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Neural patient-specific 3D-2D registration in laparoscopic liver resection.

International journal of computer assisted radiology and surgery
PURPOSE: Augmented reality guidance in laparoscopic liver resection requires the registration of a preoperative 3D model to the intraoperative 2D image. However, 3D-2D liver registration poses challenges owing to the liver's flexibility, particularly...

Needle tracking in low-resolution ultrasound volumes using deep learning.

International journal of computer assisted radiology and surgery
PURPOSE: Clinical needle insertion into tissue, commonly assisted by 2D ultrasound imaging for real-time navigation, faces the challenge of precise needle and probe alignment to reduce out-of-plane movement. Recent studies investigate 3D ultrasound i...

Virtual tissue microstructure reconstruction across species using generative deep learning.

PloS one
Analyzing tissue microstructure is essential for understanding complex biological systems in different species. Tissue functions largely depend on their intrinsic tissue architecture. Therefore, studying the three-dimensional (3D) microstructure of t...

AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: An exploratory study.

Liver international : official journal of the International Association for the Study of the Liver
BACKGROUND AND AIMS: Lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a ...

Exposure Pathways of Ambient Magnetite Nanoparticles Revealed by Machine Learning-Aided Single-Particle Mass Spectrometry.

Nano letters
Nanosized ultrafine particles (UFPs) from natural and anthropogenic sources are widespread and pose serious health risks when inhaled by humans. However, tracing the inhaled UFPs is extremely difficult, and the distribution, translocation, and metab...

ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging.

Journal of imaging informatics in medicine
As the adoption of artificial intelligence (AI) systems in radiology grows, the increase in demand for greater bandwidth and computational resources can lead to greater infrastructural costs for healthcare providers and AI vendors. To that end, we de...

Identification and validation of cuproptosis-related genes in acetaminophen-induced liver injury using bioinformatics analysis and machine learning.

Frontiers in immunology
BACKGROUND: Acetaminophen (APAP) is commonly used as an antipyretic analgesic. However, acetaminophen overdose may contribute to liver injury and even liver failure. Acetaminophen-induced liver injury (AILI) is closely related to mitochondrial oxidat...

Deep Learning-Enabled Automated Quality Control for Liver MR Elastography: Initial Results.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Several factors can impair image quality and reliability of liver magnetic resonance elastography (MRE), such as inadequate driver positioning, insufficient wave propagation and patient-related factors.

Neural Network Classification Algorithm Based on Self-attention Mechanism and Ensemble Learning for MASLD Ultrasound Images.

Ultrasound in medicine & biology
BACKGROUND: Ultrasound image examination has become the preferred choice for diagnosing metabolic dysfunction-associated steatotic liver disease (MASLD) due to its non-invasive nature. Computer-aided diagnosis (CAD) technology can assist doctors in a...

Machine Learning-Based Models for Advanced Fibrosis and Cirrhosis Diagnosis in Chronic Hepatitis B Patients With Hepatic Steatosis.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
BACKGROUND AND AIMS: The global rise of chronic hepatitis B (CHB) superimposed on hepatic steatosis (HS) warrants noninvasive, precise tools for assessing fibrosis progression. This study leveraged machine learning (ML) to develop diagnostic models f...