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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...
A Handbook for Analyzing Chinese Characters
With the fast growth of Chinese economy, the number of people learning Chinese language is increasing rapidly throughout the world. A Handbook for Analyzing Chinese Characters is intended to help those studying Chinese as a second language. It includes 5073 most frequently used Chinese characters in reading and writing. To help learners identify the most important to the least important characters, the 5073 characters are grouped into five different usage levels. Besides, they are formed with pictographic characters, self-indicative characters, compound ideographic characters and radical phonetic characters according to their structures. Each character is described with the property of the character and clarified by an illustrative sentence.Zhifang Ren is a professor of English at China Medical University. He has previously written a book titled A Handbook of Analyzing English Vocabulary published in China. This is his second literary endeavor involving ten years of painstaking research and compilation.
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 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...
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...
Three Kingdoms
“A material epic with an astonishing fidelity to history."—New York Times Book Review Three Kingdoms tells the story of the fateful last reign of the Han dynasty (206 B.C.–A.D. 220), when the Chinese empire was divided into three warring kingdoms. Writing some twelve hundred years later, the Ming author Luo Guanzhong drew on histories, dramas, and poems portraying the crisis to fashion a sophisticated, compelling narrative that has become the Chinese national epic. This abridged edition captures the novel's intimate and unsparing view of how power is wielded, how diplomacy is conducted, and how wars are planned and fought. As important for Chinese culture as the Homeric epics have been for the West, this Ming dynasty masterpiece continues to be widely influential in China, Korea, Japan, and Vietnam and remains a great work of world literature.
Dictionary of the Ben Cao Gang Mu, Volume 3
The Ben cao gang mu, compiled in the second half of the sixteenth century by a team led by the physician Li Shizhen (1518–1593) on the basis of previously published books and contemporary knowledge, is the largest encyclopedia of natural history in a long tradition of Chinese materia medica works. Its description of almost 1,900 pharmaceutically used natural and man-made substances marks the apex of the development of premodern Chinese pharmaceutical knowledge. The Ben cao gang mu dictionary offers access to this impressive work of 1,600,000 characters. This third book in a three-volume series offers detailed biographical data on all identifiable authors, patients, witnesses of therapies, transmitters of recipes, and further persons mentioned in the Ben cao gang mu and provides bibliographical data on all textual sources resorted to and quoted by Li Shizhen and his collaborators.
Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems
This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
