February 2025 SPIE Medical Imaging, San DiegoOctober 2024 AIAI Go Karting EventAugust 2024: CT Meeting in Bamberg, GermanyMay 2024: Beginning of the summer in AIAIMay 2024: Congratulations to new graduates Anqi Liu and Sixiao Lu!!!July 2023: Congratulations to Matt Tivnan on his PhD Defense!February 2023: SPIE Medical Imaging in San DiegoDecember 2022: Team AIAI at the end-of-year celebrationMay 2022: Congratulations to Wenying on receiving her PhD!Summer 2021: Conference Award Congratulations to Tess Reynolds, Quinn Ma, and Matt TivnanJuly 2021 - Official post-quarantine welcome back to lab lunchJune 2021 - Congratulations to Shaoyan on graduating!!June 2021 - First outing after relaxed quarantine rulesFebruary 2020 - Pre-pandemic OutingAugust 2019 - I-STAR 10-Year Anniversary Party July 2019 - AAPM Annual Meeting, AIAI and friendsJuly 2019 Outside on East Baltimore CampusJune 2019 - Fully3D Meeting (Philadelphia, PA)May 2019 - Congratulations to Steve Tilley on getting his PhD!!February 2019 - Congratulation to Wenying Wang on winning the SPIE Robert F. Wagner AwardAugust 2018 - AIAI Lab Group PhotoJuly 2018 - Congratulations to Grace Gang on winning the AAPM Jack Fowler AwardMay 2018 AIAI Home-cooked DinnerFebruary 2018 AIAI at SPIE Medical Imaging (Houston, TX)February 2018 - Andrew Mao wins Robert F. Wagner AwardJuly 2017 - AIAI Group PhotoJune 2017 - Fully3D Meeting - AIAI in Xi'an, ChinaFebruary 2017 - SPIE Medical Imaging (Orlando, FL)September 2016 - AIAI Group PhotoJuly 2016 - AIAI Group PhotoMay 2016 - AIAI Group Photo
Principal Investigator and Major Collaborators
J. Webster Stayman, PhD is an Associate Professor in the Biomedical Engineering Department and Principle Investigator of the AIAI Lab. His research interests have included tomographic reconstruction for emission and transmission tomography, statistical reconstruction approaches, regularization design, prior-image-based reconstruction, machine learning in image formation and analysis, cone-beam CT (CBCT) modeling and analysis, optical system modeling and analysis, test bench construction, instrumentation, physical experimentation, and task-driven and adaptive acquisitions. Google Scholar Publications
Grace Jianan Gang, PhD is an Assistant Professor in the Radiology Department of the University of Pennsylvania and Principle Investigator of the IMPACT Laboratory. She maintains an Adjunct Professor position in the Biomedical Engineering Department at Johns Hopkins. She leads research in collaboration with the AIAI Lab in task-based optimization to help design novel acquisition approaches and reconstruction methods for CT and CBCT. Her research interests also include the development and analysis of advanced reconstruction methods that integrate prior image information. Google Scholar Publications
Congratulations to Grace on winning the AAPM 2018 Jack Fowler Junior Investigator Award.
Congratulations to Grace on winning the AAPM 2022 John S. Laughlin Early-Career Scientist Award.
Tess Reynolds, PhD is a Cancer Institute of NSW Early Career Fellow and the Thoracic Theme Lead at the ACRF Image X Institute. Since receiving her PhD from the University of Adelaide in 2017, she has become one of the leading young biomedical imaging physicists in the world, with a globally unique industry partnership with Siemens Healthcare and an international collaboration with Johns Hopkins University (USA). Her current research focuses on delivering the future of interventional imaging in challenging surgical scenarios, and works closely with the AIAI team. Google Scholar Publications
Congratulations to Tess on winning the AAPM 2021 Jack Fowler Junior Investigator Award.
Congratulations to Tess on winning the 2022 Eureka Prize.
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Current Students (alphabetical)
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Yue Fan (October 2024-present) is a MSE student in Biomedical Engineering at Johns Hopkins University. She is working on augmenting our x-ray testbench capabilities.
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Xiao Jiang (July 2022-present) is a PhD student in Biomedical Engineering at Johns Hopkins. He is working on development of advanced processing methods for spectral imaging in x-ray imaging applications. Google Scholar Publications
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Junyuan Li (September 2018-present) was a MSE student and is a continuing PhD student in Biomedical Engineering at Johns Hopkins. He is working on development of various methods for CT performance assessment when nonlinear data processing is applied; methods include 3D printing of texture phantoms, observer studies, and predictive performance models. Google Scholar Publications
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Patrick Li (June 2023-present) is an undergraduate in Computer Science. He is helping to develop tools and processing methods for characterizing lung nodules.
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Shudong Li (February 2023-present) is part of the dual-degree program between Johns Hopkins and Tsinghua University. He is studying advanced tomographic reconstruction and denoising methods.
Congratulations to Shudong on being featured on the cover of the Journal of Medical Imaging, vol. 11, issue 4 for his work on diffusion posterior sampling.
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Stephen Liu (July 2018-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. He is jointly supervised by Dr. Wojtek Zbijewski in the Quantis Laboratory and by Dr. Stayman in the AIAI lab. His work involves development of methods for high-fidelity quantitative bone health metrics in the presence of metal implants including advanced reconstruction methods and spectral CT imaging. Google Scholar Publications
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Zimo Liu (October 2024-present) is a BME MSE student and is investigating new approaches using generative diffusion models.
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Altea Lorenzon (July 2023-present) is a post-doctoral fellow in the lab. She is investigating new strategies for collecting and processing spectral x-ray data, and investigating flow models in interventional procedures. Google Scholar Publications
Mitchell Pelline (May 2024-present) is a BS/MS student in Biomedical Engineering at Johns Hopkins University. He is investigating novel data acquisition strategies and associated data processing schemes.
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Shalini Subramanian (September 2021-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. She is working with Ken Taguchi and is jointly supervised by Dr. Stayman. She is investigating strategies for getting updated tissue perfusion information using single view projections. Google Scholar Publications
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Peiqing Teng (August 2022-present) joined us as a Master’s student in Applied Mathematics and Statistics at Johns Hopkins, and is continuing as a PhD Student in ECE. Peiqing is researching machine learning methods for x-ray CT that permit user-specified levels of noise control.
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Xin Wang (August 2024-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. She is jointly supervised by Dr. Zbijewski and Dr. Stayman, and is working on the development of high-resolution 3D anatomical models using deep learning methods.
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Yijie Yuan (July 2021-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. He is working on understanding the accurate representation of image features and radiomics in CT systems. Google Scholar Publications
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AIAI Alumni (reverse chronological)
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Anqi Liu (February 2023-June 2024) was a Master’s student in Biomedical Engineering at Johns Hopkins. She studied different acquisition and reconstruction strategies for 3D mammography.
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Yimeng Xu (January 2024-May 2024) was a MS student in Biomedical Engineering at Johns Hopkins University and part of the the JHU-Tsinghua Dual Degree program. She was involved in integrating new x-ray detectors into test-bench experiments in the AIAI laboratory.
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Matthew Tivnan (July 2018-August 2023) was a PhD student in Biomedical Engineering at Johns Hopkins University. His research in the AIAI laboratory spanned novel methods for collecting and processing spectral CT data for multiple material decomposition, as well as novel machine learning approaches for data processing in computed tomography. He is now a researcher at MGH. Google Scholar Publications
Congratulations to Matt on winning the Fully3D 2021 Best Oral Presentation Award!!!
Congratulations to Matt on being a SPIE Medical Imaging 2022 Wagner Award Finalist and getting 2nd Place for the SPIE Medical Imaging Best Student Paper Award!!!
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Omar Elfernani (June 2023-August 2023) was part of the SARE program, and was looking at applying machine learning methods to lung nodule classification.
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David (Tianyu) Wang (November 2021-July 2023) was a Master’s student in Biomedical Engineering at Johns Hopkins. He investigated various 3D-printing methods for realistic representation of human anatomy in radiography and CT.
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Kangjia Cai (August 2022-June 2023) was a Master’s student in Biomedical Engineering at Johns Hopkins. He helped us to assemble tools for identifying, contouring, and characterization of lung nodules in a database.
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Cecilia (Mengyuan) Xue (February 2022-June 2023) was a Master’s student in Biomedical Engineering at Johns Hopkins. She was studying strategies for recovery of radiomic metrics in images in the presence of blur and noise.
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Sixiao Lu (February 2023-May 2023) was a Master’s student in Biomedical Engineering at Johns Hopkins. He investigated advanced processing methods for x-ray computed tomography, and is now working with United Imaging.
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Vasundhara Langade (September 2022-December 2022) was a Master’s student in Biomedical Engineering at Johns Hopkins. She worked on control software for our x-ray test bench.
