FURI | Spring 2022

Using Batched Rays to Enable Higher Resolution Reconstruction of Computed Tomography Images

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In our work, we tried to enable the reconstruction of high-resolution computed tomography (CT) images using implicit neural networks which usually require access to large amounts of graphics processing unit (GPU) memory. We propose a new ray-sampling technique that enables high-resolution reconstruction using INRs. Our approach uses a random batch of rays in each training iteration and therefore enables the computation to be done on a single GPU, and consequently democratizes the need for access to a big cluster of GPUs. In future work, the method can be expanded to 3D applications of computed tomography.

Student researcher

Ali Almuallem

Ali Almuallem

Computer science

Hometown: Safwa, Eastern Province, Saudi Arabia

Graduation date: Spring 2023