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Computational intelligence and image processing in medical applications [electronic resource] / editor, C H Chen.

Contributor(s): C H Chen.
Material type: materialTypeLabelBookPublisher: Singapore : World Scientific, 2022Description: 1 online resource (336 p.).ISBN: 9789811257452; 9811257450.Subject(s): Computational intelligence | Image processing | Diagnostic imagingGenre/Form: Electronic books.DDC classification: 616.0754 Online resources: Access to full text is restricted to subscribers.
Contents:
Introduction. An introduction to computational intelligence and image processing -- Intelligent behavioral trajectory pattern recognition for longitudinal trials -- COVID-19 detection. Segmentation of COVID-19 infected lung area in CT scans with deep algorithms -- Active learning for medical image classification -- Medical imaging. Medical image segmentation: how raters' experience may affect the quality of reference information -- Machine learning approach for quantification of neuropathy using confocal microscopy images of the human cornea -- Peripheral blood smear analysis using deep learning: current challenges and future directions -- Deep learning based 3d brain tumor segmentation with multispectral MRI -- Deep learning techniques for ultrasound image enhancement and segmentation -- A fast inference framework for medical image semantic segmentation tasks using deep learning framework -- A new feature extraction approach for segmentation of intravascular ultrasound images -- Deep multi-task learning approach for bioelectrical signal analysis - 3D tomosynthesis to detect breast cancer -- Emerging topics. Using deep learning for dermatologist-level detection of ugly-duckling and suspicious pigmented skin lesions from wide-field images -- Deep learning in medical imaging and its challenges.
Summary: "In recent years, there have been significant progress in computational intelligence and image processing with machine learning and deep learning as important components of modern artificial intelligence. All these progresses face challenges in dealing with Covid-19 pandemic for detection and treatment. This comprehensive compendium provides not only updated advances of computational intelligence and image processing in the detection and treatment of Covid-19, but also other medical applications such as in cancer detection and cardiovascular diseases, etc. More traditional approaches such as 2D segmentation and 3D reconstruction are included. The useful reference text is an updated version of the edited title, Computer Vision in Medical Imaging (World Scientific, 2014) and its companion volume, Frontiers of Medical Imaging (World Scientific, 2015). The book is written for engineers, scientists and the medical community to meet the increased challenges in medical applications"-- Publisher's website.
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Introduction. An introduction to computational intelligence and image processing -- Intelligent behavioral trajectory pattern recognition for longitudinal trials -- COVID-19 detection. Segmentation of COVID-19 infected lung area in CT scans with deep algorithms -- Active learning for medical image classification -- Medical imaging. Medical image segmentation: how raters' experience may affect the quality of reference information -- Machine learning approach for quantification of neuropathy using confocal microscopy images of the human cornea -- Peripheral blood smear analysis using deep learning: current challenges and future directions -- Deep learning based 3d brain tumor segmentation with multispectral MRI -- Deep learning techniques for ultrasound image enhancement and segmentation -- A fast inference framework for medical image semantic segmentation tasks using deep learning framework -- A new feature extraction approach for segmentation of intravascular ultrasound images -- Deep multi-task learning approach for bioelectrical signal analysis - 3D tomosynthesis to detect breast cancer -- Emerging topics. Using deep learning for dermatologist-level detection of ugly-duckling and suspicious pigmented skin lesions from wide-field images -- Deep learning in medical imaging and its challenges.

"In recent years, there have been significant progress in computational intelligence and image processing with machine learning and deep learning as important components of modern artificial intelligence. All these progresses face challenges in dealing with Covid-19 pandemic for detection and treatment. This comprehensive compendium provides not only updated advances of computational intelligence and image processing in the detection and treatment of Covid-19, but also other medical applications such as in cancer detection and cardiovascular diseases, etc. More traditional approaches such as 2D segmentation and 3D reconstruction are included. The useful reference text is an updated version of the edited title, Computer Vision in Medical Imaging (World Scientific, 2014) and its companion volume, Frontiers of Medical Imaging (World Scientific, 2015). The book is written for engineers, scientists and the medical community to meet the increased challenges in medical applications"-- Publisher's website.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat reader.

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