Prof. Predrag R. Bakic
Associate Professor at Penn Medicine
SPIE Involvement:
Author | Instructor
Publications (79)

Proceedings Article | 22 May 2020 Paper
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Modeling, Medicine, Imaging systems, Computer simulations, Medical imaging, Breast imaging, Clinical trials

Proceedings Article | 22 May 2020 Paper
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Breast cancer, Imaging systems, Wavelets, Feature extraction, Mammography, X-ray imaging, Digital mammography

Proceedings Article | 22 May 2020 Paper
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Super resolution, Statistical analysis, Imaging systems, Sensors, Computer simulations, Tomography, Analytical research, Digital breast tomosynthesis, Clinical trials

Proceedings Article | 22 May 2020 Paper
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Computer aided diagnosis and therapy, Tumor growth modeling, Clouds, 3D modeling, Feature extraction, Binary data, Solid modeling, 3D image processing, Digital breast tomosynthesis

Proceedings Article | 22 May 2020 Paper
Proc. SPIE. 11513, 15th International Workshop on Breast Imaging (IWBI2020)
KEYWORDS: Breast, Medicine, Cancer, Breast cancer, Sensors, Databases, Diagnostics, Physics, Mammography, Artificial intelligence

Showing 5 of 79 publications
Course Instructor
SC1239: Virtual Clinical Trials: An In-depth Tutorial
In 2014, it was estimated that there were just 450 anatomic phantoms in the world. Today, based on advanced models of breast anatomy, an infinite number of models exist. As such, it is possible to simulate individuals and specific pathologies from the population of all humans with increasingly higher accuracy. This, together with advanced models of image simulation, image processing and image reconstruction, means that we can create arbitrarily large databases of simulated images. At the same time, advances in machine observer methods mean that it is possible to conduct virtual clinical trials (VCT) using the simulated images, together with simulations of medical displays, human optical perception and cognition. The logistics of conducting VCT with thousands of patients is similar to the logistics of organizing the data from clinical trials of similar size. As such, we have developed a standards document outlining methods for conducting VCT, storing VCT results (intermediate and final), and communicating these image data and associate metadata between VCT components. In this course, we will use our experience in conducting large-scale VCT to encourage those new to the field to adopt VCT methods and to aid those already conducting VCT. The course will have applicability to VCT for designing new medical imaging equipment and methods, to use VCT data for prototyping and/or complementing the conduct of real clinical trials, and for preparing VCT data for regulatory approvals of new systems and methods.
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