DOI: 10.6084/m9.figshare.31429481.v1
title: Dataset

description: # Hepatic Thermal Ablation Planning Dataset<br>Dataset of 50 clinical hepatic cases (94 tumor targets) for percutaneous thermal ablation planning, sourced from the Colorectal-Liver-Metastases (CRLM) database of pre-segmented images. Each case includes CT volumes, anatomical meshes, safety map visualizations, and paired treatment plans (automatic and expert).<br>## Tier Structure<br>Cases are categorized by planning difficulty following the COLLISION classification of ablability:<br>| Tier | Cases | Description || ------ | ----- | ------------------------------------------------------ || Tier 1 | 25 | Single tumor, simple access, lowest risk || Tier 2 | 15 | Intermediate: multiple lesions or bilobar distribution || Tier 3 | 10 | Multi-lesion and bilobar, highest planning complexity |<br>## Directory Layout<br>```dataset/├── metrics.csv├── tier_1/│ └── case-XXXX/├── tier_2/│ └── case-XXXX/└── tier_3/ └── case-XXXX/```<br>Each case directory contains:<br>```case-XXXX/├── volumes/ CT scan and segmentation (NRRD)├── meshes/ Anatomical structure meshes (VTK)├── plans/ Treatment plans and needle markers (VTK + JSON)└── images/ Safety map and overview visualizations (PNG)```<br>## File Descriptions<br>### volumes/<br>| File | Description || ----------------------- | ------------------------------- || `ct_scan.nrrd` | CT volume || `segmentation.seg.nrrd` | Multi-label segmentation volume |<br>### meshes/<br>Surface meshes in VTK format, named `{case_id}_{structure}.vtk`. Standard structures include: liver, skin, vessels, bones, aorta, heart, lungs, kidneys, spleen, gallbladder, stomach, colon, small bowel, duodenum, esophagus, pancreas, adrenal gland, spinal cord, muscles. Each case also contains one or more `tumor_N.vtk` meshes.<br>### plans/<br>Treatment plans contain ablation zone ellipsoid meshes and needle trajectory markers.<br>**Ablation ellipsoids** (VTK): `{method}_{target}_{needle_config}_{burn}_ellipsoid.vtk`- `method`: `auto` (optimizer) or `expert` (manual)- `target`: `T1`, `T2` (tumor target index)- `needle_config`: `N1`, `N2`, ... (needle index)- `burn`: `B0`, `B1` (burn index along the needle axis, for pullback ablations)<br>**Needle markers** (JSON, 3D Slicer markups format):- `T{n}-{i}.mrk.json` — expert needle trajectory- `T{n}_{i}_AutoPlanner.mrk.json` — automatic planner needle trajectory<br>### images/<br>| File | Description || ------------------------------ | ------------------------------------------ || `overview.png` | 3D anatomical overview of the case || `safety_map_skin.png` | Safety map projected on the skin surface || `safety_map_equirect_T{n}.png` | Equirectangular safety map for target T{n} || `closeup_T{n}.png` | Close-up view of target T{n} |<br>Tier 1 cases (single target) contain T1 images only. Tier 2 and 3 cases contain both T1 and T2 images.<br>## Root CSV Files<br>### metrics.csv<br>Per-target paired evaluation metrics for both automatic and expert plans (188 rows = 94 targets x 2 methods). Includes coverage, efficiency, Dice coefficient, Hausdorff distance (HD95), distance to closest critical structure (DTC), insertion depth, and optimization timing.