Cargando…

Classification and Segmentation Algorithm in Benign and Malignant Pulmonary Nodules under Different CT Reconstruction

METHODS: The imaging data of 55 patients with chest CT plain scan in the Xuancheng People's Hospital were collected retrospectively. The data of each patient included lung window reconstruction, mediastinum reconstruction, and bone window reconstruction. The depth neural network and 3D convolut...

Descripción completa

Detalles Bibliográficos
Autores principales:	Lu, Zhiqian, Long, Feixiang, He, Xiaodong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Hindawi 2022
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9050279/ https://www.ncbi.nlm.nih.gov/pubmed/35495882 http://dx.doi.org/10.1155/2022/3490463

Ejemplares similares

A novel fusion algorithm for benign-malignant lung nodule classification on CT images
por: Ma, Ling, et al.
Publicado: (2023)

Anatomy packing with hierarchical segments: an algorithm for segmentation of pulmonary nodules in CT images
por: Tsou, Chi-Hsuan, et al.
Publicado: (2015)

Diagnostic Value of Artificial Intelligence Based on CT Image in Benign and Malignant Pulmonary Nodules
por: Du, Wang, et al.
Publicado: (2022)

Pulmonary Multiple Nodules: Benign or Malignant?
por: Liu, Jing, et al.
Publicado: (2018)

Application of CT Postprocessing Reconstruction Technique in Differential Diagnosis of Benign and Malignant Solitary Pulmonary Nodules and Analysis of Risk Factors
por: Chen, Xiaolong, et al.
Publicado: (2022)

Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign
por: Xu, Hang, et al.
Publicado: (2023)

Retracted: Application of CT Postprocessing Reconstruction Technique in Differential Diagnosis of Benign and Malignant Solitary Pulmonary Nodules and Analysis of Risk Factors
por: Methods in Medicine, Computational and Mathematical
Publicado: (2023)

Can Spectral CT Imaging Improve the Differentiation between Malignant and Benign Solitary Pulmonary Nodules?
por: Zhang, Ying, et al.
Publicado: (2016)

Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans
por: Hendrix, Ward, et al.
Publicado: (2023)

Benign disease prone to be misdiagnosed as malignant pulmonary nodules: Minute meningothelioid nodules
por: Peng, Xiao‐Xiao, et al.
Publicado: (2019)

An Appraisal of Lung Nodules Automatic Classification Algorithms for CT Images
por: Wang, Xinqi, et al.
Publicado: (2019)

A classification of pulmonary nodules by CT scan
por: Bellomi, M
Publicado: (2012)

The value of radiomics based on dual-energy CT for differentiating benign from malignant solitary pulmonary nodules
por: Liang, Gao, et al.
Publicado: (2022)

Predictive model for the diagnosis of benign/malignant small pulmonary nodules
por: Chen, Weisong, et al.
Publicado: (2020)

Liquid biopsies to distinguish malignant from benign pulmonary nodules
por: Tao, Rui, et al.
Publicado: (2021)

Pulmonary Benign Ground-Glass Nodules: CT Features and Pathological Findings
por: Li, Wang-Jia, et al.
Publicado: (2021)

Artificial Intelligence Algorithm-Based Feature Extraction of Computed Tomography Images and Analysis of Benign and Malignant Pulmonary Nodules
por: Gao, Yuantong, et al.
Publicado: (2022)

Can Dynamic Imaging, Using (18)F-FDG PET/CT and CT Perfusion Differentiate Between Benign and Malignant Pulmonary Nodules?
por: Marin, Aleksander, et al.
Publicado: (2021)

Diagnostic value of peripheral blood eosinophils for benign and malignant pulmonary nodule
por: Xiu, Jiawei, et al.
Publicado: (2023)

Serum lncRNA THRIL predicts benign and malignant pulmonary nodules and promotes the progression of pulmonary malignancies
por: Chen, Xinyu, et al.
Publicado: (2023)

Deep-Learning Model of ResNet Combined with CBAM for Malignant–Benign Pulmonary Nodules Classification on Computed Tomography Images
por: Zhang, Yanfei, et al.
Publicado: (2023)

Value of Whole-Thyroid CT-Based Radiomics in Predicting Benign and Malignant Thyroid Nodules
por: Xu, Han, et al.
Publicado: (2022)

Relation between nodule size and (18)F-FDG-PET SUV for malignant and benign pulmonary nodules.
por: Khalaf, Majid, et al.
Publicado: (2008)

Differentiation between Benign and Malignant Solid Thyroid Nodules Using an US Classification System
por: Lee, Young Hun, et al.
Publicado: (2011)

Application of Texture Analysis Method for Classification of Benign and Malignant Thyroid Nodules in Ultrasound Images
por: Abbasian Ardakani, Ali, et al.
Publicado: (2015)

Classification of Benign and Malignant Lung Nodules Based on Deep Convolutional Network Feature Extraction
por: Lv, Enhui, et al.
Publicado: (2021)

Proteomic analysis of plasma exosomes to differentiate malignant from benign pulmonary nodules
por: Kuang, Muyu, et al.
Publicado: (2019)

Impact of CT reconstruction algorithm on auto‐segmentation performance
por: Miller, Claudia, et al.
Publicado: (2019)

The effect of the reconstruction algorithm for the pulmonary nodule detection under the metal artifact caused by a pacemaker
por: Kikuchi, Noriko, et al.
Publicado: (2020)

Spectral CT Analysis of Solitary Pulmonary Nodules for Differentiating Malignancy from Benignancy: The Value of Iodine Concentration Spatial Distribution Difference
por: Wu, Linyu, et al.
Publicado: (2018)

Benign‐malignant classification of pulmonary nodules by low‐dose spiral computerized tomography and clinical data with machine learning in opportunistic screening
por: Zheng, Yansong, et al.
Publicado: (2023)

Benign and malignant thyroid nodules with autoimmune thyroiditis
por: Kassi, Georgia N., et al.
Publicado: (2022)

Radiomics as a non-invasive adjunct to Chest CT in distinguishing benign and malignant lung nodules
por: Selvam, Minmini, et al.
Publicado: (2023)

VGG19 Network Assisted Joint Segmentation and Classification of Lung Nodules in CT Images
por: Khan, Muhammad Attique, et al.
Publicado: (2021)

Quantitative analysis of chest MRI images for benign malignant diagnosis of pulmonary solid nodules
por: Yang, Bin, et al.
Publicado: (2023)

Meta analysis of the diagnostic value of circulating miRNA in benign and malignant pulmonary nodules
por: Hong, Ziqiang, et al.
Publicado: (2023)

Factors associated with overdiagnosis of benign pulmonary nodules as malignancy: a retrospective cohort study
por: Duan, Xirui, et al.
Publicado: (2023)

Baseline whole-lung CT features deriving from deep learning and radiomics: prediction of benign and malignant pulmonary ground-glass nodules
por: Huang, Wenjun, et al.
Publicado: (2023)

A general approach for automatic segmentation of pneumonia, pulmonary nodule, and tuberculosis in CT images
por: Wang, Lu, et al.
Publicado: (2023)

Machine Learning Model of ResNet50-Ensemble Voting for Malignant–Benign Small Pulmonary Nodule Classification on Computed Tomography Images
por: Li, Weiming, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_m1tcu6ddfbmn8s0sc17g8qsrsh