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Medical Image Computing and Computer Assisted Intervention – MICCAI 2021
  • Language: en
  • Pages: 735

Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

The eight-volume set LNCS 12901, 12902, 12903, 12904, 12905, 12906, 12907, and 12908 constitutes the refereed proceedings of the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021, held in Strasbourg, France, in September/October 2021.* The 531 revised full papers presented were carefully reviewed and selected from 1630 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: image segmentation Part II: machine learning - self-supervised learning; machine learning - semi-supervised learning; and machine learning - weakly supervised learning Part III: machine learning - advances in m...

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging
  • Language: en
  • Pages: 152

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

This book constitutes the refereed proceedings of the Fourth Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2022, held in conjunction with MICCAI 2022. The conference was hybrid event held from Singapore. For this workshop, 13 papers from 22 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.

Medical Image Computing and Computer Assisted Intervention – MICCAI 2024
  • Language: en
  • Pages: 782
Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures
  • Language: en
  • Pages: 147

Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures

This book constitutes the refereed joint proceedings of the 10th International Workshop on Multimodal Learning for Clinical Decision Support, ML-CDS 2020, and the 9th International Workshop on Clinical Image-Based Procedures, CLIP 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic. The 4 full papers presented at ML-CDS 2020 and the 9 full papers presented at CLIP 2020 were carefully reviewed and selected from numerous submissions to ML-CDS and 10 submissions to CLIP. The ML-CDS papers discuss machine learning on multimodal data sets for clinical decision support and treatment planning. The CLIP workshops provides a forum for work centered on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data.

Clinical Image-Based Procedures. Translational Research in Medical Imaging
  • Language: en
  • Pages: 142

Clinical Image-Based Procedures. Translational Research in Medical Imaging

  • Type: Book
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  • Published: 2016-03-29
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  • Publisher: Springer

This book constitutes revised selected papers from the 4th International Workshop on Clinical Image-Based Procedures, CLIP 2015, held in conjunction with MICCAI 2015 in Munich, Germany, in October 2015. The 15 papers presented in this volume were carefully reviewed and selected from 22 submissions. CLIP focuses on translational research; therefore, the goal of the works presented in this workshop is to bring basic research methods closer to the clinical practice. A highlight of this workshop is the subject of strategies for personalized medicine to enhance diagnosis, treatment and interventions.

Machine Learning in Medical Imaging
  • Language: en
  • Pages: 200

Machine Learning in Medical Imaging

  • Type: Book
  • -
  • Published: 2010-09-10
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  • Publisher: Springer

The first International Workshop on Machine Learning in Medical Imaging, MLMI 2010, was held at the China National Convention Center, Beijing, China on Sept- ber 20, 2010 in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2010. Machine learning plays an essential role in the medical imaging field, including image segmentation, image registration, computer-aided diagnosis, image fusion, ima- guided therapy, image annotation, and image database retrieval. With advances in me- cal imaging, new imaging modalities, and methodologies such as cone-beam/multi-slice CT, 3D Ultrasound, tomosynthesis, diffusion-weighted MRI, electrica...

The 8th International Conference on Advances in Construction Machinery and Vehicle Engineering
  • Language: en
  • Pages: 1282
Artificial Neural Networks in Pattern Recognition
  • Language: en
  • Pages: 338

Artificial Neural Networks in Pattern Recognition

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Multimedia Technology and Enhanced Learning
  • Language: en
  • Pages: 422

Multimedia Technology and Enhanced Learning

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
  • Language: en
  • Pages: 908

Medical Image Computing and Computer Assisted Intervention – MICCAI 2019

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging.