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The purpose of this study was to assess eye lesions by analyzing wave speed (WS) of lesions using ultrasound vibro-elastography (UVE) together with a parametric ultrasound imaging approach. Ten subjects with eye lesions (5 nevus (N) vs. 5 melanoma (M)) were recruited and tested using UVE. In addition, the sliding window method was used to reconstruct and analyze horizontal Normalized Shannon Entropy (hNSE) images and Nakagami-m/omega images. Two-way ANOVA statistical analysis was performed to compare mean values of the contrast to noise ratio (CNR), hNSE, and m/omega of these images between the two types of lesions. The results show that there were significant differences in CNR of the m map images (p = 0.0174) and omega map images (p = 0.0128) reconstructed from shear wave velocity (SWV) between the two types of lesions and significant differences in CNR of the m map images (p = 0.0209) and omega map images (p < 0.0001) reconstructed from two dimensional (2D) speed maps between the two lesions Furthermore, the m values of 2D speed maps shows significant differences between N vs. M of all three frequencies (i.e., 100 Hz (p = 0.0052), 150 Hz (p = 0.0100), 200 Hz (p = 0.0174)). The results suggest that CNR, m and omega of Nakagami method are useful biomarkers for assessing eye lesion with UVE technique. Nakagami imaging of SWV and 2D speed maps have better performance than hNSE imaging for analyzing characteristics of eye lesions. UVE based Nakagami imaging is a promising method for evaluating eye lesions.
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http://dx.doi.org/10.1016/j.ultras.2025.107725 | DOI Listing |
J Neurosci Methods
September 2025
Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA.
Background: Cortico-cortical evoked potentials (CCEPs), elicited via single-pulse electrical stimulation, are used to map brain networks. These responses comprise early (N1) and late (N2) components, which reflect direct and indirect cortical connectivity. Reliable identification of these components remains difficult due to substantial variability in amplitude, phase, and timing.
View Article and Find Full Text PDFNeurologia (Engl Ed)
September 2025
Facultad de Psicología, Universidad Complutense de Madrid, Campus de Somosaguas 28223 - Pozuelo de Alarcón, Madrid, Spain. Electronic address:
Introduction: The concept of body representation overlaps with others, such as body schema, body image, body semantics, structural description, body description or body map. A taxonomy is proposed that classifies body schema, body structural description and body semantics. The aim of this narrative review is to analyze the supply of instruments for neuropsychological assessment of body representation and to propose a classification of their paradigms.
View Article and Find Full Text PDFMagn Reson Med
September 2025
Laboratorio de Procesado de Imagen (LPI), Universidad de Valladolid, Valladolid, Spain.
Purpose: (a) To design a methodology for drawing random samples of any Ensemble Average Propagator (EAP) (b) to modify the KomaMRI simulator to accommodate them as realistic spin movements to simulate diffusion MRI (dMRI) and (c) to compare these simulations with those based on the Diffusion Tensor (DT) model.
Theory And Methods: The rejection method is used for random sampling of EAPs: starting from a probability law that is easily sampled, and whose density function wraps the target EAP, samples are accepted when they lie inside the targeted region. This is used to sample the EAP as described by Mean Apparent Propagator MRI (MAP-MRI) and in Spherical Convolution (SC) based on Spherical Harmonics (SH).
Updates Surg
September 2025
Department of Pediatric Surgery, School of Medicine, Kocaeli University, Izmit, Turkey.
This study aimed to develop an AI-based diagnostic model for Hirschsprung's disease (HD) using deep learning on contrast enema (CE) images, with the goal of improving diagnostic accuracy while reducing invasiveness. The dataset included 725 CE images from histopathologically confirmed HD patients from 2013 to 2022. Employing Python and PyTorch, a deep learning model based on the YOLOv8 algorithm was trained and validated, emphasizing key metrics like mean average precision (mAP), precision, recall, and F1 score.
View Article and Find Full Text PDFBiol Psychiatry
September 2025
Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, China. Electronic address:
Background: Major depressive disorder (MDD) has been increasingly understood as a disorder of network-level functional dysconnectivity. However, previous brain connectome studies have primarily relied on node-centric approaches, neglecting critical edge-edge interactions that may capture essential features of network dysfunction.
Methods: This study included resting-state functional MRI data from 838 MDD patients and 881 healthy controls (HC) across 23 sites.