Abstract #4887

DeepSPIO: A SPIO particles quantification method using Deep Learning

Gabriel della Maggiora^1,2,3, Carlos Castillo-Passi^1,2,3, Qiu Wenqi⁴, Masaki Sekino⁴, Carlos Milovic^1,2,3, and Pablo Irarrazaval^1,2,3,5

¹Department of Electrical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, ²Biomedical Imaging Center, Pontificia Universidad Católica de Chile, Santiago, Chile, ³Millennium Nucleus for Cardiovascular Magnetic Resonance, Santiago, Chile, ⁴Department of Bioengineering, School of Engineering, University of Tokyo, Tokyo, Japan, ⁵Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

In this study we propose a method to quantify the distribution of Super Paramagnetic Iron Oxide (SPIO) particles with MRI. This task is particularly challenging due to the extreme distortion that these particles produce in the image. Our method is based on a supervised feed-forward deep learning model. The estimation of total quantity of SPIO was in the order of 9% error. This is potentially useful for detecting breast cancer metastasis by identifying residual particles in the breast and eventually other organs.

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