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Hello, I'm using segcapsbasic and segnetR3 as the model for stroke segmentation of brain image using [ISLES 2017](http://www.isles-challenge.org/ISLES2017/) dataset. I use 25 patient 3D MRI data that …
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### Context
So far, when training models using several channels/contrasts (e.g. T1w, T2w), images need to be co-registered for each subject. This takes time and is prone to error. What if we would …
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Hello, having issues with memory usage.
Is it normal that even with 48Go VRAM i cannot run the reverse process for generation with a small batch of 2 ?
What are you specs ?
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I'm trying to use your code but I don't know how you create the NumPy file with filename of the slices in the class Brats. Any advice/instruction?
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Source: https://github.com/mlperf/inference/tree/r0.7#mlperf-inference-v07-submission-9182020
I tried to compile the following onnx models. All of them are failed.
| model | onn…
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There is a number of issues with current TRT acceleration path in MONAI:
- For some networks it's only practical/possible to trace/export certain sub-module, like image_encoder. Current solution r…
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hello.
I used the Brats mri segmentation, but was unable to download the dataset.
![image](https://github.com/user-attachments/assets/bfd44f64-3cb6-4afa-8df9-863fe560649f)
skip https://www.med.upen…
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The training stage is well, consuming about 10 GB CPU memory. However, memory increases quickly once online eval (called by EvalCallback) starts, and amounts to 60G after several eval iterations. Did …
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