130 related articles for article (PubMed ID: 28231320)
21. Effects of Iterative Reconstruction Algorithms on Computer-assisted Detection (CAD) Software for Lung Nodules in Ultra-low-dose CT for Lung Cancer Screening.
Nomura Y; Higaki T; Fujita M; Miki S; Awaya Y; Nakanishi T; Yoshikawa T; Hayashi N; Awai K
Acad Radiol; 2017 Feb; 24(2):124-130. PubMed ID: 27986507
[TBL] [Abstract][Full Text] [Related]
22. Ultralow-dose chest computed tomography for pulmonary nodule detection: first performance evaluation of single energy scanning with spectral shaping.
Gordic S; Morsbach F; Schmidt B; Allmendinger T; Flohr T; Husarik D; Baumueller S; Raupach R; Stolzmann P; Leschka S; Frauenfelder T; Alkadhi H
Invest Radiol; 2014 Jul; 49(7):465-73. PubMed ID: 24598443
[TBL] [Abstract][Full Text] [Related]
23. Detection and size measurements of pulmonary nodules in ultra-low-dose CT with iterative reconstruction compared to low dose CT.
Sui X; Meinel FG; Song W; Xu X; Wang Z; Wang Y; Jin Z; Chen J; Vliegenthart R; Schoepf UJ
Eur J Radiol; 2016 Mar; 85(3):564-70. PubMed ID: 26860668
[TBL] [Abstract][Full Text] [Related]
24. Vessel suppressed chest Computed Tomography for semi-automated volumetric measurements of solid pulmonary nodules.
Milanese G; Eberhard M; Martini K; Vittoria De Martini I; Frauenfelder T
Eur J Radiol; 2018 Apr; 101():97-102. PubMed ID: 29571809
[TBL] [Abstract][Full Text] [Related]
25. Ultrafast 3D balanced steady-state free precession MRI of the lung: Assessment of anatomic details in comparison to low-dose CT.
Heye T; Sommer G; Miedinger D; Bremerich J; Bieri O
J Magn Reson Imaging; 2015 Sep; 42(3):602-9. PubMed ID: 25545835
[TBL] [Abstract][Full Text] [Related]
26. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy.
Li F; Aoyama M; Shiraishi J; Abe H; Li Q; Suzuki K; Engelmann R; Sone S; Macmahon H; Doi K
AJR Am J Roentgenol; 2004 Nov; 183(5):1209-15. PubMed ID: 15505279
[TBL] [Abstract][Full Text] [Related]
27. Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection.
Rubin GD; Lyo JK; Paik DS; Sherbondy AJ; Chow LC; Leung AN; Mindelzun R; Schraedley-Desmond PK; Zinck SE; Naidich DP; Napel S
Radiology; 2005 Jan; 234(1):274-83. PubMed ID: 15537839
[TBL] [Abstract][Full Text] [Related]
28. Commercially available computer-aided detection system for pulmonary nodules on thin-section images using 64 detectors-row CT: preliminary study of 48 cases.
Yanagawa M; Honda O; Yoshida S; Ono Y; Inoue A; Daimon T; Sumikawa H; Mihara N; Johkoh T; Tomiyama N; Nakamura H
Acad Radiol; 2009 Aug; 16(8):924-33. PubMed ID: 19394873
[TBL] [Abstract][Full Text] [Related]
29. JOURNAL CLUB: Computer-Aided Detection of Lung Nodules on CT With a Computerized Pulmonary Vessel Suppressed Function.
Lo SB; Freedman MT; Gillis LB; White CS; Mun SK
AJR Am J Roentgenol; 2018 Mar; 210(3):480-488. PubMed ID: 29336601
[TBL] [Abstract][Full Text] [Related]
30. Noise-optimized advanced image-based virtual monoenergetic imaging for improved visualization of lung cancer: Comparison with traditional virtual monoenergetic imaging.
Frellesen C; Kaup M; Wichmann JL; Hüsers K; Scholtz JE; Albrecht MH; Metzger SC; Bauer RW; Kerl JM; Lehnert T; Vogl TJ; Bodelle B
Eur J Radiol; 2016 Mar; 85(3):665-72. PubMed ID: 26860682
[TBL] [Abstract][Full Text] [Related]
31. Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images.
