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I’ve been exploring your project, and I find your work on training models for MRI and CT images incredibly useful. I am currently working on a project involving ultrasound images, and I was wondering if the model and methodology used in your repo could be adapted for ultrasound image data as well.
Specifically, I’m interested in the potential challenges or adjustments needed to apply your approach to ultrasound images. Do you think the model would perform similarly with ultrasound data, or are there significant differences in the preprocessing, network architecture, or training process that would require modification?
I’d appreciate any insights or recommendations you could share!
The text was updated successfully, but these errors were encountered:
I would recommend trying the zero-shot segmentation capability on your ultrasound data. If there is a big domain gap between your ultrasound data and the training data, fine-tuning can quickly boost the performance.
I’ve been exploring your project, and I find your work on training models for MRI and CT images incredibly useful. I am currently working on a project involving ultrasound images, and I was wondering if the model and methodology used in your repo could be adapted for ultrasound image data as well.
Specifically, I’m interested in the potential challenges or adjustments needed to apply your approach to ultrasound images. Do you think the model would perform similarly with ultrasound data, or are there significant differences in the preprocessing, network architecture, or training process that would require modification?
I’d appreciate any insights or recommendations you could share!
The text was updated successfully, but these errors were encountered: