We present a method to track vessels in angiography [contrast filled vessels in two-dimensional (2-D) x-ray fluoroscopy]. Finding correspondence of a vessel tree from consecutive angiogram frames provides significant value in computer-aided clinical applications such as fast vessel tree segmentation, three-dimensional (3-D) vessel topology reconstruction from corresponding centerlines, cardiac motion understanding, etc. However, establishing an accurate vessel tree correspondence (vessel tree tracking) is a nontrivial problem due to nonlinear periodic cardiac and breathing motion in 2-D views, foreshortening, false bifurcations due to 3-D to 2-D projection, occlusion from other anatomies, etc. The vessel tree is represented by BSpline curves. The control points of the BSpline curves are landmarks that are the tracking targets. Our method maximizes the appearance similarity while preserving the vessel structure. A directed acyclic graph (DAG) is employed to represent the appearance and shape structure of the vessel tree: nodes from the DAG encode the appearance of the vessel tree landmarks, and the edges encode the relative locations between landmarks. The vessel tree tracking problem turns into finding the most similar tree from the DAG in the next frame, and it is solved using an efficient dynamic programming algorithm. We performed evaluations on 62 x-ray angiography sequences (above 1000 frames). Experiment results show our algorithm is robust to these challenges and delivers better performance, compared to four existing methods.
Photocopies of the ballots challenged in the 2008 Minnesota elections, which constitute a public
record, were scanned on a high-speed scanner and made available on a public radio website. The
PDF files were downloaded, converted to TIF images, and posted on the PERFECT website. Based
on a review of relevant image-processing aspects of paper-based election machinery and on
additional statistics and observations on the posted sample data, robust tools were developed for
determining the underlying grid of the targets on these ballots regardless of skew, clipping, and
other degradations caused by high-speed copying and digitization. The accuracy and robustness of
a method based on both index-marks and oval targets are demonstrated on 13,435 challenged
ballot page images.
Large-scale stereo vision sensor is of great importance in the measurement for large free-form surface. The intrinsic
parameters of cameras and the structure parameters of the stereo vision sensor should be calibrated beforehand.
Traditional methods are mainly based on planar and 3D targets which are expensive and difficult to manufacture,
especially for large dimension ones. A calibration method for stereo vision sensor based on one-dimensional targets is
proposed. First random place two 1D targets, and acquire multiple images of the targets from different angles of view
with camera. Solve the intrinsic parameters of camera with the constraint that the spatial angle of the two ID target are
constant. Then set up the stereo vision sensor with two calibrated cameras, and acquire multiple images of a 1D target of
unknown motion. Based on the constraint of the known distance between two feature points on the target, estimate the
initial value of the structure parameters with linear method and the precise structure parameters of stereo vision sensor
with non-linear optimization method by setting up the minimizing function involving the scale factors. Experimental
results show that, the measurement precision of the stereo vision sensor is 0.052mm, with the working distance of
3500mm and the measurement scale of 4000mm × 3000mm. The method proposed is proved to be suitable for field
calibration of stereo vision sensor in application of large-scale measurement for its easy operation and high efficiency.
Being independent of platforms and languages is the key point of Microsoft .NET framework which will be the base of development of numerous softwares in the future. Measurement applications base on .Net framework possess advantages related on its portability, applicability and compatibility. This paper discusses how to construct a remote measurement & analysis platform based on .NET framework using NI Measurement Studio. To solve the question, some methods are introduced: Long distance controlling and monitoring via remote object methods calling based on Microsoft .NET remoting framework, High speed real-time mass data sharing based on data socket transfer protocol (DSTP) technology provided by NI Measurement Studio, and remote measurement system based on the combination of .NET remoting and DSTP. Methods above are applied to introduce an efficaciously way to develop a remote measurement platform and parallel measurement server platform in .NET framework with Measurement Studio. What's more, three application design of remote measurement platform are introduced: Remote experiment system of automatic control theory, Distributed medical consultation system and Meteorological satellite nephogram distributed processing platform.
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