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Kesavan Venkatesh (October 2022-December 2022) was a undergraduate student in Biomedical Engineering at Johns Hopkins. He was working on applications of machine learning to system calibration and data processing.
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Wenying Wang (August 2016-March 2022) graduated with a PhD in Biomedical Engineering at Johns Hopkins University in 2022. Her studies involved a wide range of investigations on advanced acquisition and reconstruction methods for computed tomography including dynamic beam modulation and analysis of imaging properties in CT, cone-beam CT, and spectral CT systems. Wenying now works at United Imaging Healthcare. Google Scholar Publications
Congratulations to Wenying on winning the SPIE 2019 Robert F. Wagner Best Paper Award!!!
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Tom Russ (July 2020-March 2022) was a PhD student at Heidelberg University. With the AIAI lab, he investigated interventional cone-beam CT including non-circular orbits and meachine-learning-based data processing approaches for arbitrary source-detector trajectories. Google Scholar Publications
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Paul Teng (June 2021-December 2021) was an undergraduate in Physics at Johns Hopkins University. He was part of the AAPM DREAM program and worked on research in the modeling, classification, and accurate representation of lung nodules.
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Chumin Zhao (September 2020-June 2021) was a postdoctoral fellow working on mammography system developing including the application of model-based methods and dictionaries for reconstruction of sparse data; and optimization of data acquisition methods in sparse-CT mammography.
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Ariyan Sajid (June 2020-August 2020; June 2021-August 2021) completed two years of the SARE Program. He worked in the lab to develop a large representative population of anthropomorphic digital phantoms for algorithm and system design and assessment.
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Jessica Flores (July 2018-July 2021) graduated with a Master’s degree in Biomedical Engineering at Johns Hopkins University in July 2021. She studied low-dose CT for imaging of lung cancer including prior-image methods and strategies to ensure robust performance.
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Shaoyan Pan (September 2019-June 2021) was a Master’s student in Biomedical Engineering at Johns Hopkins University, graduating in 2021. He used machine learning methods to develop software for generation of realistic lung nodules for investigations of CT imaging performance.
Congratulations to Shaoyan on winning the SPIE 2021 Robert F. Wagner Best Paper Award!!!
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Andrew Fwu Tay Leong (January 2019-September 2020) was a Postdoctoral Fellow working on advanced methods for low-scatter imaging and sparse CT data collection for mammography. He is now working at Los Alamos National Laboratory. Google Scholar Publications
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Amalie Shi (May 2018-December 2019) was a Master’s student in Biomedical Engineering at Johns Hopkins, graduating in December 2019. She was working on the development of new phantoms for CT image quality assessment.
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Zen Gordon (June 2019-July 2019) was a summer intern in the AIAI Laboratory and part of Johns Hopkins SARE program for high school students. During his summer in the AIAI Lab, Zen performed experiments for the development of a new spectral CT system.
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Eva Mammen (June 2019-July 2019) was a summer intern in the AIAI Laboratory. During her summer in the AIAI Lab, Eva learned how to apply Fourier optics to model a microscope and learn about Fourier ptychography.
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Gabriela Rodal (June 2017-March 2019) graduated from the Master’s program in Biomedical Engineering at Johns Hopkins University in Spring 2019. She was previously working on advanced data acquisition and reconstruction methods for imaging around metal implants.
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Steven Tilley II (June 2013-January 2019) obtained his PhD in Biomedical Engineering at Johns Hopkins University in 2019. His research in the AIAI laboratory involved the high-fidelity modeling of flat-panel CT systems including focal spot blurs, detector blur and correlations, and other physical effects particular to flat-panel systems. These sophisticated models are integrated into elements that are often ignored in model-based reconstruction algorithms to achieve improved imaging performance (e.g. ultra-high spatial resolution images). Steve currently works for KA Imaging. Google Scholar Publications
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Kailun Cheng (April 2018-December 2018) was a Master’s student in Data Science at Johns Hopkins University. She was working closely with Dr. Gang on applying machine learning methods for the analysis of CT reconstruction.
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Xueqi Guo (July 2018-September 2018) was a student intern for Summer 2018 from Shanghai Jiao Tong University. She investigated machine learning methods for denoising CT images.
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Jalen Cooke (June 2018-August 2018) was a summer intern in the AIAI Laboratory and part of Johns Hopkins SARE program for high school students. During his summer in the AIAI Lab, Jalen developed a methodology to 3D print CT phantoms emulating contrast-enhanced vascular trees.
