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i4h Catheter Navigation Setup

OfficialFree

Streamline your catheter navigation workflow setup.

by nvidia2.8k stars on nvidia/skills
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Updated Aug 7, 2026
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Free · Opens the source repo

What i4h Catheter Navigation Setup does

The i4h Catheter Navigation Setup skill is designed to assist users in verifying the necessary host and GPU requirements for the catheter navigation workflow. This skill is particularly useful for developers and engineers who are setting up, installing, or troubleshooting the catheter navigation system. It ensures that the environment is correctly configured to avoid common errors related to missing imports or GPU compatibility, which can hinder the workflow's functionality.

By running a series of bash commands, this skill checks for essential components such as Python, Git, and NVIDIA drivers, and it confirms that the required workflow is registered with the CLI. Users can also execute CPU smoke tests to validate that the system is operational before diving deeper into the workflow. The skill provides a structured approach to setting up the environment, making it easier to identify and resolve issues before they become significant roadblocks.

The skill is particularly beneficial for those working in healthcare technology, especially in fields that require precise catheter navigation systems. It streamlines the initial setup process, allowing users to focus on developing and refining their applications rather than troubleshooting setup issues. Additionally, the skill's preflight checks and logging capabilities help users maintain a clear record of their setup process, which can be invaluable for debugging and future installations.

While the skill is robust in verifying and documenting host requirements, it currently lacks a dedicated setup script, meaning users may need to rely on Docker for environments with incomplete host dependencies. However, for users with a compatible setup, this skill is an efficient tool for ensuring that their catheter navigation workflow is ready for use.

When to use it

Use this skill when setting up or troubleshooting the catheter navigation workflow to ensure all prerequisites are met.

When not to use it

This skill is not suitable for users without a compatible Linux environment or those who do not require the catheter navigation workflow.

What you can build with it

Initial Setup of Catheter Navigation

Use this skill to verify all system requirements and prepare your environment for the catheter navigation workflow.

Troubleshooting Import Errors

If you encounter import errors related to fluorosim, this skill helps identify and resolve PYTHONPATH issues.

CI/CD Integration

Integrate this skill into your CI/CD pipeline to ensure that the catheter navigation workflow is correctly set up before deployment.

How to install i4h Catheter Navigation Setup

View source

1. Install with the skills CLI

npx skills add nvidia/skills/i4h-catheter-navigation-setup --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by nvidia

i4h Catheter Navigation - Setup

Purpose

Verify host and GPU requirements, confirm the ./i4h CLI sees the workflow, and run CPU smoke tests. Use when asked to set up catheter navigation or when hitting missing imports, GPU, or slangpy errors.

Base Code

These steps drive the i4h-workflows base code (the workflows/catheter_navigation/ tree). To reuse an existing checkout, set I4H_WORKFLOWS to its path (no clone happens). Otherwise this resolves the current repo, or clones to ~/i4h-workflows - pick that default without prompting. Run every command below from the resolved root:

ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"
if [ ! -d "$ROOT/workflows/catheter_navigation" ]; then
  ROOT="${I4H_WORKFLOWS:-$HOME/i4h-workflows}"
  [ -d "$ROOT/workflows/catheter_navigation" ] || git clone https://github.com/isaac-for-healthcare/i4h-workflows "$ROOT"
fi
export I4H_WORKFLOWS="$ROOT"; cd "$ROOT"

Basics

  • Catheter navigation registers via workflows/catheter_navigation/metadata.json and runs through ./i4h run catheter_navigation <mode>.
  • Runtime is package-first: render_drr uses installed fluorosim (python -m fluorosim.examples.render_drr), while interactive_viewport is launched from the local workflow script path in metadata.json.
  • Docker image: workflows/catheter_navigation/docker/Dockerfile (drop --local on ./i4h run to use it).
  • GPU modes need slangpy, Warp, and CUDA; CPU smoke tests do not.

Preflight

command -v python3
command -v git
nvidia-smi
df -h .

Required: Linux x86_64 (Ubuntu 22.04/24.04 tested), NVIDIA GPU (CC >= 7.0), driver compatible with CUDA 12.8, >= 16 GB RAM, >= 20 GB disk.

Run the steps below in order. Each step is a separate bash call; variables persist in the local agent's tmux session.

Step 1 - resolve repo and export paths

REPO_ROOT="${I4H_WORKFLOWS:-$(git rev-parse --show-toplevel 2>/dev/null)}"; [ -d "$REPO_ROOT/workflows/catheter_navigation" ] || REPO_ROOT="$HOME/i4h-workflows"
WF_ROOT="${REPO_ROOT}/workflows/catheter_navigation"
SIM_ROOT="${WF_ROOT}/scripts/simulation"
export PYTHONPATH="${SIM_ROOT}:${PYTHONPATH:-}"
RUN_DIR="${WF_ROOT}/runs/setup_$(date +%Y%m%d_%H%M%S)"
mkdir -p "${RUN_DIR}/logs"
ln -sfn "${RUN_DIR}" "${WF_ROOT}/runs/.latest"

Step 2 - verify CLI registration

"${REPO_ROOT}/i4h" modes catheter_navigation 2>&1 | tee "${RUN_DIR}/logs/modes.log"

Step 3 - CPU smoke tests (no GPU)

python3 -m unittest workflows/catheter_navigation/tests/test_fluorosim_smoke.py \
  2>&1 | tee "${RUN_DIR}/logs/smoke.log"

Expected: Ran 7 tests ... OK. Parser error lines in stderr from negative test cases are expected.

Step 4 - optional GPU sanity (synthetic DRR)

Skip if no GPU or slangpy not installed.

"${REPO_ROOT}/i4h" run catheter_navigation render_drr --local \
  --run-args="--output ${RUN_DIR}/drr.png" \
  2>&1 | tee "${RUN_DIR}/logs/render_drr.log"

Verify

test -f "${RUN_DIR}/logs/smoke.log"
grep -q "OK" "${RUN_DIR}/logs/smoke.log"
python3 -c "import fluorosim; print('fluorosim', fluorosim.__file__)"

Prerequisites

  • Repo checkout with workflows/catheter_navigation/ present.
  • Python 3 with numpy; full GPU stack (slangpy, torch CUDA, warp) for render/viewport modes.

Limitations

  • No dedicated setup.sh yet - this skill verifies and documents host requirements; use Docker when host deps are incomplete.
  • Step 4 requires a GPU; Step 3 alone is sufficient for CI-style verification.

Troubleshooting

  • Error: fluorosim import fails - Cause: PYTHONPATH not set. Fix: re-run Step 1; confirm SIM_ROOT exists.
  • Error: ./i4h not found - Cause: not at repo root. Fix: cd "$REPO_ROOT" where ./i4h lives.
  • Error: render_drr fails with slang/GPU - Cause: missing CUDA or slangpy. Fix: use Docker (./i4h run catheter_navigation render_drr without --local) or install deps per README.

Final Response

Report setup status, smoke-test result, optional DRR output path, and recommend the next skill ([[i4h-catheter-navigation-digital-twin]] for patient data, [[i4h-catheter-navigation-viewport]] for interactive demo).

Frequently asked questions about i4h Catheter Navigation Setup

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