Liver vessels segmentation using a hybrid geometrical moments/graph cuts method
S Esneault, C Lafon… - IEEE Transactions on …, 2009 - ieeexplore.ieee.org
This paper describes a fast and fully automatic method for liver vessel segmentation on
computerized tomography scan preoperative images. The basis of this method is the …
computerized tomography scan preoperative images. The basis of this method is the …
The domain knowledge based graph-cut model for liver CT segmentation
Y Chen, Z Wang, J Hu, W Zhao, Q Wu - Biomedical Signal Processing and …, 2012 - Elsevier
In this paper, we present a semi-supervised approach for liver segmentation from computed
tomography (CT) scans, which is based on the graph cut model integrated with domain …
tomography (CT) scans, which is based on the graph cut model integrated with domain …
Liver tumour segmentation using contrast-enhanced multi-detector CT data: performance benchmarking of three semiautomated methods
Objective Automatic tumour segmentation and volumetry is useful in cancer staging and
treatment outcome assessment. This paper presents a performance benchmarking study on …
treatment outcome assessment. This paper presents a performance benchmarking study on …
Blood vessel‐based liver segmentation using the portal phase of an abdominal CT dataset
Purpose: Blood vessel (BV) information can be used to guide body organ segmentation on
computed tomography (CT) imaging. The proposed method uses abdominal BVs (ABVs) to …
computed tomography (CT) imaging. The proposed method uses abdominal BVs (ABVs) to …
[HTML][HTML] Adaptive Evolutionary Optimization of Deep Learning Architectures for Focused Liver Ultrasound Image Segmentation
A Zifan, K Zhao, M Lee, Z Peng, LJ Roney, S Pai… - Diagnostics, 2025 - mdpi.com
Background: Liver ultrasound segmentation is challenging due to low image quality and
variability. While deep learning (DL) models have been widely applied for medical …
variability. While deep learning (DL) models have been widely applied for medical …
Spatially adaptive active contours: a semi-automatic tumor segmentation framework
Purpose Tumor segmentation constitutes a crucial step in simulating cancer growth and
response to therapy. Incorporation of imaging data individualizes the simulation and assists …
response to therapy. Incorporation of imaging data individualizes the simulation and assists …
Region and boundary feature estimation on ultrasound images using moment invariants
K Wu, H Shu, JL Dillenseger - Computer methods and programs in …, 2014 - Elsevier
In ultrasound images, tissues are characterized by their speckle texture. Moment-based
techniques have proven their ability to capture texture features. However, in ultrasound …
techniques have proven their ability to capture texture features. However, in ultrasound …
Liver segmentation in CT images for intervention using a graph-cut based model
Y Chen, W Zhao, Q Wu, Z Wang, J Hu - … Imaging. Computational and …, 2012 - Springer
Liver segmentation in computerized tomography (CT) images has been widely studied in
recent years, of which the graph cut models demonstrate a great potential with the …
recent years, of which the graph cut models demonstrate a great potential with the …
Novel image processing and deep learning methods for head and neck cancer delineation from MRI data
B Zhao - 2022 - stax.strath.ac.uk
Intensity modulated radiation treatment aims to achieve accurate treatment of cancer without
introducing damage and side effects to organs at risk (OAR). Development of medical …
introducing damage and side effects to organs at risk (OAR). Development of medical …
改进的肝脏软组织分割算法及实时绘制
康飞龙， 杨杰 - 高技术通讯(中文), 2012 - hitech863.com
提出了一种基于Graph Cut 算法的高精度CT 肝脏软组织分割算法, 并利用开放运算语言(
OpenCL) 实现了肝脏软组织实时高效绘制. 这种改进的Graph Cut 算法分割准确度高 …
OpenCL) 实现了肝脏软组织实时高效绘制. 这种改进的Graph Cut 算法分割准确度高 …