4.5 Article

Quasi-automatic 3D reconstruction of the full spine from low-dose biplanar X-rays based on statistical inferences and image analysis

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Gaussian Process Morphable Models

Marcel Luthi et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2018)

Article Engineering, Biomedical

Landmark-guided diffeomorphic demons algorithm and its application to automatic segmentation of the whole spine and pelvis in CT images

Shouhei Hanaoka et al.

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY (2017)

Article Clinical Neurology

Early Detection of Progressive Adolescent Idiopathic Scoliosis

Wafa Skalli et al.

SPINE (2017)

Proceedings Paper Engineering, Biomedical

Lumbar Spine Posterior Corner Detection in X-Rays Using Haar-Based Features

Shahin Ebrahimi et al.

2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI) (2016)

Article Engineering, Biomedical

Real-scale 3D models of the scoliotic spine from biplanar radiography without calibration objects

Daniel C. Moura et al.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2014)

Article Engineering, Biomedical

Three-Dimensional Spine Model Reconstruction Using One-Class SVM Regularization

Fabian Lecron et al.

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2013)

Article Computer Science, Interdisciplinary Applications

Personalized X-Ray 3-D Reconstruction of the Scoliotic Spine From Hybrid Statistical and Image-Based Models

Samuel Kadoury et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2009)

Review Medicine, General & Internal

Current concepts - Computed tomography - An increasing source of radiation exposure

David J. Brenner et al.

NEW ENGLAND JOURNAL OF MEDICINE (2007)

Article Clinical Neurology

A clinical impact classification of scoliosis in the adult

Frank Schwab et al.

SPINE (2006)