IEEE transactions on bio-medical engineering
Jul 1, 2025
OBJECTIVE: Transventricular approach to deep-brain targets offers direct visualization but also imparts deformation that challenges accurate neuronavigation. 3D reconstruction and registration of the endoscopic view could provide up-to-date, real-tim...
DNA is emerging as a promising medium for storing huge volumes of data in a confined space that remains intact for thousands of years. Although this technique is very efficient, especially for multimedia data like images, there is a lack of efficient...
IEEE transactions on bio-medical engineering
Jul 1, 2025
OBJECTIVE: To enable context-aware computer assistance in the operating room of the future, cognitive systems need to understand automatically which surgical phase is being performed by the medical team. The primary source of information for surgical...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Graph-Level Anomaly Detection (GLAD) endeavors to pinpoint a small subset of anomalous graphs that deviate from the normal data distribution within a given set of graph data. Existing GLAD methods typically rely on Graph Neural Networks (GNNs) to ext...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Recently, quantum federated learning (QFL) has received significant attention as an innovative paradigm. QFL has remarkable features by employing quantum neural networks (QNNs) instead of conventional neural networks owing to quantum supremacy. In or...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Banding artifacts in images stem from limitations in color bit depth, image compression, or over-editing, significantly degrades image quality, especially in regions with smooth gradients. Image debanding is about eliminating these artifacts while pr...
Neural networks : the official journal of the International Neural Network Society
Jul 1, 2025
Hyperspectral anomaly detection (HAD) can identify and locate the targets without any known information and is widely applied in Earth observation and military fields. The majority of existing HAD methods use the low-rank representation (LRR) model t...
PURPOSE: Four-pool Voigt (FPV) machine learning (ML)-based fitting for Z-spectra was developed to reduce fitting times for clinical feasibility in terms of on-scanner analysis and to promote larger cohort studies. The approach was compared to four-po...
PURPOSE: To develop and evaluate a physics-driven, saturation contrast-aware, deep-learning-based framework for motion artifact correction in CEST MRI.
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