Dr. Predrag R. Bakic
Associate Professor at Univ of Pennsylvania Health System
SPIE Involvement:
Author | Instructor
Publications (68)

SPIE Journal Paper | 14 June 2019
JMI Vol. 6 Issue 02
KEYWORDS: Breast, Image processing, Mammography, Statistical analysis, Image filtering, Virtual reality, Binary data, Tissues, Imaging systems, Spatial frequencies

Proceedings Article | 1 March 2019
Proc. SPIE. 10948, Medical Imaging 2019: Physics of Medical Imaging
KEYWORDS: Signal to noise ratio, Breast, Fluctuations and noise, Sensors, Image processing, X-rays, Reconstruction algorithms, X-ray detectors, Systems modeling, Digital breast tomosynthesis

Proceedings Article | 1 March 2019
Proc. SPIE. 10948, Medical Imaging 2019: Physics of Medical Imaging
KEYWORDS: Imaging systems, Dermatology, Skin, Skin cancer, Tissue optics, Breast imaging, Clinical trials

Proceedings Article | 1 March 2019
Proc. SPIE. 10948, Medical Imaging 2019: Physics of Medical Imaging
KEYWORDS: Mathematical modeling, Breast, Sensors, X-rays, Computer simulations, Medical imaging, Virtual reality, X-ray detectors, Digital breast tomosynthesis, Clinical trials

Proceedings Article | 1 March 2019
Proc. SPIE. 10948, Medical Imaging 2019: Physics of Medical Imaging
KEYWORDS: Breast, Visualization, Tissues, Sensors, X-rays, Tomography, Mammography, X-ray imaging, Digital breast tomosynthesis

Showing 5 of 68 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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