Image Navigation and Registration Performance Assessment Evaluation Tools for GOES-R ABI and GLM

NASA Technical Reports Server (NTRS)

Houchin, Scott; Porter, Brian; Graybill, Justin; Slingerland, Philip

2017-01-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. This paper describes the software design and implementation of IPATS and provides preliminary test results.

Advanced Land Imager Assessment System

NASA Technical Reports Server (NTRS)

Chander, Gyanesh; Choate, Mike; Christopherson, Jon; Hollaren, Doug; Morfitt, Ron; Nelson, Jim; Nelson, Shar; Storey, James; Helder, Dennis; Ruggles, Tim;

Analyzing microtomography data with Python and the scikit-image library.

PubMed

Gouillart, Emmanuelle; Nunez-Iglesias, Juan; van der Walt, Stéfan

2017-01-01

The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements. scikit-image users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. scikit-image combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.

Parallel processing considerations for image recognition tasks

NASA Astrophysics Data System (ADS)

Simske, Steven J.

2011-01-01

Many image recognition tasks are well-suited to parallel processing. The most obvious example is that many imaging tasks require the analysis of multiple images. From this standpoint, then, parallel processing need be no more complicated than assigning individual images to individual processors. However, there are three less trivial categories of parallel processing that will be considered in this paper: parallel processing (1) by task; (2) by image region; and (3) by meta-algorithm. Parallel processing by task allows the assignment of multiple workflows-as diverse as optical character recognition [OCR], document classification and barcode reading-to parallel pipelines. This can substantially decrease time to completion for the document tasks. For this approach, each parallel pipeline is generally performing a different task. Parallel processing by image region allows a larger imaging task to be sub-divided into a set of parallel pipelines, each performing the same task but on a different data set. This type of image analysis is readily addressed by a map-reduce approach. Examples include document skew detection and multiple face detection and tracking. Finally, parallel processing by meta-algorithm allows different algorithms to be deployed on the same image simultaneously. This approach may result in improved accuracy.

Three-dimensional non-destructive optical evaluation of laser-processing performance using optical coherence tomography.

PubMed

Kim, Youngseop; Choi, Eun Seo; Kwak, Wooseop; Shin, Yongjin; Jung, Woonggyu; Ahn, Yeh-Chan; Chen, Zhongping

2008-06-01

We demonstrate the use of optical coherence tomography (OCT) as a non-destructive diagnostic tool for evaluating laser-processing performance by imaging the features of a pit and a rim. A pit formed on a material at different laser-processing conditions is imaged using both a conventional scanning electron microscope (SEM) and OCT. Then using corresponding images, the geometrical characteristics of the pit are analyzed and compared. From the results, we could verify the feasibility and the potential of the application of OCT to the monitoring of the laser-processing performance.

Three-dimensional non-destructive optical evaluation of laser-processing performance using optical coherence tomography

PubMed Central

Kim, Youngseop; Choi, Eun Seo; Kwak, Wooseop; Shin, Yongjin; Jung, Woonggyu; Ahn, Yeh-Chan; Chen, Zhongping

2014-01-01

We demonstrate the use of optical coherence tomography (OCT) as a non-destructive diagnostic tool for evaluating laser-processing performance by imaging the features of a pit and a rim. A pit formed on a material at different laser-processing conditions is imaged using both a conventional scanning electron microscope (SEM) and OCT. Then using corresponding images, the geometrical characteristics of the pit are analyzed and compared. From the results, we could verify the feasibility and the potential of the application of OCT to the monitoring of the laser-processing performance. PMID:24932051

Image gathering, coding, and processing: End-to-end optimization for efficient and robust acquisition of visual information

NASA Technical Reports Server (NTRS)

Huck, Friedrich O.; Fales, Carl L.

1990-01-01

Researchers are concerned with the end-to-end performance of image gathering, coding, and processing. The applications range from high-resolution television to vision-based robotics, wherever the resolution, efficiency and robustness of visual information acquisition and processing are critical. For the presentation at this workshop, it is convenient to divide research activities into the following two overlapping areas: The first is the development of focal-plane processing techniques and technology to effectively combine image gathering with coding, with an emphasis on low-level vision processing akin to the retinal processing in human vision. The approach includes the familiar Laplacian pyramid, the new intensity-dependent spatial summation, and parallel sensing/processing networks. Three-dimensional image gathering is attained by combining laser ranging with sensor-array imaging. The second is the rigorous extension of information theory and optimal filtering to visual information acquisition and processing. The goal is to provide a comprehensive methodology for quantitatively assessing the end-to-end performance of image gathering, coding, and processing.

UWGSP4: an imaging and graphics superworkstation and its medical applications

NASA Astrophysics Data System (ADS)

Jong, Jing-Ming; Park, Hyun Wook; Eo, Kilsu; Kim, Min-Hwan; Zhang, Peng; Kim, Yongmin

1992-05-01

UWGSP4 is configured with a parallel architecture for image processing and a pipelined architecture for computer graphics. The system's peak performance is 1,280 MFLOPS for image processing and over 200,000 Gouraud shaded 3-D polygons per second for graphics. The simulated sustained performance is about 50% of the peak performance in general image processing. Most of the 2-D image processing functions are efficiently vectorized and parallelized in UWGSP4. A performance of 770 MFLOPS in convolution and 440 MFLOPS in FFT is achieved. The real-time cine display, up to 32 frames of 1280 X 1024 pixels per second, is supported. In 3-D imaging, the update rate for the surface rendering is 10 frames of 20,000 polygons per second; the update rate for the volume rendering is 6 frames of 128 X 128 X 128 voxels per second. The system provides 1280 X 1024 X 32-bit double frame buffers and one 1280 X 1024 X 8-bit overlay buffer for supporting realistic animation, 24-bit true color, and text annotation. A 1280 X 1024- pixel, 66-Hz noninterlaced display screen with 1:1 aspect ratio can be windowed into the frame buffer for the display of any portion of the processed image or graphics.

A new full-field digital mammography system with and without the use of an advanced post-processing algorithm: comparison of image quality and diagnostic performance.

PubMed

Ahn, Hye Shin; Kim, Sun Mi; Jang, Mijung; Yun, Bo La; Kim, Bohyoung; Ko, Eun Sook; Han, Boo-Kyung; Chang, Jung Min; Yi, Ann; Cho, Nariya; Moon, Woo Kyung; Choi, Hye Young

2014-01-01

To compare new full-field digital mammography (FFDM) with and without use of an advanced post-processing algorithm to improve image quality, lesion detection, diagnostic performance, and priority rank. During a 22-month period, we prospectively enrolled 100 cases of specimen FFDM mammography (Brestige®), which was performed alone or in combination with a post-processing algorithm developed by the manufacturer: group A (SMA), specimen mammography without application of "Mammogram enhancement ver. 2.0"; group B (SMB), specimen mammography with application of "Mammogram enhancement ver. 2.0". Two sets of specimen mammographies were randomly reviewed by five experienced radiologists. Image quality, lesion detection, diagnostic performance, and priority rank with regard to image preference were evaluated. Three aspects of image quality (overall quality, contrast, and noise) of the SMB were significantly superior to those of SMA (p < 0.05). SMB was significantly superior to SMA for visualizing calcifications (p < 0.05). Diagnostic performance, as evaluated by cancer score, was similar between SMA and SMB. SMB was preferred to SMA by four of the five reviewers. The post-processing algorithm may improve image quality with better image preference in FFDM than without use of the software.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shoaf, S.; APS Engineering Support Division

A real-time image analysis system was developed for beam imaging diagnostics. An Apple Power Mac G5 with an Active Silicon LFG frame grabber was used to capture video images that were processed and analyzed. Software routines were created to utilize vector-processing hardware to reduce the time to process images as compared to conventional methods. These improvements allow for more advanced image processing diagnostics to be performed in real time.

High Resolution Near Real Time Image Processing and Support for MSSS Modernization

NASA Astrophysics Data System (ADS)

Duncan, R. B.; Sabol, C.; Borelli, K.; Spetka, S.; Addison, J.; Mallo, A.; Farnsworth, B.; Viloria, R.

2012-09-01

This paper describes image enhancement software applications engineering development work that has been performed in support of Maui Space Surveillance System (MSSS) Modernization. It also includes R&D and transition activity that has been performed over the past few years with the objective of providing increased space situational awareness (SSA) capabilities. This includes Air Force Research Laboratory (AFRL) use of an FY10 Dedicated High Performance Investment (DHPI) cluster award -- and our selection and planned use for an FY12 DHPI award. We provide an introduction to image processing of electro optical (EO) telescope sensors data; and a high resolution image enhancement and near real time processing and summary status overview. We then describe recent image enhancement applications development and support for MSSS Modernization, results to date, and end with a discussion of desired future development work and conclusions. Significant improvements to image processing enhancement have been realized over the past several years, including a key application that has realized more than a 10,000-times speedup compared to the original R&D code -- and a greater than 72-times speedup over the past few years. The latest version of this code maintains software efficiency for post-mission processing while providing optimization for image processing of data from a new EO sensor at MSSS. Additional work has also been performed to develop low latency, near real time processing of data that is collected by the ground-based sensor during overhead passes of space objects.

Graphics Processing Unit (GPU) implementation of image processing algorithms to improve system performance of the Control, Acquisition, Processing, and Image Display System (CAPIDS) of the Micro-Angiographic Fluoroscope (MAF).

PubMed

Vasan, S N Swetadri; Ionita, Ciprian N; Titus, A H; Cartwright, A N; Bednarek, D R; Rudin, S

2012-02-23

We present the image processing upgrades implemented on a Graphics Processing Unit (GPU) in the Control, Acquisition, Processing, and Image Display System (CAPIDS) for the custom Micro-Angiographic Fluoroscope (MAF) detector. Most of the image processing currently implemented in the CAPIDS system is pixel independent; that is, the operation on each pixel is the same and the operation on one does not depend upon the result from the operation on the other, allowing the entire image to be processed in parallel. GPU hardware was developed for this kind of massive parallel processing implementation. Thus for an algorithm which has a high amount of parallelism, a GPU implementation is much faster than a CPU implementation. The image processing algorithm upgrades implemented on the CAPIDS system include flat field correction, temporal filtering, image subtraction, roadmap mask generation and display window and leveling. A comparison between the previous and the upgraded version of CAPIDS has been presented, to demonstrate how the improvement is achieved. By performing the image processing on a GPU, significant improvements (with respect to timing or frame rate) have been achieved, including stable operation of the system at 30 fps during a fluoroscopy run, a DSA run, a roadmap procedure and automatic image windowing and leveling during each frame.

ImageJ: Image processing and analysis in Java

NASA Astrophysics Data System (ADS)

Rasband, W. S.

2012-06-01

ImageJ is a public domain Java image processing program inspired by NIH Image. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.

A review of breast tomosynthesis. Part II. Image reconstruction, processing and analysis, and advanced applications

PubMed Central

Sechopoulos, Ioannis

2013-01-01

Many important post-acquisition aspects of breast tomosynthesis imaging can impact its clinical performance. Chief among them is the reconstruction algorithm that generates the representation of the three-dimensional breast volume from the acquired projections. But even after reconstruction, additional processes, such as artifact reduction algorithms, computer aided detection and diagnosis, among others, can also impact the performance of breast tomosynthesis in the clinical realm. In this two part paper, a review of breast tomosynthesis research is performed, with an emphasis on its medical physics aspects. In the companion paper, the first part of this review, the research performed relevant to the image acquisition process is examined. This second part will review the research on the post-acquisition aspects, including reconstruction, image processing, and analysis, as well as the advanced applications being investigated for breast tomosynthesis. PMID:23298127

BioImageXD: an open, general-purpose and high-throughput image-processing platform.

PubMed

Kankaanpää, Pasi; Paavolainen, Lassi; Tiitta, Silja; Karjalainen, Mikko; Päivärinne, Joacim; Nieminen, Jonna; Marjomäki, Varpu; Heino, Jyrki; White, Daniel J

2012-06-28

BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes. We demonstrate its performance in a study of integrin clustering in response to selected inhibitors.

Multi-template image matching using alpha-rooted biquaternion phase correlation with application to logo recognition

NASA Astrophysics Data System (ADS)

DelMarco, Stephen

2011-06-01

Hypercomplex approaches are seeing increased application to signal and image processing problems. The use of multicomponent hypercomplex numbers, such as quaternions, enables the simultaneous co-processing of multiple signal or image components. This joint processing capability can provide improved exploitation of the information contained in the data, thereby leading to improved performance in detection and recognition problems. In this paper, we apply hypercomplex processing techniques to the logo image recognition problem. Specifically, we develop an image matcher by generalizing classical phase correlation to the biquaternion case. We further incorporate biquaternion Fourier domain alpha-rooting enhancement to create Alpha-Rooted Biquaternion Phase Correlation (ARBPC). We present the mathematical properties which justify use of ARBPC as an image matcher. We present numerical performance results of a logo verification problem using real-world logo data, demonstrating the performance improvement obtained using the hypercomplex approach. We compare results of the hypercomplex approach to standard multi-template matching approaches.

GPU-Based High-performance Imaging for Mingantu Spectral RadioHeliograph

NASA Astrophysics Data System (ADS)

Mei, Ying; Wang, Feng; Wang, Wei; Chen, Linjie; Liu, Yingbo; Deng, Hui; Dai, Wei; Liu, Cuiyin; Yan, Yihua

2018-01-01

As a dedicated solar radio interferometer, the MingantU SpEctral RadioHeliograph (MUSER) generates massive observational data in the frequency range of 400 MHz-15 GHz. High-performance imaging forms a significantly important aspect of MUSER’s massive data processing requirements. In this study, we implement a practical high-performance imaging pipeline for MUSER data processing. At first, the specifications of the MUSER are introduced and its imaging requirements are analyzed. Referring to the most commonly used radio astronomy software such as CASA and MIRIAD, we then implement a high-performance imaging pipeline based on the Graphics Processing Unit technology with respect to the current operational status of the MUSER. A series of critical algorithms and their pseudo codes, i.e., detection of the solar disk and sky brightness, automatic centering of the solar disk and estimation of the number of iterations for clean algorithms, are proposed in detail. The preliminary experimental results indicate that the proposed imaging approach significantly increases the processing performance of MUSER and generates images with high-quality, which can meet the requirements of the MUSER data processing. Supported by the National Key Research and Development Program of China (2016YFE0100300), the Joint Research Fund in Astronomy (No. U1531132, U1631129, U1231205) under cooperative agreement between the National Natural Science Foundation of China (NSFC) and the Chinese Academy of Sciences (CAS), the National Natural Science Foundation of China (Nos. 11403009 and 11463003).

An integral design strategy combining optical system and image processing to obtain high resolution images

NASA Astrophysics Data System (ADS)

Wang, Jiaoyang; Wang, Lin; Yang, Ying; Gong, Rui; Shao, Xiaopeng; Liang, Chao; Xu, Jun

2016-05-01

In this paper, an integral design that combines optical system with image processing is introduced to obtain high resolution images, and the performance is evaluated and demonstrated. Traditional imaging methods often separate the two technical procedures of optical system design and imaging processing, resulting in the failures in efficient cooperation between the optical and digital elements. Therefore, an innovative approach is presented to combine the merit function during optical design together with the constraint conditions of image processing algorithms. Specifically, an optical imaging system with low resolution is designed to collect the image signals which are indispensable for imaging processing, while the ultimate goal is to obtain high resolution images from the final system. In order to optimize the global performance, the optimization function of ZEMAX software is utilized and the number of optimization cycles is controlled. Then Wiener filter algorithm is adopted to process the image simulation and mean squared error (MSE) is taken as evaluation criterion. The results show that, although the optical figures of merit for the optical imaging systems is not the best, it can provide image signals that are more suitable for image processing. In conclusion. The integral design of optical system and image processing can search out the overall optimal solution which is missed by the traditional design methods. Especially, when designing some complex optical system, this integral design strategy has obvious advantages to simplify structure and reduce cost, as well as to gain high resolution images simultaneously, which has a promising perspective of industrial application.

Evaluation of the visual performance of image processing pipes: information value of subjective image attributes

NASA Astrophysics Data System (ADS)

Nyman, G.; Häkkinen, J.; Koivisto, E.-M.; Leisti, T.; Lindroos, P.; Orenius, O.; Virtanen, T.; Vuori, T.