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Hao Zhang, PhD (April 2016-June 2018) was a postdoctoral fellow in the AIAI Laboratory and is now at Stanford University doing a clinical medical physics residency. While in the AIAI Lab, he led research on prior-image-based reconstruction methods including cross-modality integration of anatomical information, region-of-difference reconstruction, and analytic methods for assessment of change admission/information propagation. Applications included CBCT reconstruction with CT prior images and variants with rigid and deformable registration. Hao is now a practicing Medical Physicist. Google Scholar Publications
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Andrew Mao (January 2017-June 2018) was a Master’s student in Biomedical Engineering at Johns Hopkins University, graduating in Summer 2018. He was working on the development of beam modulation techniques for dynamic fluence-field modulation in x-ray CT. Andrew moved on to the MD/PhD program at New York University.
Congratulations to Andrew on winning the SPIE 2018 Robert F. Wagner Best Paper Award!!!
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Lorenz Hehn (February 2018-May2018) was a PhD student at the Technical University of Munich (TUM) and was a visiting scholar in the AIAI laboratory in Spring 2018. During his stay in the AIAI laboratory he was involved with the development and investigation of blind deconvolution methods for estimating system blur for cone-beam computed tomography.
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Nischita Kaza (June 2017-September 2017) was a visiting undergraduate student from the National Institute of Technology, Karnataka in Summer 2017. She worked on the development of a Fourier Ptychography system for wide-field high-resolution microscopy.
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Tymeka Hill Adams (June 2017-August 2017) was a summer intern in the AIAI Laboratory and part of Johns Hopkins SARE program for high school students. Her summer research involved the quantitative assessment of bone health in extremities imaging.
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Hao Dang (January 2012-March 2017) obtained his PhD candidate in Biomedical Engineering in Spring 2017. Hao was jointly advised by Drs. Siewerdsen and Stayman and his research spanned projects in both the AIAI and I-STAR laboratories. His research involved the design and optimization of model-based reconstruction methods. His work has included the development of new prior-image-based reconstruction methods and the optimization of regularization strategies based on rigorous mathematical definitions of imaging task (e.g. dectectability index). Hao is currently a researcher at Philips Healthcare.Google Scholar Publications
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Esme Zhang (June 2015-March 2017) obtained her Master’s degree in Biomedical Engineering at Johns Hopkins University in Summer 2016. Her research included the development of models and reconstruction methods for multi-row dectector cardiac CT including the application of motion correction methods and known-component reconstruction methods for cardiac implants (e.g. pacing leads, catheters, etc.). Esme has since gotten a PhD and continues to work on CT, CBCT, and machine learning methods.
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Aswin Mathews, PhD (January 2015-January 2017) was a postdoctoral fellow in the AIAI Laboratory. His research was on novel methods for fluence-field modulation in x-ray CT including the modeling, design, optimization, fabrication, and control of multiple binary filters to achieve desired spatial distributions of x-ray fluence. Google Scholar Publications
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Saeed Sayyedi (July 2016-January 2017) was a PhD student at the Technical University of Munich (TUM) and a visiting scholar in the AIAI laboratory through the Biomedical Imaging & Informatics – European Research and Training Initiative (BERTI). During his stay in the AIAI laboratory he was involved with the development and investigation of advanced models and reconstruction techniques for liver CT perfusion studies. Google Scholar Publications
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Chengzhu Zhang (July 2016-September 2016) was an undergraduate in the Department of Engineering Physics at Tsinghua University. In his 2016 summer internship in the AIAI Laboratory he developed and explored strategies for applying known-component reconstruction for better visualization around metal implants. Specifically, he implemented different strategies for polyenergetic modeling of the energy-dependent effects in both implants and patient anatomy and developed strategies for applying known-component reconstruction when no shape model is available. Chengzhu went on to get a PhD at the University of Wisconsin.
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Shavona Dixon (July 2016-September 2016) was a summer intern in the AIAI Laboratory and part of Johns Hopkins SARE program for high school students. Her summer research involved the creation of a physical liver phantom for assessment of advanced contrast-enhanced CT methods. In particular, Shavona created digital models of hepatic vasculature and used 3D-printing technology to create accurate and anatomically realistic hepatic artery models that can be filled with CT contrast agents.
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Juliana Carneiro Gomes (June 2016-July 2016) was a summer intern in the AIAI Laboratory as part of the Science without Borders program. For her summer research, Juliana investigated acquisition protocols and advanced reconstruction methods for the creation of both very-low-dose 2D topograms and 3D scouts. She collected phantom data and applied model-based reconstruction methods to low exposure data, and made dose measurements using standard dosimetry equipment.
