FengheTan9/CMU-Net
[ISBI 2023] Official Pytorch implementation of "CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network"
This project helps medical professionals or researchers analyze ultrasound images more effectively. It takes raw ultrasound images, like those for breast or thyroid scans, and accurately outlines specific regions of interest within them, such as tumors or anomalies. The output is a segmented image, making it easier to identify and measure features. This tool is for medical imaging specialists or researchers working with ultrasound data.
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Use this if you need to precisely segment and highlight structures within medical ultrasound images for diagnostic or research purposes.
Not ideal if you are working with other types of medical imaging data, such as X-rays or MRI, as this is specifically designed for ultrasound.
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89
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6
Language
Python
License
MIT
Category
Last pushed
Dec 13, 2024
Commits (30d)
0
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