Computational Medical Image Analysis

doi:10.3390/books978-3-7258-1393-3

Download Url(s)

https://mdpi.com/books/pdfview/book/9429

Contributor(s)

Sen, Anando (editor)

Language

English

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Abstract

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.

URI

https://directory.doabooks.org/handle/20.500.12854/139427

Keywords

chaotic attractors; computer vision; disease diagnosis; encryption; computer-assisted diagnosis; convolutional neural networks; compressed sensing; holography cardiac cine MRI; l1-norm smooth approximations; hyperbolic tangent function; soft thresholding; breast cancer detection; magnification dependent; histopathology; BreakHis; IDC; Xception model; ResNet50 model; EfficientNetB0; 40×; medical image dataset analysis; diagnosis; machine learning; deep learning; classification; digital pathology; histology image analysis; infrared thermal segmentation; regional neuraxial analgesia; random fourier features; class activation maps; artificial intelligence; oral health; X-ray imaging; electrophysiological (EEG) signals; support vector machine; random forest; decision tree; AdaBoost; Naive Bayes; linear discriminant analysis (LDA); attention deficit hyperactivity disorder (ADHD); skin cancer; image augmentation; GAN; geometric augmentation; image classification; interpretable technique; wound monitoring; hybrid learning; image segmentation; superpixel; regression; virtual DSC-MRI examination; perfusion descriptors; tracer concentration curves; brain model; pathology simulation; deep features; COVID-19; CT scan; n/a