Ultrafast CMOS image sensors and data-enabled super-resolution for multimodal radiographic imaging and tomography

TL;DR

This paper reviews advances in ultrafast CMOS image sensors and neural network-based post-processing to enable high-resolution, multimodal radiographic imaging and tomography with sub-pixel accuracy.

Contribution

It introduces the integration of novel CMOS sensor designs with neural network post-processing for super-resolution in radiographic imaging.

Findings

Enhanced image resolution through neural network post-processing.

Potential for ultrafast, high-resolution multimodal imaging.

Combines sensor innovation with data-driven techniques.

Abstract

We summarize recent progress in ultrafast Complementary Metal Oxide Semiconductor (CMOS) image sensor development and the application of neural networks for post-processing of CMOS and charge-coupled device (CCD) image data to achieve sub-pixel resolution (thus $super$-$resolution$). The combination of novel CMOS pixel designs and data-enabled image post-processing provides a promising path towards ultrafast high-resolution multi-modal radiographic imaging and tomography applications.