155 related articles for article (PubMed ID: 36438275)
1. Investigation of small lung lesion detection for lung cancer screening in low dose FDG PET imaging by deep neural networks.
Guo H; Wu J; Xie Z; Tham IWK; Zhou L; Yan J
Front Public Health; 2022; 10():1047714. PubMed ID: 36438275
[TBL] [Abstract][Full Text] [Related]
2. Quantitative Accuracy and Lesion Detectability of Low-Dose
Schaefferkoetter JD; Yan J; Sjöholm T; Townsend DW; Conti M; Tam JK; Soo RA; Tham I
J Nucl Med; 2017 Mar; 58(3):399-405. PubMed ID: 27688481
[TBL] [Abstract][Full Text] [Related]
3.
Sibille L; Seifert R; Avramovic N; Vehren T; Spottiswoode B; Zuehlsdorff S; Schäfers M
Radiology; 2020 Feb; 294(2):445-452. PubMed ID: 31821122
[TBL] [Abstract][Full Text] [Related]
4. Performance Evaluation of a Deep Learning System for Differential Diagnosis of Lung Cancer With Conventional CT and FDG PET/CT Using Transfer Learning and Metadata.
Park YJ; Choi D; Choi JY; Hyun SH
Clin Nucl Med; 2021 Aug; 46(8):635-640. PubMed ID: 33883488
[TBL] [Abstract][Full Text] [Related]
5. Assessment of indeterminate pulmonary nodules detected in lung cancer screening: Diagnostic accuracy of FDG PET/CT.
Garcia-Velloso MJ; Bastarrika G; de-Torres JP; Lozano MD; Sanchez-Salcedo P; Sancho L; Nuñez-Cordoba JM; Campo A; Alcaide AB; Torre W; Richter JA; Zulueta JJ
Lung Cancer; 2016 Jul; 97():81-6. PubMed ID: 27237032
[TBL] [Abstract][Full Text] [Related]
6. PET/MR imaging in the detection and characterization of pulmonary lesions: technical and diagnostic evaluation in comparison to PET/CT.
Rauscher I; Eiber M; Fürst S; Souvatzoglou M; Nekolla SG; Ziegler SI; Rummeny EJ; Schwaiger M; Beer AJ
J Nucl Med; 2014 May; 55(5):724-9. PubMed ID: 24652827
[TBL] [Abstract][Full Text] [Related]
7. Automated detection of lung cancer at ultralow dose PET/CT by deep neural networks - Initial results.
Schwyzer M; Ferraro DA; Muehlematter UJ; Curioni-Fontecedro A; Huellner MW; von Schulthess GK; Kaufmann PA; Burger IA; Messerli M
Lung Cancer; 2018 Dec; 126():170-173. PubMed ID: 30527183
[TBL] [Abstract][Full Text] [Related]
8. Fluoro-deoxy-glucose positron emission tomography for evaluation of indeterminate lung nodules: assigning a probability of malignancy may be preferable to binary readings.
Kim SC; Machac J; Krynyckyi BR; Knesaurek K; Krellenstein D; Schultz B; Gribetz A; DePalo L; Teirstein A; Kim CK
Ann Nucl Med; 2008 Apr; 22(3):165-70. PubMed ID: 18498030
[TBL] [Abstract][Full Text] [Related]
9. Clinical significance of small pulmonary nodules with little or no 18F-FDG uptake on PET/CT images of patients with nonthoracic malignancies.
O JH; Yoo IeR; Kim SH; Sohn HS; Chung SK
J Nucl Med; 2007 Jan; 48(1):15-21. PubMed ID: 17204694
[TBL] [Abstract][Full Text] [Related]
10. Improving the detection of small lesions using a state-of-the-art time-of-flight PET/CT system and small-voxel reconstructions.
