Aggregation-induced emission-active micelles: synthesis, characterization, and applications

Y Liu, X Chen, X Liu, W Guan, C Lu - Chemical Society Reviews, 2023 - pubs.rsc.org
Aggregation-induced emission (AIE)-active micelles are a type of fluorescent functional
materials that exhibit enhanced emissions in the aggregated surfactant state. They have …

Radiological diagnosis of chronic liver disease and hepatocellular carcinoma: A review

S Singh, S Hoque, A Zekry, A Sowmya - Journal of Medical Systems, 2023 - Springer
Medical image analysis plays a pivotal role in the evaluation of diseases, including
screening, surveillance, diagnosis, and prognosis. Liver is one of the major organs …

Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images

M Byra, G Styczynski, C Szmigielski… - International journal of …, 2018 - Springer
Purpose The nonalcoholic fatty liver disease is the most common liver abnormality. Up to
date, liver biopsy is the reference standard for direct liver steatosis quantification in hepatic …

Artificial intelligence in imaging: the radiologist's role

DL Rubin - Journal of the American College of Radiology, 2019 - Elsevier
Rapid technological advancements in artificial intelligence (AI) methods have fueled
explosive growth in decision tools being marketed by a rapidly growing number of …

A two-stage multi-view learning framework based computer-aided diagnosis of liver tumors with contrast enhanced ultrasound images

LH Guo, D Wang, YY Qian, X Zheng… - Clinical …, 2018 - content.iospress.com
OBJECTIVE: With the fast development of artificial intelligence techniques, we proposed a
novel two-stage multi-view learning framework for the contrast-enhanced ultrasound (CEUS) …

A novel computer-aided diagnosis framework using deep learning for classification of fatty liver disease in ultrasound imaging

DS Reddy, R Bharath… - 2018 IEEE 20th …, 2018 - ieeexplore.ieee.org
Fatty Liver Disease (FLD), if left untreated can progress into fatal chronic diseases (Eg.
fibrosis, cirrhosis, liver cancer, etc.) leading to permanent liver failure. Doctors usually use …

Liver fat assessment in multiview sonography using transfer learning with convolutional neural networks

M Byra, A Han, AS Boehringer… - … of Ultrasound in …, 2022 - Wiley Online Library
Objectives To develop and evaluate deep learning models devised for liver fat assessment
based on ultrasound (US) images acquired from four different liver views: transverse plane …

[HTML][HTML] Ultrasound-based artificial intelligence in gastroenterology and hepatology

JQ Liu, JY Ren, XL Xu, LY Xiong, YX Peng… - World Journal of …, 2022 - ncbi.nlm.nih.gov
Artificial intelligence (AI), especially deep learning, is gaining extensive attention for its
excellent performance in medical image analysis. It can automatically make a quantitative …

Quantitative analysis of artificial intelligence on liver cancer: A bibliometric analysis

M Xiong, Y Xu, Y Zhao, S He, Q Zhu, Y Wu, X Hu… - Frontiers in …, 2023 - frontiersin.org
Objective To provide the current research progress, hotspots, and emerging trends for AI in
liver cancer, we have compiled a relative comprehensive and quantitative report on the …

Preliminary study of chronic liver classification on ultrasound images using an ensemble model

P Bharti, D Mittal, R Ananthasivan - Ultrasonic imaging, 2018 - journals.sagepub.com
Chronic liver diseases are fifth leading cause of fatality in developing countries. Their early
diagnosis is extremely important for timely treatment and salvage life. To examine …