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Artificial Intelligence in Clinical Medical Imaging

Edited by
April 2024
210 pages
  • ISBN978-3-7258-0876-2 (Hardback)
  • ISBN978-3-7258-0875-5 (PDF)
https://doi.org/10.3390/books978-3-7258-0875-5
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This book is a reprint of the Special Issue Artificial Intelligence in Clinical Medical Imaging that was published in

Medicine & Pharmacology
Public Health & Healthcare
Summary

The integration of artificial intelligence (AI) has propelled significant advancements in clinical medical imaging, offering unprecedented accuracy and efficiency in diagnostic procedures and treatment strategies. This transformative shift has permeated every sector of medical imaging, from traditional organ diagnostics to the dynamic realms of digital pathology and dermatology, where AI acts as a catalyst for innovation and progress. Now, consolidated into a reprint, the Special Issue titled "Artificial Intelligence in Clinical Medical Imaging" comprises 14 comprehensive contributions, ranging from insightful editorials to cutting-edge scientific articles, reviews, and commentaries.

Format
  • Hardback
License
© 2024 by the authors; CC BY-NC-ND license
Keywords
n/a; dynamic contrast-enhanced imaging; segmentation; lesion detection; small liver tumor; convolutional neural network; deep learning; CNN; diabetic retinopathy; fundus image; pooling function; functional MRI; resting state; deep learning; augmentation; autism; coronary angiography; deep learning; coronary artery stenosis detection; convolutional neural network; one-stage detection; without segmentation; bone metastasis segmentation; Double U-Net; pre-train; negative mining; transfer learning; deep learning; brain tumor classification; deep learning; residual networks; vanishing gradient; feature learning; medical diagnostics; adaptive partitioning; explainable AI; kidney tumor segmentation; optimization; weight pruning; UNet-PWP; DeepLabV3+; GCAM-attention; cardiovascular diseases; acute myocardial infarction; fractional flow reserve; machine learning; ensemble; random forest; 3D reconstruction; n/a; autism; artificial intelligence; autism spectrum disorders; fMRI; lumbar disc bulging; herniated intervertebral disc; disc height; machine learning; decision tree; plain radiography; magnetic resonance imaging; deep learning; glaucoma; image analysis; artificial intelligence; n/a