OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages
- nci-itcr
- nci-qin
- quantitative-imaging
- imaging-informatics
Repository Index
47,133 repositories indexed
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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript
- optimization
- nonlinear
- derivatives
- code-generation
A collection of GICP-based fast point cloud registration algorithms
- point-cloud
- pcl
- gicp
- icp
Development tool for CAN bus simulation
- automotive
- can
- can-bus
- genivi
Open-source cross-platform symbolic algebra library for C# and F#. Can be used for both production and research purposes.
- csharp
- algebra
- integration
- latex
Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.
- histopathology-images
- microscopy
- sliding-windows
- medical-image-analysis
Advanced date, time and interval library for Java with sun/moon-astronomy and calendars like Chinese, Coptic, Ethiopian, French Republican, Hebrew, Hijri, Historic Christian, Indian National, Japanese, Julian, Korean, Minguo, Persian, Thai, Vietnamese
- java
- time4j
- calendar
- interval
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
- artificial-intelligence
- clip
- pathology
- vision-and-language
Native R and Python sample-deletion robustness for omics: candidate certificates, minimum deletion bounds, Bioconductor model refits and donor-level pseudobulk
- bioinformatics
- exact-optimization
- metabolomics
- paired-data
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
- histology
- wsi-images
- pan-cancer-analysis
- genomics
Haplotype-aware CNV analysis from single-cell RNA-seq, ATAC-seq, and multiome
- cancer-genomics
- cnv-detection
- single-cell
- phylogeny
Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk
- cancer-imaging-research
- radiomics
- radiomics-features
- machine-learning
AI-based pathology predicts origins for cancers of unknown primary - Nature
- histology
- pathology
- wsi-images
- histopathology
A python Two Source Energy Balance model for estimation of evapotranspiration with remote sensing data
- source-energy-balance
- canopy
- soil
- radiometric-temperatures
🏃 The go-to single-cell Foundation Model
- batch-correction
- cell-biology
- celltype-annotation
- denoising
The repository host gives no description.
⚡ Open-source software for deep learning-based digital pathology
- deep-learning
- machine-learning
- digital-pathology
- computational-pathology
Learning cell communication from spatial graphs of cells
- tensorflow
- gnn
- glm
- cvae
Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux
- deep-learning
- deep-neural-networks
- gradient-descent
- automatic-differentiation
Detecting cancers on mobile phones
MCP server for spatial transcriptomics analysis through natural language interfaces.
- bioinformatics
- cell-communication
- deconvolution
- machine-learning
Predicting Cell Health with Morphological Profiles
- carpenter-lab
- morphological-profiling
- crispr
- cell-painting
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
- cancer
- foundation-model
- single-cell
3D shape analysis using deep learning
- cancer-biology
- cell-biology
- deep-learning
- geometric-deep-learning