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References from Diagnosis of osteoporotic vertebral compression fractures and fracture level detection using multitask learning with U-Net in lumbar spine lateral radiographs. Local targets link to admitted publications; unresolved targets remain external evidence.
Assessing vertebral fractures. National Osteoporosis Foundation Working Group on Vertebral Fractures
1995 · External reference
Vertebral compression fractures: a review of current management and multimodal therapy
2013 · External reference
Conservative care for patients with osteoporotic vertebral compression fractures
10.1016/j.pmr.2007.05.008 · 2007 · External reference
Osteoporotic vertebral compression fractures and vertebral augmentation
10.1055/s-0028-1103000 · 2008 · External reference
Automatic detection and segmentation of lumbar vertebrae from X-ray images for compression fracture evaluation
10.1016/j.cmpb.2020.105833 · 2021 · External reference
Performance of a deep-learning neural network model in assessing skeletal maturity on pediatric hand radiographs
10.1148/radiol.2017170236 · 2018 · External reference
Enhancement of evaluating flatfoot on a weight-bearing lateral radiograph of the foot with U-Net based semantic segmentation on the long axis of tarsal and metatarsal bones in an active learning manner
10.1016/j.compbiomed.2022.105400 · 2022 · External reference
A deep learning algorithm for automated measurement of vertebral body compression from X-ray images
10.1038/s41598-021-93017-x · 2021 · External reference
Automated vertebral segmentation and measurement of vertebral compression ratio based on deep learning in X-ray images
10.1007/s10278-021-00471-0 · 2021 · External reference
Can a deep-learning model for the automated detection of vertebral fractures approach the performance level of human subspecialists
10.1097/corr.0000000000001685 · 2021 · External reference
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10.1016/j.neuroimage.2006.01.015
10.1016/j.neuroimage.2006.01.015 · External reference
10.2307/1932409
10.2307/1932409 · External reference
Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations
10.1007/978-3-319-67558-9_28 · 2017 · External reference
10.1023/b:vlsi.0000028532.53893.82
10.1023/b:vlsi.0000028532.53893.82 · External reference
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Introduction to the DICOM standard
10.1007/s003300101100 · 2002 · External reference
U2-Net: Going deeper with nested U-structure for salient object detection
10.1016/j.patcog.2020.107404 · 2020 · External reference
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2016 · External reference
Y-Net: Joint Segmentation and Classification for Diagnosis of Breast Biopsy Images
10.1007/978-3-030-00934-2_99 · 2018 · External reference
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2019 · External reference
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10.1162/neco_a_00990
10.1162/neco_a_00990 · External reference
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2012 · External reference
10.1038/s41592-019-0686-2
10.1038/s41592-019-0686-2 · External reference
Comparing the areas under 2 or more correlated receiver operating characteristic curves - a nonparametric approach
10.2307/2531595 · 1988 · External reference
10.5244/c.30.87
10.5244/c.30.87 · External reference
10.1016/j.media.2022.102489
10.1016/j.media.2022.102489 · External reference
Multi-task learning for dense prediction tasks: a survey
2022 · External reference
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2017 · External reference
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2014 · External reference
Unresolved reference
2016 · External reference
Morphologic study of lumbar vertebral osteophytes
10.1097/00007611-199802000-00012 · 1998 · External reference
