AI Medical Compendium Journal:
IEEE transactions on bio-medical engineering

Showing 31 to 40 of 342 articles

A Physics-Informed Deep Neural Network for Harmonization of CT Images.

IEEE transactions on bio-medical engineering
OBJECTIVE: Computed Tomography (CT) quantification is affected by the variability in image acquisition and rendition. This paper aimed to reduce this variability by harmonizing the images utilizing physics-based deep neural networks (DNNs).

SeeSaw: Learning Soft Tissue Deformation From Laparoscopy Videos With GNNs.

IEEE transactions on bio-medical engineering
A major challenge in image-guided laparoscopic surgery is that structures of interest often deform and go, even if only momentarily, out of view. Methods which rely on having an up-to-date impression of those structures, such as registration or local...

Shortcomings in the Evaluation of Blood Glucose Forecasting.

IEEE transactions on bio-medical engineering
OBJECTIVE: Recent years have seen an increase in machine learning (ML)-based blood glucose (BG) forecasting models, with a growing emphasis on potential application to hybrid or closed-loop predictive glucose controllers. However, current approaches ...

A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development.

IEEE transactions on bio-medical engineering
OBJECTIVE: Brain dynamic effective connectivity (dEC), characterizes the information transmission patterns between brain regions that change over time, which provides insight into the biological mechanism underlying brain development. However, most e...

Learning Motion Primitives for the Quantification and Diagnosis of Mobility Deficits.

IEEE transactions on bio-medical engineering
The severity of mobility deficits is one of the most critical parameters in the diagnosis of Parkinson's disease (PD) and rehabilitation. The current approach for severity evaluation is clinical scaling that relies on a clinician's subjective observa...

An Efficient Muscle Segmentation Method via Bayesian Fusion of Probabilistic Shape Modeling and Deep Edge Detection.

IEEE transactions on bio-medical engineering
OBJECTIVE: Paraspinal muscle segmentation and reconstruction from MR images are critical to implement quantitative assessment of chronic and recurrent low back pains. Due to unclear muscle boundaries and shape variations, current segmentation methods...

Combining Fiber Bragg Grating and Artificial Intelligence Technologies for Supporting Epidural Procedures.

IEEE transactions on bio-medical engineering
OBJECTIVE: Loss of resistance (LOR) is a widely accepted method for performing epidural punctures in clinical settings. However, the risk of failure associated with LOR is still high. Solutions based either on Fiber Bragg grating sensors (FBG) or on ...

Deep Autoencoder for Real-Time Single-Channel EEG Cleaning and Its Smartphone Implementation Using TensorFlow Lite With Hardware/Software Acceleration.

IEEE transactions on bio-medical engineering
OBJECTIVE: To remove signal contamination in electroencephalogram (EEG) traces coming from ocular, motion, and muscular artifacts which degrade signal quality. To do this in real-time, with low computational overhead, on a mobile platform in a channe...

Nanorobot-Based Direct Implantation of Flexible Neural Electrode for BCI.

IEEE transactions on bio-medical engineering
Brain-Computer Interface (BCI) has gained remarkable prominence in biomedical community. While BCI holds vast potential across diverse domains, the implantation of neural electrodes poses multifaceted challenges to fully explore the power of BCI. Con...

Interactive Surgical Training in Neuroendoscopy: Real-Time Anatomical Feature Localization Using Natural Language Expressions.

IEEE transactions on bio-medical engineering
OBJECTIVE: This study addresses challenges in surgical education, particularly in neuroendoscopy, where the demand for optimized workflow conflicts with the need for trainees' active participation in surgeries. To overcome these challenges, we propos...