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|a 9789179290382
|q (electronic bk.)
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|a (MiAaPQ)EBC6790370
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|a (Au-PeEL)EBL6790370
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|a MiAaPQ
|b eng
|e rda
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|a Cirillo, Marco Domenico.
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|a A Path along Deep Learning for Medical Image Analysis :
|b With Focus on Burn Wounds and Brain Tumors.
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|a 1st ed.
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|a Linköping :
|b Linkopings Universitet,
|c 2021.
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|c {copy}2021.
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|a 1 online resource (101 pages)
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Linköping Studies in Science and Technology. Dissertations Series ;
|v v.2175
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|a Intro -- Abstract -- Acknowledgments -- Contents -- List of Figures -- Introduction -- Aim -- Delimitations -- Research questions -- Included papers -- Research ethics -- Outline -- Burn Wounds and Brain Tumors -- Burn wounds -- Pathophysiology -- Assessment methods -- Brain tumors -- Pathophysiology -- Assessment methods -- Reflections -- Image Features -- Type of features -- Color features -- Edge feature -- Texture features -- Mixed features -- Principal component analysis -- Independent component analysis -- Tensor decomposition -- Deep features -- Convolution -- Deep features -- Reflections -- Convolutional Neural Networks -- Deep learning basics -- Loss functions -- Forward and backward propagation -- Data pre-processing -- Weight initialization -- Normalization layers -- Activation functions -- Optimization -- Regularization -- Residual block -- Convolutional neural networks -- Convolutional layers -- CNNs for image classification -- CNNs for image segmentation -- CNNs for image generation -- Reflections -- Image Augmentation -- Image Augmentation Techniques -- Patch extraction -- Flipping -- Rotation -- Scaling -- Elastic grid-based deformation -- Brightness -- Reflections -- Generative Adversarial Networks -- Generator and discriminator -- GANs in medical imaging -- GAN losses -- Image-to-image GANs -- Pix2Pix -- Semantic image synthesis with spatially-adaptive normalization -- Reflections -- Papers, Discussions and Conclusions -- Paper I: Tensor decomposition for colour image segmentation of burn wounds -- Paper II: Time-independent prediction of burn depth using deep convolutional neural networks -- Paper III: Improving burn depth assessment for pediatric scalds by AI based on semantic segmentation of polarized light photography images -- Paper IV: Vox2Vox: 3D-GAN for brain tumour segmentation.
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|a Paper V: What is the best data augmentation for 3D brain tumor segmentation? -- Conclusions -- Bibliography -- Papers.
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|a Description based on publisher supplied metadata and other sources.
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|a Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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|a Electronic books.
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|i Print version:
|a Cirillo, Marco Domenico
|t A Path along Deep Learning for Medical Image Analysis
|d Linköping : Linkopings Universitet,c2021
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| 797 |
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|a ProQuest (Firm)
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| 830 |
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|a Linköping Studies in Science and Technology. Dissertations Series
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| 856 |
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|u https://ebookcentral.proquest.com/lib/matrademy/detail.action?docID=6790370
|z Click to View
|
