Confocal endomicroscopy provides tools for in vivo imaging of human cell architecture endoscopically. These technologies are a tough challenge since multiple trade-offs have to be overcome: resolution versus field of view, dynamic versus stability, contrast versus low laser power or low contrast agent doses. Many difficult clinical applications, such as lung, bile duct, urethral imaging and NOTES applications, need to optimize miniaturization, resolution, frame rate and contrast agent dose simultaneously. We propose one solution based on real-time video image processing to efficiently address these trade-offs. Dynamic imaging provides a flow of images that we process in real time. Images are aligned using efficientalgorithms specifically adapted to confocal devices. From the displacement that we find across the images, instantaneous velocities are computed and used to compensate for motion distortions. All images are stitched together onto the same reference space and displayed in real-time to reconstruct an image of the entire surface explored during the clinical procedure. This representation brings both stability and an increased field of view. Moreover, because a given area can be imaged by several frames, the contrast can be improved using temporal adaptive averaging. Such processing enhances the visualization of the video sequence, overcoming most classical trade-offs. The stability and increased field of view help the clinician better focus his attention on his practice which improves the patient benefit. Our tools are currently evaluated in a multicenter clinical trial to assess the improvement of the clinical practice.
This paper presents a novel fibered confocal reflectance microscopy system (FCRM) specifically designed for the medical observation of biological tissues in vivo and in situ, in real time, at the cellular level: the R-600. Reflectance imaging is based on the refraction index difference between biological components while confocal imaging allow to perform the optical sectioning slice in-depth inside the tissues. The R-600 is based on a proximal scanning system, coupled with a 7 mm diameter probe made of tens of thousands of flexible optical fibers allowing in situ imaging, associated with a dedicated software performing real-time control and image processing. The R-600 provides 12 frames per second at an optical imaging depth of 30 microns, with a high lateral resolution, 1 micron, an axial resolution of 2 microns in a field of view 160 microns in diameter.
Thanks to the miniaturization of the optical probe, unprecedented accessibility is made possible in organs such as the cervix or the otolaryngological sphere, in a completely non-invasive fashion. The aim of FCRM is to perform optical biopsy. As a first step towards this goal, we present here results obtained in vivo and in real-time on a human mouth , assessing the ability of the R-600 to perform rapid morphologic examination. Subcellular structures such as nuclei and membranes can be clearly distinguished on the images. Further miniaturization opens perspectives for an integrated endoscope-compatible system with broad medical applications.
The digital subtraction angiography (DSA) method is not directly applicable to cardiovascular sequences because of the anatomy motion. We have developed a simple cardiovascular extension of DSA that updates the mask in real time rather than applying the same mask on the whole sequence. The algorithm uses a velocity based segmentation to discriminate vessels and background. This discrimination is possible because of the cardiovascular sequences fundamental property of faster vessel motion compared to the background motion. The real time mask estimation is done as a recursively implemented generalized maximum operation over the sequence. This operation yields a sequence of masks which is subtracted from the original sequence. The algorithm is causal and can therefore be implemented in real time acquisition systems. We have applied it to x-ray fluoroscopic and radiographic cardiovascular sequences obtaining a nearly DSA-quality sequences with substantially improved vessel contrast. The algorithm de facto provides a simple cardia specific motion detection method which can be used in noise reduction algorithms. The recursive background estimation approach can be generalized to other cardiac imaging modalities.
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