We propose a formal model of Cross-Language Information Retrieval that does not rely on either query translation or document translation. Our approach leverages recent advances in language modeling to directly estimate an accurate topic model in the target language, starting with a query in the source language. The model integrates popular techniques of disambiguation and query expansion in a unified formal framework. We describe how the topic model can be estimated with either a parallel corpus or a dictionary. We test the framework by constructing Chinese topic models from English queries and using them in the CLIR task of TREC9. The model achieves performance around 95% of the strong mono-lingual baseline in terms of average precision. In initial precision, our model outperforms the monolingual baseline by 20%. The main contribution of this work is the unified formal model which integrates techniques that are essential for effective Cross-Language Retrieval.

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Real time flat panel detectors based on amorphous selenium (a-Se) have demonstrated to be the most advanced technology for direct conversion X-ray imaging in various medical applications. In continuation of real time detector development, ANRAD Corporation introduce in this paper a large size 14" x 14" active area detector built with an amorphous selenium (a-Se) converter coated on a TFT array. This new detector is a scaled up version of the 9" x 9" presented last year based on a TFT array with 150 µm x 150 µm pixel and a 1000 µm thick a-Se PIN structure operated at 10V/µm. DQE(f=0) measurements were performed in low dose range and demonstrated to be in agreement with a linear model including 2500e of electronic noise. It is also shown that the spatial resolution (MTF) could be controlled by selenium coating process and can almost reach the theoretical limit defined by the pixel pitch. Finally, the first 14" x 14" chest image is presented.

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As amorphous selenium based flat panel detectors gain more interest for direct, real-time x-ray imaging, we report in this paper the performance of such a detector by ANRAD Corporation. This new detector is based on a 1536 x 1536 array of amorphous silicon TFT pixels coupled with a 1000 m selenium converter biased at 10 V/rim. Each 150 tm x 150 tm pixel is made of a thin film transistor (TFT), a storage capacitor and a collecting electrode having a geometrical fill factor of 77 % and an effective fill factor of nearby 1 00 %.New TFT architecture and high speed electronics allow operation of this new detector under a large range of conditions from low dose fluoroscopy (few pR/frame) to DR and it supports frame rates from single shot to 60 fps. Image lag following x-ray excitation was measured to be very low.Key imaging parameters for this real time x-ray detection system such as: detective quantum efficiency (DQE), signal to noise ratio (SNR) and modulation transfer function (MTF) were measured. These results together with frames extracted from a low dose fluoroscopy sequence and an anthropomorphic phantom image will be presented.The measurements show that the dynamic performance of this new detector is very well suited for real time imaging in fluoroscopic and/or cardiac applications.