AI Medical Compendium Topic:
Ultrasonography

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Non-invasive prediction of the chronic degree of lupus nephropathy based on ultrasound radiomics.

Lupus
OBJECTIVE: Through machine learning (ML) analysis of the radiomics features of ultrasound extracted from patients with lupus nephritis (LN), this attempt was made to non-invasively predict the chronicity index (CI)of LN.

Real-time carotid plaque recognition from dynamic ultrasound videos based on artificial neural network.

Ultraschall in der Medizin (Stuttgart, Germany : 1980)
PURPOSE: Carotid ultrasound allows noninvasive assessment of vascular anatomy and function with real-time display. Based on the transfer learning method, a series of research results have been obtained on the optimal image recognition and analysis of...

Deep-learning models for differentiation of xanthogranulomatous cholecystitis and gallbladder cancer on ultrasound.

Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology
BACKGROUND: The radiological differentiation of xanthogranulomatous cholecystitis (XGC) and gallbladder cancer (GBC) is challenging yet critical. We aimed at utilizing the deep learning (DL)-based approach for differentiating XGC and GBC on ultrasoun...

A 5G-based telerobotic ultrasound system provides qualified abdominal ultrasound services for patients on a rural island: a prospective and comparative study of 401 patients.

Abdominal radiology (New York)
PURPOSE: To explore the feasibility of a 5G-based telerobotic ultrasound (US) system for providing qualified abdominal US services on a rural island.

Noninvasive diagnostic imaging for endometriosis part 1: a systematic review of recent developments in ultrasound, combination imaging, and artificial intelligence.

Fertility and sterility
Endometriosis affects 1 in 9 women and those assigned female at birth. However, it takes 6.4 years to diagnose using the conventional standard of laparoscopy. Noninvasive imaging enables a timelier diagnosis, reducing diagnostic delay as well as the ...

Review of Deep Learning Approaches for Interleaved Photoacoustic and Ultrasound (PAUS) Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Photoacoustic (PA) imaging provides optical contrast at relatively large depths within the human body, compared to other optical methods, at ultrasound (US) spatial resolution. By integrating real-time PA and US (PAUS) modalities, PAUS imaging has th...

Ultrafast Cardiac Imaging Using Deep Learning for Speckle-Tracking Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in reduced frame rate, as well as destructive interferences from high-vel...

Automated detection and segmentation of pleural effusion on ultrasound images using an Attention U-net.

Journal of applied clinical medical physics
BACKGROUND: Ultrasonic for detecting and evaluating pleural effusion is an essential part of the Extended Focused Assessment with Sonography in Trauma (E-FAST) in emergencies. Our study aimed to develop an Artificial Intelligence (AI) diagnostic mode...

Deep learning for fast super-resolution ultrasound microvessel imaging.

Physics in medicine and biology
. Ultrasound localization microscopy (ULM) enables microvascular reconstruction by localizing microbubbles (MBs). Although ULM can obtain microvascular images that are beyond the ultimate resolution of the ultrasound (US) diffraction limit, it requir...