2010-01-01

Subjective image quality data for 9 image processing pipes and 8 image contents (taken with mobile phone camera, 72 natural scene test images altogether) from 14 test subjects were collected. A triplet comparison setup and a hybrid qualitative/quantitative methodology were applied. MOS data and spontaneous, subjective image quality attributes to each test image were recorded. The use of positive and negative image quality attributes by the experimental subjects suggested a significant difference between the subjective spaces of low and high image quality. The robustness of the attribute data was shown by correlating DMOS data of the test images against their corresponding, average subjective attribute vector length data. The findings demonstrate the information value of spontaneous, subjective image quality attributes in evaluating image quality at variable quality levels. We discuss the implications of these findings for the development of sensitive performance measures and methods in profiling image processing systems and their components, especially at high image quality levels.

The Dark Energy Survey Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Morganson, E.; Gruendl, R. A.; Menanteau, F.; Carrasco Kind, M.; Chen, Y.-C.; Daues, G.; Drlica-Wagner, A.; Friedel, D. N.; Gower, M.; Johnson, M. W. G.; Johnson, M. D.; Kessler, R.; Paz-Chinchón, F.; Petravick, D.; Pond, C.; Yanny, B.; Allam, S.; Armstrong, R.; Barkhouse, W.; Bechtol, K.; Benoit-Lévy, A.; Bernstein, G. M.; Bertin, E.; Buckley-Geer, E.; Covarrubias, R.; Desai, S.; Diehl, H. T.; Goldstein, D. A.; Gruen, D.; Li, T. S.; Lin, H.; Marriner, J.; Mohr, J. J.; Neilsen, E.; Ngeow, C.-C.; Paech, K.; Rykoff, E. S.; Sako, M.; Sevilla-Noarbe, I.; Sheldon, E.; Sobreira, F.; Tucker, D. L.; Wester, W.; DES Collaboration

2018-07-01

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five optical bands (g, r, i, z, Y) to a depth of ∼24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g, r, i, z) over ∼27 deg2. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On a bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.

Identification, regression and validation of an image processing degradation model to assess the effects of aeromechanical turbulence due to installation aircraft

NASA Astrophysics Data System (ADS)

Miccoli, M.; Usai, A.; Tafuto, A.; Albertoni, A.; Togna, F.

2016-10-01

The propagation environment around airborne platforms may significantly degrade the performance of Electro-Optical (EO) self-protection systems installed onboard. To ensure the sufficient level of protection, it is necessary to understand that are the best sensors/effectors installation positions to guarantee that the aeromechanical turbulence, generated by the engine exhausts and the rotor downwash, does not interfere with the imaging systems normal operations. Since the radiation-propagation-in-turbulence is a hardly predictable process, it was proposed a high-level approach in which, instead of studying the medium under turbulence, the turbulence effects on the imaging systems processing are assessed by means of an equivalent statistical model representation, allowing a definition of a Turbulence index to classify different level of turbulence intensities. Hence, a general measurement methodology for the degradation of the imaging systems performance in turbulence conditions was developed. The analysis of the performance degradation started by evaluating the effects of turbulences with a given index on the image processing chain (i.e., thresholding, blob analysis). The processing in turbulence (PIT) index is then derived by combining the effects of the given turbulence on the different image processing primitive functions. By evaluating the corresponding PIT index for a sufficient number of testing directions, it is possible to map the performance degradation around the aircraft installation for a generic imaging system, and to identify the best installation position for sensors/effectors composing the EO self-protection suite.

High-performance image processing on the desktop

NASA Astrophysics Data System (ADS)

Jordan, Stephen D.

1996-04-01

The suitability of computers to the task of medical image visualization for the purposes of primary diagnosis and treatment planning depends on three factors: speed, image quality, and price. To be widely accepted the technology must increase the efficiency of the diagnostic and planning processes. This requires processing and displaying medical images of various modalities in real-time, with accuracy and clarity, on an affordable system. Our approach to meeting this challenge began with market research to understand customer image processing needs. These needs were translated into system-level requirements, which in turn were used to determine which image processing functions should be implemented in hardware. The result is a computer architecture for 2D image processing that is both high-speed and cost-effective. The architectural solution is based on the high-performance PA-RISC workstation with an HCRX graphics accelerator. The image processing enhancements are incorporated into the image visualization accelerator (IVX) which attaches to the HCRX graphics subsystem. The IVX includes a custom VLSI chip which has a programmable convolver, a window/level mapper, and an interpolator supporting nearest-neighbor, bi-linear, and bi-cubic modes. This combination of features can be used to enable simultaneous convolution, pan, zoom, rotate, and window/level control into 1 k by 1 k by 16-bit medical images at 40 frames/second.

Fast Pixel Buffer For Processing With Lookup Tables

NASA Technical Reports Server (NTRS)

Fisher, Timothy E.

1992-01-01

Proposed scheme for buffering data on intensities of picture elements (pixels) of image increases rate or processing beyond that attainable when data read, one pixel at time, from main image memory. Scheme applied in design of specialized image-processing circuitry. Intended to optimize performance of processor in which electronic equivalent of address-lookup table used to address those pixels in main image memory required for processing.

Assesment on the performance of electrode arrays using image processing technique

NASA Astrophysics Data System (ADS)

Usman, N.; Khiruddin, A.; Nawawi, Mohd

2017-08-01

Interpreting inverted resistivity section is time consuming, tedious and requires other sources of information to be relevant geologically. Image processing technique was used in order to perform post inversion processing which make geophysical data interpretation easier. The inverted data sets were imported into the PCI Geomatica 9.0.1 for further processing. The data sets were clipped and merged together in order to match the coordinates of the three layers and permit pixel to pixel analysis. Dipole-dipole array is more sensitive to resistivity variation with depth in comparison with Werner-Schlumberger and pole-dipole. Image processing serves as good post-inversion tool in geophysical data processing.

Digital processing of Mariner 9 television data.

NASA Technical Reports Server (NTRS)

Green, W. B.; Seidman, J. B.

1973-01-01

The digital image processing performed by the Image Processing Laboratory (IPL) at JPL in support of the Mariner 9 mission is summarized. The support is divided into the general categories of image decalibration (the removal of photometric and geometric distortions from returned imagery), computer cartographic projections in support of mapping activities, and adaptive experimenter support (flexible support to provide qualitative digital enhancements and quantitative data reduction of returned imagery). Among the tasks performed were the production of maximum discriminability versions of several hundred frames to support generation of a geodetic control net for Mars, and special enhancements supporting analysis of Phobos and Deimos images.

Multiresponse imaging system design for improved resolution

NASA Technical Reports Server (NTRS)

Alter-Gartenberg, Rachel; Fales, Carl L.; Huck, Friedrich O.; Rahman, Zia-Ur; Reichenbach, Stephen E.

1991-01-01

Multiresponse imaging is a process that acquires A images, each with a different optical response, and reassembles them into a single image with an improved resolution that can approach 1/sq rt A times the photodetector-array sampling lattice. Our goals are to optimize the performance of this process in terms of the resolution and fidelity of the restored image and to assess the amount of information required to do so. The theoretical approach is based on the extension of both image restoration and rate-distortion theories from their traditional realm of signal processing to image processing which includes image gathering and display.

On techniques for angle compensation in nonideal iris recognition.

PubMed

Schuckers, Stephanie A C; Schmid, Natalia A; Abhyankar, Aditya; Dorairaj, Vivekanand; Boyce, Christopher K; Hornak, Lawrence A

2007-10-01

The popularity of the iris biometric has grown considerably over the past two to three years. Most research has been focused on the development of new iris processing and recognition algorithms for frontal view iris images. However, a few challenging directions in iris research have been identified, including processing of a nonideal iris and iris at a distance. In this paper, we describe two nonideal iris recognition systems and analyze their performance. The word "nonideal" is used in the sense of compensating for off-angle occluded iris images. The system is designed to process nonideal iris images in two steps: 1) compensation for off-angle gaze direction and 2) processing and encoding of the rotated iris image. Two approaches are presented to account for angular variations in the iris images. In the first approach, we use Daugman's integrodifferential operator as an objective function to estimate the gaze direction. After the angle is estimated, the off-angle iris image undergoes geometric transformations involving the estimated angle and is further processed as if it were a frontal view image. The encoding technique developed for a frontal image is based on the application of the global independent component analysis. The second approach uses an angular deformation calibration model. The angular deformations are modeled, and calibration parameters are calculated. The proposed method consists of a closed-form solution, followed by an iterative optimization procedure. The images are projected on the plane closest to the base calibrated plane. Biorthogonal wavelets are used for encoding to perform iris recognition. We use a special dataset of the off-angle iris images to quantify the performance of the designed systems. A series of receiver operating characteristics demonstrate various effects on the performance of the nonideal-iris-based recognition system.

Image processing and products for the Magellan mission to Venus

NASA Technical Reports Server (NTRS)

Clark, Jerry; Alexander, Doug; Andres, Paul; Lewicki, Scott; Mcauley, Myche

1992-01-01

The Magellan mission to Venus is providing planetary scientists with massive amounts of new data about the surface geology of Venus. Digital image processing is an integral part of the ground data system that provides data products to the investigators. The mosaicking of synthetic aperture radar (SAR) image data from the spacecraft is being performed at JPL's Multimission Image Processing Laboratory (MIPL). MIPL hosts and supports the Image Data Processing Subsystem (IDPS), which was developed in a VAXcluster environment of hardware and software that includes optical disk jukeboxes and the TAE-VICAR (Transportable Applications Executive-Video Image Communication and Retrieval) system. The IDPS is being used by processing analysts of the Image Data Processing Team to produce the Magellan image data products. Various aspects of the image processing procedure are discussed.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis

PubMed Central

Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

2016-01-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

SU-D-BRD-02: A Web-Based Image Processing and Plan Evaluation Platform (WIPPEP) for Future Cloud-Based Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chai, X; Liu, L; Xing, L

Purpose: Visualization and processing of medical images and radiation treatment plan evaluation have traditionally been constrained to local workstations with limited computation power and ability of data sharing and software update. We present a web-based image processing and planning evaluation platform (WIPPEP) for radiotherapy applications with high efficiency, ubiquitous web access, and real-time data sharing. Methods: This software platform consists of three parts: web server, image server and computation server. Each independent server communicates with each other through HTTP requests. The web server is the key component that provides visualizations and user interface through front-end web browsers and relay informationmore » to the backend to process user requests. The image server serves as a PACS system. The computation server performs the actual image processing and dose calculation. The web server backend is developed using Java Servlets and the frontend is developed using HTML5, Javascript, and jQuery. The image server is based on open source DCME4CHEE PACS system. The computation server can be written in any programming language as long as it can send/receive HTTP requests. Our computation server was implemented in Delphi, Python and PHP, which can process data directly or via a C++ program DLL. Results: This software platform is running on a 32-core CPU server virtually hosting the web server, image server, and computation servers separately. Users can visit our internal website with Chrome browser, select a specific patient, visualize image and RT structures belonging to this patient and perform image segmentation running Delphi computation server and Monte Carlo dose calculation on Python or PHP computation server. Conclusion: We have developed a webbased image processing and plan evaluation platform prototype for radiotherapy. This system has clearly demonstrated the feasibility of performing image processing and plan evaluation platform through a web browser and exhibited potential for future cloud based radiotherapy.« less

Overview on METEOSAT geometrical image data processing

NASA Technical Reports Server (NTRS)

Diekmann, Frank J.

1994-01-01

Digital Images acquired from the geostationary METEOSAT satellites are processed and disseminated at ESA's European Space Operations Centre in Darmstadt, Germany. Their scientific value is mainly dependent on their radiometric quality and geometric stability. This paper will give an overview on the image processing activities performed at ESOC, concentrating on the geometrical restoration and quality evaluation. The performance of the rectification process for the various satellites over the past years will be presented and the impacts of external events as for instance the Pinatubo eruption in 1991 will be explained. Special developments both in hard and software, necessary to cope with demanding tasks as new image resampling or to correct for spacecraft anomalies, are presented as well. The rotating lens of MET-5 causing severe geometrical image distortions is an example for the latter.

New scheme for image edge detection using the switching mechanism of nonlinear optical material

NASA Astrophysics Data System (ADS)

Pahari, Nirmalya; Mukhopadhyay, Sourangshu

2006-03-01

The limitations of electronics in conducting parallel arithmetic, algebraic, and logic processing are well known. Very high-speed (terahertz) performance cannot be expected in conventional electronic mechanisms. To achieve such performance we can introduce optics instead of electronics for information processing, computing, and data handling. Nonlinear optical material (NOM) is a successful candidate in this regard to play a major role in the domain of optically controlled switching systems. The character of some NOMs is such as to reflect the probe beam in the presence of two read beams (or pump beams) exciting the material from opposite directions, using the principle of four-wave mixing. In image processing, edge extraction from an image is an important and essential task. Several optical methods of digital image processing are used for properly evaluating the image edges. We propose here a new method of image edge detection, extraction, and enhancement by use of AND-based switching operations with NOM. In this process we have used the optically inverted image of a supplied image. This can be obtained by the EXOR switching operation of the NOM.

Symmetric Phase Only Filtering for Improved DPIV Data Processing

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

2006-01-01

The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."

Halftoning processing on a JPEG-compressed image

NASA Astrophysics Data System (ADS)

Sibade, Cedric; Barizien, Stephane; Akil, Mohamed; Perroton, Laurent

2003-12-01

Digital image processing algorithms are usually designed for the raw format, that is on an uncompressed representation of the image. Therefore prior to transforming or processing a compressed format, decompression is applied; then, the result of the processing application is finally re-compressed for further transfer or storage. The change of data representation is resource-consuming in terms of computation, time and memory usage. In the wide format printing industry, this problem becomes an important issue: e.g. a 1 m2 input color image, scanned at 600 dpi exceeds 1.6 GB in its raw representation. However, some image processing algorithms can be performed in the compressed-domain, by applying an equivalent operation on the compressed format. This paper is presenting an innovative application of the halftoning processing operation by screening, to be applied on JPEG-compressed image. This compressed-domain transform is performed by computing the threshold operation of the screening algorithm in the DCT domain. This algorithm is illustrated by examples for different halftone masks. A pre-sharpening operation, applied on a JPEG-compressed low quality image is also described; it allows to de-noise and to enhance the contours of this image.

WE-G-204-01: BEST IN PHYSICS (IMAGING): Effect of Image Processing Parameters On Nodule Detectability in Chest Radiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Little, K; Lu, Z; MacMahon, H

Purpose: To investigate the effect of varying system image processing parameters on lung nodule detectability in digital radiography. Methods: An anthropomorphic chest phantom was imaged in the posterior-anterior position using a GE Discovery XR656 digital radiography system. To simulate lung nodules, a polystyrene board with 6.35mm diameter PMMA spheres was placed adjacent to the phantom (into the x-ray path). Due to magnification, the projected simulated nodules had a diameter in the radiographs of approximately 7.5 mm. The images were processed using one of GE’s default chest settings (Factory3) and reprocessed by varying the “Edge” and “Tissue Contrast” processing parameters, whichmore » were the two user-configurable parameters for a single edge and contrast enhancement algorithm. For each parameter setting, the nodule signals were calculated by subtracting the chest-only image from the image with simulated nodules. Twenty nodule signals were averaged, Gaussian filtered, and radially averaged in order to generate an approximately noiseless signal. For each processing parameter setting, this noise-free signal and 180 background samples from across the lung were used to estimate ideal observer performance in a signal-known-exactly detection task. Performance was estimated using a channelized Hotelling observer with 10 Laguerre-Gauss channel functions. Results: The “Edge” and “Tissue Contrast” parameters each had an effect on the detectability as calculated by the model observer. The CHO-estimated signal detectability ranged from 2.36 to 2.93 and was highest for “Edge” = 4 and “Tissue Contrast” = −0.15. In general, detectability tended to decrease as “Edge” was increased and as “Tissue Contrast” was increased. A human observer study should be performed to validate the relation to human detection performance. Conclusion: Image processing parameters can affect lung nodule detection performance in radiography. While validation with a human observer study is needed, model observer detectability for common tasks could provide a means for optimizing image processing parameters.« less

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanchez, A; Little, K; Chung, J

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidencemore » of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more observers, including experienced chest radiologists.« less

Comparing an FPGA to a Cell for an Image Processing Application

NASA Astrophysics Data System (ADS)

Rakvic, Ryan N.; Ngo, Hau; Broussard, Randy P.; Ives, Robert W.

2010-12-01

Modern advancements in configurable hardware, most notably Field-Programmable Gate Arrays (FPGAs), have provided an exciting opportunity to discover the parallel nature of modern image processing algorithms. On the other hand, PlayStation3 (PS3) game consoles contain a multicore heterogeneous processor known as the Cell, which is designed to perform complex image processing algorithms at a high performance. In this research project, our aim is to study the differences in performance of a modern image processing algorithm on these two hardware platforms. In particular, Iris Recognition Systems have recently become an attractive identification method because of their extremely high accuracy. Iris matching, a repeatedly executed portion of a modern iris recognition algorithm, is parallelized on an FPGA system and a Cell processor. We demonstrate a 2.5 times speedup of the parallelized algorithm on the FPGA system when compared to a Cell processor-based version.

