Vishal Patel – författare

This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.

DART 2019 accepted 12 papers for publication out of 18 submissions. The papers deal with methodological advancements and ideas that can improve the applicability of machine learning and deep learning approaches to clinical settings by making them robust and consistent across different domains.

MIL3ID accepted 16 papers out of 43 submissions for publication, dealing with best practices in medical image learning with label scarcity and data imperfection. 

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 carefully reviewed and selected from 16 submissions to iMIMIC, 28 to MIL3ID, and 12 submissions to LABELS. 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. MIL3ID deals with best practices in medical image learning with label scarcity and data imperfection. The LABELS papers present a variety of approaches for dealing with a limited number of labels, from semi-supervised learning to crowdsourcing.

Total Knee Arthroplasty: Medical and Biomedical Engineering and Science Concepts provides an extensive overview of the most recent advancements in total knee arthroplasty (TKA) through a thorough review of the literature in medicine, engineering, and technology. Coverage includes the most recent engineering and computing techniques, such as robotics, biomechanics, artificial intelligence (AI), deep learning (DL), machine learning (ML), and optimization, as well as the medical and surgical aspects of pre-existing conditions, surgical procedure types, surgical complications, patient care, and psychological factors. This book will be a valuable introduction to TKA concepts and advances for academics, students, and researchers.

This two-volume set LNCS 15046 and 15047 constitutes the refereed proceedings of the 17th International Symposium, ISVC 2024, held at Lake Tahoe, NV, USA, during October 21-23, 2024.The 54 (60) full papers and 12 poster papers were carefully reviewed and selected from 120 submissions. A total of 8 (13) papers were also accepted for oral presentation in special tracks from 15 submissions. The papers cover the following topical sections:Part I: Deep Learning; Computer Graphics; Video Analysis and Event Recognition; Motion and Tracking; Detection and Recognition; Visualization, and Medical Image Analysis.Part II: Segmentation; Recognition; Generalization in Visual Machine Learning; Vision and Robotics for Agriculture; Virtual Reality; Applications, and Poster.

This two-volume set LNCS 15046 and 15047 constitutes the refereed proceedings of the 17th International Symposium, ISVC 2024, held at Lake Tahoe, NV, USA, during October 21-23, 2024.The 54 full papers and 12 poster papers were carefully reviewed and selected from 120 submissions. A total of 8 papers were also accepted for oral presentation in special tracks from 15 submissions. The papers cover the following topical sections:Part I: Deep Learning; Computer Graphics; Video Analysis and Event Recognition; Motion and Tracking; Detection and Recognition; Visualization, and Medical Image Analysis.Part II: Segmentation; Recognition; Generalization in Visual Machine Learning; Vision and Robotics for Agriculture; Virtual Reality; Applications, and Poster.