Practical utility of liver segmentation methods in clinical surgeries and interventions
Clinical imaging (eg, magnetic resonance imaging and computed tomography) is a crucial
adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate …
adjunct for clinicians, aiding in the diagnosis of diseases and planning of appropriate …
Anatomy-aided deep learning for medical image segmentation: a review
Deep learning (DL) has become widely used for medical image segmentation in recent
years. However, despite these advances, there are still problems for which DL-based …
years. However, despite these advances, there are still problems for which DL-based …
TPCNN: two-path convolutional neural network for tumor and liver segmentation in CT images using a novel encoding approach
A Aghamohammadi, R Ranjbarzadeh, F Naiemi… - Expert Systems with …, 2021 - Elsevier
Automatic liver and tumour segmentation in CT images are crucial in numerous clinical
applications, such as postoperative assessment, surgical planning, and pathological …
applications, such as postoperative assessment, surgical planning, and pathological …
Radiomics: a primer on high-throughput image phenotyping
Radiomics is a high-throughput approach to image phenotyping. It uses computer
algorithms to extract and analyze a large number of quantitative features from radiological …
algorithms to extract and analyze a large number of quantitative features from radiological …
[HTML][HTML] Deep learning for image-based liver analysis—A comprehensive review focusing on malignant lesions
Deep learning-based methods, in particular, convolutional neural networks and fully
convolutional networks are now widely used in the medical image analysis domain. The …
convolutional networks are now widely used in the medical image analysis domain. The …
Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid–enhanced MRI
Objectives To (1) develop a fully automated deep learning (DL) algorithm based on
gadoxetic acid–enhanced hepatobiliary phase (HBP) MRI and (2) compare the diagnostic …
gadoxetic acid–enhanced hepatobiliary phase (HBP) MRI and (2) compare the diagnostic …
A deep learning algorithm proposal to automatic pharyngeal airway detection and segmentation on CBCT images
Objectives This study aims to evaluate an automatic segmentation algorithm for pharyngeal
airway in cone‐beam computed tomography (CBCT) images using a deep learning artificial …
airway in cone‐beam computed tomography (CBCT) images using a deep learning artificial …
A deep residual attention-based U-Net with a biplane joint method for liver segmentation from CT scans
Y Chen, C Zheng, T Zhou, L Feng, L Liu, Q Zeng… - Computers in Biology …, 2023 - Elsevier
Liver tumours are diseases with high morbidity and high deterioration probabilities, and
accurate liver area segmentation from computed tomography (CT) scans is a prerequisite for …
accurate liver area segmentation from computed tomography (CT) scans is a prerequisite for …
Two-stage liver and tumor segmentation algorithm based on convolutional neural network
L Meng, Q Zhang, S Bu - Diagnostics, 2021 - mdpi.com
The liver is an essential metabolic organ of the human body, and malignant liver tumors
seriously affect and threaten human life. The segmentation algorithm for liver and liver …
seriously affect and threaten human life. The segmentation algorithm for liver and liver …
TD-Net: A hybrid end-to-end network for automatic liver tumor segmentation from CT images
S Di, YQ Zhao, M Liao, F Zhang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Liver tumor segmentation plays an essential role in diagnosis and treatment of
hepatocellular carcinoma or metastasis. However, accurate and automatic tumor …
hepatocellular carcinoma or metastasis. However, accurate and automatic tumor …