V-Sipal - a Virtual Laboratory for Satellite Image Processing and Analysis

NASA Astrophysics Data System (ADS)

Buddhiraju, K. M.; Eeti, L.; Tiwari, K. K.

2011-09-01

In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL) being developed at the Indian Institute of Technology Bombay is described. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital processing and analysis of satellite images using commercial software. Currently, the experiments that are available on the server include Image Viewer, Image Contrast Enhancement, Image Smoothing, Edge Enhancement, Principal Component Transform, Texture Analysis by Co-occurrence Matrix method, Image Indices, Color Coordinate Transforms, Fourier Analysis, Mathematical Morphology, Unsupervised Image Classification, Supervised Image Classification and Accuracy Assessment. The virtual laboratory includes a theory module for each option of every experiment, a description of the procedure to perform each experiment, the menu to choose and perform the experiment, a module on interpretation of results when performed with a given image and pre-specified options, bibliography, links to useful internet resources and user-feedback. The user can upload his/her own images for performing the experiments and can also reuse outputs of one experiment in another experiment where applicable. Some of the other experiments currently under development include georeferencing of images, data fusion, feature evaluation by divergence andJ-M distance, image compression, wavelet image analysis and change detection. Additions to the theory module include self-assessment quizzes, audio-video clips on selected concepts, and a discussion of elements of visual image interpretation. V-SIPAL is at the satge of internal evaluation within IIT Bombay and will soon be open to selected educational institutions in India for evaluation.

RayPlus: a Web-Based Platform for Medical Image Processing.

PubMed

Yuan, Rong; Luo, Ming; Sun, Zhi; Shi, Shuyue; Xiao, Peng; Xie, Qingguo

2017-04-01

Medical image can provide valuable information for preclinical research, clinical diagnosis, and treatment. As the widespread use of digital medical imaging, many researchers are currently developing medical image processing algorithms and systems in order to accommodate a better result to clinical community, including accurate clinical parameters or processed images from the original images. In this paper, we propose a web-based platform to present and process medical images. By using Internet and novel database technologies, authorized users can easily access to medical images and facilitate their workflows of processing with server-side powerful computing performance without any installation. We implement a series of algorithms of image processing and visualization in the initial version of Rayplus. Integration of our system allows much flexibility and convenience for both research and clinical communities.

Parallelized multi–graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy

PubMed Central

Tankam, Patrice; Santhanam, Anand P.; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P.

2014-01-01

Abstract. Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing. PMID:24695868

Parallelized multi-graphics processing unit framework for high-speed Gabor-domain optical coherence microscopy.

PubMed

Tankam, Patrice; Santhanam, Anand P; Lee, Kye-Sung; Won, Jungeun; Canavesi, Cristina; Rolland, Jannick P

2014-07-01

Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processing. A parallelized control mechanism was developed to individually assign computation tasks to each of the GPUs. For each GPU, the optimal number of amplitude-scans (A-scans) to be processed in parallel was selected to maximize GPU memory usage and core throughput. We investigated five computing architectures for computational speed-up in processing 1000×1000 A-scans. The proposed parallelized multi-GPU computing framework enables processing at a computational speed faster than the GD-OCM image acquisition, thereby facilitating high-speed GD-OCM imaging in a clinical setting. Using two parallelized GPUs, the image processing of a 1×1×0.6  mm3 skin sample was performed in about 13 s, and the performance was benchmarked at 6.5 s with four GPUs. This work thus demonstrates that 3-D GD-OCM data may be displayed in real-time to the examiner using parallelized GPU processing.

The Dark Energy Survey Image Processing Pipeline

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morganson, E.; et al.

The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a 5000 square degree survey of the southern sky in five optical bands (g,r,i,z,Y) to a depth of ~24th magnitude. Contemporaneously, DES performs a deep, time-domain survey in four optical bands (g,r,i,z) over 27 square degrees. DES exposures are processed nightly with an evolving data reduction pipeline and evaluated for image quality to determine if they need to be retaken. Difference imaging and transient source detection are also performed in the time domain component nightly. On amore » bi-annual basis, DES exposures are reprocessed with a refined pipeline and coadded to maximize imaging depth. Here we describe the DES image processing pipeline in support of DES science, as a reference for users of archival DES data, and as a guide for future astronomical surveys.« less

Image Processing and Computer Aided Diagnosis in Computed Tomography of the Breast

DTIC Science & Technology

2007-03-01

TERMS breast imaging, breast CT, scatter compensation, denoising, CAD , Cone-beam CT 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...clinical projection images. The CAD tool based on signal known exactly (SKE) scenario is under development. Task 6: Test and compare the...performances of the CAD developed in Task 5 applied to processed projection data from Task 1 with the CAD performance on the projection data without Bayesian

Multifaceted free-space image distributor for optical interconnects in massively parrallel processing

NASA Astrophysics Data System (ADS)

Zhao, Feng; Frietman, Edward E. E.; Han, Zhong; Chen, Ray T.

1999-04-01

A characteristic feature of a conventional von Neumann computer is that computing power is delivered by a single processing unit. Although increasing the clock frequency improves the performance of the computer, the switching speed of the semiconductor devices and the finite speed at which electrical signals propagate along the bus set the boundaries. Architectures containing large numbers of nodes can solve this performance dilemma, with the comment that main obstacles in designing such systems are caused by difficulties to come up with solutions that guarantee efficient communications among the nodes. Exchanging data becomes really a bottleneck should al nodes be connected by a shared resource. Only optics, due to its inherent parallelism, could solve that bottleneck. Here, we explore a multi-faceted free space image distributor to be used in optical interconnects in massively parallel processing. In this paper, physical and optical models of the image distributor are focused on from diffraction theory of light wave to optical simulations. the general features and the performance of the image distributor are also described. The new structure of an image distributor and the simulations for it are discussed. From the digital simulation and experiment, it is found that the multi-faceted free space image distributing technique is quite suitable for free space optical interconnection in massively parallel processing and new structure of the multifaceted free space image distributor would perform better.

Onboard Image Processing for Autonomous Spacecraft Detection of Volcanic Plumes

NASA Astrophysics Data System (ADS)

Thompson, D. R.; Bunte, M.; Castaño, R.; Chien, S.; Greeley, R.

2011-03-01

Onboard spacecraft image processing could enable long-term monitoring for volcanic plume activity in the outer planets. A new plume detection technique shows strong performance on images of Enceladus and Io taken by Cassini, Voyager, and Galileo.

A survey of GPU-based medical image computing techniques

PubMed Central

Shi, Lin; Liu, Wen; Zhang, Heye; Xie, Yongming

2012-01-01

Medical imaging currently plays a crucial role throughout the entire clinical applications from medical scientific research to diagnostics and treatment planning. However, medical imaging procedures are often computationally demanding due to the large three-dimensional (3D) medical datasets to process in practical clinical applications. With the rapidly enhancing performances of graphics processors, improved programming support, and excellent price-to-performance ratio, the graphics processing unit (GPU) has emerged as a competitive parallel computing platform for computationally expensive and demanding tasks in a wide range of medical image applications. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in GPU-based medical image processing. Within this survey, the continuous advancement of GPU computing is reviewed and the existing traditional applications in three areas of medical image processing, namely, segmentation, registration and visualization, are surveyed. The potential advantages and associated challenges of current GPU-based medical imaging are also discussed to inspire future applications in medicine. PMID:23256080

Operation and Performance of the Mars Exploration Rover Imaging System on the Martian Surface

NASA Technical Reports Server (NTRS)

Maki, Justin N.; Litwin, Todd; Herkenhoff, Ken

2005-01-01

This slide presentation details the Mars Exploration Rover (MER) imaging system. Over 144,000 images have been gathered from all Mars Missions, with 83.5% of them being gathered by MER. Each Rover has 9 cameras (Navcam, front and rear Hazcam, Pancam, Microscopic Image, Descent Camera, Engineering Camera, Science Camera) and produces 1024 x 1024 (1 Megapixel) images in the same format. All onboard image processing code is implemented in flight software and includes extensive processing capabilities such as autoexposure, flat field correction, image orientation, thumbnail generation, subframing, and image compression. Ground image processing is done at the Jet Propulsion Laboratory's Multimission Image Processing Laboratory using Video Image Communication and Retrieval (VICAR) while stereo processing (left/right pairs) is provided for raw image, radiometric correction; solar energy maps,triangulation (Cartesian 3-spaces) and slope maps.

PScan 1.0: flexible software framework for polygon based multiphoton microscopy

NASA Astrophysics Data System (ADS)

Li, Yongxiao; Lee, Woei Ming

2016-12-01

Multiphoton laser scanning microscopes exhibit highly localized nonlinear optical excitation and are powerful instruments for in-vivo deep tissue imaging. Customized multiphoton microscopy has a significantly superior performance for in-vivo imaging because of precise control over the scanning and detection system. To date, there have been several flexible software platforms catered to custom built microscopy systems i.e. ScanImage, HelioScan, MicroManager, that perform at imaging speeds of 30-100fps. In this paper, we describe a flexible software framework for high speed imaging systems capable of operating from 5 fps to 1600 fps. The software is based on the MATLAB image processing toolbox. It has the capability to communicate directly with a high performing imaging card (Matrox Solios eA/XA), thus retaining high speed acquisition. The program is also designed to communicate with LabVIEW and Fiji for instrument control and image processing. Pscan 1.0 can handle high imaging rates and contains sufficient flexibility for users to adapt to their high speed imaging systems.

Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

PubMed

Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

2016-05-01

High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Performance assessment of multi-frequency processing of ICU chest images for enhanced visualization of tubes and catheters

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Couwenhoven, Mary E.; Foos, David H.; Doran, James; Yankelevitz, David F.; Henschke, Claudia I.

2008-03-01

An image-processing method has been developed to improve the visibility of tube and catheter features in portable chest x-ray (CXR) images captured in the intensive care unit (ICU). The image-processing method is based on a multi-frequency approach, wherein the input image is decomposed into different spatial frequency bands, and those bands that contain the tube and catheter signals are individually enhanced by nonlinear boosting functions. Using a random sampling strategy, 50 cases were retrospectively selected for the study from a large database of portable CXR images that had been collected from multiple institutions over a two-year period. All images used in the study were captured using photo-stimulable, storage phosphor computed radiography (CR) systems. Each image was processed two ways. The images were processed with default image processing parameters such as those used in clinical settings (control). The 50 images were then separately processed using the new tube and catheter enhancement algorithm (test). Three board-certified radiologists participated in a reader study to assess differences in both detection-confidence performance and diagnostic efficiency between the control and test images. Images were evaluated on a diagnostic-quality, 3-megapixel monochrome monitor. Two scenarios were studied: the baseline scenario, representative of today's workflow (a single-control image presented with the window/level adjustments enabled) vs. the test scenario (a control/test image pair presented with a toggle enabled and the window/level settings disabled). The radiologists were asked to read the images in each scenario as they normally would for clinical diagnosis. Trend analysis indicates that the test scenario offers improved reading efficiency while providing as good or better detection capability compared to the baseline scenario.

Distorted images of one's own body activates the prefrontal cortex and limbic/paralimbic system in young women: a functional magnetic resonance imaging study.

PubMed

Kurosaki, Mitsuhaya; Shirao, Naoko; Yamashita, Hidehisa; Okamoto, Yasumasa; Yamawaki, Shigeto

2006-02-15

Our aim was to study the gender differences in brain activation upon viewing visual stimuli of distorted images of one's own body. We performed functional magnetic resonance imaging on 11 healthy young men and 11 healthy young women using the "body image tasks" which consisted of fat, real, and thin shapes of the subject's own body. Comparison of the brain activation upon performing the fat-image task versus real-image task showed significant activation of the bilateral prefrontal cortex and left parahippocampal area including the amygdala in the women, and significant activation of the right occipital lobe including the primary and secondary visual cortices in the men. Comparison of brain activation upon performing the thin-image task versus real-image task showed significant activation of the left prefrontal cortex, left limbic area including the cingulate gyrus and paralimbic area including the insula in women, and significant activation of the occipital lobe including the left primary and secondary visual cortices in men. These results suggest that women tend to perceive distorted images of their own bodies by complex cognitive processing of emotion, whereas men tend to perceive distorted images of their own bodies by object visual processing and spatial visual processing.

Analysis of scalability of high-performance 3D image processing platform for virtual colonoscopy

NASA Astrophysics Data System (ADS)

Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli

2014-03-01

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. For this purpose, we previously developed a software platform for high-performance 3D medical image processing, called HPC 3D-MIP platform, which employs increasingly available and affordable commodity computing systems such as the multicore, cluster, and cloud computing systems. To achieve scalable high-performance computing, the platform employed size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D-MIP algorithms, supported task scheduling for efficient load distribution and balancing, and consisted of a layered parallel software libraries that allow image processing applications to share the common functionalities. We evaluated the performance of the HPC 3D-MIP platform by applying it to computationally intensive processes in virtual colonoscopy. Experimental results showed a 12-fold performance improvement on a workstation with 12-core CPUs over the original sequential implementation of the processes, indicating the efficiency of the platform. Analysis of performance scalability based on the Amdahl's law for symmetric multicore chips showed the potential of a high performance scalability of the HPC 3DMIP platform when a larger number of cores is available.

[Image processing system of visual prostheses based on digital signal processor DM642].

PubMed

Xie, Chengcheng; Lu, Yanyu; Gu, Yun; Wang, Jing; Chai, Xinyu

2011-09-01

This paper employed a DSP platform to create the real-time and portable image processing system, and introduced a series of commonly used algorithms for visual prostheses. The results of performance evaluation revealed that this platform could afford image processing algorithms to be executed in real time.

Real-time computer treatment of THz passive device images with the high image quality

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Trofimov, Vladislav V.

2012-06-01

We demonstrate real-time computer code improving significantly the quality of images captured by the passive THz imaging system. The code is not only designed for a THz passive device: it can be applied to any kind of such devices and active THz imaging systems as well. We applied our code for computer processing of images captured by four passive THz imaging devices manufactured by different companies. It should be stressed that computer processing of images produced by different companies requires using the different spatial filters usually. The performance of current version of the computer code is greater than one image per second for a THz image having more than 5000 pixels and 24 bit number representation. Processing of THz single image produces about 20 images simultaneously corresponding to various spatial filters. The computer code allows increasing the number of pixels for processed images without noticeable reduction of image quality. The performance of the computer code can be increased many times using parallel algorithms for processing the image. We develop original spatial filters which allow one to see objects with sizes less than 2 cm. The imagery is produced by passive THz imaging devices which captured the images of objects hidden under opaque clothes. For images with high noise we develop an approach which results in suppression of the noise after using the computer processing and we obtain the good quality image. With the aim of illustrating the efficiency of the developed approach we demonstrate the detection of the liquid explosive, ordinary explosive, knife, pistol, metal plate, CD, ceramics, chocolate and other objects hidden under opaque clothes. The results demonstrate the high efficiency of our approach for the detection of hidden objects and they are a very promising solution for the security problem.

Advanced technology development for image gathering, coding, and processing

NASA Technical Reports Server (NTRS)

Huck, Friedrich O.

1990-01-01

Three overlapping areas of research activities are presented: (1) Information theory and optimal filtering are extended to visual information acquisition and processing. The goal is to provide a comprehensive methodology for quantitatively assessing the end-to-end performance of image gathering, coding, and processing. (2) Focal-plane processing techniques and technology are developed to combine effectively image gathering with coding. The emphasis is on low-level vision processing akin to the retinal processing in human vision. (3) A breadboard adaptive image-coding system is being assembled. This system will be used to develop and evaluate a number of advanced image-coding technologies and techniques as well as research the concept of adaptive image coding.

IMAGES: An interactive image processing system

NASA Technical Reports Server (NTRS)

Jensen, J. R.

1981-01-01

The IMAGES interactive image processing system was created specifically for undergraduate remote sensing education in geography. The system is interactive, relatively inexpensive to operate, almost hardware independent, and responsive to numerous users at one time in a time-sharing mode. Most important, it provides a medium whereby theoretical remote sensing principles discussed in lecture may be reinforced in laboratory as students perform computer-assisted image processing. In addition to its use in academic and short course environments, the system has also been used extensively to conduct basic image processing research. The flow of information through the system is discussed including an overview of the programs.

MEMS-based system and image processing strategy for epiretinal prosthesis.

