A review on segmentation of positron emission tomography images

B Foster, U Bagci, A Mansoor, Z Xu… - Computers in biology and …, 2014 - Elsevier
Abstract Positron Emission Tomography (PET), a non-invasive functional imaging method at
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 …

[HTML][HTML] Head and neck tumor segmentation in PET/CT: the HECKTOR challenge

V Oreiller, V Andrearczyk, M Jreige, S Boughdad… - Medical image …, 2022 - Elsevier
This paper relates the post-analysis of the first edition of the HEad and neCK TumOR
(HECKTOR) challenge. This challenge was held as a satellite event of the 23rd International …

HyperDense-Net: a hyper-densely connected CNN for multi-modal image segmentation

J Dolz, K Gopinath, J Yuan, H Lombaert… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Recently, dense connections have attracted substantial attention in computer vision
because they facilitate gradient flow and implicit deep supervision during training …

Co-learning feature fusion maps from PET-CT images of lung cancer

A Kumar, M Fulham, D Feng… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The analysis of multi-modality positron emission tomography and computed tomography
(PET-CT) images for computer-aided diagnosis applications (eg, detection and …

Multimodal spatial attention module for targeting multimodal PET-CT lung tumor segmentation

X Fu, L Bi, A Kumar, M Fulham… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
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 …

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 …

Liver CT sequence segmentation based with improved U-Net and graph cut

Z Liu, YQ Song, VS Sheng, L Wang, R Jiang… - Expert Systems with …, 2019 - Elsevier
Liver segmentation has always been the focus of researchers because it plays an important
role in medical diagnosis. However, under the condition of low contrast between a liver and …

Classification and evaluation strategies of auto‐segmentation approaches for PET: Report of AAPM task group No. 211

M Hatt, JA Lee, CR Schmidtlein, IE Naqa… - Medical …, 2017 - Wiley Online Library
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 …

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 …