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Automatic Detection of the Lumbar Spine using Transfer Learning for Quantitative Fluoroscopy
  • +1
  • Rantilini Samaratunga,
  • Marcin Budka,
  • Alexander Breen,
  • Alan Breen
Rantilini Samaratunga

Corresponding Author:[email protected]

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Marcin Budka
Alexander Breen
Alan Breen


Quantitative assessment of spinal motion plays a pivotal role in diagnosing and understanding lower back pain. This paper utilises a Convolutional Neural Network for precise landmark localisation of bounding boxes encompassing the lumbar spine in sagittal plane lumbar fluoroscopy image sequences. The proposed methodology aims to automate spinal movement tracking and provide a benchmark for future research, thereby enhancing the efficiency and accuracy of low back pain diagnosis.
02 Mar 2024Submitted to TechRxiv
04 Mar 2024Published in TechRxiv