PubMed

Xia, Peng; Hu, Jie; Qi, Jin; Gu, Chaochen; Peng, Yinghong

2015-01-01

Retinal prostheses have the potential to restore some level of visual function to the patients suffering from retinal degeneration. In this paper, an epiretinal approach with active stimulation devices is presented. The MEMS-based processing system consists of an external micro-camera, an information processor, an implanted electrical stimulator and a microelectrode array. The image processing strategy combining image clustering and enhancement techniques was proposed and evaluated by psychophysical experiments. The results indicated that the image processing strategy improved the visual performance compared with direct merging pixels to low resolution. The image processing methods assist epiretinal prosthesis for vision restoration.

Image processing system performance prediction and product quality evaluation

NASA Technical Reports Server (NTRS)

Stein, E. K.; Hammill, H. B. (Principal Investigator)

1976-01-01

The author has identified the following significant results. A new technique for image processing system performance prediction and product quality evaluation was developed. It was entirely objective, quantitative, and general, and should prove useful in system design and quality control. The technique and its application to determination of quality control procedures for the Earth Resources Technology Satellite NASA Data Processing Facility are described.

Almost equivalence of combinatorial and distance processes for discrimination in multielement images.

PubMed

Ferraro, M; Foster, D H

1991-01-01

Under certain experimental conditions, visual discrimination performance in multielement images is closely related to visual identification performance: elements of the image are distinguished only insofar as they appear to have distinct, discrete, internal characterizations. This report is concerned with the detailed relationship between such internal characterizations and observable discrimination performance. Two types of general processes that might underline discrimination are considered. The first is based on computing all possible internal image characterizations that could allow a correct decision, each characterization weighted by the probability of its occurrence and of a correct decision being made. The second process is based on computing the difference between the probabilities associated with the internal characterizations of the individual image elements, the difference quantified naturally with an l(p) norm. The relationship between the two processes was investigated analytically and by Monte Carlo simulations over a plausible range of numbers n of the internal characterizations of each of the m elements in the image. The predictions of the two processes were found to be closely similar. The relationship was precisely one-to-one, however, only for n = 2, m = 3, 4, 6, and for n greater than 2, m = 3, 4, p = 2. For all other cases tested, a one-to-one relationship was shown to be impossible.

Metal-induced streak artifact reduction using iterative reconstruction algorithms in x-ray computed tomography image of the dentoalveolar region.

PubMed

Dong, Jian; Hayakawa, Yoshihiko; Kannenberg, Sven; Kober, Cornelia

2013-02-01

The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.

Comparing multiple turbulence restoration algorithms performance on noisy anisoplanatic imagery

NASA Astrophysics Data System (ADS)

Rucci, Michael A.; Hardie, Russell C.; Dapore, Alexander J.

2017-05-01

In this paper, we compare the performance of multiple turbulence mitigation algorithms to restore imagery degraded by atmospheric turbulence and camera noise. In order to quantify and compare algorithm performance, imaging scenes were simulated by applying noise and varying levels of turbulence. For the simulation, a Monte-Carlo wave optics approach is used to simulate the spatially and temporally varying turbulence in an image sequence. A Poisson-Gaussian noise mixture model is then used to add noise to the observed turbulence image set. These degraded image sets are processed with three separate restoration algorithms: Lucky Look imaging, bispectral speckle imaging, and a block matching method with restoration filter. These algorithms were chosen because they incorporate different approaches and processing techniques. The results quantitatively show how well the algorithms are able to restore the simulated degraded imagery.

Processing and refinement of steel microstructure images for assisting in computerized heat treatment of plain carbon steel

NASA Astrophysics Data System (ADS)

Gupta, Shubhank; Panda, Aditi; Naskar, Ruchira; Mishra, Dinesh Kumar; Pal, Snehanshu

2017-11-01

Steels are alloys of iron and carbon, widely used in construction and other applications. The evolution of steel microstructure through various heat treatment processes is an important factor in controlling properties and performance of steel. Extensive experimentations have been performed to enhance the properties of steel by customizing heat treatment processes. However, experimental analyses are always associated with high resource requirements in terms of cost and time. As an alternative solution, we propose an image processing-based technique for refinement of raw plain carbon steel microstructure images, into a digital form, usable in experiments related to heat treatment processes of steel in diverse applications. The proposed work follows the conventional steps practiced by materials engineers in manual refinement of steel images; and it appropriately utilizes basic image processing techniques (including filtering, segmentation, opening, and clustering) to automate the whole process. The proposed refinement of steel microstructure images is aimed to enable computer-aided simulations of heat treatment of plain carbon steel, in a timely and cost-efficient manner; hence it is beneficial for the materials and metallurgy industry. Our experimental results prove the efficiency and effectiveness of the proposed technique.

Pleiades image quality: from users' needs to products definition

NASA Astrophysics Data System (ADS)

Kubik, Philippe; Pascal, Véronique; Latry, Christophe; Baillarin, Simon

2005-10-01

Pleiades is the highest resolution civilian earth observing system ever developed in Europe. This imagery programme is conducted by the French National Space Agency, CNES. It will operate in 2008-2009 two agile satellites designed to provide optical images to civilian and defence users. Images will be simultaneously acquired in Panchromatic (PA) and multispectral (XS) mode, which allows, in Nadir acquisition condition, to deliver 20 km wide, false or natural colored scenes with a 70 cm ground sampling distance after PA+XS fusion. Imaging capabilities have been highly optimized in order to acquire along-track mosaics, stereo pairs and triplets, and multi-targets. To fulfill the operational requirements and ensure quick access to information, ground processing has to automatically perform the radiometrical and geometrical corrections. Since ground processing capabilities have been taken into account very early in the programme development, it has been possible to relax some costly on-board components requirements, in order to achieve a cost effective on-board/ground compromise. Starting from an overview of the system characteristics, this paper deals with the image products definition (raw level, perfect sensor, orthoimage and along-track orthomosaics), and the main processing steps. It shows how each system performance is a result of the satellite performance followed by an appropriate ground processing. Finally, it focuses on the radiometrical performances of final products which are intimately linked to the following processing steps : radiometrical corrections, PA restoration, image resampling and PAN-sharpening.

High performance computing environment for multidimensional image analysis

PubMed Central

Rao, A Ravishankar; Cecchi, Guillermo A; Magnasco, Marcelo

2007-01-01

Background The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. Results We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478× speedup. Conclusion Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets. PMID:17634099

High performance computing environment for multidimensional image analysis.

PubMed

Rao, A Ravishankar; Cecchi, Guillermo A; Magnasco, Marcelo

2007-07-10

The processing of images acquired through microscopy is a challenging task due to the large size of datasets (several gigabytes) and the fast turnaround time required. If the throughput of the image processing stage is significantly increased, it can have a major impact in microscopy applications. We present a high performance computing (HPC) solution to this problem. This involves decomposing the spatial 3D image into segments that are assigned to unique processors, and matched to the 3D torus architecture of the IBM Blue Gene/L machine. Communication between segments is restricted to the nearest neighbors. When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478x speedup. Our parallel solution dramatically improves the performance of image processing, feature extraction and 3D reconstruction tasks. This increased throughput permits biologists to conduct unprecedented large scale experiments with massive datasets.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Fast optically sectioned fluorescence HiLo endomicroscopy.

PubMed

Ford, Tim N; Lim, Daryl; Mertz, Jerome

2012-02-01

We describe a nonscanning, fiber bundle endomicroscope that performs optically sectioned fluorescence imaging with fast frame rates and real-time processing. Our sectioning technique is based on HiLo imaging, wherein two widefield images are acquired under uniform and structured illumination and numerically processed to reject out-of-focus background. This work is an improvement upon an earlier demonstration of widefield optical sectioning through a flexible fiber bundle. The improved device features lateral and axial resolutions of 2.6 and 17 μm, respectively, a net frame rate of 9.5 Hz obtained by real-time image processing with a graphics processing unit (GPU) and significantly reduced motion artifacts obtained by the use of a double-shutter camera. We demonstrate the performance of our system with optically sectioned images and videos of a fluorescently labeled chorioallantoic membrane (CAM) in the developing G. gallus embryo. HiLo endomicroscopy is a candidate technique for low-cost, high-speed clinical optical biopsies.

Fast optically sectioned fluorescence HiLo endomicroscopy

NASA Astrophysics Data System (ADS)

Ford, Tim N.; Lim, Daryl; Mertz, Jerome

2012-02-01

We describe a nonscanning, fiber bundle endomicroscope that performs optically sectioned fluorescence imaging with fast frame rates and real-time processing. Our sectioning technique is based on HiLo imaging, wherein two widefield images are acquired under uniform and structured illumination and numerically processed to reject out-of-focus background. This work is an improvement upon an earlier demonstration of widefield optical sectioning through a flexible fiber bundle. The improved device features lateral and axial resolutions of 2.6 and 17 μm, respectively, a net frame rate of 9.5 Hz obtained by real-time image processing with a graphics processing unit (GPU) and significantly reduced motion artifacts obtained by the use of a double-shutter camera. We demonstrate the performance of our system with optically sectioned images and videos of a fluorescently labeled chorioallantoic membrane (CAM) in the developing G. gallus embryo. HiLo endomicroscopy is a candidate technique for low-cost, high-speed clinical optical biopsies.

Towards Portable Large-Scale Image Processing with High-Performance Computing.

PubMed

Huo, Yuankai; Blaber, Justin; Damon, Stephen M; Boyd, Brian D; Bao, Shunxing; Parvathaneni, Prasanna; Noguera, Camilo Bermudez; Chaganti, Shikha; Nath, Vishwesh; Greer, Jasmine M; Lyu, Ilwoo; French, William R; Newton, Allen T; Rogers, Baxter P; Landman, Bennett A

2018-05-03

High-throughput, large-scale medical image computing demands tight integration of high-performance computing (HPC) infrastructure for data storage, job distribution, and image processing. The Vanderbilt University Institute for Imaging Science (VUIIS) Center for Computational Imaging (CCI) has constructed a large-scale image storage and processing infrastructure that is composed of (1) a large-scale image database using the eXtensible Neuroimaging Archive Toolkit (XNAT), (2) a content-aware job scheduling platform using the Distributed Automation for XNAT pipeline automation tool (DAX), and (3) a wide variety of encapsulated image processing pipelines called "spiders." The VUIIS CCI medical image data storage and processing infrastructure have housed and processed nearly half-million medical image volumes with Vanderbilt Advanced Computing Center for Research and Education (ACCRE), which is the HPC facility at the Vanderbilt University. The initial deployment was natively deployed (i.e., direct installations on a bare-metal server) within the ACCRE hardware and software environments, which lead to issues of portability and sustainability. First, it could be laborious to deploy the entire VUIIS CCI medical image data storage and processing infrastructure to another HPC center with varying hardware infrastructure, library availability, and software permission policies. Second, the spiders were not developed in an isolated manner, which has led to software dependency issues during system upgrades or remote software installation. To address such issues, herein, we describe recent innovations using containerization techniques with XNAT/DAX which are used to isolate the VUIIS CCI medical image data storage and processing infrastructure from the underlying hardware and software environments. The newly presented XNAT/DAX solution has the following new features: (1) multi-level portability from system level to the application level, (2) flexible and dynamic software development and expansion, and (3) scalable spider deployment compatible with HPC clusters and local workstations.

Comparison of Photoluminescence Imaging on Starting Multi-Crystalline Silicon Wafers to Finished Cell Performance: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnston, S.; Yan, F.; Dorn, D.

2012-06-01

Photoluminescence (PL) imaging techniques can be applied to multicrystalline silicon wafers throughout the manufacturing process. Both band-to-band PL and defect-band emissions, which are longer-wavelength emissions from sub-bandgap transitions, are used to characterize wafer quality and defect content on starting multicrystalline silicon wafers and neighboring wafers processed at each step through completion of finished cells. Both PL imaging techniques spatially highlight defect regions that represent dislocations and defect clusters. The relative intensities of these imaged defect regions change with processing. Band-to-band PL on wafers in the later steps of processing shows good correlation to cell quality and performance. The defect bandmore » images show regions that change relative intensity through processing, and better correlation to cell efficiency and reverse-bias breakdown is more evident at the starting wafer stage as opposed to later process steps. We show that thermal processing in the 200 degrees - 400 degrees C range causes impurities to diffuse to different defect regions, changing their relative defect band emissions.« less

Structural and functional correlates for language efficiency in auditory word processing.

PubMed

Jung, JeYoung; Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally.

Structural and functional correlates for language efficiency in auditory word processing

PubMed Central

Kim, Sunmi; Cho, Hyesuk; Nam, Kichun

2017-01-01

This study aims to provide convergent understanding of the neural basis of auditory word processing efficiency using a multimodal imaging. We investigated the structural and functional correlates of word processing efficiency in healthy individuals. We acquired two structural imaging (T1-weighted imaging and diffusion tensor imaging) and functional magnetic resonance imaging (fMRI) during auditory word processing (phonological and semantic tasks). Our results showed that better phonological performance was predicted by the greater thalamus activity. In contrary, better semantic performance was associated with the less activation in the left posterior middle temporal gyrus (pMTG), supporting the neural efficiency hypothesis that better task performance requires less brain activation. Furthermore, our network analysis revealed the semantic network including the left anterior temporal lobe (ATL), dorsolateral prefrontal cortex (DLPFC) and pMTG was correlated with the semantic efficiency. Especially, this network acted as a neural efficient manner during auditory word processing. Structurally, DLPFC and cingulum contributed to the word processing efficiency. Also, the parietal cortex showed a significate association with the word processing efficiency. Our results demonstrated that two features of word processing efficiency, phonology and semantics, can be supported in different brain regions and, importantly, the way serving it in each region was different according to the feature of word processing. Our findings suggest that word processing efficiency can be achieved by in collaboration of multiple brain regions involved in language and general cognitive function structurally and functionally. PMID:28892503

Performance enhancement of various real-time image processing techniques via speculative execution

NASA Astrophysics Data System (ADS)

Younis, Mohamed F.; Sinha, Purnendu; Marlowe, Thomas J.; Stoyenko, Alexander D.

1996-03-01

In real-time image processing, an application must satisfy a set of timing constraints while ensuring the semantic correctness of the system. Because of the natural structure of digital data, pure data and task parallelism have been used extensively in real-time image processing to accelerate the handling time of image data. These types of parallelism are based on splitting the execution load performed by a single processor across multiple nodes. However, execution of all parallel threads is mandatory for correctness of the algorithm. On the other hand, speculative execution is an optimistic execution of part(s) of the program based on assumptions on program control flow or variable values. Rollback may be required if the assumptions turn out to be invalid. Speculative execution can enhance average, and sometimes worst-case, execution time. In this paper, we target various image processing techniques to investigate applicability of speculative execution. We identify opportunities for safe and profitable speculative execution in image compression, edge detection, morphological filters, and blob recognition.

Image processing system design for microcantilever-based optical readout infrared arrays

NASA Astrophysics Data System (ADS)

Tong, Qiang; Dong, Liquan; Zhao, Yuejin; Gong, Cheng; Liu, Xiaohua; Yu, Xiaomei; Yang, Lei; Liu, Weiyu

2012-12-01

Compared with the traditional infrared imaging technology, the new type of optical-readout uncooled infrared imaging technology based on MEMS has many advantages, such as low cost, small size, producing simple. In addition, the theory proves that the technology's high thermal detection sensitivity. So it has a very broad application prospects in the field of high performance infrared detection. The paper mainly focuses on an image capturing and processing system in the new type of optical-readout uncooled infrared imaging technology based on MEMS. The image capturing and processing system consists of software and hardware. We build our image processing core hardware platform based on TI's high performance DSP chip which is the TMS320DM642, and then design our image capturing board based on the MT9P031. MT9P031 is Micron's company high frame rate, low power consumption CMOS chip. Last we use Intel's company network transceiver devices-LXT971A to design the network output board. The software system is built on the real-time operating system DSP/BIOS. We design our video capture driver program based on TI's class-mini driver and network output program based on the NDK kit for image capturing and processing and transmitting. The experiment shows that the system has the advantages of high capturing resolution and fast processing speed. The speed of the network transmission is up to 100Mbps.

