Prof. Nimesha Ranasinghe Profile

Prof. Nimesha Ranasinghe

at The Univ. of Maine

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Proceedings Article | 3 April 2023 Presentation + Paper

Toward three-dimensional (3D) human biomimetic models for x-ray radiation dosimetry and biomedical image analysis

Avery Gosselin, Nimesha Ranasinghe, Terry Yoo

Proceedings Volume 12466, 124661B (2023) https://doi.org/10.1117/12.2655789

KEYWORDS: 3D modeling, X-rays, Attenuation, Fused deposition modeling, Dosimetry, 3D printing, 3D image processing

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Studying the impact of diagnostic x-ray dose on human tissue has historically been problematic; it is unethical to subject patients to unnecessary procedures and impossible to implant dosimetry sensors in vivo. Further, the rapid growth of machine learning in early disease detection is creating enormous demand for radiological screening data. We are adapting additive manufacturing methods to create x-ray CT phantoms with smooth gradients of X-ray attenuation coefficients, mimicking invasive disease, edema, and perfusion events. Using a Crane Quad fused deposition modeling printer equipped with an M3D QuadFusion print head capable of blending materials from up to four different filaments, we are constructing solid models from mixed media that have x-ray attenuation characteristics that mimic human tissue when imaged with a CT scanner. Our work includes exploring the design and production of solid models with human x-ray characteristics with embedded dosimetry sensors. Using four different filaments, Polylactic Acid (PLA), lightweight PLA, and PLA copper-filled and bronze-filled composite filaments, we constructed phantoms with progressive densities. We had the resulting phantoms scanned with three different x-ray energies and analyzed the resulting signatures of Hounsfield Units. We demonstrate our ability to express gradients of X-ray attenuation in solid models. Lastly, we have also produced models of 2D images. This work is the first step in generating reproducible phantoms that mimic the radiological responses of human anatomy and pathology. Future studies will linearize our printing scale and later embed photodiode-based dosimetry sensors in 3D phantoms of the human body.

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