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Xin Bai (October 2015-May 2016) was in the AIAI lab conducting independent research while he was a Master’s Student in the Electrical and Computer Engineering Department at Johns Hopkins University. Xin’s research involved the development of methods for high-resolution radiography – specifically, using multi-frame dealiasing techniques to overcome sampling limitations in flat-panel-based x-ray imaging. He graduated with his Master’s in June 2016.
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Amir Pourmorteza (June 2014-July 2015) was a postdoctoral fellow in the AIAI Laboratory. His research involved the development and application of prior-image-based reconstruction methods. In particular, he investigated strategies for cross-modality integration of anatomical information for CBCT reconstruction using CT prior images. His efforts led to the development of the Reconstruction of Difference algorithm, which seeks to directly reconstruct anatomical change between subsequent scans, and the development of a new class of prior-image penalty that permits selective incorporation of prior information based on spatial frequency content (avoiding integration of, for example, low-frequency artifacts). Amir is currently an Assistant Professor at Emory University. Google Scholar Publications
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Shiyu Xu (January 2015-June 2016) was a postdoctoral fellow in the AIAI Laboratory. His research involved the development and application of known-component reconstruction (KCR) methods for imaging around metallic surgical devices and implants. In particular, he lead the effort to develop a polyenergetic KCR approach for which neither the material composition of the implant nor the energy-dependent aspects of the CT system (e.g. beam quality, detector energy-sensitivity) are known. The methodology was applied in physical CBCT experiments with an implanted cadaveric sample illustrating good visualization of features up the implant/tissue boundary. Shiyu is currently a Researcher at Reflexion. Google Scholar Publications
J. Webster Stayman, PhD is an Associate Professor in the Biomedical Engineering Department and Principle Investigator of the AIAI Lab. His research interests have included tomographic reconstruction for emission and transmission tomography, statistical reconstruction approaches, regularization design, prior-image-based reconstruction, machine learning in image formation and analysis, cone-beam CT (CBCT) modeling and analysis, optical system modeling and analysis, test bench construction, instrumentation, physical experimentation, and task-driven and adaptive acquisitions. Google Scholar Publications
Grace Jianan Gang, PhD is an Assistant Professor in the Radiology Department of the University of Pennsylvania and Principle Investigator of the IMPACT Laboratory. She maintains an Adjunct Professor position in the Biomedical Engineering Department at Johns Hopkins. She leads research in collaboration with the AIAI Lab in task-based optimization to help design novel acquisition approaches and reconstruction methods for CT and CBCT. Her research interests also include the development and analysis of advanced reconstruction methods that integrate prior image information. Google Scholar Publications
Tess Reynolds, PhD is a Cancer Institute of NSW Early Career Fellow and the Thoracic Theme Lead at the ACRF Image X Institute. Since receiving her PhD from the University of Adelaide in 2017, she has become one of the leading young biomedical imaging physicists in the world, with a globally unique industry partnership with Siemens Healthcare and an international collaboration with Johns Hopkins University (USA). Her current research focuses on delivering the future of interventional imaging in challenging surgical scenarios, and works closely with the AIAI team. Google Scholar Publications
Yue Fan (October 2024-present) is a MSE student in Biomedical Engineering at Johns Hopkins University. She is working on augmenting our x-ray testbench capabilities.
Xiao Jiang (July 2022-present) is a PhD student in Biomedical Engineering at Johns Hopkins. He is working on development of advanced processing methods for spectral imaging in x-ray imaging applications. Google Scholar Publications
Junyuan Li (September 2018-present) was a MSE student and is a continuing PhD student in Biomedical Engineering at Johns Hopkins. He is working on development of various methods for CT performance assessment when nonlinear data processing is applied; methods include 3D printing of texture phantoms, observer studies, and predictive performance models. Google Scholar Publications
Patrick Li (June 2023-present) is an undergraduate in Computer Science. He is helping to develop tools and processing methods for characterizing lung nodules.
Shudong Li (February 2023-present) is part of the dual-degree program between Johns Hopkins and Tsinghua University. He is studying advanced tomographic reconstruction and denoising methods.
Stephen Liu (July 2018-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. He is jointly supervised by Dr. Wojtek Zbijewski in the Quantis Laboratory and by Dr. Stayman in the AIAI lab. His work involves development of methods for high-fidelity quantitative bone health metrics in the presence of metal implants including advanced reconstruction methods and spectral CT imaging. Google Scholar Publications
Zimo Liu (October 2024-present) is a BME MSE student and is investigating new approaches using generative diffusion models.