Efficient Parallel Levenberg-Marquardt Model Fitting towards Real-Time Automated Parametric Imaging Microscopy

PubMed Central

Zhu, Xiang; Zhang, Dianwen

2013-01-01

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance of GPU-LMFit for the applications in superresolution localization microscopy and fluorescence lifetime imaging microscopy. PMID:24130785

Real-time blood flow visualization using the graphics processing unit

NASA Astrophysics Data System (ADS)

Yang, Owen; Cuccia, David; Choi, Bernard

2011-01-01

Laser speckle imaging (LSI) is a technique in which coherent light incident on a surface produces a reflected speckle pattern that is related to the underlying movement of optical scatterers, such as red blood cells, indicating blood flow. Image-processing algorithms can be applied to produce speckle flow index (SFI) maps of relative blood flow. We present a novel algorithm that employs the NVIDIA Compute Unified Device Architecture (CUDA) platform to perform laser speckle image processing on the graphics processing unit. Software written in C was integrated with CUDA and integrated into a LabVIEW Virtual Instrument (VI) that is interfaced with a monochrome CCD camera able to acquire high-resolution raw speckle images at nearly 10 fps. With the CUDA code integrated into the LabVIEW VI, the processing and display of SFI images were performed also at ~10 fps. We present three video examples depicting real-time flow imaging during a reactive hyperemia maneuver, with fluid flow through an in vitro phantom, and a demonstration of real-time LSI during laser surgery of a port wine stain birthmark.

Real-time blood flow visualization using the graphics processing unit

PubMed Central

Yang, Owen; Cuccia, David; Choi, Bernard

2011-01-01

Laser speckle imaging (LSI) is a technique in which coherent light incident on a surface produces a reflected speckle pattern that is related to the underlying movement of optical scatterers, such as red blood cells, indicating blood flow. Image-processing algorithms can be applied to produce speckle flow index (SFI) maps of relative blood flow. We present a novel algorithm that employs the NVIDIA Compute Unified Device Architecture (CUDA) platform to perform laser speckle image processing on the graphics processing unit. Software written in C was integrated with CUDA and integrated into a LabVIEW Virtual Instrument (VI) that is interfaced with a monochrome CCD camera able to acquire high-resolution raw speckle images at nearly 10 fps. With the CUDA code integrated into the LabVIEW VI, the processing and display of SFI images were performed also at ∼10 fps. We present three video examples depicting real-time flow imaging during a reactive hyperemia maneuver, with fluid flow through an in vitro phantom, and a demonstration of real-time LSI during laser surgery of a port wine stain birthmark. PMID:21280915

Some advances/results in monitoring road cracks from 2D pavement images within the scope of the collaborative FP7 TRIMM project

NASA Astrophysics Data System (ADS)

Baltazart, Vincent; Moliard, Jean-Marc; Amhaz, Rabih; Wright, Dean; Jethwa, Manish

2015-04-01

Monitoring road surface conditions is an important issue in many countries. Several projects have looked into this issue in recent years, including TRIMM 2011-2014. The objective of such projects has been to detect surface distresses, like cracking, raveling and water ponding, in order to plan effective road maintenance and to afford a better sustainability of the pavement. The monitoring of cracking conventionally focuses on open cracks on the surface of the pavement, as opposed to reflexive cracks embedded in the pavement materials. For monitoring surface condition, in situ human visual inspection has been gradually replaced by automatic image data collection at traffic speed. Off-line image processing techniques have been developed for monitoring surface condition in support of human visual control. Full automation of crack monitoring has been approached with caution, and depends on a proper manual assessment of the performance. This work firstly presents some aspects of the current state of monitoring that have been reported so far in the literature and in previous projects: imaging technology and image processing techniques. Then, the work presents the two image processing techniques that have been developed within the scope of the TRIMM project to automatically detect pavement cracking from images. The first technique is a heuristic approach (HA) based on the search for gradient within the image. It was originally developed to process pavement images from the French imaging device, Aigle-RN. The second technique, the Minimal Path Selection (MPS) method, has been developed within an ongoing PhD work at IFSTTAR. The proposed new technique provides a fine and accurate segmentation of the crack pattern along with the estimation of the crack width. HA has been assessed against the field data collection provided by Yotta and TRL with the imaging device Tempest 2. The performance assessment has been threefold: first it was performed against the reference data set including 130 km of pavement images over UK roads, second over a few selected short sections of contiguous pavement images, and finally over a few sample images as a case study. The performance of MPS has been assessed against an older image data base. Pixel-based PGT was available to provide the most sensitive performance assessment. MPS has shown its ability to provide a very accurate cracking pattern without reducing the image resolution on the segmented images. Thus, it allows measurement of the crack width; it is found to behave more robustly against the image texture and better matched for dealing with low contrast pavement images. The benchmarking of seven automatic segmentation techniques has been provided at both the pixel and the grid levels. The performance assessment includes three minimal path selection algorithms, namely MPS, Free Form Anisotropy (FFA), one geodesic contour with automatic selection of points of interests (GC-POI), HA, and two Markov-based methods. Among others, MPS approach reached the best performance at the pixel level while it is matched to the FFA approach at the grid level. Finally, the project has emphasized the need for a reliable ground truth data collection. Owing to its accuracy, MPS may serve as a reference benchmark for other methods to provide the automatic segmentation of pavement images at the pixel level and beyond. As a counterpart, MPS requires a reduction in the computing time. Keywords: cracking, automatic segmentation, image processing, pavement, surface distress, monitoring, DICE, performance

Automated inspection of hot steel slabs

DOEpatents

Martin, R.J.

1985-12-24

The disclosure relates to a real time digital image enhancement system for performing the image enhancement segmentation processing required for a real time automated system for detecting and classifying surface imperfections in hot steel slabs. The system provides for simultaneous execution of edge detection processing and intensity threshold processing in parallel on the same image data produced by a sensor device such as a scanning camera. The results of each process are utilized to validate the results of the other process and a resulting image is generated that contains only corresponding segmentation that is produced by both processes. 5 figs.

Automated inspection of hot steel slabs

DOEpatents

Martin, Ronald J.

1985-01-01

The disclosure relates to a real time digital image enhancement system for performing the image enhancement segmentation processing required for a real time automated system for detecting and classifying surface imperfections in hot steel slabs. The system provides for simultaneous execution of edge detection processing and intensity threshold processing in parallel on the same image data produced by a sensor device such as a scanning camera. The results of each process are utilized to validate the results of the other process and a resulting image is generated that contains only corresponding segmentation that is produced by both processes.

Real-Time Noise Removal for Line-Scanning Hyperspectral Devices Using a Minimum Noise Fraction-Based Approach

PubMed Central

Bjorgan, Asgeir; Randeberg, Lise Lyngsnes

2015-01-01

Processing line-by-line and in real-time can be convenient for some applications of line-scanning hyperspectral imaging technology. Some types of processing, like inverse modeling and spectral analysis, can be sensitive to noise. The MNF (minimum noise fraction) transform provides suitable denoising performance, but requires full image availability for the estimation of image and noise statistics. In this work, a modified algorithm is proposed. Incrementally-updated statistics enables the algorithm to denoise the image line-by-line. The denoising performance has been compared to conventional MNF and found to be equal. With a satisfying denoising performance and real-time implementation, the developed algorithm can denoise line-scanned hyperspectral images in real-time. The elimination of waiting time before denoised data are available is an important step towards real-time visualization of processed hyperspectral data. The source code can be found at http://www.github.com/ntnu-bioopt/mnf. This includes an implementation of conventional MNF denoising. PMID:25654717

Phase correction system for automatic focusing of synthetic aperture radar

DOEpatents

Eichel, Paul H.; Ghiglia, Dennis C.; Jakowatz, Jr., Charles V.

1990-01-01

A phase gradient autofocus system for use in synthetic aperture imaging accurately compensates for arbitrary phase errors in each imaged frame by locating highlighted areas and determining the phase disturbance or image spread associated with each of these highlight areas. An estimate of the image spread for each highlighted area in a line in the case of one dimensional processing or in a sector, in the case of two-dimensional processing, is determined. The phase error is determined using phase gradient processing. The phase error is then removed from the uncorrected image and the process is iteratively performed to substantially eliminate phase errors which can degrade the image.

Integration of image capture and processing: beyond single-chip digital camera

NASA Astrophysics Data System (ADS)

Lim, SukHwan; El Gamal, Abbas

2001-05-01

An important trend in the design of digital cameras is the integration of capture and processing onto a single CMOS chip. Although integrating the components of a digital camera system onto a single chip significantly reduces system size and power, it does not fully exploit the potential advantages of integration. We argue that a key advantage of integration is the ability to exploit the high speed imaging capability of CMOS image senor to enable new applications such as multiple capture for enhancing dynamic range and to improve the performance of existing applications such as optical flow estimation. Conventional digital cameras operate at low frame rates and it would be too costly, if not infeasible, to operate their chips at high frame rates. Integration solves this problem. The idea is to capture images at much higher frame rates than he standard frame rate, process the high frame rate data on chip, and output the video sequence and the application specific data at standard frame rate. This idea is applied to optical flow estimation, where significant performance improvements are demonstrate over methods using standard frame rate sequences. We then investigate the constraints on memory size and processing power that can be integrated with a CMOS image sensor in a 0.18 micrometers process and below. We show that enough memory and processing power can be integrated to be able to not only perform the functions of a conventional camera system but also to perform applications such as real time optical flow estimation.

Fast Image Restoration for Spatially Varying Defocus Blur of Imaging Sensor

PubMed Central

Cheong, Hejin; Chae, Eunjung; Lee, Eunsung; Jo, Gwanghyun; Paik, Joonki

2015-01-01

This paper presents a fast adaptive image restoration method for removing spatially varying out-of-focus blur of a general imaging sensor. After estimating the parameters of space-variant point-spread-function (PSF) using the derivative in each uniformly blurred region, the proposed method performs spatially adaptive image restoration by selecting the optimal restoration filter according to the estimated blur parameters. Each restoration filter is implemented in the form of a combination of multiple FIR filters, which guarantees the fast image restoration without the need of iterative or recursive processing. Experimental results show that the proposed method outperforms existing space-invariant restoration methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed to a wide area of image restoration applications, such as mobile imaging devices, robot vision, and satellite image processing. PMID:25569760

The Pan-STARRS PS1 Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Magnier, E.

The Pan-STARRS PS1 Image Processing Pipeline (IPP) performs the image processing and data analysis tasks needed to enable the scientific use of the images obtained by the Pan-STARRS PS1 prototype telescope. The primary goals of the IPP are to process the science images from the Pan-STARRS telescopes and make the results available to other systems within Pan-STARRS. It also is responsible for combining all of the science images in a given filter into a single representation of the non-variable component of the night sky defined as the "Static Sky". To achieve these goals, the IPP also performs other analysis functions to generate the calibrations needed in the science image processing, and to occasionally use the derived data to generate improved astrometric and photometric reference catalogs. It also provides the infrastructure needed to store the incoming data and the resulting data products. The IPP inherits lessons learned, and in some cases code and prototype code, from several other astronomy image analysis systems, including Imcat (Kaiser), the Sloan Digital Sky Survey (REF), the Elixir system (Magnier & Cuillandre), and Vista (Tonry). Imcat and Vista have a large number of robust image processing functions. SDSS has demonstrated a working analysis pipeline and large-scale databasesystem for a dedicated project. The Elixir system has demonstrated an automatic image processing system and an object database system for operational usage. This talk will present an overview of the IPP architecture, functional flow, code development structure, and selected analysis algorithms. Also discussed is the HW highly parallel HW configuration necessary to support PS1 operational requirements. Finally, results are presented of the processing of images collected during PS1 early commissioning tasks utilizing the Pan-STARRS Test Camera #3.

SIproc: an open-source biomedical data processing platform for large hyperspectral images.

PubMed

Berisha, Sebastian; Chang, Shengyuan; Saki, Sam; Daeinejad, Davar; He, Ziqi; Mankar, Rupali; Mayerich, David

2017-04-10

There has recently been significant interest within the vibrational spectroscopy community to apply quantitative spectroscopic imaging techniques to histology and clinical diagnosis. However, many of the proposed methods require collecting spectroscopic images that have a similar region size and resolution to the corresponding histological images. Since spectroscopic images contain significantly more spectral samples than traditional histology, the resulting data sets can approach hundreds of gigabytes to terabytes in size. This makes them difficult to store and process, and the tools available to researchers for handling large spectroscopic data sets are limited. Fundamental mathematical tools, such as MATLAB, Octave, and SciPy, are extremely powerful but require that the data be stored in fast memory. This memory limitation becomes impractical for even modestly sized histological images, which can be hundreds of gigabytes in size. In this paper, we propose an open-source toolkit designed to perform out-of-core processing of hyperspectral images. By taking advantage of graphical processing unit (GPU) computing combined with adaptive data streaming, our software alleviates common workstation memory limitations while achieving better performance than existing applications.

Light-Field Imaging Toolkit

NASA Astrophysics Data System (ADS)

Bolan, Jeffrey; Hall, Elise; Clifford, Chris; Thurow, Brian

The Light-Field Imaging Toolkit (LFIT) is a collection of MATLAB functions designed to facilitate the rapid processing of raw light field images captured by a plenoptic camera. An included graphical user interface streamlines the necessary post-processing steps associated with plenoptic images. The generation of perspective shifted views and computationally refocused images is supported, in both single image and animated formats. LFIT performs necessary calibration, interpolation, and structuring steps to enable future applications of this technology.

[Investigation of the accurate measurement of the basic imaging properties for the digital radiographic system based on flat panel detector].

PubMed

Katayama, R; Sakai, S; Sakaguchi, T; Maeda, T; Takada, K; Hayabuchi, N; Morishita, J

2008-07-20

PURPOSE/AIM OF THE EXHIBIT: The purpose of this exhibit is: 1. To explain "resampling", an image data processing, performed by the digital radiographic system based on flat panel detector (FPD). 2. To show the influence of "resampling" on the basic imaging properties. 3. To present accurate measurement methods of the basic imaging properties of the FPD system. 1. The relationship between the matrix sizes of the output image and the image data acquired on FPD that automatically changes depending on a selected image size (FOV). 2. The explanation of the image data processing of "resampling". 3. The evaluation results of the basic imaging properties of the FPD system using two types of DICOM image to which "resampling" was performed: characteristic curves, presampled MTFs, noise power spectra, detective quantum efficiencies. CONCLUSION/SUMMARY: The major points of the exhibit are as follows: 1. The influence of "resampling" should not be disregarded in the evaluation of the basic imaging properties of the flat panel detector system. 2. It is necessary for the basic imaging properties to be measured by using DICOM image to which no "resampling" is performed.

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Spotlight-8 Image Analysis Software

NASA Technical Reports Server (NTRS)

Klimek, Robert; Wright, Ted

2006-01-01

Spotlight is a cross-platform GUI-based software package designed to perform image analysis on sequences of images generated by combustion and fluid physics experiments run in a microgravity environment. Spotlight can perform analysis on a single image in an interactive mode or perform analysis on a sequence of images in an automated fashion. Image processing operations can be employed to enhance the image before various statistics and measurement operations are performed. An arbitrarily large number of objects can be analyzed simultaneously with independent areas of interest. Spotlight saves results in a text file that can be imported into other programs for graphing or further analysis. Spotlight can be run on Microsoft Windows, Linux, and Apple OS X platforms.

Right hemisphere performance and competence in processing mental images, in a case of partial interhemispheric disconnection.

PubMed

Blanc-Garin, J; Faure, S; Sabio, P

1993-05-01

The objective of this study was to analyze dynamic aspects of right hemisphere implementation in processing visual images. Two tachistoscopic, divided visual field experiments were carried out on a partial split-brain patient with no damage to the right hemisphere. In the first experiment, image generation performance for letters presented in the right visual field (/left hemisphere) was undeniably optimal. In the left visual field (/right hemisphere), performance was no better than chance level at first, but then improved dramatically across stimulation blocks, in each of five successive sessions. This was interpreted as revealing the progressive spontaneous activation of the right hemisphere's competence not shown initially. The aim of the second experiment was to determine some conditions under which this pattern was obtained. The experimental design contrasted stimuli (words and pictures) and representational activity (phonologic and visuo-imaged processing). The right visual field (/left hemisphere: LH) elicited higher performance than the left visual field (/right hemisphere, RH) in the three situations where verbal activity was required. No superiority could be found when visual images were to be generated from pictures: parallel and weak improvement of both hemispheres was observed across sessions. Two other patterns were obtained: improvement in RH performance (although LH performance remained superior) and an unexpectedly large decrease in RH performance. These data are discussed in terms of RH cognitive competence and hemisphere implementation.

Our transthoracic biopsy practices accompanied by the imaging process: The contribution of positron emission tomography usage to accurate diagnosis.

