| 書目名稱 | Handbook of Biomedical Imaging | | 副標(biāo)題 | Methodologies and Cl | | 編輯 | Nikos Paragios,James Duncan,Nicholas Ayache | | 視頻video | http://file.papertrans.cn/421/420906/420906.mp4 | | 概述 | Authors are leaders in the field.Current and thorough review of biomedical image analysis.Application-oriented.Authors from both Computer Science and Radiology communities | | 圖書封面 |  | | 描述 | .This book explains the process of computer assisted biomedical image analysis diagnosis through mathematical modeling and inference of image-based bio-markers. It covers five crucial thematic areas: methodologies, statistical and physiological models, biomedical perception, clinical biomarkers, and emerging modalities and domains. .The dominant state-of-the-art methodologies for content extraction and interpretation of medical images include fuzzy methods, level set methods, kernel methods, and geometric deformable models. The models and techniques discussed are used in the diagnosis, planning, control and follow-up of medical procedures. Throughout the book, challenges and limitations are explored along with new research directions..Handbook of Biomedical Imaging. offers a unique guide to the entire chain of biomedical imaging, explaining how image formation is done and how the most appropriate techniques are used to address demands and diagnoses. Radiologists, research scientists, senior undergraduate and graduate students in health sciences and engineering, and university professors will find this to be an exceptional reference.. | | 出版日期 | Book 2015 | | 關(guān)鍵詞 | Algorithms; Atlas-based; Automated diagnosis; Bioinformatics; Biomedical perception; Curve propogation; Fu | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-09749-7 | | isbn_softcover | 978-1-4899-7775-5 | | isbn_ebook | 978-0-387-09749-7 | | copyright | Springer Science+Business Media New York 2015 |
The information of publication is updating
|
|
|Archiver|手機(jī)版|小黑屋|
派博傳思國(guó)際
( 京公網(wǎng)安備110108008328)
GMT+8, 2025-10-10 01:16
發(fā)表于 2025-3-21 19:09:24