Jacobs C; van Rikxoort EM; Twellmann T; Scholten ET; de Jong PA; Kuhnigk JM; Oudkerk M; de Koning HJ; Prokop M; Schaefer-Prokop C; van Ginneken B
Med Image Anal; 2014 Feb; 18(2):374-84. PubMed ID: 24434166
[TBL] [Abstract][Full Text] [Related]
32. Volumetric quantification of lung nodules in CT with iterative reconstruction (ASiR and MBIR).
Chen B; Barnhart H; Richard S; Robins M; Colsher J; Samei E
Med Phys; 2013 Nov; 40(11):111902. PubMed ID: 24320435
[TBL] [Abstract][Full Text] [Related]
33. Assessment of prior image induced nonlocal means regularization for low-dose CT reconstruction: Change in anatomy.
Zhang H; Ma J; Wang J; Moore W; Liang Z
Med Phys; 2017 Sep; 44(9):e264-e278. PubMed ID: 28901622
[TBL] [Abstract][Full Text] [Related]
34. Solid, part-solid, or non-solid?: classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system.
Jacobs C; van Rikxoort EM; Scholten ET; de Jong PA; Prokop M; Schaefer-Prokop C; van Ginneken B
Invest Radiol; 2015 Mar; 50(3):168-73. PubMed ID: 25478740
[TBL] [Abstract][Full Text] [Related]
35. Influence of field of view size on image quality: ultra-high-resolution CT vs. conventional high-resolution CT.
Miyata T; Yanagawa M; Hata A; Honda O; Yoshida Y; Kikuchi N; Tsubamoto M; Tsukagoshi S; Uranishi A; Tomiyama N
Eur Radiol; 2020 Jun; 30(6):3324-3333. PubMed ID: 32072253
[TBL] [Abstract][Full Text] [Related]
36. Improved efficiency of CT interpretation using an automated lung nodule matching program.
Koo CW; Anand V; Girvin F; Wickstrom ML; Fantauzzi JP; Bogoni L; Babb JS; Ko JP
AJR Am J Roentgenol; 2012 Jul; 199(1):91-5. PubMed ID: 22733898
[TBL] [Abstract][Full Text] [Related]
37. Improving image quality of sparse-view lung tumor CT images with U-Net.
Ries A; Dorosti T; Thalhammer J; Sasse D; Sauter A; Meurer F; Benne A; Lasser T; Pfeiffer F; Schaff F; Pfeiffer D
Eur Radiol Exp; 2024 May; 8(1):54. PubMed ID: 38698099
[TBL] [Abstract][Full Text] [Related]
38. Ultra-Low-Dose CT of the Thorax Using Iterative Reconstruction: Evaluation of Image Quality and Radiation Dose Reduction.
Kim Y; Kim YK; Lee BE; Lee SJ; Ryu YJ; Lee JH; Chang JH
AJR Am J Roentgenol; 2015 Jun; 204(6):1197-202. PubMed ID: 26001228
[TBL] [Abstract][Full Text] [Related]
39. Iterative Reconstructions in Reduced-Dose CT: Which Type Ensures Diagnostic Image Quality in Young Oncology Patients?
Pauchard B; Higashigaito K; Lamri-Senouci A; Knebel JF; Berthold D; Verdun FR; Alkadhi H; Schmidt S
Acad Radiol; 2017 Sep; 24(9):1114-1124. PubMed ID: 28365232
[TBL] [Abstract][Full Text] [Related]
40. Comparison of image quality and visibility of normal and abnormal findings at submillisievert chest CT using filtered back projection, iterative model reconstruction (IMR) and iDose
Laqmani A; Avanesov M; Butscheidt S; Kurfürst M; Sehner S; Schmidt-Holtz J; Derlin T; Behzadi C; Nagel HD; Adam G; Regier M
Eur J Radiol; 2016 Nov; 85(11):1971-1979. PubMed ID: 27776648
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
