mlsanityData to 14 Oct 2026

CTSpinoPelvic1K: spine, pelvis, ribs and femora in one coordinate frame, annotated for lumbosacral transitional anatomy

arXiv 2609.22760 ↗First posted 19 Sep 2026cs.AI cs.LGcited by 0

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Abstract (arXiv)

Purpose: A vertebra at the lumbosacral junction is named by counting caudally from C2 on whole-spine imaging, but a lumbar case is planned on lumbar-only imaging (T12 to S1), without C2. Abdominopelvic CT holds that span plus the lowest ribs and pelvis. Where a lumbosacral transitional vertebra (LSTV) alters the count, the local anatomy is ambiguous: four rib-free vertebrae may be an L1 with a lumbar rib or an L5 assimilated to the sacrum, and six may be a sixth lumbar vertebra, a T12 with aplastic ribs, or a lumbarized S1. CTSpinoPelvic1K asks whether local morphology resolves it without the count. CTSpine1K's vertebrae and CTPelvic1K's pelvis covered these patients but were never joined; this release joins them on one series and adds the bones neither had. It provides 802 CT records with per-level ribs and femora, levels anchored on the lowest rib-bearing vertebra and S1, and classes for L6, T13, a separate S1 and lumbar ribs, so anomalies are recorded as such. Acquisition and Validation Methods: Records pair CTSpine1K and CTPelvic1K labels on each patient's bone-richest series under a VerSe-native scheme. Validation covered geometric invariants (802/802 pass), rib-vertebra incidence across 5,749 ribs (0.035% offset), and spinopelvic measures matching published values. Data Format and Usage Notes: NIfTI image/label pairs with patient-grouped LSTV-stratified five-fold splits and a loader; archived at https://doi.org/10.5281/zenodo.22139642. Potential Applications: Classifying a vertebra from local features; updating cadaveric morphometry; spinopelvic assessment; opportunistic screening; and, absent a public preoperative lumbar cohort, surgical planning research (377 records prone). Limitations: thoracic ground truth is field-of-view limited; postural angles supine; no held-out test set; ribs are triaged-review pseudolabels; Castellvi grades two-reader consensus on 33 records.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 49 references that are in the map. First posted on arXiv 19 Sep 2026.

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References · 9

  1. 2022TotalSegmentator: robust segmentation of 104 anatomical structures in CT imagescited by 613
  2. 2020VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Imagescited by 111
  3. 2021CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomographycited by 46
  4. 2020Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Modelscited by 45
  5. 2021A Computed Tomography Vertebral Segmentation Dataset with Anatomical Variations and Multi-Vendor Scanner Datacited by 28
  6. 2022RibSeg v2: A Large-scale Benchmark for Rib Labeling and Anatomical Centerline Extractioncited by 11
  7. 2024SPINEPS -- Automatic Whole Spine Segmentation of T2-weighted MR images using a Two-Phase Approach to Multi-class Semantic and Instance Segmentationcited by 9
  8. 2025Automated Thoracolumbar Stump Rib Detection and Analysis in a Large CT Cohortcited by 1
  9. 2026VERIDAH: Solving Enumeration Anomaly Aware Vertebra Labeling across Imaging Sequencescited by 1

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