{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "l5769389-voxenra--pet-ct-fusion-review",
 "repo": "l5769389/voxenra",
 "repo_url": "https://github.com/l5769389/voxenra",
 "repo_slug": "l5769389-voxenra",
 "title": "Review PET/CT fusion and align it manually",
 "page_title": "How to review PET/CT fusion and align it manually with Voxenra",
 "summary": "Fuse PET and CT in slices and 3D, adjust the blend, and register the two volumes by hand.",
 "who": "A nuclear medicine or imaging researcher who needs to check where PET activity sits on the CT anatomy.",
 "problem": "PET and CT are acquired separately, so the two datasets can be misaligned and need a fusion view with manual correction.",
 "outcome": "A fused view of CT, PET and MIP with a rigidly registered PET volume, adjustable colour table and blend ratio, and a 3D fusion view.",
 "steps": [
  "Clone the repo from https://github.com/l5769389/voxenra and enter the folder.",
  "Run `uv run voxenra` and import the paired CT and PET series.",
  "Open the PET/CT fusion view and choose the three-plane slice mode.",
  "Adjust the colour table and the fusion ratio, then apply a manual rigid registration until the anatomy lines up.",
  "Switch to the fused 3D view and control the CT and PET display separately."
 ],
 "agent_prompt": "Work in the repo l5769389/voxenra. Run `uv run voxenra`, import the PET and CT series at <path to PET/CT study>, and open the fusion view. Report whether the PET overlay aligns with CT anatomy at the slice you chose, and state the blend ratio used.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "The README says PET quantification depends on the image metadata, and dynamic or gated PET is not supported.",
 "category": "Security and science",
 "tags": [
  "Security and science"
 ],
 "lang": "python",
 "requirements": [
  "Python with uv installed, so the README command `uv run voxenra` works",
  "Local DICOM, NRRD or PACS-accessible CT, MR or PET/CT data you are allowed to use",
  "For AI auto-segmentation: a separately installed TotalSegmentator environment and CT fast model, detected under Settings → AI",
  "A desktop OS: macOS Apple Silicon or Windows x64 release builds are listed, or a source checkout run with uv"
 ],
 "risk": "sensitive",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/l5769389-voxenra/pet-ct-fusion-review/",
 "md": "https://dedupedai.com/use-cases/l5769389-voxenra/pet-ct-fusion-review/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/l5769389-voxenra--pet-ct-fusion-review.json",
 "api_version": "v1"
}