Computational Medical Image Analysis

This Special Issue covers a variety of computational applications in medical image analysis. With a vast majority of the articles reporting on machine learning or deep learning-based methodologies, it highlights the transistion toward artificial intelligence over the past decade.

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Bibliographische Detailangaben
Format:	Buch
Sprache:	eng
Schlagworte:	40 AdaBoost artificial intelligence attention deficit hyperactivity disorder (ADHD) brain model BreakHis breast cancer detection chaotic attractors class activation maps classification compressed sensing computer vision computer-assisted diagnosis convolutional neural networks COVID-19 CT scan decision tree deep features deep learning diagnosis digital pathology disease diagnosis EfficientNetB0 electrophysiological (EEG) signals encryption GAN geometric augmentation histology image analysis histopathology holography cardiac cine MRI hybrid learning hyperbolic tangent function IDC image augmentation image classification image segmentation infrared thermal segmentation interpretable technique l1-norm smooth approximations linear discriminant analysis (LDA) machine learning magnification dependent medical image dataset analysis Medicine and Nursing Medicine: general issues n/a Naive Bayes oral health pathology simulation perfusion descriptors Public health and preventive medicine random forest random fourier features regional neuraxial analgesia regression ResNet50 model skin cancer soft thresholding superpixel support vector machine tracer concentration curves virtual DSC-MRI examination wound monitoring X-ray imaging Xception model
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Beschreibung
Zusammenfassung:	This Special Issue covers a variety of computational applications in medical image analysis. With a vast majority of the articles reporting on machine learning or deep learning-based methodologies, it highlights the transistion toward artificial intelligence over the past decade.
DOI:	10.3390/books978-3-7258-1393-3