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Titlebook: Biomedical Image Analysis; Segmentation Scott T. Acton,Nilanjan Ray Book 2009 Springer Nature Switzerland AG 2009

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发表于 2025-3-21 16:12:49 | 显示全部楼层 |阅读模式
期刊全称Biomedical Image Analysis
期刊简称Segmentation
影响因子2023Scott T. Acton,Nilanjan Ray
视频video
学科分类Synthesis Lectures on Image, Video, and Multimedia Processing
图书封面Titlebook: Biomedical Image Analysis; Segmentation Scott T. Acton,Nilanjan Ray Book 2009 Springer Nature Switzerland AG 2009
影响因子The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models,and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical
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https://doi.org/10.1007/978-3-031-27387-2Anytime you have a 50–50 chance of getting something right, there’s a 90 percent probability that you’ll get it wrong.
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https://doi.org/10.1007/978-3-031-27387-2The only basis parameter in computer vision algorithms is scale.
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Introduction,Isn’t it strange that I who have written only unpopular books should be such a popular fellow?
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Parametric Active Contours,Do you want to know who you are? Don’t ask. Act! Action will delineate and define you.
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Active Contours in a Bayesian Framework,Anytime you have a 50–50 chance of getting something right, there’s a 90 percent probability that you’ll get it wrong.
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Geometric Active Contours,“Make level paths for your feet and take only ways that are firm.”
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