Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images

[1]  Harri Valpola,et al.  Weight-averaged consistency targets improve semi-supervised deep learning results , 2017, ArXiv.

[2]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[3]  Perry J Pickhardt,et al.  Predicting Future Hip Fractures on Routine Abdominal CT Using Opportunistic Osteoporosis Screening Measures: A Matched Case-Control Study. , 2017, AJR. American journal of roentgenology.

[4]  Eitan Bachmat,et al.  Automated opportunistic osteoporotic fracture risk assessment using computed tomography scans to aid in FRAX underutilization , 2020, Nature Medicine.

[5]  Sergey Ioffe,et al.  Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.

[6]  Timothy J Ziemlewicz,et al.  Opportunistic Osteoporosis Screening at Routine Abdominal and Thoracic CT: Normative L1 Trabecular Attenuation Values in More than 20 000 Adults. , 2019, Radiology.

[7]  M. Reiser,et al.  Papillary vs clear cell renal cell carcinoma. Differentiation and grading by iodine concentration using DECT—correlation with microvascular density , 2019, European Radiology.

[8]  Estanislao Arana,et al.  Opportunistic screening for osteoporosis by routine CT in Southern Europe , 2017, Osteoporosis International.

[9]  Weijian Li,et al.  Structured Landmark Detection via Topology-Adapting Deep Graph Learning , 2020, ECCV.

[10]  Bin Zhang,et al.  Deep learning of lumbar spine X-ray for osteopenia and osteoporosis screening: A multicenter retrospective cohort study. , 2020, Bone.

[11]  Timo Aila,et al.  Temporal Ensembling for Semi-Supervised Learning , 2016, ICLR.

[12]  Yaling Pan,et al.  Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening , 2020, European Radiology.

[13]  T. Ozaki,et al.  Deep Learning for Osteoporosis Classification Using Hip Radiographs and Patient Clinical Covariates , 2020, Biomolecules.

[14]  Enhua Wu,et al.  Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[16]  K Mei,et al.  Feasibility of opportunistic osteoporosis screening in routine contrast-enhanced multi detector computed tomography (MDCT) using texture analysis , 2018, Osteoporosis International.

[17]  Eun Kyung Choe,et al.  The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population , 2019, Skeletal Radiology.