I4h Catheter Navigation Render Drr Agent Skill
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.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/NVIDIA/skills --skill i4h-catheter-navigation-render-drrWhat comes with it
17 711 bytes besides the instructionThe instruction itself
12 sections, as written by the authori4h 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 "$ROOT"
Basics
- Default mode in
metadata.json; self-contained with synthetic phantom when no--cacheis given. - GPU + slangpy required for actual rendering.
- Entry mode:
./i4h run catheter_navigation render_drr(preferred).
Run
Run the steps below in order. Each step is a separate bash call; variables persist in the local agent's tmux session.
Step 1 - resolve run dir
REPO_ROOT="${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
CatheterProviderin custom scripts (not the default example).
Troubleshooting
- Error: slangpy / CUDA failures - Fix: run without
--localto 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.
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How to use it
Take nvidia/i4h-catheter-navigation-render-drr from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
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.