This paper describes a software system currently being developed at Clemson University in which a client provides recently obtained data to a remote server running a compute-intensive algorithm. To improve performance and speed up delivery of the results, the server distributes the data among multiple sub-server processors and assembles partial output from each processor into a coherent whole before sending the final results to the client. To demonstrate the
capabilities of the system, a specific application is presented in this paper: a fluorescence image reconstruction system for breast cancer detection. An experimental instrument optically scans the patient’s breast and generates some files of experimental data which are then sent to the server via the web. The data is processed by the numerical finite-element based algorithm running in parallel on a server and several sub-servers at Clemson. The algorithm is based on a set of coupled diffusion equations which are used to describe the propagation of excitation and fluorescent emission light in multiply scattering media (such as a breast). The algorithm reconstructs the fluorescence image of the breast in parallel. The resulting fluorescence lifetime and quantum yield mapping data can be sent back to the doctor for image display and analysis. This paper describes the numerical algorithm briefly and the software system which uses Java servlets to collect the data from the client and remote method invocation (Java RMI) to distribute the data to multiple processors.
The output of the numerical algorithm, combined with the corresponding finite element mesh information, are input into
a mathematical software package called Matlab which is used to produce the final images. Experiments are performed using indocyanine green (ICG) dye and tissue-like phantoms in both single- and multi-target configurations. Phantom experimental results of both lifetime and quantum yield are shown in this paper. Future work includes a refinement of the algorithm to incorporate adaptive mesh techniques. The expectation is that such techniques will improve the accuracy of the reconstructed images.
3D images of human subjects are, today, easily obtained using 3D wholebody scanners. 3D human images can provide static information about the physical characteristics of a person, information valuable to professionals such as clothing designers, anthropometrists, medical doctors, physical therapists, athletic trainers, and sculptors. Can 3D human images can be used to provide e more than static physical information. This research described in this paper attempts to answer the question by explaining a way that animated sequences may be generated from a single 3D scan. The process stars by subdividing the human image into segments and mapping the segments to those of a human model defined in a human-motion simulation package. The simulation software provides information used to display movement of the human image. Snapshots of the movement are captured and assembled to create an animated sequence. All of the postures and motion of the human images come from a single 3D scan. This paper describes the process involved in animating human figures from static 3D wholebody scans, presents an example of a generated animated sequence, and discusses possible applications of this approach.
KEYWORDS: Image segmentation, 3D scanning, 3D metrology, Scanners, 3D image processing, Software development, Image analysis, Control systems, Neck, Manufacturing
Reliable 3D wholebody scanners which output digitized 3D images of a complete human body are now commercially available. This paper describes a software package, called 3DM, being developed by researchers at Clemson University and which manipulates and extracts measurements from such images. The focus of this paper is on tilted planes, a 3DM tool which allows a user to define a plane through a scanned image, tilt it in any direction, and effectively define three disjoint regions on the image: the points on the plane and the points on either side of the plane. With tilted planes, the user can accurately take measurements required in applications such as apparel manufacturing. The user can manually segment the body rather precisely. Tilted planes assist the user in analyzing the form of the body and classifying the body in terms of body shape. Finally, titled planes allow the user to eliminate extraneous and unwanted points often generated by a 3D scanner. This paper describes the user interface for tilted planes, the equations defining the plane as the user moves it through the scanned image, an overview of the algorithms, and the interaction of the tilted plane feature with other tools in 3DM.
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