A 40-nm 169mW Ultrasound Imaging Processor Supporting Advanced Modes for Hand-Held Devices.

Hand-held ultrasound devices have been widely used in the field of healthcare and power-efficient, real-time imaging is essential. This work presents the world's first ultrasound imaging processor supporting advanced modes, including vector flow imaging and elastography imaging. Plane-wave beamforming is utilized to ensure that the pulse repetition frequency (PRF) is sufficiently high for the advanced mode.

Applying ONCO-RADS to whole-body MRI cancer screening in a retrospective cohort of asymptomatic individuals.

Background: Whole-body magnetic resonance imaging (WB-MRI) has emerged as a valuable tool for cancer detection. This study evaluated the prevalence rates of cancer in asymptomatic individuals undergoing WB-MRI according to the Oncologically Relevant Findings Reporting and Data System (ONCO-RADS) classifications in order to assess the reliability of the classification method.

Methods: We retrospectively enrolled 2064 asymptomatic individuals who participated in a WB-MRI cancer screening program between 2017 and 2022.

A Case of Tubular Adenoma of Gallbladder Diagnosed Using Contrast-Enhanced Ultrasonography.

Contrast-enhanced ultrasound (CEUS) has been used to diagnose gallbladder (GB) diseases for recent years because it is sensitive to visualize vascularity. Herein, we report a case who had a 1.7 cm × 1.

Laser and Anti-Vascular Endothelial Growth Factor Agent Treatments for Retinal Arterial Macroaneurysm.

Purpose: To describe the efficacy of laser and intravitreal injection of anti-vascular endothelial growth factor (anti-VEGF) agents for patients with symptomatic retinal arterial macroaneurysm (RAM).

Design: From 2009 to 2016, we collected patients with exudative or hemorrhagic RAM all treated by focal laser photocoagulation.

Methods: Nd:YAG laser was performed in patients with subinternal limiting membrane (sub-ILM) hemorrhage.

A General Fuzzy Cerebellar Model Neural Network Multidimensional Classifier Using Intuitionistic Fuzzy Sets for Medical Identification.

The diversity of medical factors makes the analysis and judgment of uncertainty one of the challenges of medical diagnosis. A well-designed classification and judgment system for medical uncertainty can increase the rate of correct medical diagnosis. In this paper, a new multidimensional classifier is proposed by using an intelligent algorithm, which is the general fuzzy cerebellar model neural network (GFCMNN).