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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 performance 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 to whole spine images with minimal drop in accuracy, achieving a detection rate of 99.4%.
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The Ladder Algorithm: Finding Repetitive Structures in Medical Images by Induction
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 performance 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 to whole spine images with minimal drop in accuracy, achieving a detection rate of 99.4%.