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Results for “Image Interpretation, Computer-Assisted/methods”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Composite x-ray image assembly for large-field digital mammography with one- and two-dimensional positioning of a focal plane array

To demonstrate the feasibility of a novel large-field digital mammography technique, a 1024 x 1024 pixel Loral charge-coupled device (CCD) focal plane array (FPA) was positioned in a mammographic field with one- and two-dimensional scan sequences to obtain 950 x 1800 pixel and 3600 x 3600 pixel composite images, respectively. These experiments verify that precise positioning of FPAs produced seamless composites and that the CCD mosaic concept has potential for high-resolution, large-field imaging. The proposed CCD mosaic concept resembles a checkerboard pattern with spacing left between the CCDs for the driver and readout electronics. To obtain a complete x-ray image, the mosaic must be repositioned four times, with an x-ray exposure at each position. To reduce the patient dose, a lead shield with appropriately patterned holes is placed between the x-ray source and the patient. The high-precision motorized translation stages and the fiber-coupled-scintillating-screen-CCD sensor assembly were placed in the position usually occupied by the film cassette. Because of the high mechanical precision, seamless composites were constructed from the subimages. This paper discusses the positioning, image alignment procedure, and composite image results. The paper only addresses the formation of a seamless composite image from subimages and will not consider the effects of the lead shield, multiple CCDs, or the speed of motion.

Mammography/methods/statistics & numerical data↗

Use of multiresolution wavelet feature pyramids for automatic registration of multisensor imagery

The problem of image registration, or the alignment of two or more images representing the same scene or object, has to be addressed in various disciplines that employ digital imaging. In the area of remote sensing, just like in medical imaging or computer vision, it is necessary to design robust, fast, and widely applicable algorithms that would allow automatic registration of images generated by various imaging platforms at the same or different times and that would provide subpixel accuracy. One of the main issues that needs to be addressed when developing a registration algorithm is what type of information should be extracted from the images being registered, to be used in the search for the geometric transformation that best aligns them. The main objective of this paper is to evaluate several wavelet pyramids that may be used both for invariant feature extraction and for representing images at multiple spatial resolutions to accelerate registration. We find that the bandpass wavelets obtained from the steerable pyramid due to Simoncelli performs best in terms of accuracy and consistency, while the low-pass wavelets obtained from the same pyramid give the best results in terms of the radius of convergence. Based on these findings, we propose a modification of a gradient-based registration algorithm that has recently been developed for medical data. We test the modified algorithm on several sets of real and synthetic satellite imagery.

Evaluation Studies↗

Automated quantification of mitral valve regurgitation based on normalized centerline velocity distribution

Previous echocardiographic techniques for quantifying valvular regurgitation are limited by factors including uncertainties for orifice location and a hemispheric convergence assumption that often results in over- and underestimation of flow rate and regurgitant orifice area. Using computational fluid dynamics simulations, these factors were eliminated, allowing a more accurate assessment of regurgitation. A model was developed to allow automated quantification of regurgitant orifice diameter based on the centerline velocity data available from color M-mode echocardiography. The model, validated using in vitro unsteady flow data, demonstrated improved accuracy for orifice diameter (y=0.95x + 0.38, r=0.96) and volume (y=1.18x - 4.72, r=0.93).

NASA Program Biomedical Research and Countermeasur↗