Publications by authors named "M Lago"
Background: In silico clinical trials are becoming more sophisticated and allow for realistic assessment and comparisons of medical image system models. These fully computational models enable fast and affordable trial designs that can closely capture trends seen on real clinical trials.
Purpose: To evaluate three breast imaging system models for digital mammography (DM) and digital breast tomosynthesis (DBT) in a fully-in-silico longitudinal study.
Visual perception on virtual reality head-mounted displays (VR HMDs) involves human vision in the imaging pipeline. Image quality evaluation of VR HMDs may need to be expanded from optical bench testing by incorporating human visual perception. In this study, we implement a 5-degree-of-freedom (5DoF) experimental setup that simulates the human eye geometry and rotation mechanism.
View Article and Find Full Text PDFIn the past decade, artificial intelligence (AI) algorithms have made promising impacts in many areas of healthcare. One application is AI-enabled prioritization software known as computer-aided triage and notification (CADt). This type of software as a medical device is intended to prioritize reviews of radiological images with time-sensitive findings, thus shortening the waiting time for patients with these findings.
View Article and Find Full Text PDFArticle Synopsis
- * Virtual trials (in silico trials) offer a viable alternative by employing computational models, but there’s a pressing need for a unified framework that the medical imaging community can adopt.
- * Essential requirements for these virtual trial frameworks include ensuring credibility through rigorous assessments, enhancing reproducibility with thorough documentation, and improving accessibility via user-friendly tools and data-sharing solutions.
Evaluation of monocular and binocular contrast perception on virtual reality head-mounted displays.
J Med Imaging (Bellingham)
November 2024
Purpose: Visualization of medical images on a virtual reality (VR) head-mounted display (HMD) requires binocular fusion of a stereoscopic pair of graphical views. However, current image quality assessment on VR HMDs for medical applications has been primarily limited to time-consuming monocular optical bench measurement on a single eyepiece.
Approach: As an alternative to optical bench measurement to quantify the image quality on VR HMDs, we developed a WebXR test platform to perform contrast perceptual experiments that can be used for binocular image quality assessment.