A minimally invasive lens-free computational microendoscope

Area of Science:

• Biomedical Engineering
• Optical Imaging
• Computational Photography

Background:

• Ultra-miniaturized microendoscopes are crucial for minimally invasive biomedical applications, enabling deep brain imaging in animals.
• Conventional microendoscopes often use distal microlenses, which can cause aberrations and limit the field of view as they shrink.
• Existing variable focusing microendoscopes typically require complex, heavy, and actuated distal components.

Purpose of the Study:

• To develop a novel, actuation-free, lensless microendoscopy technique.
• To overcome the limitations of conventional lens-based microendoscopes, such as aberrations and restricted fields of view.
• To improve the space-bandwidth product and enable advanced imaging capabilities like refocusing and color resolution.

Main Methods:

• A distal lens-free approach utilizing a single pseudorandom spatial mask at the end of a multicore fiber.
• Implementation of computational image recovery algorithms to reconstruct images.
• Demonstration of color-resolved imaging and refocusing across multiple depth planes from a single acquired frame.

Main Results:

• The lensless microendoscope achieved a threefold increase in space-bandwidth product compared to optimal lens-based systems.
• The system successfully performed color-resolved imaging.
• Variable refocusing to 11 distinct depth planes was achieved without any actuated components.

Conclusions:

• The developed lens-free microendoscopy approach offers a significant advancement over traditional lens-based methods.
• This actuation-free technique enhances imaging performance and simplifies microendoscope design for biomedical applications.
• Computational image recovery combined with a spatial mask provides a powerful platform for future microendoscope development.