IEEE journal of biomedical and health informatics
Jun 1, 2025
The differences between cross-modality medical images are significant, so several studies are working on unsupervised domain adaptation (UDA) segmentation, which aims to adapt a segmentation model trained on a labeled source domain to an unlabeled ta...
The incidence of hypotension after a lumbosacral epidural in dogs depends on the volume of local anaesthetic administered. So far, there are no reports comparing both methods used to calculate this volume-body weight (BW) and occipito-coccygeal lengt...
Journal of computer assisted tomography
May 13, 2025
The applications of machine learning in clinical radiology practice and in particular oncologic imaging practice are steadily evolving. However, there are several potential hurdles for widespread implementation of machine learning in oncologic imagin...
Studies in health technology and informatics
May 2, 2025
The goal of segmentation in abdominal imaging for emergency medicine is to accurately identify and delineate organs, as well as to detect and localize pathological areas. This precision is critical for rapid, informed decision-making in acute care sc...
PURPOSE: To evaluate the feasibility of a high-precision single-shot fast spin-echo (SS-FSE) sequence using the deep learning-based Precise IQ Engine (PIQE) algorithm in comparison with standard SS-FSE for T2-weighted MR imaging of the abdomen, and t...
The Journal of international medical research
Nov 1, 2024
OBJECTIVE: To externally validate by revision and update the study on the efficacy of nosocomial infection control (SENIC) model of surgical site infection (SSI) using logistic regression (LR) and machine learning (ML) approaches.
Deep learning has shown great potential to automate abdominal organ segmentation and quantification. However, most existing algorithms rely on expert annotations and do not have comprehensive evaluations in real-world multinational settings. To addre...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Fetal movement is a commonly monitored indicator of fetal wellbeing with reductions in fetal movement being associated with poor perinatal outcomes. However, more informative datasets of fetal movement are required for improved clinical decision maki...
Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based denoising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstructi...
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy contr...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.