Validation of Knee KL-classifying Deep Neural Network with Finnish Patient Data

[1]  T. Rantalainen,et al.  Effects of a progressive aquatic resistance exercise program on the biochemical composition and morphology of cartilage in women with mild knee osteoarthritis: protocol for a randomised controlled trial , 2013, BMC Musculoskeletal Disorders.

[2]  I. Kiviranta,et al.  Physical Activity Is Related with Cartilage Quality in Women with Knee Osteoarthritis , 2017, Medicine and science in sports and exercise.

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

[4]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[5]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[6]  T. Rantalainen,et al.  Relationship between lower limb neuromuscular performance and bone strength in postmenopausal women with mild knee osteoarthritis. , 2014, Journal of musculoskeletal & neuronal interactions.

[7]  T. Rantalainen,et al.  Efficacy of progressive aquatic resistance training for tibiofemoral cartilage in postmenopausal women with mild knee osteoarthritis: a randomised controlled trial. , 2016, Osteoarthritis and cartilage.

[8]  Simo Saarakkala,et al.  Automatic Grading of Individual Knee Osteoarthritis Features in Plain Radiographs Using Deep Convolutional Neural Networks , 2019, Diagnostics.

[9]  Sebastian Thrun,et al.  Dermatologist-level classification of skin cancer with deep neural networks , 2017, Nature.

[10]  Joseph Antony,et al.  Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks , 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

[11]  Simo Saarakkala,et al.  Automatic Knee Osteoarthritis Diagnosis from Plain Radiographs: A Deep Learning-Based Approach , 2017, Scientific Reports.

[12]  Hiroshi Fujita,et al.  Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique. , 2016, Medical physics.

[13]  Xiaoshuang Shi,et al.  Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss , 2019, Comput. Medical Imaging Graph..

[14]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[15]  T. Rantalainen,et al.  Effects of high intensity resistance aquatic training on body composition and walking speed in women with mild knee osteoarthritis: a 4-month RCT with 12-month follow-up. , 2017, Osteoarthritis and cartilage.

[16]  Simo Saarakkala,et al.  A Novel Method for Automatic Localization of Joint Area on Knee Plain Radiographs , 2017, SCIA.

[17]  Noel E. O'Connor,et al.  Predicting knee osteoarthritis severity: comparative modeling based on patient’s data and plain X-ray images , 2019, Scientific Reports.

[18]  Noel E. O'Connor,et al.  Automatic Detection of Knee Joints and Quantification of Knee Osteoarthritis Severity Using Convolutional Neural Networks , 2017, MLDM.

[19]  Bram van Ginneken,et al.  A survey on deep learning in medical image analysis , 2017, Medical Image Anal..