Automatic motion compensation for structured illumination endomicroscopy using a flexible fiber bundle

Significance: Confocal laser scanning enables optical sectioning in clinical fiber bundle endomicroscopes, but lower-cost, simplified endomicroscopes use widefield incoherent illumination instead. Optical sectioning can be introduced in these simple systems using structured illumination microscopy (SIM), a multiframe digital subtraction process. However, SIM results in artifacts when the probe is in motion, making the technique difficult to use in vivo and preventing the use of mosaicking to synthesize a larger effective field of view (FOV). Aim: We report and validate an automatic motion compensation technique to overcome motion artifacts and allow generation of mosaics in SIM endomicroscopy. Approach: Motion compensation is achieved using image registration and real-time pattern orientation correction via a digital micromirror device. We quantify the similarity of moving probe reconstructions to those acquired with a stationary probe using the relative mean of the absolute differences (MAD). We further demonstrate mosaicking with a moving probe in mechanical and freehand operation. Results: Reconstructed SIM images show an improvement in the MAD from 0.85 to 0.13 for lens paper and from 0.27 to 0.12 for bovine tissue. Mosaics also show vastly reduced artifacts. Conclusion: The reduction in motion artifacts in individual SIM reconstructions leads to mosaics that more faithfully represent the morphology of tissue, giving clinicians a larger effective FOV than the probe itself can provide

Online robust endomicroscopy video mosaicking using robot prior

International audienceThis paper discusses the development of a mosaicking algorithm for building large and high resolution confocal images. Due to the nature of optics and vision systems in general, there is still a dilemma between choosing a wide field-of-view (FOV) and high-resolution. The most accepted solution is to opt for a high-resolution optics and expand the FOV algorithmically thanks to mosaicking approaches. The study reported in this paper consists of online and real-time construction of large mosaics using individual confocal images with a micrometer resolution. These individual images are provided by a confocal laser endomicroscopy system which can grab in vivo real-time images through a minimally invasive access. The acquisition of the confocal images is achieved by moving the imaging probe on the studied sample surface with a constant contact between the probe and the sample. The mosaicking algorithm proposed in this paper deals with the combination of both the robot inputs and the image registrations. The proposed method has demonstrated very promising performances in terms of accuracy and robustness with regard to image noise (poor image quality or loss of contact between the probe and the sample) as well as misregistration issues. Experiments carried out with a highly accurate robotic system and a ground truth obtained by conventional optical microscopy demonstrate the robustness of the proposed approach