Value of 18F-FDG PET/CT radiomic features to distinguish solitary lung adenocarcinoma from tuberculosis
Y Hu, X Zhao, J Zhang, J Han, M Dai - European Journal of Nuclear …, 2021 - Springer
Purpose To develop a predictive model by 18 F-FDG PET/CT radiomic features and to
validate the predictive value of the model for distinguishing solitary lung adenocarcinoma …
validate the predictive value of the model for distinguishing solitary lung adenocarcinoma …
Use of radiomics based on 18F-FDG PET/CT and machine learning methods to aid clinical decision-making in the classification of solitary pulmonary lesions: an …
Y Zhou, X Ma, T Zhang, J Wang, T Zhang… - European journal of …, 2021 - Springer
Purpose This study was designed and performed to assess the ability of 18 F-
fluorodeoxyglucose (FDG) positron emission tomography (PET) and computed tomography …
fluorodeoxyglucose (FDG) positron emission tomography (PET) and computed tomography …
Development of a radiomics prediction model for histological type diagnosis in solitary pulmonary nodules: the combination of CT and FDG PET
M Yan, W Wang - Frontiers in Oncology, 2020 - frontiersin.org
Purpose To develop a diagnostic model for histological subtypes in lung cancer combined
CT and FDG PET. Methods Machine learning binary and four class classification of a cohort …
CT and FDG PET. Methods Machine learning binary and four class classification of a cohort …
Machine learning based on clinico-biological features integrated 18F-FDG PET/CT radiomics for distinguishing squamous cell carcinoma from adenocarcinoma of …
C Ren, J Zhang, M Qi, J Zhang, Y Zhang… - European journal of …, 2021 - Springer
Purpose To develop and validate a clinico-biological features and 18 F-fluorodeoxyglucose
(FDG) positron emission tomography/computed tomography (PET/CT) radiomic-based …
(FDG) positron emission tomography/computed tomography (PET/CT) radiomic-based …
[HTML][HTML] Diagnostic performance of machine learning models based on 18F-FDG PET/CT radiomic features in the classification of solitary pulmonary nodules
YS Salihoğlu, RU Erdemir, BA Püren… - Molecular Imaging …, 2022 - ncbi.nlm.nih.gov
Objectives: This study aimed to evaluate the ability of 18 fluorine-fluorodeoxyglucose (18 F-
FDG) positron emission tomography/computed tomography (PET/CT) radiomic features …
FDG) positron emission tomography/computed tomography (PET/CT) radiomic features …
Potential feature exploration and model development based on 18F-FDG PET/CT images for differentiating benign and malignant lung lesions
Purpose The study is to explore potential features and develop classification models for
distinguishing benign and malignant lung lesions based on CT-radiomics features and PET …
distinguishing benign and malignant lung lesions based on CT-radiomics features and PET …
Differentiation of focal organising pneumonia and peripheral adenocarcinoma in solid lung lesions using thin-section CT-based radiomics
T Zhang, M Yuan, Y Zhong, YD Zhang, H Li, JF Wu… - Clinical radiology, 2019 - Elsevier
Aim To evaluate the predictive role of radiomics based on computed tomography (CT) in
discriminating focal organising pneumonia (FOP) from peripheral lung adenocarcinoma …
discriminating focal organising pneumonia (FOP) from peripheral lung adenocarcinoma …
Evaluation of the diagnostic efficacy of 18F‐Fluorine‐2‐Deoxy‐D‐Glucose PET/CT for lung cancer and pulmonary tuberculosis in a Tuberculosis‐endemic Country
A Niyonkuru, X Chen, KH Bakari… - Cancer …, 2020 - Wiley Online Library
Objective To determine the diagnostic efficacy of 18F‐FDG PET/CT in distinguishing
between pulmonary tuberculosis (PTB) and lung cancer in solitary pulmonary nodule (SPN) …
between pulmonary tuberculosis (PTB) and lung cancer in solitary pulmonary nodule (SPN) …
Value of Shape and Texture Features from 18F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental …
In this paper, we investigate the role of shape and texture features from 18 F-FDG PET/CT to
discriminate between benign and malignant solitary pulmonary nodules. To this end, we …
discriminate between benign and malignant solitary pulmonary nodules. To this end, we …
A machine-learning approach using PET-based radiomics to predict the histological subtypes of lung cancer
SH Hyun, MS Ahn, YW Koh, SJ Lee - Clinical nuclear medicine, 2019 - journals.lww.com
Purpose We sought to distinguish lung adenocarcinoma (ADC) from squamous cell
carcinoma using a machine-learning algorithm with PET-based radiomic features. Methods …
carcinoma using a machine-learning algorithm with PET-based radiomic features. Methods …
相关搜索
- solitary lung adenocarcinoma
- radiomic features diagnostic performance
- peripheral adenocarcinoma lung lesions
- adenocarcinoma of lung machine learning
- adenocarcinoma of lung cell carcinoma
- lung cancer pulmonary tuberculosis
- peripheral adenocarcinoma organising pneumonia
- lung cancer histological subtypes
- lung cancer diagnostic efficacy
- organising pneumonia lung lesions