Image segmentation - general superpixel segmentation & center detection & region growing
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Updated
Jan 4, 2022 - Python
Image segmentation - general superpixel segmentation & center detection & region growing
π€ PyTorch toolkit for biomedical imaging β€οΈ
Repository for the paper "Synthetic optical coherence tomography angiographs for detailed retinal vessel segmentation without human annotations" (2024).
A Rat fMRI multi-center study
Paper List for Medical Anomaly Detection
π§π»ββοΈ ε»ε¦δΊΊε·₯ζΊθ½ε ₯ι¨ζε Medical-AI-Guide
EndoL2H: Deep Super-Resolution for Capsule Endoscopy
BS-LDM: Effective Bone Suppression in High-Resolution Chest X-Ray Images with Conditional Latent Diffusion Models
Histology Image Viewer and Converter
Generate Synthetic Shapes in 3D for Biomedical Image Augmentation and Synthesis.
This repository contains a Python application using OpenCV for detecting mitosis in images. Aimed at researchers and biologists, it provides tools to automate the counting and identification of mitotic figures in microscopic images, supporting studies in cellular biology and medical diagnostics.
Deep Learning-Based CLI for Tissue Masking 3D OCT Images
This work was done just to present the idea that could be beneficial if used with computer science for medical imaging
π― Top 204 solution for Elucidata AI Challenge 2025 β Predicting spatial cell-type composition from histology images using CNNs with EfficientNet & ResNet backbones, multi-scale patching, and coordinate-aware ensemble modeling.
This repository offers a deep learning solution for predicting spatial cell-type compositions from histology images, achieving a top 204 rank in the Global AI Kaggle Hackathon 2025. Explore the code and methodologies used to extract and analyze image data effectively. π±π»π
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