A deep learning model with data integration of ultrasound contrast ...
Objective To develop and investigate a deep learning model with data integration of ultrasound contrast-enhanced micro-flow (CEMF) cines, B-mode images, and patients’ clinical parameters to improve the …
A deep learning model with data integration of ultrasound contrast ...
Key Points • The combined use of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical data in a deep learning model has potential to improve the diagnosis of significant liver fibrosis .
Correction: A deep learning model with data integration of ultrasound ...
Correction: A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with …
A deep learning model with data integration of ultrasound contrast ...
A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with chronic …
A deep learning model with data integration of ultrasound contrast ...
To develop and investigate a deep learning model with data integration of ultrasound contrast-enhanced micro-flow (CEMF) cines, B-mode images, and patients’ clinical parameters to improve the diagnosis …
A deep learning model with data integration of ultrasound contrast ...
A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with ...
Contrast-Enhanced Ultrasound with Deep Learning with Attention ...
Rationale and Objectives Prediction of microvascular invasion (MVI) status of hepatocellular carcinoma (HCC) holds clinical significance for decision-making regarding the treatment strategy and evaluation …
Contrast-Enhanced Ultrasound with Deep Learning with Attention ...
Abstract Rationale and objectives: Prediction of microvascular invasion (MVI) status of hepatocellular carcinoma (HCC) holds clinical significance for decision-making regarding the treatment strategy and …
A Comparative Study of Contrast Enhanced Ultrasound Imaging Using …
In contrast enhanced ultrasound (CEUS) imaging, nonlinear extraction of microbubble signals typically involves multi-pulse acquisitions, such as amplitude modulation (AM), where two consecutive pulses …
Deep Learning of Liver Contrast-Enhanced Ultrasound to Predict ...
This study aimed to develop a deep convolutional neural network (DCNN) model based on contrast-enhanced ultrasound (CEUS) to predict MVI, and thus to predict prognosis in patients with HCC. …
Deep learning model based on contrast-enhanced ultrasound for ...
Preoperative biopsy to determine VETC status in HCC patients is limited. The contrast-enhanced DL model provides a non-invasive tool for the prediction of VETC-HCC. The proposed deep-learning …
Deep Learning in Medical Ultrasound Analysis: A Review - ScienceDirect
Deep learning, which is a branch of machine learning, is considered to be a representation learning approach that can directly process and automatically learn mid-level and high-level abstract features …
Deep Learning-Based Medical Ultrasound Image and Video …
The intricate imaging structures, artifacts, and noise present in ultrasound images and videos pose significant challenges for accurate segmentation. Deep learning has recently emerged as a …
Improving Breast Cancer Diagnosis in Ultrasound Images Using Deep ...
Materials and Methods: In this study, we proposed a feature fusion-based deep learning model for classifying benign and malignant lesions in ultrasound images. The model leverages advanced …