The Ladder Algorithm: Finding Repetitive Structures in Medical Images by Induction
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Abstract (arXiv)
In this paper we introduce the Ladder Algorithm; a novel recurrent algorithm to detect repetitive structures in natural images with high accuracy using little training data. We then demonstrate the algorithm on the task of extracting vertebrae from whole spine magnetic resonance scans with only lumbar MR scans for training data. It is shown to achieve high perforamance with 99.8% precision and recall, exceeding current state of the art approaches for lumbar vertebrae detection in T1 and T2 weighted scans. It also generalises without retraining to whole spine images with minimal drop in accuracy, achieving 99.4% detection rate.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jan 2020.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 2; 2025: 1.
5 papers.
- 2022Context-Aware Transformers For Spinal Cancer Detection and Radiological Gradingcited by 8
- 2022SpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scanscited by 7
- 2024X-Diffusion: Generating Detailed 3D MRI Volumes From a Single Image Using Cross-Sectional Diffusion Modelscited by 5
- 2025UKBOB: One Billion MRI Labeled Masks for Generalizable 3D Medical Image Segmentationcited by 4
- 2024SpineFM: Leveraging Foundation Models for Automatic Spine X-ray Segmentationcited by 1
- 2025UKBOB: One Billion MRI Labeled Masks for Generalizable 3D Medical Image Segmentation9 Apr 2025
- 2024SpineFM: Leveraging Foundation Models for Automatic Spine X-ray Segmentation1 Nov 2024
- 2024X-Diffusion: Generating Detailed 3D MRI Volumes From a Single Image Using Cross-Sectional Diffusion Models30 Apr 2024
- 2022Context-Aware Transformers For Spinal Cancer Detection and Radiological Grading27 Jun 2022
- 2022SpineNetV2: Automated Detection, Labelling and Radiological Grading Of Clinical MR Scans3 May 2022