Performance of a Deep Neural Network Algorithm Based on a Small Medical Image Dataset: Incremental Impact of 3D-to-2D Reformation Combined with Novel Data Augmentation, Photometric Conversion, or Transfer Learning.

[BibT_eX]

[DOI]

Vikash Gupta

Mutlu Demirer

Matthew T. Bigelow

Kevin J. Little

Sema Candemir

Luciano M. Prevedello

J. Digit. Imaging, 2020

Automatic CAD-RADS Scoring Using Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Abstract: Coronary Artery Plaque Characterization from CCTA Scans Using DL and Radiomics.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

Deep Learning Algorithms for Coronary Artery Plaque Characterisation from CCTA Scans.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2020 - Algorithmen - Systeme, 2020

2019

Coronary Artery Plaque Characterization from CCTA Scans Using Deep Learning and Radiomics.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

General purpose radiomics for multi-modal clinical research.

[BibT_eX]

[DOI]

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

2018

Geometric modeling of the aortic inner and outer vessel wall from CTA for aortic dissection analysis.

[BibT_eX]

[DOI]

Katharina Eigen

Michael Wels

Daniel Sebastian Dohle

Michael Sühling

Andreas K. Maier

Proceedings of the Medical Imaging 2018: Image-Guided Procedures, 2018

2017

Growing a Random Forest with Fuzzy Spatial Features for Fully Automatic Artery-Specific Coronary Calcium Scoring.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017

2016

Inner and outer coronary vessel wall segmentation from CCTA using an active contour model with machine learning-based 3D voxel context-aware image force.

[BibT_eX]

[DOI]

Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016

2014

Estimating a Patient Surface Model for Optimizing the Medical Scanning Workflow.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

2013

Image-based Co-Registration of Angiography and Intravascular Ultrasound Images.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2013

Spine detection in CT and MR using iterated marginal space learning.

[BibT_eX]

[DOI]

Medical Image Anal., 2013

Pectoral Muscle Detection in Digital Breast Tomosynthesis and Mammography.

[BibT_eX]

[DOI]

Proceedings of the Medical Computer Vision. Large Data in Medical Imaging, 2013

Fast and robust 3D vertebra segmentation using statistical shape models.

[BibT_eX]

[DOI]

Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2012

Data-Driven Breast Decompression and Lesion Mapping from Digital Breast Tomosynthesis.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2012, 2012

Multi-stage osteolytic spinal bone lesion detection from CT data with internal sensitivity control.

[BibT_eX]

[DOI]

Proceedings of the Medical Imaging 2012: Computer-Aided Diagnosis, San Diego, 2012

2010

Probabilistic modeling for segmentation in magnetic resonance images of the human brain.

[BibT_eX]

[DOI]

Michael Wels

PhD thesis, 2010

Detection of 3D Spinal Geometry Using Iterated Marginal Space Learning.

[BibT_eX]

[DOI]

Proceedings of the Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging, 2010

2009

Fast and Robust 3-D MRI Brain Structure Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2009

2008

A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2008

2006

Ultrasound-Specific Segmentation via Decorrelation and Statistical Region-Based Active Contours.

[BibT_eX]

[DOI]

Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006

Michael Wels

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