Deep learning in medical ultrasound image analysis: a review
Ultrasound (US) is one of the most widely used imaging modalities in medical diagnosis. It
has the advantages of real-time, low cost, noninvasive nature, and easy to operate …
has the advantages of real-time, low cost, noninvasive nature, and easy to operate …
[HTML][HTML] Pre-training in medical data: A survey
Medical data refers to health-related information associated with regular patient care or as
part of a clinical trial program. There are many categories of such data, such as clinical …
part of a clinical trial program. There are many categories of such data, such as clinical …
Noninvasive diagnosis of nonalcoholic fatty liver disease and quantification of liver fat with radiofrequency ultrasound data using one-dimensional convolutional …
Background Radiofrequency ultrasound data from the liver contain rich information about
liver microstructure and composition. Deep learning might exploit such information to assess …
liver microstructure and composition. Deep learning might exploit such information to assess …
Two-dimensional convolutional neural network using quantitative US for noninvasive assessment of hepatic steatosis in NAFLD
Background Quantitative US (QUS) using radiofrequency data analysis has been recently
introduced for noninvasive evaluation of hepatic steatosis. Deep learning algorithms may …
introduced for noninvasive evaluation of hepatic steatosis. Deep learning algorithms may …
US quantification of liver fat: past, present, and future
DT Fetzer, TT Pierce, ML Robbin, G Cloutier, A Mufti… - …, 2023 - pubs.rsna.org
Fatty liver disease has a high and increasing prevalence worldwide, is associated with
adverse cardiovascular events and higher long-term medical costs, and may lead to liver …
adverse cardiovascular events and higher long-term medical costs, and may lead to liver …
[HTML][HTML] Automatic classification of fatty liver disease based on supervised learning and genetic algorithm
Fatty liver disease is considered a critical illness that should be diagnosed and detected at
an early stage. In advanced stages, liver cancer or cirrhosis arise, and to identify this …
an early stage. In advanced stages, liver cancer or cirrhosis arise, and to identify this …
[HTML][HTML] Artificial intelligence for detecting and quantifying fatty liver in ultrasound images: A systematic review
FM Alshagathrh, MS Househ - Bioengineering, 2022 - mdpi.com
Background: Non-alcoholic Fatty Liver Disease (NAFLD) is growing more prevalent
worldwide. Although non-invasive diagnostic approaches such as conventional …
worldwide. Although non-invasive diagnostic approaches such as conventional …
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 …
based on ultrasound (US) images acquired from four different liver views: transverse plane …
[HTML][HTML] Artificial intelligence in liver ultrasound
LL Cao, M Peng, X Xie, GQ Chen… - World journal of …, 2022 - ncbi.nlm.nih.gov
Artificial intelligence (AI) is playing an increasingly important role in medicine, especially in
the field of medical imaging. It can be used to diagnose diseases and predict certain …
the field of medical imaging. It can be used to diagnose diseases and predict certain …
[HTML][HTML] Implementation of combinational deep learning algorithm for non-alcoholic fatty liver classification in ultrasound images
Background: Nowadays, fatty liver is one of the commonly occurred diseases for the liver
which can be observed generally in obese patients. Final results from a variety of exams and …
which can be observed generally in obese patients. Final results from a variety of exams and …