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1 March 2019 Simulation pipeline for virtual clinical trials of dermatology images
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Abstract
Skin cancer is the most common cancer in the US; one in five Americans will develop it by the age of 70. Early diagnosis offers more favorable treatment options; currently available diagnostics, however, shows large readerdependence. The simulation approach (virtual trials) to development and validation offers advantages in terms of quantitative and objective assessment of system performance in the design of novel imaging methods, and validation of clinical trial designs prior to execution of real clinical trials. We have designed a pipeline for performing Virtual Clinical Trials of optical imaging of skin lesions. This pipeline includes modules to simulate healthy skin and subcutaneous tissue, to create skin lesions and insert those in the skin models, and to simulate the acquisition of optical images resulting in simulated/virtual images of skin. The last module of the pipeline performs virtual reading of simulated images, which is based on the clinical task-based performance analysis. The physical properties of the skin and lesions used in our simulations were selected to represent clinically plausible conditions. Skin lesion images were simulated assuming the ambient white light, and a linear camera model. We have utilized the standards for optimal data representation based upon the XML schema, adopted from the VCT pipeline developed for breast imaging research. This paper describes the principles used for designing the proposed VCT pipeline and presents preliminary simulation results, including visual and quantitative evaluation. Integration of pipeline modules and its validation is ongoing.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Varun Vasudev, Bastian Piepers, Andrew D. A. Maidment, Tom Kimpe, Ljiljana Platisa, Wilfried Philips, and Predrag R. Bakic "Simulation pipeline for virtual clinical trials of dermatology images", Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109482D (1 March 2019); https://doi.org/10.1117/12.2512204
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