rezazad68/BCDU-Net
BCDU-Net : Medical Image Segmentation
This tool helps medical professionals, researchers, and clinicians accurately outline specific features within medical images. By inputting various types of medical scans (like skin lesion images, retinal scans, or lung CT data), it automatically identifies and highlights areas of interest, such as lesions, blood vessels, or lung tissues. The output is a precisely segmented image, making it easier to analyze and measure these critical anatomical or pathological structures.
784 stars. No commits in the last 6 months.
Use this if you need to precisely segment and analyze specific structures within medical images, such as identifying skin lesions, mapping retinal blood vessels, or isolating lung regions for diagnostic or research purposes.
Not ideal if your task involves general image classification, object detection across a broad range of everyday images, or processing non-medical image data.
Stars
784
Forks
276
Language
Python
License
—
Category
Last pushed
Jan 30, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/rezazad68/BCDU-Net"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
dipy/dipy
DIPY is the paragon 3D/4D+ medical imaging library in Python. Contains generic methods for...
Project-MONAI/MONAI
AI Toolkit for Healthcare Imaging
Project-MONAI/MONAILabel
MONAI Label is an intelligent open source image labeling and learning tool.
neuronets/nobrainer
A framework for developing neural network models for 3D image processing.
Project-MONAI/monai-deploy-app-sdk
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify...