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Computer Vision for Biomedical Image Applications
With the rapid increase in the variety and quantity of biomedical images in recent years, we see a steadily growing number of computer vision technologies applied to biomedical applications. The time is ripe for us to take a closer look at the accomplishments and experiences gained in this research subdomain, and to strategically plan the directions of our future research. The scientific goal of our workshop, “Computer Vision for Biomedical Image Applications: Current Techniques and Future Trends” (CVBIA), is to examine the diverse applications of computer vision to biomedical image applications, considering both current methods and promising new trends. An additional goal is to provide ...
AACR 2022 Proceedings: Part B April 11-13
The AACR Annual Meeting is the focal point of the cancer research community, where scientists, clinicians, other health care professionals, survivors, patients, and advocates gather to share the latest advances in cancer science and medicine. From population science and prevention; to cancer biology, translational, and clinical studies; to survivorship and advocacy; the AACR Annual Meeting highlights the work of the best minds in cancer research from institutions all over the world.
Machine Learning in Medical Imaging
This book constitutes the proceedings of the 11th International Workshop on Machine Learning in Medical Imaging, MLMI 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 papers presented in this volume were carefully reviewed and selected from 101 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc.
Identifying Neuroimaging-Based Markers for Distinguishing Brain Disorders
There has been increasing interests in exploring biomarkers from brain images, aiming to have a better understanding and a more effective diagnosis of brain disorders such as schizophrenia, bipolar disorder, schizoaffective disorder, autism spectrum disorder, attention-deficit/hyperactivity disorder, Alzheimer’s disease and so on. Therefore, it is important to identify disease-specific changes for distinguishing healthy controls and patients with brain disorders as well as for differentiating patients with different disorders showing similar clinical symptoms. Biomarkers can be identified from different types of brain Imaging techniques including functional magnetic resonance imaging (fMRI...
MICCAI 2005
The two-volume set LNCS 3749 and LNCS 3750 constitutes the refereed proceedings of the 8th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2005, held in Palm Springs, CA, USA, in October 2005. Based on rigorous peer reviews the program committee selected 237 carefully revised full papers from 632 submissions for presentation in two volumes. The first volume includes all the contributions related to image analysis and validation, vascular image segmentation, image registration, diffusion tensor image analysis, image segmentation and analysis, clinical applications - validation, imaging systems - visualization, computer assisted diagnosis, cellular and molecular image analysis, physically-based modeling, robotics and intervention, medical image computing for clinical applications, and biological imaging - simulation and modeling. The second volume collects the papers related to robotics, image-guided surgery and interventions, image registration, medical image computing , structural and functional brain analysis, model-based image analysis, image-guided intervention: simulation, modeling and display, and image segmentation and analysis.
Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing
The book provides details regarding the application of various signal processing and artificial intelligence-based methods for electroencephalography data analysis. It will help readers in understanding the use of electroencephalography signals for different neural information processing and cognitive neuroscience applications. The book: Covers topics related to the application of signal processing and machine learning-based techniques for the analysis and classification of electroencephalography signals Presents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interface Highlights the latest machine learn...
Information Processing in Medical Imaging
This book constitutes the refeered proceedings of the 19th International Conference on Information Processing in Medical Imaging, IPMI 2005, held in Glenwood Springs, Colorado, in July 2005. The 63 revised full papers presented were carefully reviewed and selected from 245 submissions. The papers are organized in topical sections on shape and population modeling, diffusion tensor imaging and functional magnetic resonance, segmentation and filtering, small animal imaging, surfaces and segmentation, applications, image registration, registration and segmentation.
Metadata and Semantic Research
This book constitutes the thoroughly refereed proceedings of the 13th International Conference on Metadata and Semantic Research, MTSR 2019, held in Rome, Italy, in October 2019. The 27 full and 15 short papers presented were carefully reviewed and selected from 96 submissions. The papers are organized in the following tracks: metadata and semantics for digital libraries, information retrieval, big, linked, social and open data; metadata and semantics for agriculture, food, and environment; digital humanities and digital curation; cultural collections and applications; european and national projects; metadata, identifiers and semantics in decentralized applications, blockchains and P2P systems.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006
The two-volume set LNCS 4190 and LNCS 4191 constitute the refereed proceedings of the 9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006. The program committee carefully selected 39 revised full papers and 193 revised poster papers for presentation in two volumes. This second volume collects 118 papers related to segmentation, validation and quantitative image analysis, brain image processing, and much more.
