Fully automatic estimation of pelvic sagittal inclination from anterior-posterior radiography image using deep learning framework

Computer Methods and Programs in Biomedicine(2020)

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摘要
•Malposition of the acetabular component cause dislocation and prosthetic impingement after total hip arthroplasty, which significantly affect postoperative quality of life and implant longevity.•We introduce a new method for accurate estimation of functional PSI without requiring CT image in order to lower radiation exposure of the patient which opens up the possibility of increasing its application in a larger number of hospitals where CT is not acquired in a routine protocol.•We investigate the Mask R-CNN performance on radiography image segmentation and compare it with U-Net that widely is used in biomedical tasks.•The benefit of using transfer learning, multi-task learning and data augmentation is investigated.
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关键词
Total hip arthroplasty,Pelvic tilt,Deep learning,Convolutional neural network,Segmentation,Mask R-CNN
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