A vertebral compression fracture score based on deep generative contextual modelingDownload PDF

Published: 09 May 2022, Last Modified: 12 May 2023MIDL 2022 Short PapersReaders: Everyone
Keywords: spine, compression fractures, generative model, inpainting, anomaly detection
TL;DR: This paper proposes a novel automatic method to express the degree of abnormality of the three-dimensional shape of the vertebral body.
Abstract: Grading of vertebral compression fractures most commonly relies on a semi-quantitative grading scale that defines fractures as height loss of the vertebral body. This paper presents an alternative approach that instead considers the three-dimensional shape of the vertebral body and expresses the abnormality of the shape on a scale from 0 to 100. The abnormality is expressed relative to the expected healthy shape, which is predicted by a deep generative model that is provided with contextual information, namely shape and orientation of surrounding vertebrae.
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Paper Type: novel methodological ideas without extensive validation
Primary Subject Area: Detection and Diagnosis
Secondary Subject Area: Segmentation
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