Towards fracture risk assessment by deep-learning-based classification of prevalent vertebral fractures

Artificialintelligence detects fractures on CTimages for osteoporosis diagnostics

Osteoporosis is a complex multifactorial skeletal disease and has become a major socioeconomic issue, causing tremendous hospitalization and rehabilitation costs. In addition to age, premature menopause or the use of oral corticosteroids, vertebral fractures are regarded as main risk factors for developing osteoporosis and associated fractures.

The sum of the classified grades was then evaluated according to the German radiology guidelines. A hyperparameter search on validation data showed the most promising results for an output configuration based on three sequentially applied binary classification outputs trained using binary cross-entropy: Grade 0–1 vs 2–3, and 0 vs 1–3, and 0–2 vs 3.

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