A Critical Analysis on Vertebra Identification and Cobb Angle Estimation Using Deep Learning for Scoliosis Detection
Author:
Affiliation:
1. Department of Computer Science and Engineering, Chandigarh University, Chandigarh, Punjab, India
2. School of Computer Science Engineering and Technology, Bennett University, Greater Noida, Uttar Pradesh, India
Funder
Analytical Center for the Government of the Russian Federation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10399479.pdf?arnumber=10399479
Reference46 articles.
1. Development of a CapsNet and Fuzzy Logic Decision Support System for Diagnosing the Scoliosis and Planning Treatments via Schroth Method
2. Accurate Cobb Angle Estimation on Scoliosis X-Ray Images via Deeply-Coupled Two-Stage Network With Differentiable Cropping and Random Perturbation
3. Vertebrae Identification and Localization Utilizing Fully Convolutional Networks and a Hidden Markov Model
4. Automation of Spine Curve Assessment in Frontal Radiographs Using Deep Learning of Vertebral-Tilt Vector
5. Vertebrae Labeling via End-to-End Integral Regression Localization and Multi-Label Classification Network
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