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A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation

European spine journal, 2020-09, Vol.29 (9), p.2295-2305

2020

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Spinopelvic measurements of sagittal balance with deep learning: systematic review and critical evaluation

European spine journal, 2022-08, Vol.31 (8), p.2031-2045

2022

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Auto‐segmentation of organs at risk for head and neck radiotherapy planning: From atlas‐based to deep learning methods

Medical physics (Lancaster), 2020-09, Vol.47 (9), p.e929-e950

2020

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A benchmark for comparison of dental radiography analysis algorithms

Medical image analysis, 2016-07, Vol.31, p.63-76

2016

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A Framework for Automated Spine and Vertebrae Interpolation-Based Detection and Model-Based Segmentation

IEEE transactions on medical imaging, 2015-08, Vol.34 (8), p.1649-1662

2015

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A review of methods for quantitative evaluation of spinal curvature

European spine journal, 2009-05, Vol.18 (5), p.593-607

2009

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Računalniško podprto merjenje parametrov sagitalne orientacije medenice iz rentgenskih slik

Zdravniški vestnik (Ljubljana, Slovenia : 1992), 2019-01, Vol.87 (11-12), p.519-529

2019

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Computational Methods and Clinical Applications in Musculoskeletal Imaging: 6th International Workshop, MSKI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers

1st Edition 2019, 2019

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A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation

European spine journal, 2022-08, Vol.31 (8), p.2115-2124

2022

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Shape Representation for Efficient Landmark-Based Segmentation in 3-D

IEEE transactions on medical imaging, 2014-04, Vol.33 (4), p.861-874

2014

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HaN‐Seg: The head and neck organ‐at‐risk CT and MR segmentation dataset

Medical physics (Lancaster), 2023-03, Vol.50 (3), p.1917-1927

2023

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Computational Methods and Clinical Applications in Musculoskeletal Imaging: 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers

1st Edition 2018, 2018

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Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification

Medical image analysis, 2022-05, Vol.78, p.102417-102417, Article 102417

2022

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A review of methods for evaluating the quantitative parameters of sagittal pelvic alignment

The spine journal, 2012-05, Vol.12 (5), p.433-446

2012

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vOARiability: Interobserver and intermodality variability analysis in OAR contouring from head and neck CT and MR images

Medical physics (Lancaster), 2024-03, Vol.51 (3), p.2175-2186

2024

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Computer‐assisted pedicle screw trajectory planning using CT‐inferred bone density: A demonstration against surgical outcomes

Medical physics (Lancaster), 2019-08, Vol.46 (8), p.3543-3554

2019

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Computerized three-dimensional pedicle morphometry from computed tomography images of the thoracic spine

Image analysis & stereology, 2020-01, Vol.39 (2), p.101-109

2020

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Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge

IEEE transactions on medical imaging, 2015-09, Vol.34 (9), p.1890-1900

2015

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Computer-Assisted Screw Size and Insertion Trajectory Planning for Pedicle Screw Placement Surgery

IEEE transactions on medical imaging, 2016-06, Vol.35 (6), p.1420-1430

2016

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Image Analysis & Stereology: 2017 Research Highlights

Image analysis & stereology, 2018-01, Vol.37 (1), p.1-7

Vrtovec, Tomaž

2018

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Parametric modelling and segmentation of vertebral bodies in 3D CT and MR spine images

Physics in medicine & biology, 2011-12, Vol.56 (23), p.7505-7522

2011

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Reinforcement learning-based anatomical maps for pancreas subregion and duct segmentation

Medical physics (Lancaster), 2024-07

2024

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HaN-Seg: The head and neck organ-at-risk CT and MR segmentation challenge

Radiotherapy and oncology, 2024-09, Vol.198, p.110410, Article 110410

2024

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Computational Methods and Clinical Applications for Spine Imaging: Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings

1st ed. 2016, 2016

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A multi-center milestone study of clinical vertebral CT segmentation

Computerized medical imaging and graphics, 2016-04, Vol.49, p.16-28

2016

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A deep learning tool for fully automated measurements of sagittal spinopelvic balance from X-ray images: performance evaluation

Spinopelvic measurements of sagittal balance with deep learning: systematic review and critical evaluation

Auto‐segmentation of organs at risk for head and neck radiotherapy planning: From atlas‐based to deep learning methods

A benchmark for comparison of dental radiography analysis algorithms

A Framework for Automated Spine and Vertebrae Interpolation-Based Detection and Model-Based Segmentation

A review of methods for quantitative evaluation of spinal curvature

Računalniško podprto merjenje parametrov sagitalne orientacije medenice iz rentgenskih slik

Computational Methods and Clinical Applications in Musculoskeletal Imaging: 6th International Workshop, MSKI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers

A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation

Shape Representation for Efficient Landmark-Based Segmentation in 3-D

HaN‐Seg: The head and neck organ‐at‐risk CT and MR segmentation dataset

Computational Methods and Clinical Applications in Musculoskeletal Imaging: 5th International Workshop, MSKI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Revised Selected Papers

Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification

A review of methods for evaluating the quantitative parameters of sagittal pelvic alignment

vOARiability: Interobserver and intermodality variability analysis in OAR contouring from head and neck CT and MR images

Computer‐assisted pedicle screw trajectory planning using CT‐inferred bone density: A demonstration against surgical outcomes

Computerized three-dimensional pedicle morphometry from computed tomography images of the thoracic spine

Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge

Computer-Assisted Screw Size and Insertion Trajectory Planning for Pedicle Screw Placement Surgery

Image Analysis & Stereology: 2017 Research Highlights

Parametric modelling and segmentation of vertebral bodies in 3D CT and MR spine images

Reinforcement learning-based anatomical maps for pancreas subregion and duct segmentation

HaN-Seg: The head and neck organ-at-risk CT and MR segmentation challenge

Computational Methods and Clinical Applications for Spine Imaging: Third International Workshop and Challenge, CSI 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Proceedings

A multi-center milestone study of clinical vertebral CT segmentation

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