PubMed

İntepe, Yavuz Selim; Metin, Bayram; Şahin, Sevinç; Kaya, Buğra; Okur, Aylin

2016-08-01

The objective of this study was to compare the results of transthoracic biopsies performed through the use of FDG PET/CT imaging with the results of transthoracic needle biopsy performed without using the FDG PET/CT imaging. The medical files of a total of 58 patients with pulmonary and mediastinal masses. A total of 20 patients, who were suspected of malignancy with the SUVmax value of over 2.5 in FDG PET/CT, underwent a biopsy process. Twelve patients with no suspicion of malignancy in accordance with CT images and with the SUVmax value below 2.5 underwent no biopsy procedure, and hence, they were excluded from the study. On the other hand, 26 patients directly went through a biopsy process with the suspicion of malignancy according to CT imaging, regardless of performing any FDG PET/CT imaging. According to the biopsy results, the number of the patients diagnosed with cancer was 20 (43.5%), while the number of non-cancerous patients was 26 (56.5%). When these findings were considered, it was determined that the sensitivity of the whole TTNB (transthoracic needle biopsy) was 80.8%, and the specificity was found as 100%. The positive predictive value of the whole TTNB was 100%, while its negative predictive value was found to be 80%. The sensitivity in TTNB performed together with FDG PET/CT was 90.9%, whereas the specificity was 100%. The positive predictive value of TTNB with FDG PET/CT was 100%, while its negative predictive value was found to be 81.8%. The sensitivity in TTNB performed without the use of FDG PET/CT was 73.3%, whereas the specificity was determined as 100%. Performing FDG PET/CT imaging process prior to a transthoracic biopsy as well as preferring FDG PET/CT for the spot on which the biopsy will be performed during the transthoracic biopsy procedure increases the rate of receiving accurate diagnosis.

[Imaging center - optimization of the imaging process].

PubMed

Busch, H-P

2013-04-01

Hospitals around the world are under increasing pressure to optimize the economic efficiency of treatment processes. Imaging is responsible for a great part of the success but also of the costs of treatment. In routine work an excessive supply of imaging methods leads to an "as well as" strategy up to the limit of the capacity without critical reflection. Exams that have no predictable influence on the clinical outcome are an unjustified burden for the patient. They are useless and threaten the financial situation and existence of the hospital. In recent years the focus of process optimization was exclusively on the quality and efficiency of performed single examinations. In the future critical discussion of the effectiveness of single exams in relation to the clinical outcome will be more important. Unnecessary exams can be avoided, only if in addition to the optimization of single exams (efficiency) there is an optimization strategy for the total imaging process (efficiency and effectiveness). This requires a new definition of processes (Imaging Pathway), new structures for organization (Imaging Center) and a new kind of thinking on the part of the medical staff. Motivation has to be changed from gratification of performed exams to gratification of process quality (medical quality, service quality, economics), including the avoidance of additional (unnecessary) exams. © Georg Thieme Verlag KG Stuttgart · New York.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

PubMed

Leong, Siow Hoo; Ong, Seng Huat

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

PubMed Central

Leong, Siow Hoo

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

Performance of an image analysis processing system for hen tracking in an environmental preference chamber.

PubMed

Kashiha, Mohammad Amin; Green, Angela R; Sales, Tatiana Glogerley; Bahr, Claudia; Berckmans, Daniel; Gates, Richard S

2014-10-01

Image processing systems have been widely used in monitoring livestock for many applications, including identification, tracking, behavior analysis, occupancy rates, and activity calculations. The primary goal of this work was to quantify image processing performance when monitoring laying hens by comparing length of stay in each compartment as detected by the image processing system with the actual occurrences registered by human observations. In this work, an image processing system was implemented and evaluated for use in an environmental animal preference chamber to detect hen navigation between 4 compartments of the chamber. One camera was installed above each compartment to produce top-view images of the whole compartment. An ellipse-fitting model was applied to captured images to detect whether the hen was present in a compartment. During a choice-test study, mean ± SD success detection rates of 95.9 ± 2.6% were achieved when considering total duration of compartment occupancy. These results suggest that the image processing system is currently suitable for determining the response measures for assessing environmental choices. Moreover, the image processing system offered a comprehensive analysis of occupancy while substantially reducing data processing time compared with the time-intensive alternative of manual video analysis. The above technique was used to monitor ammonia aversion in the chamber. As a preliminary pilot study, different levels of ammonia were applied to different compartments while hens were allowed to navigate between compartments. Using the automated monitor tool to assess occupancy, a negative trend of compartment occupancy with ammonia level was revealed, though further examination is needed. ©2014 Poultry Science Association Inc.

Synthesizing parallel imaging applications using the CAP (computer-aided parallelization) tool

NASA Astrophysics Data System (ADS)

Gennart, Benoit A.; Mazzariol, Marc; Messerli, Vincent; Hersch, Roger D.

1997-12-01

Imaging applications such as filtering, image transforms and compression/decompression require vast amounts of computing power when applied to large data sets. These applications would potentially benefit from the use of parallel processing. However, dedicated parallel computers are expensive and their processing power per node lags behind that of the most recent commodity components. Furthermore, developing parallel applications remains a difficult task: writing and debugging the application is difficult (deadlocks), programs may not be portable from one parallel architecture to the other, and performance often comes short of expectations. In order to facilitate the development of parallel applications, we propose the CAP computer-aided parallelization tool which enables application programmers to specify at a high-level of abstraction the flow of data between pipelined-parallel operations. In addition, the CAP tool supports the programmer in developing parallel imaging and storage operations. CAP enables combining efficiently parallel storage access routines and image processing sequential operations. This paper shows how processing and I/O intensive imaging applications must be implemented to take advantage of parallelism and pipelining between data access and processing. This paper's contribution is (1) to show how such implementations can be compactly specified in CAP, and (2) to demonstrate that CAP specified applications achieve the performance of custom parallel code. The paper analyzes theoretically the performance of CAP specified applications and demonstrates the accuracy of the theoretical analysis through experimental measurements.

Neural Substrates for Processing Task-Irrelevant Sad Images in Adolescents

ERIC Educational Resources Information Center

Wang, Lihong; Huettel, Scott; De Bellis, Michael D.

2008-01-01

Neural systems related to cognitive and emotional processing were examined in adolescents using event-related functional magnetic resonance imaging (fMRI). Ten healthy adolescents performed an emotional oddball task. Subjects detected infrequent circles (targets) within a continual stream of phase-scrambled images (standards). Sad and neutral…

Image processing for flight crew enhanced situation awareness

NASA Technical Reports Server (NTRS)

Roberts, Barry

1993-01-01

This presentation describes the image processing work that is being performed for the Enhanced Situational Awareness System (ESAS) application. Specifically, the presented work supports the Enhanced Vision System (EVS) component of ESAS.

Building high-performance system for processing a daily large volume of Chinese satellites imagery

NASA Astrophysics Data System (ADS)

Deng, Huawu; Huang, Shicun; Wang, Qi; Pan, Zhiqiang; Xin, Yubin

2014-10-01

The number of Earth observation satellites from China increases dramatically recently and those satellites are acquiring a large volume of imagery daily. As the main portal of image processing and distribution from those Chinese satellites, the China Centre for Resources Satellite Data and Application (CRESDA) has been working with PCI Geomatics during the last three years to solve two issues in this regard: processing the large volume of data (about 1,500 scenes or 1 TB per day) in a timely manner and generating geometrically accurate orthorectified products. After three-year research and development, a high performance system has been built and successfully delivered. The high performance system has a service oriented architecture and can be deployed to a cluster of computers that may be configured with high end computing power. The high performance is gained through, first, making image processing algorithms into parallel computing by using high performance graphic processing unit (GPU) cards and multiple cores from multiple CPUs, and, second, distributing processing tasks to a cluster of computing nodes. While achieving up to thirty (and even more) times faster in performance compared with the traditional practice, a particular methodology was developed to improve the geometric accuracy of images acquired from Chinese satellites (including HJ-1 A/B, ZY-1-02C, ZY-3, GF-1, etc.). The methodology consists of fully automatic collection of dense ground control points (GCP) from various resources and then application of those points to improve the photogrammetric model of the images. The delivered system is up running at CRESDA for pre-operational production and has been and is generating good return on investment by eliminating a great amount of manual labor and increasing more than ten times of data throughput daily with fewer operators. Future work, such as development of more performance-optimized algorithms, robust image matching methods and application workflows, is identified to improve the system in the coming years.

AOIPS - An interactive image processing system. [Atmospheric and Oceanic Information Processing System

NASA Technical Reports Server (NTRS)

Bracken, P. A.; Dalton, J. T.; Quann, J. J.; Billingsley, J. B.

1978-01-01

The Atmospheric and Oceanographic Information Processing System (AOIPS) was developed to help applications investigators perform required interactive image data analysis rapidly and to eliminate the inefficiencies and problems associated with batch operation. This paper describes the configuration and processing capabilities of AOIPS and presents unique subsystems for displaying, analyzing, storing, and manipulating digital image data. Applications of AOIPS to research investigations in meteorology and earth resources are featured.

Gradient-based multiresolution image fusion.

PubMed

Petrović, Valdimir S; Xydeas, Costas S

2004-02-01

A novel approach to multiresolution signal-level image fusion is presented for accurately transferring visual information from any number of input image signals, into a single fused image without loss of information or the introduction of distortion. The proposed system uses a "fuse-then-decompose" technique realized through a novel, fusion/decomposition system architecture. In particular, information fusion is performed on a multiresolution gradient map representation domain of image signal information. At each resolution, input images are represented as gradient maps and combined to produce new, fused gradient maps. Fused gradient map signals are processed, using gradient filters derived from high-pass quadrature mirror filters to yield a fused multiresolution pyramid representation. The fused output image is obtained by applying, on the fused pyramid, a reconstruction process that is analogous to that of conventional discrete wavelet transform. This new gradient fusion significantly reduces the amount of distortion artefacts and the loss of contrast information usually observed in fused images obtained from conventional multiresolution fusion schemes. This is because fusion in the gradient map domain significantly improves the reliability of the feature selection and information fusion processes. Fusion performance is evaluated through informal visual inspection and subjective psychometric preference tests, as well as objective fusion performance measurements. Results clearly demonstrate the superiority of this new approach when compared to conventional fusion systems.

Image quality and dose differences caused by vendor-specific image processing of neonatal radiographs.

PubMed

Sensakovic, William F; O'Dell, M Cody; Letter, Haley; Kohler, Nathan; Rop, Baiywo; Cook, Jane; Logsdon, Gregory; Varich, Laura

2016-10-01

Image processing plays an important role in optimizing image quality and radiation dose in projection radiography. Unfortunately commercial algorithms are black boxes that are often left at or near vendor default settings rather than being optimized. We hypothesize that different commercial image-processing systems, when left at or near default settings, create significant differences in image quality. We further hypothesize that image-quality differences can be exploited to produce images of equivalent quality but lower radiation dose. We used a portable radiography system to acquire images on a neonatal chest phantom and recorded the entrance surface air kerma (ESAK). We applied two image-processing systems (Optima XR220amx, by GE Healthcare, Waukesha, WI; and MUSICA(2) by Agfa HealthCare, Mortsel, Belgium) to the images. Seven observers (attending pediatric radiologists and radiology residents) independently assessed image quality using two methods: rating and matching. Image-quality ratings were independently assessed by each observer on a 10-point scale. Matching consisted of each observer matching GE-processed images and Agfa-processed images with equivalent image quality. A total of 210 rating tasks and 42 matching tasks were performed and effective dose was estimated. Median Agfa-processed image-quality ratings were higher than GE-processed ratings. Non-diagnostic ratings were seen over a wider range of doses for GE-processed images than for Agfa-processed images. During matching tasks, observers matched image quality between GE-processed images and Agfa-processed images acquired at a lower effective dose (11 ± 9 μSv; P < 0.0001). Image-processing methods significantly impact perceived image quality. These image-quality differences can be exploited to alter protocols and produce images of equivalent image quality but lower doses. Those purchasing projection radiography systems or third-party image-processing software should be aware that image processing can significantly impact image quality when settings are left near default values.

Image processing methods in two and three dimensions used to animate remotely sensed data. [cloud cover

NASA Technical Reports Server (NTRS)

Hussey, K. J.; Hall, J. R.; Mortensen, R. A.

1986-01-01

Image processing methods and software used to animate nonimaging remotely sensed data on cloud cover are described. Three FORTRAN programs were written in the VICAR2/TAE image processing domain to perform 3D perspective rendering, to interactively select parameters controlling the projection, and to interpolate parameter sets for animation images between key frames. Operation of the 3D programs and transferring the images to film is automated using executive control language and custom hardware to link the computer and camera.

Spatial Statistics for Tumor Cell Counting and Classification

NASA Astrophysics Data System (ADS)

Wirjadi, Oliver; Kim, Yoo-Jin; Breuel, Thomas

To count and classify cells in histological sections is a standard task in histology. One example is the grading of meningiomas, benign tumors of the meninges, which requires to assess the fraction of proliferating cells in an image. As this process is very time consuming when performed manually, automation is required. To address such problems, we propose a novel application of Markov point process methods in computer vision, leading to algorithms for computing the locations of circular objects in images. In contrast to previous algorithms using such spatial statistics methods in image analysis, the present one is fully trainable. This is achieved by combining point process methods with statistical classifiers. Using simulated data, the method proposed in this paper will be shown to be more accurate and more robust to noise than standard image processing methods. On the publicly available SIMCEP benchmark for cell image analysis algorithms, the cell count performance of the present paper is significantly more accurate than results published elsewhere, especially when cells form dense clusters. Furthermore, the proposed system performs as well as a state-of-the-art algorithm for the computer-aided histological grading of meningiomas when combined with a simple k-nearest neighbor classifier for identifying proliferating cells.

Gaussian Process Interpolation for Uncertainty Estimation in Image Registration

PubMed Central

Wachinger, Christian; Golland, Polina; Reuter, Martin; Wells, William

2014-01-01

Intensity-based image registration requires resampling images on a common grid to evaluate the similarity function. The uncertainty of interpolation varies across the image, depending on the location of resampled points relative to the base grid. We propose to perform Bayesian inference with Gaussian processes, where the covariance matrix of the Gaussian process posterior distribution estimates the uncertainty in interpolation. The Gaussian process replaces a single image with a distribution over images that we integrate into a generative model for registration. Marginalization over resampled images leads to a new similarity measure that includes the uncertainty of the interpolation. We demonstrate that our approach increases the registration accuracy and propose an efficient approximation scheme that enables seamless integration with existing registration methods. PMID:25333127

Double Density Dual Tree Discrete Wavelet Transform implementation for Degraded Image Enhancement

NASA Astrophysics Data System (ADS)

Vimala, C.; Aruna Priya, P.

2018-04-01

Wavelet transform is a main tool for image processing applications in modern existence. A Double Density Dual Tree Discrete Wavelet Transform is used and investigated for image denoising. Images are considered for the analysis and the performance is compared with discrete wavelet transform and the Double Density DWT. Peak Signal to Noise Ratio values and Root Means Square error are calculated in all the three wavelet techniques for denoised images and the performance has evaluated. The proposed techniques give the better performance when comparing other two wavelet techniques.

The power of Kawaii: viewing cute images promotes a careful behavior and narrows attentional focus.

PubMed

Nittono, Hiroshi; Fukushima, Michiko; Yano, Akihiro; Moriya, Hiroki

2012-01-01

Kawaii (a Japanese word meaning "cute") things are popular because they produce positive feelings. However, their effect on behavior remains unclear. In this study, three experiments were conducted to examine the effects of viewing cute images on subsequent task performance. In the first experiment, university students performed a fine motor dexterity task before and after viewing images of baby or adult animals. Performance indexed by the number of successful trials increased after viewing cute images (puppies and kittens; M ± SE=43.9 ± 10.3% improvement) more than after viewing images that were less cute (dogs and cats; 11.9 ± 5.5% improvement). In the second experiment, this finding was replicated by using a non-motor visual search task. Performance improved more after viewing cute images (15.7 ± 2.2% improvement) than after viewing less cute images (1.4 ± 2.1% improvement). Viewing images of pleasant foods was ineffective in improving performance (1.2 ± 2.1%). In the third experiment, participants performed a global-local letter task after viewing images of baby animals, adult animals, and neutral objects. In general, global features were processed faster than local features. However, this global precedence effect was reduced after viewing cute images. Results show that participants performed tasks requiring focused attention more carefully after viewing cute images. This is interpreted as the result of a narrowed attentional focus induced by the cuteness-triggered positive emotion that is associated with approach motivation and the tendency toward systematic processing. For future applications, cute objects may be used as an emotion elicitor to induce careful behavioral tendencies in specific situations, such as driving and office work.

