Medical Imaging
Showing 36 of 53 projects
A curated list of semantic segmentation papers, code, datasets, and resources across various deep learning frameworks.
A PyTorch-based open-source framework for deep learning in healthcare imaging, providing domain-specific tools and workflows.
A curated list of publicly available medical datasets for machine learning, covering imaging, EHRs, literature, and speech.
A zero-footprint, configurable, and extensible web-based medical imaging viewer for DICOM and oncology data.
A curated list of awesome open source healthcare software, libraries, tools, and resources.
A free, open-source multi-platform software for 3D visualization and medical image analysis.
A lightweight JavaScript library for displaying medical images in web browsers using HTML5 canvas.
A cross-platform .NET library for reading, writing, and communicating with DICOM medical imaging files and services.
An open-source library providing chest X-ray datasets, pre-trained models, and tools for medical imaging research and analysis.
Converts neuroimaging data from the DICOM format to the NIfTI format and generates BIDS JSON sidecars.
A high-performance Go library and CLI tool for parsing, writing, and working with DICOM medical image files.
Open-source software for 3D medical imaging reconstruction from CT and MRI DICOM files.
A vision transformer foundation model pre-trained on over 200 million pathology images for computational pathology tasks.
Interactive segmentation and tracking tools for microscopy images built on Segment Anything.
A Python interface for interactive web-based visualization of multidimensional images, point sets, and geometry in Jupyter notebooks.
A pure JavaScript medical research image viewer for DICOM and NIFTI formats with advanced visualization tools.
A pure Rust ecosystem of libraries and tools for DICOM-compliant systems, enabling reading, writing, and processing of medical imaging data.
A U-Net implementation for brain tumor segmentation using the BRATS 2017 dataset with data augmentation and dice loss.
An extensible, open-source PACS archive software that replaces traditional centralized databases with agile indexing and retrieval for medical images.
A vision-language foundation model for computational pathology, pretrained on 1.17M histopathology image-caption pairs for diverse AI tasks.
A sliding window framework for classifying high-resolution whole-slide microscopy and histopathology images using deep neural networks.
A C library for reading whole slide image files (virtual slides) with a consistent API across multiple vendor formats.
An open-source implementation of the DICOMweb standard for medical imaging data storage and retrieval.
An open-source toolkit for scalable, standardized computational pathology analysis, enabling AI and machine learning on large imaging datasets.
A vision transformer-based deep learning model for automated instance segmentation and classification of cell nuclei in histopathology images.
A Python toolbox for image segmentation featuring superpixel segmentation, object center detection, and region growing with shape priors.
A neural networks toolbox for medical image analysis, providing specialized layers, models, and utilities for TensorFlow/Keras.
A large-scale scientific visualization platform for interactive ray-tracing of neurons and other biological data.
An open-source toolkit for federated learning and AI workflow management in medical imaging analysis.
A curated list of open-source software tools for medical imaging research, including segmentation, visualization, and deep learning libraries.
A standalone DICOMweb server with RESTful implementation of QIDO-RS, WADO-RS, STOW-RS, and WADO-URI services for medical imaging.
A foundation model for cell segmentation that achieves state-of-the-art performance across diverse cellular targets and imaging modalities.
A PyTorch-based segmentation toolbox for electron microscopy connectomics, enabling neural structure analysis in 3D volumes.
A simple C# library for reading, writing, and manipulating DICOM files in medical imaging applications.
A deep learning model using generative adversarial networks for fast compressed sensing MRI reconstruction.
A web-based DICOM slide microscopy viewer and annotation tool for imaging data science and computational pathology.
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