Design of on-chip coded X-ray sensors for high-confidence super-resolution radiological imaging

Robustness and confidence are crucial in super-resolution tasks for X-ray radiological imaging, both in terms of X-ray sensors and image processing techniques. Due to the extremely short wavelengths of X-rays, optical modulation in X-ray imaging systems is highly challenging. Consequently, single-image super-resolution techniques in computer vision have become a popular approach in medical imaging. However, these methods can lead to artifacts and the plasticity phenomenon, potentially compromising image quality and diagnostic accuracy. In this manuscript, we introduce an on-chip coded aperture design that is both cost-effective and helps overcome the additional constraints and limitations commonly found in traditional computational-imaging-based super-resolution X-ray systems. This design generates sub-pixel physical coding on X-ray sensors, and thus a three-dimensional (3D) computational decoding approach is presented that transforms the two-dimensional (2D) super-resolution reconstruction into a 3D compressed sensing problem. Unlike super-resolution restoration in computer vision, this problem can be mathematically solved to yield interpretable reconstructions under the constraints of the restricted isometry property. Our experimental results, complemented by qualitative analysis, demonstrate the superiority of our design in X-ray radiological imaging, effectively mitigating artifacts and the “plastic-like” appearance frequently associated with conventional super-resolution techniques.