At NASA Goddard Space Flight Center, we have been developing spaceborne lidar instruments for space sciences. We have successfully flown several missions in the past based on mature diode pumped solid-state laser transmitters. In recent years, we have been developing advanced laser technologies for applications such as laser spectroscopy, laser communications, and interferometry. In this article, we will discuss recent experimental progress on these systems and instrument prototypes for ongoing development.

Bronchoscopy is a major step in lung cancer staging. To perform bronchoscopy, the physician uses a procedure plan, derived from a patient's 3D computed-tomography (CT) chest scan, to navigate the bronchoscope through the lung airways. Unfortunately, physicians vary greatly in their ability to perform bronchoscopy. As a result, image-guided bronchoscopy systems, drawing upon the concept of CT-based virtual bronchoscopy (VB), have been proposed. These systems attempt to register the bronchoscope's live position within the chest to a CT-based virtual chest space. Recent methods, which register the bronchoscopic video to CT-based endoluminal airway renderings, show promise but do not enable continuous real-time guidance. We present a CT-video registration method inspired by computer-vision innovations in the fields of image alignment and image-based rendering. In particular, motivated by the Lucas-Kanade algorithm, we propose an inverse-compositional framework built around a gradient-based optimization procedure. We next propose an implementation of the framework suitable for image-guided bronchoscopy. Laboratory tests, involving both single frames and continuous video sequences, demonstrate the robustness and accuracy of the method. Benchmark timing tests indicate that the method can run continuously at 300 frames/s, well beyond the real-time bronchoscopic video rate of 30 frames/s. This compares extremely favorably to the ≥ 1 s/frame speeds of other methods and indicates the method's potential for real-time continuous registration. A human phantom study confirms the method's efficacy for real-time guidance in a controlled setting, and, hence, points the way toward the first interactive CT-video registration approach for image-guided bronchoscopy. Along this line, we demonstrate the method's efficacy in a complete guidance system by presenting a clinical study involving lung cancer patients.

The assessment of lung cancer involves off-line threedimensional (3D) computed-tomography (CT) image assessment followed by live bronchoscopy. While standard bronchoscopy provides live video of information inside the lung airways, it does not give any information outside the airways. This results in a low procedure success rate. The success rate can be improved if the physician receives 3D CT-based image guidance. We describe a fast robust method that provides 3D CT-based image guidance during live bronchoscopy. The method enables a continuous registration between the 3D CT image space and the real bronchoscopic video. At a top level, it involves an interleaving of continuous video tracking and CT-video fine registration. During video tracking, the bronchoscope’s 3D motion is estimated using a point-based 3D-2D pose estimation method. Registration is performed via a warpingbased Gauss-Newton method that uses a normalized crosscorrelation- based cost for measuring similarity between the bronchoscopic video and CT image data. The method operates at a real-time rate of 10 frames per second, which is over an order of magnitude faster than past approaches. This real-time performance enables live guidance during a procedure. The method is incorporated into a computerbased system for image-guided bronchoscopy and has been applied to human lung-cancer patients. Results are presented for a phantom and lung-cancer patients. Keywords: 3D medical imaging, video tracking, image registration, virtual endoscopy, image-guided surgery

Two extended-range phase detectors (PDs), including the tanlock PD, are derived from the iterated extended Kalman filter. Fast converging recursion and concise initialization equations are given. Simulations of a Wiener phase process and a first-order Markov FM process show slightly reduced mean-square error near threshold and faster phase acquisition than a sinusoidal PD.>

This paper presents a simple phase tracking and demodulation algorithm which uses a state model of the phase process to unwrap and track noisy phase measurements. The wrapped phase measurements are compared with the predictions of three Kalman filters to obtain distance metrics for Viterbi decoding of a trinary unwrapping symbol sequence. The algorithm is used to demodulate an FM signal and the results are compared with those of a first order PLL and the MAP frequency estimation technique of Tufts and Francis [3].