395 related articles for article (PubMed ID: 31583870)
1. Added Value of Bone Suppression Image in the Detection of Subtle Lung Lesions on Chest Radiographs with Regard to Reader's Expertise.
Hong GS; Do KH; Lee CW
J Korean Med Sci; 2019 Oct; 34(38):e250. PubMed ID: 31583870
[TBL] [Abstract][Full Text] [Related]
2. Improved detection of focal pneumonia by chest radiography with bone suppression imaging.
Li F; Engelmann R; Pesce L; Armato SG; Macmahon H
Eur Radiol; 2012 Dec; 22(12):2729-35. PubMed ID: 22763504
[TBL] [Abstract][Full Text] [Related]
3. Bone suppressed images improve radiologists' detection performance for pulmonary nodules in chest radiographs.
Schalekamp S; van Ginneken B; Meiss L; Peters-Bax L; Quekel LG; Snoeren MM; Tiehuis AM; Wittenberg R; Karssemeijer N; Schaefer-Prokop CM
Eur J Radiol; 2013 Dec; 82(12):2399-405. PubMed ID: 24113431
[TBL] [Abstract][Full Text] [Related]
4. Computer-aided detection of lung cancer on chest radiographs: effect on observer performance.
de Hoop B; De Boo DW; Gietema HA; van Hoorn F; Mearadji B; Schijf L; van Ginneken B; Prokop M; Schaefer-Prokop C
Radiology; 2010 Nov; 257(2):532-40. PubMed ID: 20807851
[TBL] [Abstract][Full Text] [Related]
5. Detectability of pulmonary nodules on chest radiographs: bone suppression versus standard technique with single versus dual monitors for visualization.
Endo K; Kaneko A; Horiuchi Y; Kasuga N; Ishizaki U; Sakai S
Jpn J Radiol; 2020 Jul; 38(7):676-682. PubMed ID: 32198572
[TBL] [Abstract][Full Text] [Related]
6. Effectiveness of bone suppression imaging in the diagnosis of tuberculosis from chest radiographs in Vietnam: An observer study.
Kodama N; Loc TV; Hai PT; Cong NV; Katsuhara S; Kasai S; Sheikh A
Clin Imaging; 2018; 51():196-201. PubMed ID: 29860192
[TBL] [Abstract][Full Text] [Related]
7. Deep learning in chest radiography: Detection of findings and presence of change.
Singh R; Kalra MK; Nitiwarangkul C; Patti JA; Homayounieh F; Padole A; Rao P; Putha P; Muse VV; Sharma A; Digumarthy SR
PLoS One; 2018; 13(10):e0204155. PubMed ID: 30286097
[TBL] [Abstract][Full Text] [Related]
8. Artificial intelligence-supported lung cancer detection by multi-institutional readers with multi-vendor chest radiographs: a retrospective clinical validation study.
Ueda D; Yamamoto A; Shimazaki A; Walston SL; Matsumoto T; Izumi N; Tsukioka T; Komatsu H; Inoue H; Kabata D; Nishiyama N; Miki Y
BMC Cancer; 2021 Oct; 21(1):1120. PubMed ID: 34663260
[TBL] [Abstract][Full Text] [Related]
9. Diagnostic impact of digital tomosynthesis in oncologic patients with suspected pulmonary lesions on chest radiography.
Quaia E; Baratella E; Poillucci G; Gennari AG; Cova MA
Eur Radiol; 2016 Aug; 26(8):2837-44. PubMed ID: 26628064
[TBL] [Abstract][Full Text] [Related]
10. Comparison of Baseline, Bone-Subtracted, and Enhanced Chest Radiographs for Detection of Pneumothorax.
Homayounieh F; Digumarthy SR; Febbo JA; Garrana S; Nitiwarangkul C; Singh R; Khera RD; Gilman M; Kalra MK
Can Assoc Radiol J; 2021 Aug; 72(3):519-524. PubMed ID: 32186414
[TBL] [Abstract][Full Text] [Related]
11. Comparison of conventional chest x ray with a novel projection technique for ultra-low dose CT.
Carey S; Kandel S; Farrell C; Kavanagh J; Chung T; Hamilton W; Rogalla P
Med Phys; 2021 Jun; 48(6):2809-2815. PubMed ID: 32181495
[TBL] [Abstract][Full Text] [Related]
12. Value of bone suppression software in chest radiographs for improving image quality and reducing radiation dose.
Hong GS; Do KH; Son AY; Jo KW; Kim KP; Yun J; Lee CW
Eur Radiol; 2021 Jul; 31(7):5160-5171. PubMed ID: 33439320
[TBL] [Abstract][Full Text] [Related]
13. Lung nodule CAD software as a second reader: a multicenter study.
White CS; Pugatch R; Koonce T; Rust SW; Dharaiya E
Acad Radiol; 2008 Mar; 15(3):326-33. PubMed ID: 18280930
[TBL] [Abstract][Full Text] [Related]
14. Computer-Aided Detection of Seven Chest Pathologies on Standard Posteroanterior Chest X-Rays Compared to Radiologists Reading Dual-Energy Subtracted Radiographs.
Fischer G; De Silvestro A; Müller M; Frauenfelder T; Martini K
Acad Radiol; 2022 Aug; 29(8):e139-e148. PubMed ID: 34706849
[TBL] [Abstract][Full Text] [Related]
15. Digital tomosynthesis of the thorax: the influence of respiratory motion artifacts on lung nodule detection.
Kim SM; Chung MJ; Lee KS; Kang H; Song IY; Lee EJ; Hwang HS
Acta Radiol; 2013 Jul; 54(6):634-9. PubMed ID: 23528563
[TBL] [Abstract][Full Text] [Related]
16. AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset.
Yoo H; Lee SH; Arru CD; Doda Khera R; Singh R; Siebert S; Kim D; Lee Y; Park JH; Eom HJ; Digumarthy SR; Kalra MK
Eur Radiol; 2021 Dec; 31(12):9664-9674. PubMed ID: 34089072
[TBL] [Abstract][Full Text] [Related]
17. Bone Suppression on Chest Radiographs for Pulmonary Nodule Detection: Comparison between a Generative Adversarial Network and Dual-Energy Subtraction.
Bae K; Oh DY; Yun ID; Jeon KN
Korean J Radiol; 2022 Jan; 23(1):139-149. PubMed ID: 34983100
[TBL] [Abstract][Full Text] [Related]
18. Improved detection of subtle lung nodules by use of chest radiographs with bone suppression imaging: receiver operating characteristic analysis with and without localization.
Li F; Hara T; Shiraishi J; Engelmann R; MacMahon H; Doi K
AJR Am J Roentgenol; 2011 May; 196(5):W535-41. PubMed ID: 21512042
[TBL] [Abstract][Full Text] [Related]
19. Added Value of Ultra-low-dose Computed Tomography, Dose Equivalent to Chest X-Ray Radiography, for Diagnosing Chest Pathology.
Kroft LJM; van der Velden L; Girón IH; Roelofs JJH; de Roos A; Geleijns J
J Thorac Imaging; 2019 May; 34(3):179-186. PubMed ID: 30870305
[TBL] [Abstract][Full Text] [Related]
20. Bone suppression increases the visibility of invasive pulmonary aspergillosis in chest radiographs.
Schalekamp S; van Ginneken B; van den Berk IA; Hartmann IJ; Snoeren MM; Odink AE; van Lankeren W; Pegge SA; Schijf LJ; Karssemeijer N; Schaefer-Prokop CM
PLoS One; 2014; 9(10):e108551. PubMed ID: 25279774
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
