Pipeline meant to segment and classify organoids, or any other blob-like structures (star-convex polygons). Microscopy images can be easily annotated in QuPath and automatically processed afterwards to count the class distribution within each image using this pipeline (TIF files will be converted to grayscale)

collection of diffusion model papers categorized by their subareas

Multi-platform, free open source software for visualization and image computing.

State-of-the-art, deep learning-based segmentation of the brainstem on MRI

Open source Python library for building bioimage analysis pipelines

[MICCAI 2024] Codebase for "Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse Process"

A procedural Blender pipeline for photorealistic training image generation

[CVPR'24] Code for Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models

Julia library for visualization and annotation medical images, specialized particularly for rapid development segmentation of 3 dimensional images like CT or PET/CT scans. Has full support of nuclear medicine Data.

RiverSnap - estimation of river hydraulic parameters using machine learning/AI models

A. Moghimi, M. Welzel, T. Celik, and T. Schlurmann, "A Comparative Performance Analysis of Popular Deep Learning Models and Segment Anything Model (SAM) for River Water Segmentation in Close-Range Remote Sensing Imagery,"

Project Page for "LISA: Reasoning Segmentation via Large Language Model"

Developing a Handwritten Digits Classifier using PyTorch on the MNIST dataset .Implemented pytorch, CNN, image segmentation and classification

Create image annotations. Classify and tag images using polygons, bounding boxes, or circles.

Anime background remover

Sudachi in Rust 🦀 and new generation of SudachiPy

[ICLR 2024] Supervised Pre-Trained 3D Models for Medical Image Analysis

Scan Tailor Experimental is an interactive post-processing tool for scanned pages.

A framework for easy application of established machine learning techniques on large, multi-dimensional images.

Lung segmentation in chest X-ray images using U-Net