Hughes introduces an open-source Python toolkit designed to enhance image quality from optical fiber bundle imaging systems, which are increasingly employed as ultra-thin endomicroscopic imaging probes in medical and biological applications.

Leveraging their miniature size (often less than 1mm in diameter, reaching as low as 0.1mm), fiber bundles enable the creation of miniaturized imaging devices. Notably, they are suitable for constructing endomicroscopes capable of high-resolution cellular imaging deep within the body through an endoscope. A growing range of imaging modalities, including confocal fluorescence microscopy, can be performed using fiber bundles. However, raw images acquired through fibers often exhibit poor quality, characterized by significant pixelation, distortions, non-uniform intensity, and lower resolution compared to conventional cameras. To mitigate these issues, various techniques involving bundle and core location, interpolation, normalization, and resolution enhancement have been developed. To date, these techniques have primarily existed as isolated, custom software solutions often limited to offline operation.

To address this, Hughes presents PyFibreBundle, a versatile Python library offering high-performance implementations of essential fiber bundle operations, including multi-frame resolution enhancement and mosaicking. Notably, these functionalities are demonstrated to run in real-time even on a Raspberry Pi system, making PyFibreBundle well-suited for deployment in low-cost medical imaging systems.

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