Automatic lung segmentation in low-dose chest CT scans using convolutional deep and wide network (CDWN)
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3877-3
Abstract: Computed tomography (CT) imaging is the preferred imaging modality for diagnosing lung-related complaints. Automatic lung segmentation is the most common prerequisite to develop a computerized diagnosis system for analyzing chest CT images. In this paper,… read more here.
Keywords: deep wide; segmentation; lung segmentation; automatic lung ... See more keywords
Fully automated lung segmentation from chest radiographs using SLICO superpixels
Sign Up to like & getrecommendations! Published in 2018 at "Analog Integrated Circuits and Signal Processing"
DOI: 10.1007/s10470-018-1153-1
Abstract: This project aims to create a computer-aided diagnosis (CAD) system that can be used to identify tuberculosis (TB) from chest radiographs (CXRs) and, in particular, to observe the progress of the disease where patients have… read more here.
Keywords: automated lung; fully automated; chest radiographs; lung segmentation ... See more keywords
Hybrid Automatic Lung Segmentation on Chest CT Scans
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DOI: 10.1109/access.2020.2987925
Abstract: Accurate lung segmentation in chest Computed Tomography (CT) scans is a challenging problem because of variations in lung volume shape, susceptibility to partial volume effects that affect thin antero-posterior junction lines, and lack of contrast… read more here.
Keywords: segmentation chest; lung; lung segmentation; method ... See more keywords
TAE-Seg: Generalized Lung Segmentation via Tilewise AutoEncoder Enhanced Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2022.3217870
Abstract: Computer-aided diagnosis based on deep learning is progressively deployed for the analysis of medical images, yet poor robustness and generalization of the model pose a challenge for clinical application. In addition, the lack of large… read more here.
Keywords: tilewise autoencoder; segmentation; generalized lung; model ... See more keywords
Research on CT Lung Segmentation Method of Preschool Children based on Traditional Image Processing and ResUnet
Sign Up to like & getrecommendations! Published in 2022 at "Computational and Mathematical Methods in Medicine"
DOI: 10.1155/2022/7321330
Abstract: Lung segmentation using computed tomography (CT) images is important for diagnosing various lung diseases. Currently, no lung segmentation method has been developed for assessing the CT images of preschool children, which may differ from those… read more here.
Keywords: segmentation method; lung segmentation; preschool children; segmentation ... See more keywords
Automated Lung Segmentation from Computed Tomography Images of Normal and COVID-19 Pneumonia Patients
Sign Up to like & getrecommendations! Published in 2022 at "Iranian Journal of Medical Sciences"
DOI: 10.30476/ijms.2022.90791.2178
Abstract: Background: Automated image segmentation is an essential step in quantitative image analysis. This study assesses the performance of a deep learning-based model for lung segmentation from computed tomography (CT) images of normal and COVID-19 patients.… read more here.
Keywords: covid patients; normal covid; segmentation; model ... See more keywords
Anterior Mediastinal Lesion Segmentation Based on Two-Stage 3D ResUNet With Attention Gates and Lung Segmentation
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Oncology"
DOI: 10.3389/fonc.2020.618357
Abstract: Objectives Anterior mediastinal disease is a common disease in the chest. Computed tomography (CT), as an important imaging technology, is widely used in the diagnosis of mediastinal diseases. Doctors find it difficult to distinguish lesions… read more here.
Keywords: anterior mediastinal; image; two stage; segmentation ... See more keywords
Automatic Lung Segmentation and Quantification of Aeration in Computed Tomography of the Chest Using 3D Transfer Learning
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Physiology"
DOI: 10.3389/fphys.2021.725865
Abstract: Background Identification of lung parenchyma on computer tomographic (CT) scans in the research setting is done semi-automatically and requires cumbersome manual correction. This is especially true in pathological conditions, hindering the clinical application of aeration… read more here.
Keywords: lung; transfer learning; lung segmentation; aeration ... See more keywords