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  • Machine Learning Empowering Personalized Medicine: A . . . - MDPI
    Artificial intelligence (AI) advancements, especially deep learning, have significantly improved medical image processing and analysis in various tasks such as disease detection, classification, and anatomical structure segmentation This work overviews fundamental concepts, state-of-the-art models, and publicly available datasets in the field of medical imaging First, we introduce the types
  • Medical Image Analysis - MDPI
    Papers are welcomed on issues that are related to image processing techniques for biomedical applications, including: medical image reconstruction; medical image retrieval; medical image segmentation; deep or handcrafted features for biomedical image classification; visualization in biomedical imaging; machine learning and artificial
  • Frontiers | Applications, image analysis, and interpretation of . . .
    Unlike natural image analysis with large-scale labeled datasets such as ImageNet, medical image analysis faces a major challenge of lacking labeled data to construct reliable and robust models (20) Image quality, resolution, artifacts, and variability across imaging devices and protocols pose challenges for standardized workflows (21)
  • A Review of Non-Fully Supervised Deep Learning for Medical Image . . . - MDPI
    Medical image segmentation, a critical task in medical image analysis, aims to precisely delineate regions of interest (ROIs) such as organs, lesions, and cells, and is crucial for applications including computer-aided diagnosis, surgical planning, radiation therapy, and pathological analysis While fully supervised deep learning methods have demonstrated remarkable performance in this domain
  • Deep Convolutional Neural Networks in Medical Image Analysis: A . . . - MDPI
    Deep convolutional neural networks (CNNs) have revolutionized medical image analysis by enabling the automated learning of hierarchical features from complex medical imaging datasets This review provides a focused analysis of CNN evolution and architectures as applied to medical image analysis, highlighting their application and performance in different medical fields, including oncology
  • Gamma and X-Ray Technologies for Medical Research: Image Analysis and . . .
    1 Introduction The continuous pursuit of innovative diagnostic and medical research methods plays a crucial role in improving public health Among the many available tools, technologies utilizing gamma and X-ray radiation form the foundation of modern medical imaging, enabling a minimally invasive yet detailed view inside the human body
  • Critical Analysis of the Current Medical Image-Based Processing . . . - MDPI
    Medical image processing and analysis techniques play a significant role in diagnosing diseases Thus, during the last decade, several noteworthy improvements in medical diagnostics have been made based on medical image processing techniques In this article, we reviewed articles published in the most important journals and conferences that used or proposed medical image analysis techniques to
  • Special Issue on “Machine Learning-Aided Medical Image Analysis” - MDPI
    The aim of this Special Issue was to highlight recent advances in emerging ML and DL methodologies, with a particular focus on medical image analysis This Special Issue includes six selected papers covering a wide range of ML applications across diverse medical imaging tasks and domains
  • Deep Learning in Medical Image Analysis - MDPI
    The purpose of this Special Issue (SI) “Deep Learning in Medical Image Analysis” is to present and highlight novel algorithms, architectures, techniques, and applications of DL for medical image analysis This SI called for papers in April 2020 It received more than 60 submissions from over 30 different countries





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