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Ferrero, Andrea

0000-0001-9712-8913

Mayo Clinic

Mayo Clinic

Citations 28

Determination of iodine detectability in different types of multiple-energy images for a photon-counting detector computed tomography system
Michalak, Gregory J. , Weaver, Jayse , Ferrero, Andrea , Gong, Hao , Fetterly, Kenneth A. , Zhou, Wei , McCollough, Cynthia H , Leng, Shuai , Zhou, Wei , McCollough, Cynthia H. , Leng, Shuai

Journal of Medical Imaging | October 15, 2019 | Volume: 6 | Issue: 04 | Pages: 1

10.1117/1.jmi.6.4.043501 Get It

Detection and Characterization of Renal Stones by Using Photon-Counting–based CT
Marcus, Roy , Fletcher, Joel G. , Ferrero, Andrea , Leng, Shuai , Halaweish, Ahmed F., Gutjahr, Ralf , Vrtiska, Terri J., Wells, Mike L., McCollough, Cynthia H. , Marcus, Roy P, Enders, Felicity T, McCollough, Cynthia H , Fletcher, Joel G , Leng, Shuai , Enders, Felicity

Radiology | August 7, 2018 | Volume: 289 | Issue: 2 | Pages: 436-442

10.1148/radiol.2018180126 Get It

Use of a channelized Hotelling observer to assess CT image quality and optimize dose reduction for iteratively reconstructed images
Favazza, Christopher , Ferrero, Andrea , Yu, Lifeng , McMillan, Kyle, Favazza, Christopher P, McMillan, Kyle L, McCollough, Cynthia H , Leng, Shuai , Yu, Lifeng , Leng, Shuai

Journal of Medical Imaging | October 3, 2017 | Volume: 4 | Issue: 03 | Pages: 1

10.1117/1.jmi.4.3.031213 Get It

Lung nodule volume quantification and shape differentiation with an ultra-high resolution technique on a photon counting detector CT system
Zhou, Wei , Montoya, Juan , Gutjahr, Ralf , Ferrero, Andrea , Halaweish, A., Kappler, S. , Halaweish, A., McCollough, Cynthia H. , Leng, Shuai , Zhou, Wei

SPIE Proceedings | March 9, 2017 | Volume: 10132 | Issue: No issue available | Pages: 101323Q

10.1117/12.2255736 Get It

Ultra-high spatial resolution multi-energy CT using photon counting detector technology
Gutjahr, Ralf , Ferrero, Andrea , Kappler, S. , Henning, André , Halaweish, A., Zhou, Wei , Montoya, Juan , Leng, Shuai , Halaweish, A., McCollough, Cynthia H. , Zhou, Wei

SPIE Proceedings | March 9, 2017 | Volume: 10132 | Issue: No issue available | Pages: 101320Y

10.1117/12.2255589 Get It

Renal stone characterization using high resolution imaging mode on a photon counting detector CT system
Ferrero, Andrea , Gutjahr, Ralf , Henning, André , Kappler, S. , Halaweish, A., Abdurakhimova, Dilbar, Peterson, Zhane, Montoya, Juan , McCollough, C, Halaweish, A., Leng, Shuai

SPIE Proceedings | March 8, 2017 | Volume: 10132 | Issue: No issue available | Pages: 101323J

10.1117/12.2255651 Get It

Practical implementation of channelized hotelling observers: effect of ROI size
Ferrero, Andrea , Favazza, Christopher , Yu, Lifeng , Favazza, Christopher P, Yu, Lifeng , Leng, Shuai , McCollough, Cynthia H.

SPIE Proceedings | March 8, 2017 | Volume: 10132 | Issue: No issue available | Pages: 101320G

10.1117/12.2255530 Get It

Technical Note: Insertion of digital lesions in the projection domain for dual‐source, dual‐energy CT
Ferrero, Andrea , Chen, Baiyu , Li, Zhoubo , Yu, Lifeng , McCollough, Cynthia, Yu, Lifeng , McCollough, Cynthia H.

Medical Physics | February 27, 2017 | Volume: 44 | Issue: 5 | Pages: 1655-1660

10.1002/mp.12185 Get It

PurposeTo compare algorithms performing material decomposition and classification in dual‐energy CT, it is desirable to know the ground truth of the lesion to be analyzed in real patient data. In this work, we developed and validated a framework to insert digital lesions of arbitrary chemical composition into patient projection data acquired on a dual‐source, dual‐energy CT system.MethodsA model that takes into account beam‐hardening effects was developed to predict the CT number of objects with known chemical composition. The model utilizes information about the x‐ray energy spectra, the patient/phantom attenuation, and the x‐ray detector energy response. The beam‐hardening model was validated on samples of iodine (I) and calcium (Ca) for a second‐generation dual‐source, dual‐energy CT scanner for all tube potentials available and a wide range of patient sizes. The seven most prevalent mineral components of renal stones were modeled and digital stones were created with CT numbers computed for each patient/phantom size and x‐ray energy spectra using the developed beam‐hardening model. Each digital stone was inserted in the dual‐energy projection data of a water phantom scanned on a dual‐source scanner and reconstructed with the routine algorithms in use in our practice. The geometry of the forward projection for dual‐energy data was validated by comparing CT number accuracy and high‐contrast resolution of simulated dual‐energy CT data of the ACR phantom with experimentally acquired data.ResultsThe beam‐hardening model and forward projection method accurately predicted the CT number of I and Ca over a wide range of tube potentials and phantom sizes. The images reconstructed after the insertion of digital kidney stones were consistent with the images reconstructed from the scanner, and the CT number ratios for different kidney stone types were consistent with data in the literature. A sample application of the proposed tool was also demonstrated.ConclusionA framework was developed and validated for the creation of digital objects of known mineral composition, and for inserting the digital objects into projection data from a commercial dual‐source, dual‐energy CT scanner. Among other applications, it will allow a systematic investigation of the impact of scan and reconstruction parameters on kidney stone dual‐energy properties under rigorously controlled conditions.