Python Library for NASA Earthdata APIs
A Vision Foundation Model for Cine Cardiac Magnetic Resonance Imaging
A decompilation of Colin McRae Rally 2.0 (PC) (2000)
MICCAI 2024: Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images and has been invited for an ORAL presentation (2.7%)🔥 and nominated for the Best Paper Award.
This Github repository contains the reconstruction algorithms for "Motion-robust free-running volumetric cardiovascular MRI" (Arshad et al., 2024). Datasets for in-vivo studies can be found at https://zenodo.org/records/12515230
A Clojure(Script) & JavaScript Client for NASA's Common Metadata Repository
This repository provides guides, short how-tos, and tutorials to help users access and work with ASTER data.
Unsupervised Domain Adaptation (AX2SAX) for CMR images, Koehler et al. 2021, IEEE TMI
Elixir client for Pipedrive's REST API
Self-supervised method for cardiac phase detection in 4D CMR. Model consists of a deformable registration part, the derivation of the per-voxel deformation angle and a rule-set based on the physiological properties of a contracting ventricle. Implemented in TF2.X. Koehler et al. 2022, STACOM workshop @ MICCAI
Free, open dataset of NAS hard drives: full specs, verified CMR vs SMR, and real-world Backblaze failure rates (AFR). 100+ drives, JSON + CSV.
Mobile data collection tool to support field research using Capture Mark Recapture (CMR) methods.
MikroTik CMR for Home Assistant: fleet status, RouterOS upgrades, alerts and a live network map from your CMR controller
Flow Matching-enabled Test-Time Refinement for Unsupervised Cardiac MR Registration
A JavaScript project to automatically manage the recruitment and correspondence of a company with candidates
Desktop data management tool for the Field Day biological research project.
Official MATLAB implementation of EMORe, a framework for motion-robust 5D cardiac MRI reconstruction presented in DOI: 10.1016/j.jocmr.2024.101509. Sample dataset is available at the link below:
Radiomics Signatures of Cardiovascular Risk Factors in Cardiac MRI: Results From the UK Biobank
An end-to-end deep learning solution to perform motion correction (MC) and super-resolution (SR) concurrently in CMR SAX slices. Author: Zhennong Chen, PhD
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