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Intelligent Multimedia Surveillance
  • Language: en
  • Pages: 196

Intelligent Multimedia Surveillance

Intelligent multimedia surveillance concerns the analysis of multiple sensing inputs including video and audio streams, radio-frequency identification (RFID), and depth data. These data are processed for the automated detection and tracking of people, vehicles, and other objects. The goal is to locate moving targets, to understand their behavior, and to detect suspicious or abnormal activities for crime prevention. Despite its benefits, there is societal apprehension regarding the use of such technology, so an important challenge in this research area is to balance public safety and privacy. This edited book presents recent findings in the field of intelligent multimedia surveillance emergin...

Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data
  • Language: en
  • Pages: 138

Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data

This book constitutes the refereed joint proceedings of the 4th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, and the First International Workshop on Topological Data Analysis and Its Applications for Medical Data, TDA4MedicalData 2021, held on September 27, 2021, in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021. The 7 full papers presented at iMIMIC 2021 and 5 full papers held at TDA4MedicalData 2021 were carefully reviewed and selected from 12 submissions each. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. TDA4MedicalData is focusing on using TDA techniques to enhance the performance, generalizability, efficiency, and explainability of the current methods applied to medical data.

Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2010
  • Language: en
  • Pages: 751

Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2010

The three-volume set LNCS 6361, 6362 and 6363 constitutes the refereed proceedings of the 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010, held in Beijing, China, in September 2010. Based on rigorous peer reviews, the program committee carefully selected 251 revised papers from 786 submissions for presentation in three volumes. The first volume includes 84 papers organized in topical sections on computer-aided diagnosis, planning and guidance of interventions, image segmentation, image reconstruction and restoration, functional and diffusion-weighted MRI, modeling and simulation, instrument and patient localization and tracking, quantitative image analysis, image registration, computational and interventional cardiology, and diffusion tensor MR imaging and analysis.

Ophthalmic Medical Image Analysis
  • Language: en
  • Pages: 202

Ophthalmic Medical Image Analysis

This book constitutes the refereed proceedings of the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 22 full papers (out of 36 submissions) presented at OMIA 2019 were carefully reviewed and selected. The papers cover various topics in the field of ophthalmic image analysis.

Medical Image Computing and Computer Assisted Intervention – MICCAI 2024
  • Language: en
  • Pages: 805
Medical Image Computing and Computer Assisted Intervention − MICCAI 2017
  • Language: en
  • Pages: 739

Medical Image Computing and Computer Assisted Intervention − MICCAI 2017

  • Type: Book
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  • Published: 2017-09-03
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  • Publisher: Springer

The three-volume set LNCS 10433, 10434, and 10435 constitutes the refereed proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, held inQuebec City, Canada, in September 2017. The 255 revised full papers presented were carefully reviewed and selected from 800 submissions in a two-phase review process. The papers have been organized in the following topical sections: Part I: atlas and surface-based techniques; shape and patch-based techniques; registration techniques, functional imaging, connectivity, and brain parcellation; diffusion magnetic resonance imaging (dMRI) and tensor/fiber processing; and image segmentation and modelling. Part II: optical imaging; airway and vessel analysis; motion and cardiac analysis; tumor processing; planning and simulation for medical interventions; interventional imaging and navigation; and medical image computing. Part III: feature extraction and classification techniques; and machine learning in medical image computing.

Machine Learning in Medical Imaging
  • Language: en
  • Pages: 336

Machine Learning in Medical Imaging

  • Type: Book
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  • Published: 2016-10-10
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  • Publisher: Springer

This book constitutes the refereed proceedings of the 7th International Workshop on Machine Learning in Medical Imaging, MLMI 2016, held in conjunction with MICCAI 2016, in Athens, Greece, in October 2016. The 38 full papers presented in this volume were carefully reviewed and selected from 60 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging.

Interpretable and Annotation-Efficient Learning for Medical Image Computing
  • Language: en
  • Pages: 306

Interpretable and Annotation-Efficient Learning for Medical Image Computing

This book constitutes the refereed joint proceedings of the Third International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, the Second International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020, and the 5th International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, LABELS 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 8 full papers presented at iMIMIC 2020, 11 full papers to MIL3ID 2020, and the 10 full papers presented at LABELS 2020 were carefull...

Medical Image Computing and Computer Assisted Intervention – MICCAI 2023
  • Language: en
  • Pages: 821

Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning – transfer learning; Part II: Machine learning – learning strategies; machine learning – explainability, bias, and uncertainty; Part III: Machine learnin...

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...