A review on segmentation of positron emission tomography images
Abstract Positron Emission Tomography (PET), a non-invasive functional imaging method at
the molecular level, images the distribution of biologically targeted radiotracers with high …
the molecular level, images the distribution of biologically targeted radiotracers with high …
A survey of graph cuts/graph search based medical image segmentation
X Chen, L Pan - IEEE reviews in biomedical engineering, 2018 - ieeexplore.ieee.org
Medical image segmentation is a fundamental and challenging problem for analyzing
medical images. Among different existing medical image segmentation methods, graph …
medical images. Among different existing medical image segmentation methods, graph …
Deep learning-based image segmentation on multimodal medical imaging
Multimodality medical imaging techniques have been increasingly applied in clinical
practice and research studies. Corresponding multimodal image analysis and ensemble …
practice and research studies. Corresponding multimodal image analysis and ensemble …
HyperDense-Net: a hyper-densely connected CNN for multi-modal image segmentation
Recently, dense connections have attracted substantial attention in computer vision
because they facilitate gradient flow and implicit deep supervision during training …
because they facilitate gradient flow and implicit deep supervision during training …
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 …
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 …
Adaptive rectification based adversarial network with spectrum constraint for high-quality PET image synthesis
Positron emission tomography (PET) is a typical nuclear imaging technique, which can
provide crucial functional information for early brain disease diagnosis. Generally, clinically …
provide crucial functional information for early brain disease diagnosis. Generally, clinically …
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 …
Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method
X Zhou, R Takayama, S Wang, T Hara… - Medical …, 2017 - Wiley Online Library
Purpose We propose a single network trained by pixel‐to‐label deep learning to address
the general issue of automatic multiple organ segmentation in three‐dimensional (3D) …
the general issue of automatic multiple organ segmentation in three‐dimensional (3D) …
Classification and evaluation strategies of auto‐segmentation approaches for PET: Report of AAPM task group No. 211
Purpose The purpose of this educational report is to provide an overview of the present state‐
of‐the‐art PET auto‐segmentation (PET‐AS) algorithms and their respective validation, with …
of‐the‐art PET auto‐segmentation (PET‐AS) algorithms and their respective validation, with …