paper, it's written that the images are randomly divided into three subsets for training, validating and testing, respectively.
While in this repo, authors perform 5-folds cross-validation.
S…
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I recently read your article "A Benchmark for Studying Diabetic Retinopathy: Segmentation, Grading, and Transferability" published in TMI. Regarding task 1, segmentation of multiple fundus lesions, I …
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With SCIseg, we noticed that the model was also decently segmenting DCM lesions, which strongly suggested that it simply learned to be sensitive to T2w hyperintensities in the images. We could use thi…
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In this issue, I use the segmentation of the lesions on the spinal cord after cropping the images (issue #37 ).
The analysis of the segmentations accounts for the following:
- [x] Identifying a …