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dl-cs: Accelerate MRI Reconstruction with Data‑Driven Compressed Sensing

Leverage dl-cs to translate cutting‑edge compressed‑sensing research into practical MRI reconstruction pipelines. Ideal for founders building AI‑enabled medical imaging solutions.

From the repo · “Compressed Sensing: From Research to Clinical Practice with Data-Driven Learning”

45 stars11 forksPythonGuide quality 8/10 · reviewed Oct 11Updated 3/20/2019100% free · open source
What it does

dl-cs is a Python tool that uses data-driven learning to improve MRI image quality through compressed sensing, allowing for faster and more accurate medical imaging

When to use it
  • •When you need to accelerate MRI scan times without compromising image quality
  • •When you want to reduce the amount of data required for MRI image reconstruction
  • •When you are working with limited or noisy MRI data and need to improve image quality
Ready-to-paste prompt
python run.py --train --data_path /path/to/data --acceleration_factor 4 --num_epochs 100
Heads up: The dl-cs tool requires a specific version of Python (3.8 or later) and the PyTorch library, as well as a significant amount of computational resources and memory to train the model
Saves to your device
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Claude Code
mkdir -p ~/.claude/skills/dl-cs && curl -fsSL https://workflowstacks.com/api/skills/dl-cs/claude-skill -o ~/.claude/skills/dl-cs/SKILL.md
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12
top-level files
2
folders
2.1M
source size
MIT
license
Key files
README.md
requirements.txt
File tree
images/
utils/
.gitignore
data_prep.py
data.py
LICENSE
model.py
mridata_org.txt
README.md
recon_compare.py
recon_run.py
recon_train.py
requirements.txt
train_all.sh
Quick Actions
Details
Creator
MRSRL
Language
Python
Category
ai-agent
Published
1/18/2019

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