Medical Imaging
Showing 36 of 41 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.
Converts neuroimaging data from the DICOM format to the NIfTI format and generates BIDS JSON sidecars.
An open-source library providing chest X-ray datasets, pre-trained models, and tools for medical imaging research and analysis.
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 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.
A vision-language foundation model for computational pathology, pretrained on 1.17M histopathology image-caption pairs for diverse AI tasks.
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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