Radiology

EVALUATING POSTERIOR VITREOUS DETACHMENT ANNOTATION CONSISTENCY ON OPTICAL COHERENCE TOMOGRAPHY SCANS IN PATIENTS WITH DISEASE OF THE VITREOMACULAR INTERFACE.

PURPOSE: To evaluate intergrader variability in posterior vitreous detachment (PVD) classification in patients with epiretinal membrane and macular hole on spectral-domain optical coherence tomography (SD-OCT) and identify challenges in defining a reliable ground truth for artificial intelligence-based tools. METHODS: A total of 437 horizontal SD-OCT B-scans were retrospectively selected and indep...

BRACTIVE: A Brain Activation Approach to Human Visual Brain Learning.

The human brain is a highly efficient processing unit, and understanding how it works can inspire new algorithms and architectures in machine learning. In this work, we introduce a novel framework named Brain Activation Network (BRACTIVE), a transformer-based approach to studying the human visual brain. The primary objective of BRACTIVE is to align the visual features of subjects with their corres...

Ultrasound Scanner ASIC With 1-D CNN-Based Echo Pattern Recognition for Arterial Distension Monitoring.

This paper presents an A-mode ultrasound scanner application-specific integrated circuit (ASIC) for arterial distension monitoring. The ASIC operates ...

THE ROLE OF EN FACE IMAGING OF RETINAL PIGMENT EPITHELIUM ALTERATIONS IN RAPID CLASSIFICATION OF CENTRAL SEROUS CHORIORETINOPATHY USING WIDEFIELD SWEPT-SOURCE OPTICAL COHERENCE TOMOGRAPHY.

PURPOSE: To investigate the role of widefield en face imaging of retinal pigment epithelium (RPE) alterations using swept-source optical coherence tom...

Artificial intelligence and computer-aided diagnosis in diagnostic decisions: 5 questions for medical informatics and human-computer interface research.

OBJECTIVES: Artificial intelligence (AI) has the potential to transform medical informatics by supporting clinical decision-making, reducing diagnosti...

A Deep Learning-Based Human-Robot Collaborative Navigation Framework for Vascular Interventional Surgery.

BACKGROUND: Autonomous robotic surgery has demonstrated its potential for the optimal outcomes. However, vascular interventional surgery (VIS) with fl...

Genetic Information Enhances a Novel Non-Invasive Steatosis Index and Outperforms Existing Steatosis Indices.

BACKGROUND AND AIMS: Early detection of individuals with metabolic dysfunction-associated steatotic liver disease (MASLD) is important as intervention...

Genomics of kidney volumes: one size does not fit all.

To characterize the genetic basis of chronic kidney disease, genome-wide association studies focused on chronic kidney disease-defining traits that we...

The application of generative neural radiance fields in medical imaging: A systematic review.

BACKGROUND: Generative neural radiance fields (GNeRF) extend NeRF with adversarial, variational, and pose-aware techniques, enabling 3D reconstruction...

Image reconstruction and elongation artifact reduction for a dual-panel dedicated prostate PET scanner.

BACKGROUND: The development of PET scanners dedicated to high temporal and spatial resolution organ-specific imaging is an active research area, motiv...

Comparison of Digital Mammography Plus Full ABUS Review and Digital Mammography Plus Selective ABUS Review Guided by ABUS Artificial Intelligence-Computer-Aided Diagnosis for Breast Cancer Screening.

OBJECTIVE: To compare two breast cancer screening strategies, digital mammography (DM) plus radiologist-interpreted automated breast ultrasound (ABUS)...

Deep learning-based lung volume estimation with dynamic chest radiography.

BACKGROUND: Dynamic chest radiography (DCR) is a recently developed low-dose pulmonary functional imaging method that can be performed in a general X-...

Functional and Clinical: An Explainable Deep Learning Model for Multimodal Alzheimer's Disease Classification.

PURPOSE: Functional magnetic resonance imaging (fMRI) and deep learning models can classify Alzheimer's disease (AD) with high accuracy. These models ...

Monitoring the lateral ventricles in the presence of intracranial hemorrhage using automated dual segmentation.

BACKGROUND: Segmentation of intracranial hemorrhage (ICH) alongside the brain's ventricles can provide crucial information in the management stroke or...

A segmentation method with a large vision model for magnetic resonance imaging-guided adaptive radiotherapy.

BACKGROUND: Segmentation is the most effort-consuming step for magnetic resonance imaging guided adaptive radiotherapy (MRIgART). Although the segment...

The Intelligent Needle: The Role of Artificial Intelligence in Ultrasound-guided Regional Anesthesia.

The integration of artificial intelligence (AI) into ultrasound-guided regional anesthesia (UGRA) marks a new stage in anesthetic practice. Since ultr...

Advances in photoacoustic imaging reconstruction and quantitative analysis for biomedical applications.

Photoacoustic imaging (PAI), a modality that combines the high contrast of optical imaging with the deep penetration of ultrasound, is rapidly transit...

Automatic lymphedema segmentation in T2-STIR MRI using an unsupervised clustering method.

PURPOSE: To develop and evaluate an unsupervised artificial intelligence (AI)-based method for the automated segmentation and quantitative assessment ...

A Deep Learning Framework for Predicting Teprotumumab Treatment Response in Thyroid Eye Disease.

PURPOSE: To develop and evaluate a deep learning-based framework for quantifying thyroid eye disease (TED) severity before and after teprotumumab trea...

Deep learning for high-resolution magnetic resonance vessel wall imaging: image reconstruction, stenosis diagnosis and plaque calculation.

OBJECTIVES: This study developed an automated AI-based method for accurate image reconstruction, stenosis detection and plaque calculation in high-res...