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 …
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 …
Recently, dense connections have attracted substantial attention in computer vision because they facilitate gradient flow and implicit deep supervision during training …
The analysis of multi-modality positron emission tomography and computed tomography (PET-CT) images for computer-aided diagnosis applications (eg, detection and …
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 …
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 …
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 …
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 …
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 …