The Power of Kawaii: Viewing Cute Images Promotes a Careful Behavior and Narrows Attentional Focus

PubMed Central

Nittono, Hiroshi; Fukushima, Michiko; Yano, Akihiro; Moriya, Hiroki

2012-01-01

Kawaii (a Japanese word meaning “cute”) things are popular because they produce positive feelings. However, their effect on behavior remains unclear. In this study, three experiments were conducted to examine the effects of viewing cute images on subsequent task performance. In the first experiment, university students performed a fine motor dexterity task before and after viewing images of baby or adult animals. Performance indexed by the number of successful trials increased after viewing cute images (puppies and kittens; M ± SE = 43.9±10.3% improvement) more than after viewing images that were less cute (dogs and cats; 11.9±5.5% improvement). In the second experiment, this finding was replicated by using a non-motor visual search task. Performance improved more after viewing cute images (15.7±2.2% improvement) than after viewing less cute images (1.4±2.1% improvement). Viewing images of pleasant foods was ineffective in improving performance (1.2±2.1%). In the third experiment, participants performed a global–local letter task after viewing images of baby animals, adult animals, and neutral objects. In general, global features were processed faster than local features. However, this global precedence effect was reduced after viewing cute images. Results show that participants performed tasks requiring focused attention more carefully after viewing cute images. This is interpreted as the result of a narrowed attentional focus induced by the cuteness-triggered positive emotion that is associated with approach motivation and the tendency toward systematic processing. For future applications, cute objects may be used as an emotion elicitor to induce careful behavioral tendencies in specific situations, such as driving and office work. PMID:23050022

A cost-effective line-based light-balancing technique using adaptive processing.

PubMed

Hsia, Shih-Chang; Chen, Ming-Huei; Chen, Yu-Min

2006-09-01

The camera imaging system has been widely used; however, the displaying image appears to have an unequal light distribution. This paper presents novel light-balancing techniques to compensate uneven illumination based on adaptive signal processing. For text image processing, first, we estimate the background level and then process each pixel with nonuniform gain. This algorithm can balance the light distribution while keeping a high contrast in the image. For graph image processing, the adaptive section control using piecewise nonlinear gain is proposed to equalize the histogram. Simulations show that the performance of light balance is better than the other methods. Moreover, we employ line-based processing to efficiently reduce the memory requirement and the computational cost to make it applicable in real-time systems.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.

PubMed

Cao, Jianfang; Chen, Lichao; Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.

Fast optically sectioned fluorescence HiLo endomicroscopy

PubMed Central

Lim, Daryl; Mertz, Jerome

2012-01-01

Abstract. We describe a nonscanning, fiber bundle endomicroscope that performs optically sectioned fluorescence imaging with fast frame rates and real-time processing. Our sectioning technique is based on HiLo imaging, wherein two widefield images are acquired under uniform and structured illumination and numerically processed to reject out-of-focus background. This work is an improvement upon an earlier demonstration of widefield optical sectioning through a flexible fiber bundle. The improved device features lateral and axial resolutions of 2.6 and 17 μm, respectively, a net frame rate of 9.5 Hz obtained by real-time image processing with a graphics processing unit (GPU) and significantly reduced motion artifacts obtained by the use of a double-shutter camera. We demonstrate the performance of our system with optically sectioned images and videos of a fluorescently labeled chorioallantoic membrane (CAM) in the developing G. gallus embryo. HiLo endomicroscopy is a candidate technique for low-cost, high-speed clinical optical biopsies. PMID:22463023

Sentinel-2 ArcGIS Tool for Environmental Monitoring

NASA Astrophysics Data System (ADS)

Plesoianu, Alin; Cosmin Sandric, Ionut; Anca, Paula; Vasile, Alexandru; Calugaru, Andreea; Vasile, Cristian; Zavate, Lucian

2017-04-01

This paper addresses one of the biggest challenges regarding Sentinel-2 data, related to the need of an efficient tool to access and process the large collection of images that are available. Consequently, developing a tool for the automation of Sentinel-2 data analysis is the most immediate need. We developed a series of tools for the automation of Sentinel-2 data download and processing for vegetation health monitoring. The tools automatically perform the following operations: downloading image tiles from ESA's Scientific Hub or other venders (Amazon), pre-processing of the images to extract the 10-m bands, creating image composites, applying a series of vegetation indexes (NDVI, OSAVI, etc.) and performing change detection analyses on different temporal data sets. All of these tools run in a dynamic way in the ArcGIS Platform, without the need of creating intermediate datasets (rasters, layers), as the images are processed on-the-fly in order to avoid data duplication. Finally, they allow complete integration with the ArcGIS environment and workflows

A novel image toggle tool for comparison of serial mammograms: automatic density normalization and alignment-development of the tool and initial experience.

PubMed

Honda, Satoshi; Tsunoda, Hiroko; Fukuda, Wataru; Saida, Yukihisa

2014-12-01

The purpose is to develop a new image toggle tool with automatic density normalization (ADN) and automatic alignment (AA) for comparing serial digital mammograms (DMGs). We developed an ADN and AA process to compare the images of serial DMGs. In image density normalization, a linear interpolation was applied by taking two points of high- and low-brightness areas. The alignment was calculated by determining the point of the greatest correlation while shifting the alignment between the current and prior images. These processes were performed on a PC with a 3.20-GHz Xeon processor and 8 GB of main memory. We selected 12 suspected breast cancer patients who had undergone screening DMGs in the past. Automatic processing was retrospectively performed on these images. Two radiologists subjectively evaluated them. The process of the developed algorithm took approximately 1 s per image. In our preliminary experience, two images could not be aligned approximately. When they were aligned, image toggling allowed detection of differences between examinations easily. We developed a new tool to facilitate comparative reading of DMGs on a mammography viewing system. Using this tool for toggling comparisons might improve the interpretation efficiency of serial DMGs.

Flame analysis using image processing techniques

NASA Astrophysics Data System (ADS)

Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng

2018-04-01

This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.

Automated segmentation of three-dimensional MR brain images

NASA Astrophysics Data System (ADS)

Park, Jonggeun; Baek, Byungjun; Ahn, Choong-Il; Ku, Kyo Bum; Jeong, Dong Kyun; Lee, Chulhee

2006-03-01

Brain segmentation is a challenging problem due to the complexity of the brain. In this paper, we propose an automated brain segmentation method for 3D magnetic resonance (MR) brain images which are represented as a sequence of 2D brain images. The proposed method consists of three steps: pre-processing, removal of non-brain regions (e.g., the skull, meninges, other organs, etc), and spinal cord restoration. In pre-processing, we perform adaptive thresholding which takes into account variable intensities of MR brain images corresponding to various image acquisition conditions. In segmentation process, we iteratively apply 2D morphological operations and masking for the sequences of 2D sagittal, coronal, and axial planes in order to remove non-brain tissues. Next, final 3D brain regions are obtained by applying OR operation for segmentation results of three planes. Finally we reconstruct the spinal cord truncated during the previous processes. Experiments are performed with fifteen 3D MR brain image sets with 8-bit gray-scale. Experiment results show the proposed algorithm is fast, and provides robust and satisfactory results.

Prototype Focal-Plane-Array Optoelectronic Image Processor

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi; Shaw, Timothy; Yu, Jeffrey

1995-01-01

Prototype very-large-scale integrated (VLSI) planar array of optoelectronic processing elements combines speed of optical input and output with flexibility of reconfiguration (programmability) of electronic processing medium. Basic concept of processor described in "Optical-Input, Optical-Output Morphological Processor" (NPO-18174). Performs binary operations on binary (black and white) images. Each processing element corresponds to one picture element of image and located at that picture element. Includes input-plane photodetector in form of parasitic phototransistor part of processing circuit. Output of each processing circuit used to modulate one picture element in output-plane liquid-crystal display device. Intended to implement morphological processing algorithms that transform image into set of features suitable for high-level processing; e.g., recognition.

Image navigation and registration performance assessment tool set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

NASA Astrophysics Data System (ADS)

De Luccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

2016-05-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99. 73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

NASA Technical Reports Server (NTRS)

DeLuccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

2016-01-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

NASA Technical Reports Server (NTRS)

De Luccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

2016-01-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Processing Strategies Based on a Visual Saliency Model for Object Recognition Under Simulated Prosthetic Vision.

PubMed

Wang, Jing; Li, Heng; Fu, Weizhen; Chen, Yao; Li, Liming; Lyu, Qing; Han, Tingting; Chai, Xinyu

2016-01-01

Retinal prostheses have the potential to restore partial vision. Object recognition in scenes of daily life is one of the essential tasks for implant wearers. Still limited by the low-resolution visual percepts provided by retinal prostheses, it is important to investigate and apply image processing methods to convey more useful visual information to the wearers. We proposed two image processing strategies based on Itti's visual saliency map, region of interest (ROI) extraction, and image segmentation. Itti's saliency model generated a saliency map from the original image, in which salient regions were grouped into ROI by the fuzzy c-means clustering. Then Grabcut generated a proto-object from the ROI labeled image which was recombined with background and enhanced in two ways--8-4 separated pixelization (8-4 SP) and background edge extraction (BEE). Results showed that both 8-4 SP and BEE had significantly higher recognition accuracy in comparison with direct pixelization (DP). Each saliency-based image processing strategy was subject to the performance of image segmentation. Under good and perfect segmentation conditions, BEE and 8-4 SP obtained noticeably higher recognition accuracy than DP, and under bad segmentation condition, only BEE boosted the performance. The application of saliency-based image processing strategies was verified to be beneficial to object recognition in daily scenes under simulated prosthetic vision. They are hoped to help the development of the image processing module for future retinal prostheses, and thus provide more benefit for the patients. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic imaging model and parameter optimization for a star tracker.

PubMed

Yan, Jinyun; Jiang, Jie; Zhang, Guangjun

2016-03-21

Under dynamic conditions, star spots move across the image plane of a star tracker and form a smeared star image. This smearing effect increases errors in star position estimation and degrades attitude accuracy. First, an analytical energy distribution model of a smeared star spot is established based on a line segment spread function because the dynamic imaging process of a star tracker is equivalent to the static imaging process of linear light sources. The proposed model, which has a clear physical meaning, explicitly reflects the key parameters of the imaging process, including incident flux, exposure time, velocity of a star spot in an image plane, and Gaussian radius. Furthermore, an analytical expression of the centroiding error of the smeared star spot is derived using the proposed model. An accurate and comprehensive evaluation of centroiding accuracy is obtained based on the expression. Moreover, analytical solutions of the optimal parameters are derived to achieve the best performance in centroid estimation. Finally, we perform numerical simulations and a night sky experiment to validate the correctness of the dynamic imaging model, the centroiding error expression, and the optimal parameters.

Near Real-Time Image Reconstruction

NASA Astrophysics Data System (ADS)

Denker, C.; Yang, G.; Wang, H.

2001-08-01

In recent years, post-facto image-processing algorithms have been developed to achieve diffraction-limited observations of the solar surface. We present a combination of frame selection, speckle-masking imaging, and parallel computing which provides real-time, diffraction-limited, 256×256 pixel images at a 1-minute cadence. Our approach to achieve diffraction limited observations is complementary to adaptive optics (AO). At the moment, AO is limited by the fact that it corrects wavefront abberations only for a field of view comparable to the isoplanatic patch. This limitation does not apply to speckle-masking imaging. However, speckle-masking imaging relies on short-exposure images which limits its spectroscopic applications. The parallel processing of the data is performed on a Beowulf-class computer which utilizes off-the-shelf, mass-market technologies to provide high computational performance for scientific calculations and applications at low cost. Beowulf computers have a great potential, not only for image reconstruction, but for any kind of complex data reduction. Immediate access to high-level data products and direct visualization of dynamic processes on the Sun are two of the advantages to be gained.

F3D Image Processing and Analysis for Many - and Multi-core Platforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expeditesmore » any scientific workflow with image processing requirements. F3D performs several different types of 3D image processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.« less

EVALUATION OF REGISTRATION, COMPRESSION AND CLASSIFICATION ALGORITHMS

NASA Technical Reports Server (NTRS)

Jayroe, R. R.

1994-01-01

Several types of algorithms are generally used to process digital imagery such as Landsat data. The most commonly used algorithms perform the task of registration, compression, and classification. Because there are different techniques available for performing registration, compression, and classification, imagery data users need a rationale for selecting a particular approach to meet their particular needs. This collection of registration, compression, and classification algorithms was developed so that different approaches could be evaluated and the best approach for a particular application determined. Routines are included for six registration algorithms, six compression algorithms, and two classification algorithms. The package also includes routines for evaluating the effects of processing on the image data. This collection of routines should be useful to anyone using or developing image processing software. Registration of image data involves the geometrical alteration of the imagery. Registration routines available in the evaluation package include image magnification, mapping functions, partitioning, map overlay, and data interpolation. The compression of image data involves reducing the volume of data needed for a given image. Compression routines available in the package include adaptive differential pulse code modulation, two-dimensional transforms, clustering, vector reduction, and picture segmentation. Classification of image data involves analyzing the uncompressed or compressed image data to produce inventories and maps of areas of similar spectral properties within a scene. The classification routines available include a sequential linear technique and a maximum likelihood technique. The choice of the appropriate evaluation criteria is quite important in evaluating the image processing functions. The user is therefore given a choice of evaluation criteria with which to investigate the available image processing functions. All of the available evaluation criteria basically compare the observed results with the expected results. For the image reconstruction processes of registration and compression, the expected results are usually the original data or some selected characteristics of the original data. For classification processes the expected result is the ground truth of the scene. Thus, the comparison process consists of determining what changes occur in processing, where the changes occur, how much change occurs, and the amplitude of the change. The package includes evaluation routines for performing such comparisons as average uncertainty, average information transfer, chi-square statistics, multidimensional histograms, and computation of contingency matrices. This collection of routines is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 computer with a central memory requirement of approximately 662K of 8 bit bytes. This collection of image processing and evaluation routines was developed in 1979.

High performance thermal imaging for the 21st century

NASA Astrophysics Data System (ADS)

Clarke, David J.; Knowles, Peter

2003-01-01

In recent years IR detector technology has developed from early short linear arrays. Such devices require high performance signal processing electronics to meet today's thermal imaging requirements for military and para-military applications. This paper describes BAE SYSTEMS Avionics Group's Sensor Integrated Modular Architecture thermal imager which has been developed alongside the group's Eagle 640×512 arrays to provide high performance imaging capability. The electronics architecture also supprots High Definition TV format 2D arrays for future growth capability.

An optical processor for object recognition and tracking

NASA Technical Reports Server (NTRS)

Sloan, J.; Udomkesmalee, S.

1987-01-01

The design and development of a miniaturized optical processor that performs real time image correlation are described. The optical correlator utilizes the Vander Lugt matched spatial filter technique. The correlation output, a focused beam of light, is imaged onto a CMOS photodetector array. In addition to performing target recognition, the device also tracks the target. The hardware, composed of optical and electro-optical components, occupies only 590 cu cm of volume. A complete correlator system would also include an input imaging lens. This optical processing system is compact, rugged, requires only 3.5 watts of operating power, and weighs less than 3 kg. It represents a major achievement in miniaturizing optical processors. When considered as a special-purpose processing unit, it is an attractive alternative to conventional digital image recognition processing. It is conceivable that the combined technology of both optical and ditital processing could result in a very advanced robot vision system.

Graphics processing unit accelerated intensity-based optical coherence tomography angiography using differential frames with real-time motion correction.

PubMed

Watanabe, Yuuki; Takahashi, Yuhei; Numazawa, Hiroshi

2014-02-01

We demonstrate intensity-based optical coherence tomography (OCT) angiography using the squared difference of two sequential frames with bulk-tissue-motion (BTM) correction. This motion correction was performed by minimization of the sum of the pixel values using axial- and lateral-pixel-shifted structural OCT images. We extract the BTM-corrected image from a total of 25 calculated OCT angiographic images. Image processing was accelerated by a graphics processing unit (GPU) with many stream processors to optimize the parallel processing procedure. The GPU processing rate was faster than that of a line scan camera (46.9 kHz). Our OCT system provides the means of displaying structural OCT images and BTM-corrected OCT angiographic images in real time.

Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems.

PubMed

Choi, Hyungsuk; Choi, Woohyuk; Quan, Tran Minh; Hildebrand, David G C; Pfister, Hanspeter; Jeong, Won-Ki

2014-12-01

As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and GPU accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing GPU clusters is difficult for novice programmers, and even experienced programmers often fail to fully leverage the computing power of new parallel architectures due to their steep learning curve and programming complexity. In this paper, we propose Vivaldi, a new domain-specific language for volume processing and visualization on distributed heterogeneous computing systems. Vivaldi's Python-like grammar and parallel processing abstractions provide flexible programming tools for non-experts to easily write high-performance parallel computing code. Vivaldi provides commonly used functions and numerical operators for customized visualization and high-throughput image processing applications. We demonstrate the performance and usability of Vivaldi on several examples ranging from volume rendering to image segmentation.

