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I4h Catheter Navigation Render Drr

nvidia/i4h-catheter-navigation-render-drr

Render a single DRR fluoroscopy frame from a CT cache or synthetic phantom. Use when asked to render DRR, generate a fluoro image, or smoke-test the Slang renderer.

5k tokens
context cost
the whole folder, loaded on every use
5
files
instructions only
0
copies elsewhere
how many repositories repackaged it
2778
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/NVIDIA/skills --skill i4h-catheter-navigation-render-drr

What comes with it

17 711 bytes besides the instruction
BENCHMARK.md
evals/evals.json
skill-card.md
skill.oms.sig

The instruction itself

12 sections, as written by the author

i4h Catheter Navigation - Render DRR

Purpose

Render a single digitally reconstructed radiograph (DRR) frame. Works with a preprocessed CT cache from [[i4h-catheter-navigation-digital-twin]], a direct NIfTI/DICOM path, or the built-in synthetic phantom (no data required).

Base Code

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

  • Default mode in metadata.json; self-contained with synthetic phantom when no --cache is given.
  • GPU + slangpy required for actual rendering.
  • Entry mode: ./i4h run catheter_navigation render_drr (preferred).

Run

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 run dir

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="${REPO_ROOT}/workflows/catheter_navigation"
RUN_DIR="${WF_ROOT}/runs/render_drr_$(date +%Y%m%d_%H%M%S)"
mkdir -p "${RUN_DIR}/logs"
ln -sfn "${RUN_DIR}" "${WF_ROOT}/runs/.latest"
OUTPUT="${RUN_DIR}/drr.png"
CACHE="${CACHE:-}"

Step 2 - render (pick one variant)

Synthetic phantom (fastest smoke, no data):

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

From preprocessed cache:

if [ ! -d "${CACHE}" ] || [ ! -f "${CACHE}/mu_volume.npy" ]; then
  echo "render-drr: set CACHE to a preprocess_ct output dir (missing mu_volume.npy)." >&2
  exit 1
fi
"${REPO_ROOT}/i4h" run catheter_navigation render_drr --local \
  --run-args="--cache ${CACHE} --output ${OUTPUT}" \
  2>&1 | tee "${RUN_DIR}/logs/render_drr.log"

Verify

test -f "${OUTPUT}"
file "${OUTPUT}"

Prerequisites

  • [[i4h-catheter-navigation-setup]] completed.
  • NVIDIA GPU with slangpy for rendering (CPU smoke tests do not cover GPU render).

Limitations

  • Single-frame render only; batch multi-env RL rendering uses the fluorosim Python API directly.
  • Catheter compositing in DRR requires attaching a CatheterProvider in custom scripts (not the default example).

Troubleshooting

  • Error: slangpy / CUDA failures - Fix: run without --local to use Docker, or verify GPU driver >= 570 and CUDA 12.8.
  • Error: cache not found - Fix: run [[i4h-catheter-navigation-digital-twin]] first or use synthetic mode (no --cache).

Final Response

Report output PNG path, whether synthetic or patient cache was used, and log path. Recommend [[i4h-catheter-navigation-viewport]] for interactive navigation.

How to use it

Copy the folder

Take nvidia/i4h-catheter-navigation-render-drr from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.