The Ladder Algorithm: Finding Repetitive Structures in Medical Images by Induction
This provides a high-accuracy solution for medical image analysis, particularly in radiology, though it appears incremental as it builds on existing detection methods with a novel algorithm.
The paper tackles the problem of detecting repetitive structures in medical images, specifically vertebrae in spine MRI scans, by introducing the Ladder Algorithm, which achieves 99.8% precision and recall for lumbar vertebrae detection and generalizes to whole spine images with 99.4% accuracy.
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.