PURPOSE: This study investigates the feasibility of using complex-valued neural networks (NNs) to estimate quantitative transmit magnetic RF field (B ) maps from multi-slice localizer scans with different slice orientations in the human head at 7T, a...
AIMS: Heart failure with preserved ejection fraction (HFpEF) requires an efficient screening method. We developed a deep learning model (DLM) to screen HFpEF risk using electrocardiograms (ECGs).
OBJECTIVES: This work proposes a novel method to evaluate root canal filling (RCF) success using artificial intelligence (AI) and image analysis techniques.
Malignant melanoma is the most severe skin cancer with a rising incidence rate. Several noninvasive image techniques and computer-aided diagnosis systems have been developed to help find melanoma in its early stages. However, most previous research u...
Diagnostic and interventional imaging
Oct 26, 2024
PURPOSE: The purpose of this study was to evaluate an artificial intelligence (AI) software that automatically detects and quantifies breast arterial calcifications (BAC).
Salivary gland neoplasms (SGNs) represent a group of human neoplasms characterized by a remarkable cytomorphologic diversity, which frequently poses diagnostic challenges. Accurate histologic categorization of salivary gland tumors is crucial to make...
Animal pose estimation is crucial for animal health assessment, species protection, and behavior analysis. It is an inevitable and unstoppable trend to apply deep learning to animal pose estimation. In many practical application scenarios, pose estim...
Journal of the Formosan Medical Association = Taiwan yi zhi
Oct 25, 2024
PURPOSE: To compare deep learning (DL)-based and conventional reconstruction through subjective and objective analysis and ascertain whether DL-based reconstruction improves the quality and acquisition speed of clinical abdominal magnetic resonance i...
Journal of imaging informatics in medicine
Oct 25, 2024
Bladder cancer, often asymptomatic in the early stages, is a type of cancer where early detection is crucial. Herein, endoscopic images are meticulously evaluated by experts, and sometimes even by different disciplines, to identify tissue types. It i...
Journal of imaging informatics in medicine
Oct 25, 2024
The purpose of this study is to investigate the impact of using morphological information in classifying suspicious breast lesions. The widespread use of deep transfer learning can significantly improve the performance of the mammogram based CADx sch...
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