Image rendering of spatial light modulators (SLMs) is often degraded by various effects. Some efficient methods to get around nonuniformity, nonlinearity, and remanence and improve image rendering are presented. Optical laboratory results are presented for an analog ferroelectric liquid-crystal SLM using a high-speed camera. Focus is made on a preprocessing compensation method, using a spatial-dependant correction table. A high-speed "on-the-fly" implementation is also suggested.
KEYWORDS: Digital signal processing, Reconstruction algorithms, Optoelectronics, Computed tomography, Distortion, Signal to noise ratio, Prototyping, Electro optical modeling, Optical engineering, Surgery
This paper presents a hybrid processor dedicated to the reconstruction algorithm in multislice spiral computed tomography. The described architecture focuses on the advanced single-slice rebinning algorithm, which is a basic 2-D-to-3-D rebinning method developed in 2000. The hybrid processor is composed of four cores (rebinning, filtering, backprojection, and interpolation), including an optical processor for the backprojection. The system is modeled with a multi-abstraction-level approach. The model permits one to evaluate the dependence of both the reconstruction quality and the computation time with different parameters (reconstruction parameters, device features, etc.). It is used in a substantial simulation process allowing the identification of predominant degradation sources and the evaluation of their impact, and leading to the specification of each subsystem. A prototype of each core has been realized. The optical core has been identified as the most critical element, although results are very encouraging. This study has underlined that a computational speedup of more than two orders of magnitude could be reached. This is expected to be very useful for future challenging applications in the field of image-guided computer-assisted surgery, where the reconstruction rate would become critical to ensuring acceptable responsiveness.
Filtered backprojection (FBP) is the basic operation of image reconstruction algorithms in tomography. It is widely used but very time-consuming. We propose a new implementation, based on an optoelectronic architecture, providing a speedup of about two orders of magnitude over a classical digital implementation. The realization of the optical core, based on a rotated Dove prism, requires careful attention in order to ensure good image quality. This aspect has been studied in simulation with a suitable model of the architecture, and in practice with an experimental setup. Results are very encouraging.
Most of the present high-speed light modulator technologies perform only binary modulation, which is not sufficient for visualization applications. A greyscale images could be obtained using temporal accumulation of binary images. This technique, known as temporal multiplexing, is applied without difficulties in applications with incoherent light (e.g. DMD video projectors). In coherent application, where the phase of the light is to take into account, temporal decomposition could introduce errors. In this paper, this point will be studied theoretically and with simulations on an optical image processor.
In this paper, we present the conception of a holographic combiner for an augmented reality Head Mounted Display (HMD) dedicated to surgical applications. The recording of this holographic component has been performed at the Laboratoire des Systemes Photoniques (LSP) in Strasbourg, France. We present in this paper two different approaches for the recording of such a component: one using plane waves, and the other using spherical waves. The setup linked to the first approach has been developed and built, so that measurments of the diffraction efficiency can be shown. For the other way of recording the holographic combiner, we have performed numerical simulations to find the best recording setup to fit our specifications.
In order to help hepatic surgery planning, an unsupervised method is needed to automate the delineation of liver tumors. Moreover, due to the large amount of images acquired by Computer Tomography Scanner (CT-Scan), the processing has to be fast for a clinical use. Current methods are based on filterings and have the drawback of being time consuming. In this paper, to reach the purpose of speed and quality, we propose a fast unsupervised method which is implementable on an opto-electronical processor. The proposed method is based on the expansion/compression paradigm and combines a multiresolution approach with the principal component analysis (PCA). The multiresolution representation is done by several Gaussian filterings. The compression of the expanded information is then achieved by only keeping the first PCA factorial image. Endly, the object of interest is detected and delineated using the standard valley thresholding technique which is applied to the first factorial image. For the delineation of liver tumors, regions of interest (ROI) containing tumors have been preliminary extracted before applying PCA. Experimental results obtained by the processing of difficult clinical cases show, according to the radiologist experts, that our method is able to efficiently delineate liver tumors. Because Gaussian filterings are time consuming when carried out on a digital processor, we propose to implement them on an optical correlator. Clinical cases have been processed using the resulting opto-electronical processor to show the feasibility of such an implementation.
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