Altea Lorenzon (July 2023-present) is a post-doctoral fellow in the lab. She is investigating new strategies for collecting and processing spectral x-ray data, and investigating flow models in interventional procedures. Google Scholar Publications
Quinn (Yiqun) Ma (July 2019-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. He is studying novel and task-driven acquisition methods for interventional cone-beam CT. Google Scholar Publications
Mitchell Pelline (May 2024-present) is a BS/MS student in Biomedical Engineering at Johns Hopkins University. He is investigating novel data acquisition strategies and associated data processing schemes.
Shalini Subramanian (September 2021-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. She is working with Ken Taguchi and is jointly supervised by Dr. Stayman. She is investigating strategies for getting updated tissue perfusion information using single view projections. Google Scholar Publications
Peiqing Teng (August 2022-present) joined us as a Master’s student in Applied Mathematics and Statistics at Johns Hopkins, and is continuing as a PhD Student in ECE. Peiqing is researching machine learning methods for x-ray CT that permit user-specified levels of noise control.
Xin Wang (August 2024-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. She is jointly supervised by Dr. Zbijewski and Dr. Stayman, and is working on the development of high-resolution 3D anatomical models using deep learning methods.
Yijie Yuan (July 2021-present) is a PhD student in Biomedical Engineering at Johns Hopkins University. He is working on understanding the accurate representation of image features and radiomics in CT systems. Google Scholar Publications
Anqi Liu (February 2023-June 2024) was a Master’s student in Biomedical Engineering at Johns Hopkins. She studied different acquisition and reconstruction strategies for 3D mammography.
Matthew Tivnan (July 2018-August 2023) was a PhD student in Biomedical Engineering at Johns Hopkins University. His research in the AIAI laboratory spanned novel methods for collecting and processing spectral CT data for multiple material decomposition, as well as novel machine learning approaches for data processing in computed tomography. He is now a researcher at MGH. Google Scholar Publications
Omar Elfernani (June 2023-August 2023) was part of the SARE program, and was looking at applying machine learning methods to lung nodule classification.
David (Tianyu) Wang (November 2021-July 2023) was a Master’s student in Biomedical Engineering at Johns Hopkins. He investigated various 3D-printing methods for realistic representation of human anatomy in radiography and CT.
Kangjia Cai (August 2022-June 2023) was a Master’s student in Biomedical Engineering at Johns Hopkins. He helped us to assemble tools for identifying, contouring, and characterization of lung nodules in a database.
Cecilia (Mengyuan) Xue (February 2022-June 2023) was a Master’s student in Biomedical Engineering at Johns Hopkins. She was studying strategies for recovery of radiomic metrics in images in the presence of blur and noise.
Sixiao Lu (February 2023-May 2023) was a Master’s student in Biomedical Engineering at Johns Hopkins. He investigated advanced processing methods for x-ray computed tomography, and is now working with United Imaging.
Vasundhara Langade (September 2022-December 2022) was a Master’s student in Biomedical Engineering at Johns Hopkins. She worked on control software for our x-ray test bench.
Kesavan Venkatesh (October 2022-December 2022) was a undergraduate student in Biomedical Engineering at Johns Hopkins. He was working on applications of machine learning to system calibration and data processing.
Wenying Wang (August 2016-March 2022) graduated with a PhD in Biomedical Engineering at Johns Hopkins University in 2022. Her studies involved a wide range of investigations on advanced acquisition and reconstruction methods for computed tomography including dynamic beam modulation and analysis of imaging properties in CT, cone-beam CT, and spectral CT systems. Wenying now works at United Imaging Healthcare. Google Scholar Publications
Tom Russ (July 2020-March 2022) was a PhD student at Heidelberg University. With the AIAI lab, he investigated interventional cone-beam CT including non-circular orbits and meachine-learning-based data processing approaches for arbitrary source-detector trajectories. Google Scholar Publications
Paul Teng (June 2021-December 2021) was an undergraduate in Physics at Johns Hopkins University. He was part of the AAPM DREAM program and worked on research in the modeling, classification, and accurate representation of lung nodules.
Chumin Zhao (September 2020-June 2021) was a postdoctoral fellow working on mammography system developing including the application of model-based methods and dictionaries for reconstruction of sparse data; and optimization of data acquisition methods in sparse-CT mammography.
