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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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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-I-51: CT/MR Image Deformation: The Clinical Assessment QA in Target Delineation

Purpose: To study the deformation effects in CT/MR image registration of head and neck (HN) cancers. We present a clinical indication in guiding and simplifying registration procedures of this process while CT images possessed artifacts. Methods: CT/MR image fusion provides better soft tissue contrast in intracranial GTV definition with artifacts. However, whether the fusion process should include the deformation process is questionable and not recommended. We performed CT/MR image registration of a HN patient with tonsil GTV and nodes delineation on Varian Velocity™ system. Both rigid transformation and deformable registration of the same CT/MR imaging data were processed separately. Physician’s selection of target delineation was implemented to identify the variations. Transformation matrix was shown with visual identification, as well as the deformation QA numbers and figures were assessed. Results: The deformable CT/MR images were traced with the calculated matrix, both translation and rotational parameters were summarized. In deformable quality QA, the calculated Jacobian matrix was analyzed, which the min/mean/max of 0.73/0/99/1.37, respectively. Jacobian matrix of right neck node was 0.84/1.13/1.41, which present dis-similarity of the nodal area. If Jacobian = 1, the deformation is at the optimum situation. In this case, the deformation results have shown better target delineation for CT/MR deformation than rigid transformation. Though the root-mean-square vector difference is 1.48 mm, with similar rotational components, the cord and vertebrae position were aligned much better in the deformable MR images than the rigid transformation. Conclusion: CT/MR with/without image deformation presents similar image registration matrix; there were significant differentiate the anatomical structures in the region of interest by deformable process. Though vendor suggested only rigid transformation between CT/MR assuming the geometry remain similar, our findings indicated with patient positional variations, deformation registration is needed to generate proper GTV coverage, which will be irradiated more accurately in the following boost phase.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-AB-202-06: Quantitative Evaluation of Deformable Image Registration in MRI-Guided Adaptive Radiation Therapy

Purpose: To assess the performance of the deformable image registration algorithm used for MRI-guided adaptive radiation therapy using image feature analysis. Methods: MR images were collected from five patients treated on the MRIdian (ViewRay, Inc., Oakwood Village, OH), a three head Cobalt-60 therapy machine with an 0.35 T MR system. The images were acquired immediately prior to treatment with a uniform 1.5 mm resolution. Treatment sites were as follows: head/neck, lung, breast, stomach, and bladder. Deformable image registration was performed using the ViewRay software between the first fraction MRI and the final fraction MRI, and the DICE similarity coefficient (DSC) for the skin contours was reported. The SIFT and Harris feature detection and matching algorithms identified point features in each image separately, then found matching features in the other image. The target registration error (TRE) was defined as the vector distance between matched features on the two image sets. Each deformation was evaluated based on comparison of average TRE and DSC. Results: Image feature analysis produced between 2000–9500 points for evaluation on the patient images. The average (± standard deviation) TRE for all patients was 3.3 mm (±3.1 mm), and the passing rate of TRE<3 mm was 60% on the images. The head/neck patient had the best average TRE (1.9 mm±2.3 mm) and the best passing rate (80%). The lung patient had the worst average TRE (4.8 mm±3.3 mm) and the worst passing rate (37.2%). DSC was not significantly correlated with either TRE (p=0.63) or passing rate (p=0.55). Conclusions: Feature matching provides a quantitative assessment of deformable image registration, with a large number of data points for analysis. The TRE of matched features can be used to evaluate the registration of many objects throughout the volume, whereas DSC mainly provides a measure of gross overlap. We have a research agreement with ViewRay Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-209-04: Testing of Digital Image Receptors Using AAPM TG-150’s Draft Recommendations - Investigating the Impact of Different Processing Parameters

Purpose: To evaluate implementation of AAPM TG-150’s draft recommendations via a parameter study for testing the performance of digital image receptors. Methods: Flat field images were acquired from 9 calibrated digital image receptors associated with 9 new portable digital radiography systems (Carestream Health, Inc.) based on the draft recommendations and manufacturer-specified calibration conditions (set of 4 images at input detector air kerma ranging from 1 to 25 µGy). Effects of exposure response function (linearized and logarithmic), ‘Presentation Intent Type’ (‘For Processing’ and ‘For Presentation’), detector orientation with respect to the anode-cathode axis (4 orientations; 900 rotations per iteration), different ROI sizes (5×5–40×40 mm{sup 2}) and elimination of varying dimensions of image border (0 mm i.e., without boundary elimination to 150 mm) on signal, noise, signal-to-noise ratio (SNR) and the associated nonuniformities were evaluated. Images were analyzed in Matlab and quantities were compared using ANOVA. Results: Signal, noise and SNR values averaged over 9 systems with default parameter values in draft recommendations were 4837.2±139.4, 19.7±0.9 and 246.4±10.1 (mean ± standard deviation), respectively (at input detector air kerma: 12.5 µGy). Signal, noise and SNR showed characteristic dependency on exposure response function and on ‘Presentation Intent Type’. These values were not affected by ROI size and detector orientation, but analysis showed that eliminating the edge pixels along the boundary was required for the noise parameter (coefficient of variation range for noise: 72%–106% and 3%–4% without and with boundary elimination; respectively). Local and global nonuniformities showed a similar dependence on the need for boundary elimination. Interestingly, computed non-uniformities showed agreement with manufacturer-reported values except for noise non-uniformities in two units; artifacts were seen in images from these two units highlighting the importance of independent evaluations. Conclusion: The effect of different parameters on performance characterization of digital image receptors was evaluated based on TG-150’s draft recommendations.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1973

A method for digital image registration using a mathematical programming technique

A new algorithm based on a nonlinear programming technique to correct the geometrical distortions of one digital image with respect to another is discussed. This algorithm promises to be superior to existing ones in that it is capable of treating localized differential scaling, translational and rotational errors over the whole image plane. A series of piece-wise 'rubber-sheet' approximations are used, constrained in such a manner that a smooth approximation over the entire image can be obtained. The theoretical derivation is included. The result of using the algorithm to register four channel S065 Apollo IX digitized photography over Imperial Valley, California, is discussed in detail.

