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Medical Image Computing and Computer Assisted Intervention – MICCAI 2022
The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022. The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology; Part II: Computational (integrative) pathology; computational anatomy and physiology; op...
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020
The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applica...
Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2012
The three-volume set LNCS 7510, 7511, and 7512 constitutes the refereed proceedings of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, held in Nice, France, in October 2012. Based on rigorous peer reviews, the program committee carefully selected 252 revised papers from 781 submissions for presentation in three volumes. The first volume includes 91 papers organized in topical sections on abdominal imaging, computer-assisted interventions and robotics; computer-aided diagnosis and planning; image reconstruction and enhancement; analysis of microscopic and optical images; computer-assisted interventions and robotics; image segmentation; cardiovascular imaging; and brain imaging: structure, function and disease evolution.
Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data
This book constitutes three challenges that were held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020*: the Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images Challenge, the Learn2Reg Challenge, and the Thyroid Nodule Segmentation and Classification in Ultrasound Images Challenge. The 19 papers presented in this volume were carefully reviewed and selected form numerous submissions. The ABCs challenge aims to identify the best methods of segmenting brain structures that serve as barriers to the spread of brain cancers and structures to be spared from irradiation, for use in computer assisted target definition for glioma and radiotherapy plan optimization. The papers of the L2R challenge cover a wide spectrum of conventional and learning-based registration methods and often describe novel contributions. The main goal of the TN-SCUI challenge is to find automatic algorithms to accurately segment and classify the thyroid nodules in ultrasound images. *The challenges took place virtually due to the COVID-19 pandemic.
New Technologies in Radiation Oncology
- Summarizes the state of the art in the most relevant areas of medical physics and engineering applied to radiation oncology - Covers all relevant areas of the subject in detail, including 3D imaging and image processing, 3D treatment planning, modern treatment techniques, patient positioning, and aspects of verification and quality assurance - Conveys information in a readily understandable way that will appeal to professionals and students with a medical background as well as to newcomers to radiation oncology from the field of physics
Database Systems for Advanced Applications
This two volume set LNCS 9642 and LNCS 9643 constitutes the refereed proceedings of the 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016, held in Dallas, TX, USA, in April 2016. The 61 full papers presented were carefully reviewed and selected from a total of 183 submissions. The papers cover the following topics: crowdsourcing, data quality, entity identification, data mining and machine learning, recommendation, semantics computing and knowledge base, textual data, social networks, complex queries, similarity computing, graph databases, and miscellaneous, advanced applications.
Characterizing Cardiac Electrophysiology During Radiofrequency Ablation
Catheter ablation is a major treatment for atrial tachycardias. Hereby, the precise monitoring of the lesion formation is an important success factor. This book presents computational, wet-lab, and clinical studies with the aim of evaluating the signal characteristics of the intracardiac electrograms (IEGMs) recorded around ablation lesions from different perspectives. The detailed analysis of the IEGMs can optimize the description of durable and complex lesions during the ablation procedure. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data
This book constitutes three challenges that were held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020*: the Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images Challenge, the Learn2Reg Challenge, and the Thyroid Nodule Segmentation and Classification in Ultrasound Images Challenge. The 19 papers presented in this volume were carefully reviewed and selected form numerous submissions. The ABCs challenge aims to identify the best methods of segmenting brain structures that serve as barriers to the spread of brain cancers and structures to be spared from irradiation, for use in computer assisted target definition for glioma and radiotherapy plan optimization. The papers of the L2R challenge cover a wide spectrum of conventional and learning-based registration methods and often describe novel contributions. The main goal of the TN-SCUI challenge is to find automatic algorithms to accurately segment and classify the thyroid nodules in ultrasound images. *The challenges took place virtually due to the COVID-19 pandemic.
Intensity-Modulated Radiation Therapy
Clinical conformal radiotherapy is the holy grail of radiation treatment and is now becoming a reality through the combined efforts of physical scientists and engineers, who have improved the physical basis of radiotherapy, and the interest and concern of imaginative radiotherapists and radiographers. Intensity-Modulated Radiation Therapy de
