Caroline Essert

Stefanie Speidel

Marleen de Bruijne

Philippe C. Cattin

Stéphane Cotin

Nicolas Padoy

Yefeng Zheng

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 machine learning theory; machine learning - attention models; machine learning - domain adaptation; machine learning - federated learning; machine learning - interpretability / explainability; and machine learning - uncertainty Part IV: image registration; image-guided interventions and surgery; surgical data science; surgical planning and simulation; surgical skill and work flow analysis; and surgical visualization and mixed, augmented and virtual reality Part V: computer aided diagnosis; integration of imaging with non-imaging biomarkers; and outcome/disease prediction Part VI: image reconstruction; clinical applications - cardiac; and clinical applications - vascular Part VII: clinical applications - abdomen; clinical applications - breast; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - neuroimaging - brain development; clinical applications - neuroimaging - DWI and tractography; clinical applications - neuroimaging - functional brain networks; clinical applications - neuroimaging – others; and clinical applications - oncology Part VIII: clinical applications - ophthalmology; computational (integrative) pathology; modalities - microscopy; modalities - histopathology; and modalities - ultrasound *The conference was held virtually.

24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part I

Medical Image Computing and Computer Assisted Intervention – MICCAI 2021

24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part VI

24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part II

24th International Conference, Strasbourg, France, September 27 – October 1, 2021, Proceedings, Part VII

Le Lu

Lin Yang

Gustavo Carneiro

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

Precision Medicine, High Performance and Large-Scale Datasets

Deep Learning and Convolutional Neural Networks for Medical Image Computing

24th International Conference, Strasbourg, France, September 27–October 1, 2021, Proceedings, Part IV

24th International Conference, Strasbourg, France, September 27 – October 1, 2021, Proceedings, Part VIII

Yefeng Zheng

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