Yao, S. S.↗
NASA NTRS1977

On three-dimensional reconstruction of optically thin solar emission sources

Calculations are given for constructing the three dimensional distribution of optically thin EUV emission sources associated with solar active regions, from two dimensional observations (projections) recorded by the spectroheliograph on the OSO 7 satellite. The relation of the method to other image reconstruction methods is briefly discussed as well as the special requirements imposed in the solar case such as a knowledge of the true solar rotation function. A useful correlation criterion for establishing the physical validity of solutions is given.

Kastner, S. O.↗
NASA NTRS1976

Experimental examination of similarity measures and preprocessing methods used for image registration

The criterion used to measure the similarity between images and thus find the position where the images are registered is examined. The three similarity measures considered are the correlation coefficient, the sum of the absolute differences, and the correlation function. Three basic types of preprocessing are then discussed: taking the magnitude of the gradient of the images, thresholding the images at their medians, and thresholding the magnitude of the gradient of the images at an arbitrary level to be determined experimentally. These multitemporal registration techniques are applied to remote imagery of agricultural areas.

Svedlow, M.↗
NASA NTRS1979

Medical diagnosis system and method with multispectral imaging

A skin diagnosis system includes a scanning and optical arrangement whereby light reflected from each incremental area (pixel) of the skin is directed simultaneously to three separate light filters, e.g., IR, red, and green. As a result, the three devices simultaneously produce three signals which are directly related to the reflectance of light of different wavelengths from the corresponding pixel. These three signals for each pixel after processing are used as inputs to one or more output devices to produce a visual color display and/or a hard copy color print, for one usable as a diagnostic aid by a physician.

Anselmo, V. J.↗
NASA NTRS1985

Studies on the interference of wings and propeller slipstreams

The small disturbance potential flow theory is applied to determine the lift of an airfoil in a nonuniform parallel stream. The given stream is replaced by an equivalent stream with a certain number of velocity discontinuities, and the influence of these discontinuities is obtained by the method of images. Next, this method is extended to the problem of an airfoil in a nonuniform stream of smooth velocity profile. This model allows perturbation velocity potential in a rotational undisturbed stream. A comparison of these results with numerical solutions of Euler equations indicates that, although approximate, the present method provides useful information about the interaction problem while avoiding the need to solve the Euler equations.

Prabhu, R. K.↗
NASA NTRS2011

Split-screen display system and standardized methods for ultrasound image acquisition and multi-frame data processing

A standardized acquisition methodology assists operators to accurately replicate high resolution B-mode ultrasound images obtained over several spaced-apart examinations utilizing a split-screen display in which the arterial ultrasound image from an earlier examination is displayed on one side of the screen while a real-time "live" ultrasound image from a current examination is displayed next to the earlier image on the opposite side of the screen. By viewing both images, whether simultaneously or alternately, while manually adjusting the ultrasound transducer, an operator is able to bring into view the real-time image that best matches a selected image from the earlier ultrasound examination. Utilizing this methodology, dynamic material properties of arterial structures, such as IMT and diameter, are measured in a standard region over successive image frames. Each frame of the sequence has its echo edge boundaries automatically determined by using the immediately prior frame's true echo edge coordinates as initial boundary conditions. Computerized echo edge recognition and tracking over multiple successive image frames enhances measurement of arterial diameter and IMT and allows for improved vascular dimension measurements, including vascular stiffness and IMT determinations.

Selzer, Robert H.↗
NASA NTRS2022

Test methods for image-based information in next-generation manufacturing

Typical control designs in the process systems engineering literature have assumed that the primary sensing methodologies are traditional instruments such as thermocouples. Digitalization is changing the landscape for manufacturing, and data-based sensing modalities (e.g., image-based sensing) are becoming of greater interest for plant control. These considerations require novel test/evaluation solutions. For example, process systems engineering researchers may wish to test image-based sensors in simulation. In this work, we provide preliminary thoughts on how image-based technologies might be evaluated via simulation for process systems.

Henrique Oyama↗
NASA NTRS1987

An unsupervised feature extraction method for high dimensional image data compaction

A new on-line unsupervised feature extraction method for high-dimensional remotely sensed image data compaction is presented. This method can be utilized to solve the problem of data redundancy in scene representation by satellite-borne high resolution multispectral sensors. The algorithm first partitions the observation space into an exhaustive set of disjoint objects. Then, pixels that belong to an object are characterized by an object feature. Finally, the set of object features is used for data transmission and classification. The example results show that the performance with the compacted features provides a slight improvement in classification accuracy instead of any degradation. Also, the information extraction method does not need to be preceded by a data decompaction.

Ghassemian, Hassan↗
NASA NTRS2007

Automated Recognition of 3D Features in GPIR Images

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Park, Han↗