xmindflow/LHUNet
LHU-Net: A Lean Hybrid U-Net for Cost-efficient, High-performance Volumetric Medical Image Segmentation
This project helps medical professionals and researchers accurately identify specific structures within 3D medical images, like organs or tumors. It takes CT or MRI scans as input and outputs precise segmented regions, making it easier to analyze and diagnose. Radiologists, oncologists, and medical researchers would find this tool valuable for detailed image analysis.
Use this if you need highly accurate and computationally efficient segmentation of volumetric medical images from CT or MRI scans.
Not ideal if you are working with non-medical images or require segmentation of 2D images only.
Stars
65
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Jan 30, 2026
Commits (30d)
0
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