Ariyan Sajid (June 2020-August 2020; June 2021-August 2021) completed two years of the SARE Program. He worked in the lab to develop a large representative population of anthropomorphic digital phantoms for algorithm and system design and assessment.
Jessica Flores (July 2018-July 2021) graduated with a Master’s degree in Biomedical Engineering at Johns Hopkins University in July 2021. She studied low-dose CT for imaging of lung cancer including prior-image methods and strategies to ensure robust performance.
Shaoyan Pan (September 2019-June 2021) was a Master’s student in Biomedical Engineering at Johns Hopkins University, graduating in 2021. He used machine learning methods to develop software for generation of realistic lung nodules for investigations of CT imaging performance.
Andrew Fwu Tay Leong (January 2019-September 2020) was a Postdoctoral Fellow working on advanced methods for low-scatter imaging and sparse CT data collection for mammography. He is now working at Los Alamos National Laboratory.
Amalie Shi (May 2018-December 2019) was a Master’s student in Biomedical Engineering at Johns Hopkins, graduating in December 2019. She was working on the development of new phantoms for CT image quality assessment.
Zen Gordon (June 2019-July 2019) was a summer intern in the AIAI Laboratory and part of Johns Hopkins SARE program for high school students. During his summer in the AIAI Lab, Zen performed experiments for the development of a new spectral CT system.
Eva Mammen (June 2019-July 2019) was a summer intern in the AIAI Laboratory. During her summer in the AIAI Lab, Eva learned how to apply Fourier optics to model a microscope and learn about Fourier ptychography.
Gabriela Rodal (June 2017-March 2019) graduated from the Master’s program in Biomedical Engineering at Johns Hopkins University in Spring 2019. She was previously working on advanced data acquisition and reconstruction methods for imaging around metal implants.
Steven Tilley II (June 2013-January 2019) obtained his PhD in Biomedical Engineering at Johns Hopkins University in 2019. His research in the AIAI laboratory involved the high-fidelity modeling of flat-panel CT systems including focal spot blurs, detector blur and correlations, and other physical effects particular to flat-panel systems. These sophisticated models are integrated into elements that are often ignored in model-based reconstruction algorithms to achieve improved imaging performance (e.g. ultra-high spatial resolution images). Steve currently works for KA Imaging. Google Scholar Publications
Kailun Cheng (April 2018-December 2018) was a Master’s student in Data Science at Johns Hopkins University. She was working closely with Dr. Gang on applying machine learning methods for the analysis of CT reconstruction.
Xueqi Guo (July 2018-September 2018) was a student intern for Summer 2018 from Shanghai Jiao Tong University. She investigated machine learning methods for denoising CT images.
Jalen Cooke (June 2018-August 2018) was a summer intern in the AIAI Laboratory and part of Johns Hopkins SARE program for high school students. During his summer in the AIAI Lab, Jalen developed a methodology to 3D print CT phantoms emulating contrast-enhanced vascular trees.
Hao Zhang, PhD (April 2016-June 2018) was a postdoctoral fellow in the AIAI Laboratory and is now at Stanford University doing a clinical medical physics residency. While in the AIAI Lab, he led research on prior-image-based reconstruction methods including cross-modality integration of anatomical information, region-of-difference reconstruction, and analytic methods for assessment of change admission/information propagation. Applications included CBCT reconstruction with CT prior images and variants with rigid and deformable registration. Hao is now a practicing Medical Physicist. Google Scholar Publications
Andrew Mao (January 2017-June 2018) was a Master’s student in Biomedical Engineering at Johns Hopkins University, graduating in Summer 2018. He was working on the development of beam modulation techniques for dynamic fluence-field modulation in x-ray CT. Andrew moved on to the MD/PhD program at New York University.
Lorenz Hehn (February 2018-May2018) was a PhD student at the Technical University of Munich (TUM) and was a visiting scholar in the AIAI laboratory in Spring 2018. During his stay in the AIAI laboratory he was involved with the development and investigation of blind deconvolution methods for estimating system blur for cone-beam computed tomography.
Nischita Kaza (June 2017-September 2017) was a visiting undergraduate student from the National Institute of Technology, Karnataka in Summer 2017. She worked on the development of a Fourier Ptychography system for wide-field high-resolution microscopy.
Tymeka Hill Adams (June 2017-August 2017) was a summer intern in the AIAI Laboratory and part of Johns Hopkins SARE program for high school students. Her summer research involved the quantitative assessment of bone health in extremities imaging.
