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For: Li Q, Liang Y, Huang Q, Zong M, Berman B, Gavrielides MA, Schwartz LH, Zhao B, Petrick N. Volumetry of low-contrast liver lesions with CT: Investigation of estimation uncertainties in a phantom study. Med Phys 2017;43:6608. [PMID: 27908157 DOI: 10.1118/1.4967776] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]  Open
Number Cited by Other Article(s)
1
Imaging standardisation in metastatic colorectal cancer: A joint EORTC-ESOI-ESGAR expert consensus recommendation. Eur J Cancer 2022;176:193-206. [PMID: 36274570 DOI: 10.1016/j.ejca.2022.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 12/15/2022]
2
CT Volumetry of Convoluted Objects-A Simple Method Using Volume Averaging. ACTA ACUST UNITED AC 2021;7:120-129. [PMID: 33924342 PMCID: PMC8167628 DOI: 10.3390/tomography7020011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 03/31/2021] [Accepted: 04/08/2021] [Indexed: 11/17/2022]
3
Variability of quantitative measurements of metastatic liver lesions: a multi-radiation-dose-level and multi-reader comparison. Abdom Radiol (NY) 2021;46:226-236. [PMID: 32524151 DOI: 10.1007/s00261-020-02601-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 05/26/2020] [Indexed: 02/06/2023]
4
Impact of ultra-low dose CT acquisition on semi-automated RECIST tool in the evaluation of malignant focal liver lesions. Diagn Interv Imaging 2020;101:473-479. [DOI: 10.1016/j.diii.2020.05.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Revised: 05/05/2020] [Accepted: 05/06/2020] [Indexed: 12/21/2022]
5
Bagheri MH, Roth H, Kovacs W, Yao J, Farhadi F, Li X, Summers RM. Technical and Clinical Factors Affecting Success Rate of a Deep Learning Method for Pancreas Segmentation on CT. Acad Radiol 2020;27:689-695. [PMID: 31537506 DOI: 10.1016/j.acra.2019.08.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Revised: 08/21/2019] [Accepted: 08/27/2019] [Indexed: 02/07/2023]
6
Gavrielides MA, Berman BP, Supanich M, Schultz K, Li Q, Petrick N, Zeng R, Siegelman J. Quantitative assessment of nonsolid pulmonary nodule volume with computed tomography in a phantom study. Quant Imaging Med Surg 2017;7:623-635. [PMID: 29312867 DOI: 10.21037/qims.2017.12.07] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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