OSUPCVLab/MobileUNETR
Official Implementation of MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image Segmentation (ECCV2024) (Oral)
This project offers a lightweight, efficient tool for precisely outlining structures within medical images and complex scenes like urban landscapes. You provide input images (e.g., medical scans, aerial photos) and it outputs segmented images, highlighting specific regions of interest. It's designed for researchers and practitioners who need accurate image segmentation without heavy computational demands.
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Use this if you need to accurately identify and delineate objects or regions in images, such as tumors in medical scans or specific features in satellite imagery, using an efficient deep learning model.
Not ideal if your primary goal is general image classification or object detection without the need for pixel-level segmentation masks.
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Language
Python
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Last pushed
Nov 13, 2024
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