Co-learning feature fusion maps from PET-CT images of lung cancer
The analysis of multi-modality positron emission tomography and computed tomography
(PET-CT) images for computer-aided diagnosis applications (eg, detection and …
(PET-CT) images for computer-aided diagnosis applications (eg, detection and …
Recurrent feature fusion learning for multi-modality pet-ct tumor segmentation
Abstract Background and objective:[18f]-fluorodeoxyglucose (fdg) positron emission
tomography–computed tomography (pet-ct) is now the preferred imaging modality for …
tomography–computed tomography (pet-ct) is now the preferred imaging modality for …
A physics-guided modular deep-learning based automated framework for tumor segmentation in PET
KH Leung, W Marashdeh, R Wray… - Physics in Medicine …, 2020 - iopscience.iop.org
An important need exists for reliable positron emission tomography (PET) tumor-
segmentation methods for tasks such as PET-based radiation-therapy planning and reliable …
segmentation methods for tasks such as PET-based radiation-therapy planning and reliable …
Multimodal spatial attention module for targeting multimodal PET-CT lung tumor segmentation
Multimodal positron emission tomography-computed tomography (PET-CT) is used routinely
in the assessment of cancer. PET-CT combines the high sensitivity for tumor detection of …
in the assessment of cancer. PET-CT combines the high sensitivity for tumor detection of …
3D fully convolutional networks for co-segmentation of tumors on PET-CT images
Positron emission tomography and computed tomography (PET-CT) dual-modality imaging
provides critical diagnostic information in modern cancer diagnosis and therapy. Automated …
provides critical diagnostic information in modern cancer diagnosis and therapy. Automated …
Tumor co-segmentation in PET/CT using multi-modality fully convolutional neural network
X Zhao, L Li, W Lu, S Tan - Physics in Medicine & Biology, 2018 - iopscience.iop.org
Automatic tumor segmentation from medical images is an important step for computer-aided
cancer diagnosis and treatment. Recently, deep learning has been successfully applied to …
cancer diagnosis and treatment. Recently, deep learning has been successfully applied to …
Simultaneous cosegmentation of tumors in PET‐CT images using deep fully convolutional networks
Purpose To investigate the use and efficiency of 3‐D deep learning, fully convolutional
networks (DFCN) for simultaneous tumor cosegmentation on dual‐modality nonsmall cell …
networks (DFCN) for simultaneous tumor cosegmentation on dual‐modality nonsmall cell …
Deep learning for variational multimodality tumor segmentation in PET/CT
L Li, X Zhao, W Lu, S Tan - Neurocomputing, 2020 - Elsevier
Positron emission tomography/computed tomography (PET/CT) imaging can simultaneously
acquire functional metabolic information and anatomical information of the human body …
acquire functional metabolic information and anatomical information of the human body …
Automatic segmentation of head and neck tumors and nodal metastases in PET-CT scans
Radiomics, the prediction of disease characteristics using quantitative image biomarkers
from medical images, relies on expensive manual annotations of Regions of Interest (ROI) to …
from medical images, relies on expensive manual annotations of Regions of Interest (ROI) to …
FDGNet: A pair feature difference guided network for multimodal medical image fusion
G Zhang, R Nie, J Cao, L Chen, Y Zhu - Biomedical Signal Processing and …, 2023 - Elsevier
Most multimodal medical image fusion (MMIF) methods suffer from insufficient
complementary feature extraction and luminance degradation, such that the fused results …
complementary feature extraction and luminance degradation, such that the fused results …