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Osteoporosis is a common and frequent disease in the aging population.
Osteoporosis is a common and frequent disease in the aging population.
There are other indications (such as urinary or yearly medsci.
Recently, a study published in European Radiology explored the application of deep learning in patients with primary osteoporosis, and developed a fully automated CT based on deep convolutional neural network (DCNN) The image vertebral body segmentation and bone mineral density (BMD) calculation method are designed to evaluate the accuracy of the automatic method to locate the lumbar vertebral body and calculate the performance of the BMD.
This study retrospectively selected 1449 patients who underwent CT scans of the spine or abdomen for other indications from March 2018 to May 2020 for verification and analysis.
This study retrospectively selected 1449 patients who underwent CT scans of the spine or abdomen for other indications from March 2018 to May 2020 for verification and analysis.
According to different CT vendors, all test cases are divided into the following three test queues: test set 1 (n = 463), test set 2 (n = 200) and test set 3 (n = 200).
The visual comparison between the automatic segmentation results and the manual segmentation results.
The visual comparison between the automatic segmentation results and the manual segmentation results.
This study shows that the DCNN-based method can accurately segment the lumbar vertebral body and automatically calculate the bone density, making it an effective tool for clinicians to screen for opportunistic osteoporosis.
Original source: Original source:
Yijie Fang,Wei Li,Xiaojun Chen,et al.
Yijie Fang,Wei Li,Xiaojun Chen,et al.
Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks.
DOI: org/10.
1007/s00330-020-07312-8">10.
1007/s00330-020-07312-8 Yijie Fang,Wei Li,Xiaojun Chen,et al.
Osteoporosis Screening in Multi-Opportunistic Detector CT ImagesRF Royalty Free a using Deep Convolutional Neural networks.
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