AI-based methods to generate images have seen unprecedented advances in recent years challenging both image forensic and human perceptual capabilities. Accordingly, these methods are expected to play an increasingly important role in the fraudulent f...
Feature extraction and selection from medical data are the basis of radiomics and image biomarker discovery for various architectures, including convolutional neural networks (CNNs). We herein describe the typical radiomics steps and the components o...
SIGNIFICANCE: Early detection of melanoma is crucial for improving patient outcomes, and dermoscopy is a critical tool for this purpose. However, hair presence in dermoscopic images can obscure important features, complicating the diagnostic process....
Ship detection over long distances is crucial for the visual perception of intelligent ships. Since traditional image processing-based methods are not robust, deep learning-based image recognition methods can automatically obtain the features of smal...
BACKGROUND: Multi-material decomposition is an interesting topic in dual-energy CT (DECT) imaging; however, the accuracy and performance may be limited using the conventional algorithms.
While advances in single-particle cryo-EM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the 'preferred' orientation problem) remains a complication for most specimens. Existing ...
Journal of applied clinical medical physics
Nov 18, 2024
The integration of machine learning (ML) with radiotherapy has emerged as a pivotal innovation in outcome prediction, bringing novel insights amid unique challenges. This review comprehensively examines the current scope of ML applications in various...
Pediatric and developmental pathology : the official journal of the Society for Pediatric Pathology and the Paediatric Pathology Society
Nov 18, 2024
The integration of artificial intelligence (AI) into healthcare is becoming increasingly mainstream. Leveraging digital technologies, such as AI and deep learning, impacts researchers, clinicians, and industry due to promising performance and clinica...
Artificial intelligence (AI) is an interdisciplinary field that combines computer technology, mathematics, and several other fields. Recently, with the rapid development of machine learning (ML) and deep learning (DL), significant progress has been m...
Synthetic data is becoming a valuable tool for computational pathologists, aiding in tasks like data augmentation and addressing data scarcity and privacy. However, its use necessitates careful planning and evaluation to prevent the creation of clini...
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