Koopman D; van Dalen JA; Lagerweij MC; Arkies H; de Boer J; Oostdijk AH; Slump CH; Jager PL
J Nucl Med Technol; 2015 Mar; 43(1):21-7. PubMed ID: 25613334
[TBL] [Abstract][Full Text] [Related]
11. Initial assessment of image quality for low-dose PET: evaluation of lesion detectability.
Schaefferkoetter JD; Yan J; Townsend DW; Conti M
Phys Med Biol; 2015 Jul; 60(14):5543-56. PubMed ID: 26134119
[TBL] [Abstract][Full Text] [Related]
12. Prediction of lung malignancy progression and survival with machine learning based on pre-treatment FDG-PET/CT.
Huang B; Sollee J; Luo YH; Reddy A; Zhong Z; Wu J; Mammarappallil J; Healey T; Cheng G; Azzoli C; Korogodsky D; Zhang P; Feng X; Li J; Yang L; Jiao Z; Bai HX
EBioMedicine; 2022 Aug; 82():104127. PubMed ID: 35810561
[TBL] [Abstract][Full Text] [Related]
13. Comparative Performance of ¹⁸F-FDG PET/MRI and ¹⁸F-FDG PET/CT in Detection and Characterization of Pulmonary Lesions in 121 Oncologic Patients.
Sawicki LM; Grueneisen J; Buchbender C; Schaarschmidt BM; Gomez B; Ruhlmann V; Wetter A; Umutlu L; Antoch G; Heusch P
J Nucl Med; 2016 Apr; 57(4):582-6. PubMed ID: 26742715
[TBL] [Abstract][Full Text] [Related]
14. A pilot study on lung cancer detection based on regional metabolic activity distribution in digital low-dose 18F-FDG PET.
Messerli M; Muehlematter UJ; Fassbind S; Franzen D; Ferraro DA; Huellner MW; Treyer V; Curioni-Fontecedro A; Burger IA
Br J Radiol; 2021 Mar; 94(1119):20200244. PubMed ID: 33529052
[TBL] [Abstract][Full Text] [Related]
15. A method to assess image quality for Low-dose PET: analysis of SNR, CNR, bias and image noise.
Yan J; Schaefferkoette J; Conti M; Townsend D
Cancer Imaging; 2016 Aug; 16(1):26. PubMed ID: 27565136
[TBL] [Abstract][Full Text] [Related]
16. Indeterminate lung nodules in cancer patients: pretest probability of malignancy and the role of 18F-FDG PET/CT.
Evangelista L; Panunzio A; Polverosi R; Pomerri F; Rubello D
AJR Am J Roentgenol; 2014 Mar; 202(3):507-14. PubMed ID: 24555586
[TBL] [Abstract][Full Text] [Related]
17. Hybrid PET/MRI in non-small cell lung cancer (NSCLC) and lung nodules-a literature review.
Dahlsgaard-Wallenius SE; Hildebrandt MG; Johansen A; Vilstrup MH; Petersen H; Gerke O; Høilund-Carlsen PF; Morsing A; Andersen TL
Eur J Nucl Med Mol Imaging; 2021 Feb; 48(2):584-591. PubMed ID: 32719914
[TBL] [Abstract][Full Text] [Related]
18. Narrow time-window dual-point 18F-FDG PET for the diagnosis of thoracic malignancy.
Conrad GR; Sinha P
Nucl Med Commun; 2003 Nov; 24(11):1129-37. PubMed ID: 14569166
[TBL] [Abstract][Full Text] [Related]
19. 18F-FSPG PET imaging for the evaluation of indeterminate pulmonary nodules.
Paez R; Shah C; Cords AJ; Muterspaugh A; Helton JE; Antic S; Eisenberg R; Chen H; Grogan EL; Manning HC; Walker RC; Massion PP
PLoS One; 2022; 17(3):e0265427. PubMed ID: 35294486
[TBL] [Abstract][Full Text] [Related]
20. Differentiation Between Malignant and Benign Pulmonary Nodules by Using Automated Three-Dimensional High-Resolution Representation Learning With Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography.
Lai YC; Wu KC; Tseng NC; Chen YJ; Chang CJ; Yen KY; Kao CH
Front Med (Lausanne); 2022; 9():773041. PubMed ID: 35372415
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