Hao Dang (January 2012-March 2017) obtained his PhD candidate in Biomedical Engineering in Spring 2017. Hao was jointly advised by Drs. Siewerdsen and Stayman and his research spanned projects in both the AIAI and I-STAR laboratories. His research involved the design and optimization of model-based reconstruction methods. His work has included the development of new prior-image-based reconstruction methods and the optimization of regularization strategies based on rigorous mathematical definitions of imaging task (e.g. dectectability index). Hao is currently a researcher at Philips Healthcare.Google Scholar Publications
Esme Zhang (June 2015-March 2017) obtained her Master’s degree in Biomedical Engineering at Johns Hopkins University in Summer 2016. Her research included the development of models and reconstruction methods for multi-row dectector cardiac CT including the application of motion correction methods and known-component reconstruction methods for cardiac implants (e.g. pacing leads, catheters, etc.). Esme has since gotten a PhD and continues to work on CT, CBCT, and machine learning methods.
Aswin Mathews, PhD (January 2015-January 2017) was a postdoctoral fellow in the AIAI Laboratory. His research was on novel methods for fluence-field modulation in x-ray CT including the modeling, design, optimization, fabrication, and control of multiple binary filters to achieve desired spatial distributions of x-ray fluence. Google Scholar Publications
Saeed Sayyedi (July 2016-January 2017) was a PhD student at the Technical University of Munich (TUM) and a visiting scholar in the AIAI laboratory through the Biomedical Imaging & Informatics – European Research and Training Initiative (BERTI). During his stay in the AIAI laboratory he was involved with the development and investigation of advanced models and reconstruction techniques for liver CT perfusion studies. Google Scholar Publications
Chengzhu Zhang (July 2016-September 2016) was an undergraduate in the Department of Engineering Physics at Tsinghua University. In his 2016 summer internship in the AIAI Laboratory he developed and explored strategies for applying known-component reconstruction for better visualization around metal implants. Specifically, he implemented different strategies for polyenergetic modeling of the energy-dependent effects in both implants and patient anatomy and developed strategies for applying known-component reconstruction when no shape model is available. Chengzhu went on to get a PhD at the University of Wisconsin.
Shavona Dixon (July 2016-September 2016) was a summer intern in the AIAI Laboratory and part of Johns Hopkins SARE program for high school students. Her summer research involved the creation of a physical liver phantom for assessment of advanced contrast-enhanced CT methods. In particular, Shavona created digital models of hepatic vasculature and used 3D-printing technology to create accurate and anatomically realistic hepatic artery models that can be filled with CT contrast agents.
Juliana Carneiro Gomes (June 2016-July 2016) was a summer intern in the AIAI Laboratory as part of the Science without Borders program. For her summer research, Juliana investigated acquisition protocols and advanced reconstruction methods for the creation of both very-low-dose 2D topograms and 3D scouts. She collected phantom data and applied model-based reconstruction methods to low exposure data, and made dose measurements using standard dosimetry equipment.
Xin Bai (October 2015-May 2016) was in the AIAI lab conducting independent research while he was a Master’s Student in the Electrical and Computer Engineering Department at Johns Hopkins University. Xin’s research involved the development of methods for high-resolution radiography – specifically, using multi-frame dealiasing techniques to overcome sampling limitations in flat-panel-based x-ray imaging. He graduated with his Master’s in June 2016.
Amir Pourmorteza (June 2014-July 2015) was a postdoctoral fellow in the AIAI Laboratory. His research involved the development and application of prior-image-based reconstruction methods. In particular, he investigated strategies for cross-modality integration of anatomical information for CBCT reconstruction using CT prior images. His efforts led to the development of the Reconstruction of Difference algorithm, which seeks to directly reconstruct anatomical change between subsequent scans, and the development of a new class of prior-image penalty that permits selective incorporation of prior information based on spatial frequency content (avoiding integration of, for example, low-frequency artifacts). Amir is currently an Assistant Professor at Emory University. Google Scholar Publications
Shiyu Xu (January 2015-June 2016) was a postdoctoral fellow in the AIAI Laboratory. His research involved the development and application of known-component reconstruction (KCR) methods for imaging around metallic surgical devices and implants. In particular, he lead the effort to develop a polyenergetic KCR approach for which neither the material composition of the implant nor the energy-dependent aspects of the CT system (e.g. beam quality, detector energy-sensitivity) are known. The methodology was applied in physical CBCT experiments with an implanted cadaveric sample illustrating good visualization of features up the implant/tissue boundary. Shiyu is currently a Researcher at Reflexion. Google Scholar Publications