Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas.
- Published in:
- Scientific Reports, 2018, v. 8, n. 1, p. 1, doi. 10.1038/s41598-018-33473-0
- By:
- Publication type:
- Article
Works matching AU Orooji, Mahdi
Results: 13
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Distinguishing Adenocarcinomas from Granulomas in the CT scan of the chest: performance degradation evaluation in the automatic segmentation framework.
- Published in:
- BMC Research Notes, 2021, v. 14, n. 1, p. 1, doi. 10.1186/s13104-021-05502-1
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- Publication type:
- Article
3
Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm.
- Published in:
- Journal of Biomedical Optics, 2018, v. 23, n. 2, p. 026002-1, doi. 10.1117/1.JBO.23.2.026002
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- Publication type:
- Article
4
Segmentation of the pulmonary nodule and the attached vessels in the CT scan of the chest using morphological features and topological skeleton of the nodule.
- Published in:
- IET Image Processing (Wiley-Blackwell), 2020, v. 14, n. 8, p. 1520, doi. 10.1049/iet-ipr.2019.1054
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- Publication type:
- Article
5
A Novel Dictionary-Based Image Reconstruction for Photoacoustic Computed Tomography.
- Published in:
- Applied Sciences (2076-3417), 2018, v. 8, n. 9, p. 1570, doi. 10.3390/app8091570
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- Publication type:
- Article
6
Dental stem cell banking: Techniques and protocols.
- Published in:
- Cell Biology International, 2021, v. 45, n. 9, p. 1851, doi. 10.1002/cbin.11626
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- Publication type:
- Article
7
Brown adipose tissue does not seem to mediate metabolic adaptation to overfeeding in men.
- Published in:
- 2017
- By:
- Publication type:
- journal article
8
Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography.
- Published in:
- Journal of Medical Imaging, 2018, v. 5, n. 2, p. 024501-1, doi. 10.1117/1.JMI.5.2.024501
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- Publication type:
- Article
9
Author Correction: Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas.
- Published in:
- 2019
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- Publication type:
- Correction Notice
10
Early Detection of Avian Diseases Based on Thermography and Artificial Intelligence.
- Published in:
- Animals (2076-2615), 2023, v. 13, n. 14, p. 2348, doi. 10.3390/ani13142348
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- Publication type:
- Article
11
Post-revascularization Ejection Fraction Prediction for Patients Undergoing Percutaneous Coronary Intervention Based on Myocardial Perfusion SPECT Imaging Radiomics: a Preliminary Machine Learning Study.
- Published in:
- Journal of Digital Imaging, 2023, v. 36, n. 4, p. 1348, doi. 10.1007/s10278-023-00820-1
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- Publication type:
- Article
12
Validation of delay‐multiply‐and‐standard‐deviation weighting factor for improved photoacoustic imaging of sentinel lymph node.
- Published in:
- Journal of Biophotonics, 2019, v. 12, n. 6, p. N.PAG, doi. 10.1002/jbio.201800292
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- Publication type:
- Article
13
An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.
- Published in:
- Medical Physics, 2017, v. 44, n. 7, p. 3556, doi. 10.1002/mp.12208
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- Publication type:
- Article