I.Q. Project Highlight: Medical Imaging
Despite the rapid progress in biomedical optics in the past decade, a need for ever-greater speed, resolution, and depth of imaging persists. For example, tissue sectioning with confocal reflectance microscopy to evaluate cellular and sub-cellular features in vivo is a popular method but has limitations. This technique can produce 2D images with 500 x 500 pixels in around 0.1 seconds and can section the upper layers of skin and, after a couple of decades of research, it is coming into more widespread clinical use. However, this technique requires point-scanning of the optical system with mechanical components and complicated optical relays. Because of the small number of pixels, several images must be stitched together, which can lead to distortion due to lighting changes or patient movement.
This is just one example of the need for high-information-content images with high resolution and a large field-of-view in three dimensions. Thus, Professor DiMarzio proposes a project that aims to develop a new type of microscopy technique called random structured illumination microscopy. This technology would build on advances in structured illumination over the past decade and more recent developments in Fourier ptychography, a super-resolution imaging modality for gigapixel microscopy, to address problems with high-content multimodal imaging in biophotonics.
The research could enable full-field optical sectioning at high-resolution and high-throughput and to digitally extract 3D information. It may hold the potential to achieve many of the same advantages of confocal microscopy at reduced complexity and cost.
This project immediately demonstrates two biomedical applications. First, it will show in-vivo skin imaging with a wide field-of-view, subcellular resolution and optical sectioning. The proposed technology unifies 3D sectioning, and structured illumination microscopy under the same computational recovery framework.
Second, using two cameras, it will simultaneously image samples of cellular structure and melanin in skin with no staining or tissue processing required, making it useful for both in-vivo and ex-vivo imaging. Image reconstruction on both channels will use a single computational framework that will provide, super-resolution imaging, wide field-of-view, and long depth-of-focus.
Professor DiMarzio envisions the broader impacts of this research being greatly significant for many fields of biomedical research, as well as clinical applications as there is a great need for high-content 3D tissue sectioning. Also, the prospect of high-content multicolor fluorescence imaging could open up exciting opportunities for computational multispectral imaging.