A novel configurable VLSI architecture design of window-based image processing method

NASA Astrophysics Data System (ADS)

Zhao, Hui; Sang, Hongshi; Shen, Xubang

2018-03-01

Most window-based image processing architecture can only achieve a certain kind of specific algorithms, such as 2D convolution, and therefore lack the flexibility and breadth of application. In addition, improper handling of the image boundary can cause loss of accuracy, or consume more logic resources. For the above problems, this paper proposes a new VLSI architecture of window-based image processing operations, which is configurable and based on consideration of the image boundary. An efficient technique is explored to manage the image borders by overlapping and flushing phases at the end of row and the end of frame, which does not produce new delay and reduce the overhead in real-time applications. Maximize the reuse of the on-chip memory data, in order to reduce the hardware complexity and external bandwidth requirements. To perform different scalar function and reduction function operations in pipeline, this can support a variety of applications of window-based image processing. Compared with the performance of other reported structures, the performance of the new structure has some similarities to some of the structures, but also superior to some other structures. Especially when compared with a systolic array processor CWP, this structure at the same frequency of approximately 12.9% of the speed increases. The proposed parallel VLSI architecture was implemented with SIMC 0.18-μm CMOS technology, and the maximum clock frequency, power consumption, and area are 125Mhz, 57mW, 104.8K Gates, respectively, furthermore the processing time is independent of the different window-based algorithms mapped to the structure

Resiliency of the Multiscale Retinex Image Enhancement Algorithm

NASA Technical Reports Server (NTRS)

Rahman, Zia-Ur; Jobson, Daniel J.; Woodell, Glenn A.

1998-01-01

The multiscale retinex with color restoration (MSRCR) continues to prove itself in extensive testing to be very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition, However, issues remain with regard to the resiliency of the MSRCR to different image sources and arbitrary image manipulations which may have been applied prior to retinex processing. In this paper we define these areas of concern, provide experimental results, and, examine the effects of commonly occurring image manipulation on retinex performance. In virtually all cases the MSRCR is highly resilient to the effects of both the image source variations and commonly encountered prior image-processing. Significant artifacts are primarily observed for the case of selective color channel clipping in large dark zones in a image. These issues are of concerning the processing of digital image archives and other applications where there is neither control over the image acquisition process, nor knowledge about any processing done on th data beforehand.

Radar data processing and analysis

NASA Technical Reports Server (NTRS)

Ausherman, D.; Larson, R.; Liskow, C.

1976-01-01

Digitized four-channel radar images corresponding to particular areas from the Phoenix and Huntington test sites were generated in conjunction with prior experiments performed to collect X- and L-band synthetic aperture radar imagery of these two areas. The methods for generating this imagery are documented. A secondary objective was the investigation of digital processing techniques for extraction of information from the multiband radar image data. Following the digitization, the remaining resources permitted a preliminary machine analysis to be performed on portions of the radar image data. The results, although necessarily limited, are reported.

Comparison of ring artifact removal methods using flat panel detector based CT images

PubMed Central

2011-01-01

Background Ring artifacts are the concentric rings superimposed on the tomographic images often caused by the defective and insufficient calibrated detector elements as well as by the damaged scintillator crystals of the flat panel detector. It may be also generated by objects attenuating X-rays very differently in different projection direction. Ring artifact reduction techniques so far reported in the literature can be broadly classified into two groups. One category of the approaches is based on the sinogram processing also known as the pre-processing techniques and the other category of techniques perform processing on the 2-D reconstructed images, recognized as the post-processing techniques in the literature. The strength and weakness of these categories of approaches are yet to be explored from a common platform. Method In this paper, a comparative study of the two categories of ring artifact reduction techniques basically designed for the multi-slice CT instruments is presented from a common platform. For comparison, two representative algorithms from each of the two categories are selected from the published literature. A very recently reported state-of-the-art sinogram domain ring artifact correction method that classifies the ring artifacts according to their strength and then corrects the artifacts using class adaptive correction schemes is also included in this comparative study. The first sinogram domain correction method uses a wavelet based technique to detect the corrupted pixels and then using a simple linear interpolation technique estimates the responses of the bad pixels. The second sinogram based correction method performs all the filtering operations in the transform domain, i.e., in the wavelet and Fourier domain. On the other hand, the two post-processing based correction techniques actually operate on the polar transform domain of the reconstructed CT images. The first method extracts the ring artifact template vector using a homogeneity test and then corrects the CT images by subtracting the artifact template vector from the uncorrected images. The second post-processing based correction technique performs median and mean filtering on the reconstructed images to produce the corrected images. Results The performances of the comparing algorithms have been tested by using both quantitative and perceptual measures. For quantitative analysis, two different numerical performance indices are chosen. On the other hand, different types of artifact patterns, e.g., single/band ring, artifacts from defective and mis-calibrated detector elements, rings in highly structural object and also in hard object, rings from different flat-panel detectors are analyzed to perceptually investigate the strength and weakness of the five methods. An investigation has been also carried out to compare the efficacy of these algorithms in correcting the volume images from a cone beam CT with the parameters determined from one particular slice. Finally, the capability of each correction technique in retaining the image information (e.g., small object at the iso-center) accurately in the corrected CT image has been also tested. Conclusions The results show that the performances of the algorithms are limited and none is fully suitable for correcting different types of ring artifacts without introducing processing distortion to the image structure. To achieve the diagnostic quality of the corrected slices a combination of the two approaches (sinogram- and post-processing) can be used. Also the comparing methods are not suitable for correcting the volume images from a cone beam flat-panel detector based CT. PMID:21846411

Processing Infrared Images For Fire Management Applications

NASA Astrophysics Data System (ADS)

Warren, John R.; Pratt, William K.

1981-12-01

The USDA Forest Service has used airborne infrared systems for forest fire detection and mapping for many years. The transfer of the images from plane to ground and the transposition of fire spots and perimeters to maps has been performed manually. A new system has been developed which uses digital image processing, transmission, and storage. Interactive graphics, high resolution color display, calculations, and computer model compatibility are featured in the system. Images are acquired by an IR line scanner and converted to 1024 x 1024 x 8 bit frames for transmission to the ground at a 1.544 M bit rate over a 14.7 GHZ carrier. Individual frames are received and stored, then transferred to a solid state memory to refresh the display at a conventional 30 frames per second rate. Line length and area calculations, false color assignment, X-Y scaling, and image enhancement are available. Fire spread can be calculated for display and fire perimeters plotted on maps. The performance requirements, basic system, and image processing will be described.

System and method for image mapping and visual attention

NASA Technical Reports Server (NTRS)

Peters, II, Richard A. (Inventor)

2010-01-01

A method is described for mapping dense sensory data to a Sensory Ego Sphere (SES). Methods are also described for finding and ranking areas of interest in the images that form a complete visual scene on an SES. Further, attentional processing of image data is best done by performing attentional processing on individual full-size images from the image sequence, mapping each attentional location to the nearest node, and then summing attentional locations at each node.

System and method for image mapping and visual attention

NASA Technical Reports Server (NTRS)

Peters, II, Richard A. (Inventor)

2011-01-01

A method is described for mapping dense sensory data to a Sensory Ego Sphere (SES). Methods are also described for finding and ranking areas of interest in the images that form a complete visual scene on an SES. Further, attentional processing of image data is best done by performing attentional processing on individual full-size images from the image sequence, mapping each attentional location to the nearest node, and then summing all attentional locations at each node.

Pictures, images, and recollective experience.

PubMed

Dewhurst, S A; Conway, M A

1994-09-01

Five experiments investigated the influence of picture processing on recollective experience in recognition memory. Subjects studied items that differed in visual or imaginal detail, such as pictures versus words and high-imageability versus low-imageability words, and performed orienting tasks that directed processing either toward a stimulus as a word or toward a stimulus as a picture or image. Standard effects of imageability (e.g., the picture superiority effect and memory advantages following imagery) were obtained only in recognition judgments that featured recollective experience and were eliminated or reversed when recognition was not accompanied by recollective experience. It is proposed that conscious recollective experience in recognition memory is cued by attributes of retrieved memories such as sensory-perceptual attributes and records of cognitive operations performed at encoding.

Tracker: Image-Processing and Object-Tracking System Developed

NASA Technical Reports Server (NTRS)

Klimek, Robert B.; Wright, Theodore W.

1999-01-01

Tracker is an object-tracking and image-processing program designed and developed at the NASA Lewis Research Center to help with the analysis of images generated by microgravity combustion and fluid physics experiments. Experiments are often recorded on film or videotape for analysis later. Tracker automates the process of examining each frame of the recorded experiment, performing image-processing operations to bring out the desired detail, and recording the positions of the objects of interest. It can load sequences of images from disk files or acquire images (via a frame grabber) from film transports, videotape, laser disks, or a live camera. Tracker controls the image source to automatically advance to the next frame. It can employ a large array of image-processing operations to enhance the detail of the acquired images and can analyze an arbitrarily large number of objects simultaneously. Several different tracking algorithms are available, including conventional threshold and correlation-based techniques, and more esoteric procedures such as "snake" tracking and automated recognition of character data in the image. The Tracker software was written to be operated by researchers, thus every attempt was made to make the software as user friendly and self-explanatory as possible. Tracker is used by most of the microgravity combustion and fluid physics experiments performed by Lewis, and by visiting researchers. This includes experiments performed on the space shuttles, Mir, sounding rockets, zero-g research airplanes, drop towers, and ground-based laboratories. This software automates the analysis of the flame or liquid s physical parameters such as position, velocity, acceleration, size, shape, intensity characteristics, color, and centroid, as well as a number of other measurements. It can perform these operations on multiple objects simultaneously. Another key feature of Tracker is that it performs optical character recognition (OCR). This feature is useful in extracting numerical instrumentation data that are embedded in images. All the results are saved in files for further data reduction and graphing. There are currently three Tracking Systems (workstations) operating near the laboratories and offices of Lewis Microgravity Science Division researchers. These systems are used independently by students, scientists, and university-based principal investigators. The researchers bring their tapes or films to the workstation and perform the tracking analysis. The resultant data files generated by the tracking process can then be analyzed on the spot, although most of the time researchers prefer to transfer them via the network to their offices for further analysis or plotting. In addition, many researchers have installed Tracker on computers in their office for desktop analysis of digital image sequences, which can be digitized by the Tracking System or some other means. Tracker has not only provided a capability to efficiently and automatically analyze large volumes of data, saving many hours of tedious work, but has also provided new capabilities to extract valuable information and phenomena that was heretofore undetected and unexploited.

Digital Image Processing Overview For Helmet Mounted Displays

NASA Astrophysics Data System (ADS)

Parise, Michael J.

1989-09-01

Digital image processing provides a means to manipulate an image and presents a user with a variety of display formats that are not available in the analog image processing environment. When performed in real time and presented on a Helmet Mounted Display, system capability and flexibility are greatly enhanced. The information content of a display can be increased by the addition of real time insets and static windows from secondary sensor sources, near real time 3-D imaging from a single sensor can be achieved, graphical information can be added, and enhancement techniques can be employed. Such increased functionality is generating a considerable amount of interest in the military and commercial markets. This paper discusses some of these image processing techniques and their applications.

Architecture Of High Speed Image Processing System

NASA Astrophysics Data System (ADS)

Konishi, Toshio; Hayashi, Hiroshi; Ohki, Tohru

1988-01-01

One of architectures for a high speed image processing system which corresponds to a new algorithm for a shape understanding is proposed. And the hardware system which is based on the archtecture was developed. Consideration points of the architecture are mainly that using processors should match with the processing sequence of the target image and that the developed system should be used practically in an industry. As the result, it was possible to perform each processing at a speed of 80 nano-seconds a pixel.

Validating a Geographical Image Retrieval System.

ERIC Educational Resources Information Center

Zhu, Bin; Chen, Hsinchun

2000-01-01

Summarizes a prototype geographical image retrieval system that demonstrates how to integrate image processing and information analysis techniques to support large-scale content-based image retrieval. Describes an experiment to validate the performance of this image retrieval system against that of human subjects by examining similarity analysis…

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

NASA Technical Reports Server (NTRS)

Wemet, Mark P.

2008-01-01

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Satellite on-board real-time SAR processor prototype

NASA Astrophysics Data System (ADS)

Bergeron, Alain; Doucet, Michel; Harnisch, Bernd; Suess, Martin; Marchese, Linda; Bourqui, Pascal; Desnoyers, Nicholas; Legros, Mathieu; Guillot, Ludovic; Mercier, Luc; Châteauneuf, François

2017-11-01

A Compact Real-Time Optronic SAR Processor has been successfully developed and tested up to a Technology Readiness Level of 4 (TRL4), the breadboard validation in a laboratory environment. SAR, or Synthetic Aperture Radar, is an active system allowing day and night imaging independent of the cloud coverage of the planet. The SAR raw data is a set of complex data for range and azimuth, which cannot be compressed. Specifically, for planetary missions and unmanned aerial vehicle (UAV) systems with limited communication data rates this is a clear disadvantage. SAR images are typically processed electronically applying dedicated Fourier transformations. This, however, can also be performed optically in real-time. Originally the first SAR images were optically processed. The optical Fourier processor architecture provides inherent parallel computing capabilities allowing real-time SAR data processing and thus the ability for compression and strongly reduced communication bandwidth requirements for the satellite. SAR signal return data are in general complex data. Both amplitude and phase must be combined optically in the SAR processor for each range and azimuth pixel. Amplitude and phase are generated by dedicated spatial light modulators and superimposed by an optical relay set-up. The spatial light modulators display the full complex raw data information over a two-dimensional format, one for the azimuth and one for the range. Since the entire signal history is displayed at once, the processor operates in parallel yielding real-time performances, i.e. without resulting bottleneck. Processing of both azimuth and range information is performed in a single pass. This paper focuses on the onboard capabilities of the compact optical SAR processor prototype that allows in-orbit processing of SAR images. Examples of processed ENVISAT ASAR images are presented. Various SAR processor parameters such as processing capabilities, image quality (point target analysis), weight and size are reviewed.

Processing Satellite Images on Tertiary Storage: A Study of the Impact of Tile Size on Performance

NASA Technical Reports Server (NTRS)

Yu, JieBing; DeWitt, David J.

1996-01-01

Before raw data from a satellite can be used by an Earth scientist, it must first undergo a number of processing steps including basic processing, cleansing, and geo-registration. Processing actually expands the volume of data collected by a factor of 2 or 3 and the original data is never deleted. Thus processing and storage requirements can exceed 2 terrabytes/day. Once processed data is ready for analysis, a series of algorithms (typically developed by the Earth scientists) is applied to a large number of images in a data set. The focus of this paper is how best to handle such images stored on tape using the following assumptions: (1) all images of interest to a scientist are stored on a single tape, (2) images are accessed and processed in the order that they are stored on tape, and (3) the analysis requires access to only a portion of each image and not the entire image.

Ongoing quality control in digital radiography: Report of AAPM Imaging Physics Committee Task Group 151.

PubMed

Jones, A Kyle; Heintz, Philip; Geiser, William; Goldman, Lee; Jerjian, Khachig; Martin, Melissa; Peck, Donald; Pfeiffer, Douglas; Ranger, Nicole; Yorkston, John

2015-11-01

Quality control (QC) in medical imaging is an ongoing process and not just a series of infrequent evaluations of medical imaging equipment. The QC process involves designing and implementing a QC program, collecting and analyzing data, investigating results that are outside the acceptance levels for the QC program, and taking corrective action to bring these results back to an acceptable level. The QC process involves key personnel in the imaging department, including the radiologist, radiologic technologist, and the qualified medical physicist (QMP). The QMP performs detailed equipment evaluations and helps with oversight of the QC program, the radiologic technologist is responsible for the day-to-day operation of the QC program. The continued need for ongoing QC in digital radiography has been highlighted in the scientific literature. The charge of this task group was to recommend consistency tests designed to be performed by a medical physicist or a radiologic technologist under the direction of a medical physicist to identify problems with an imaging system that need further evaluation by a medical physicist, including a fault tree to define actions that need to be taken when certain fault conditions are identified. The focus of this final report is the ongoing QC process, including rejected image analysis, exposure analysis, and artifact identification. These QC tasks are vital for the optimal operation of a department performing digital radiography.

Real-time implementations of image segmentation algorithms on shared memory multicore architecture: a survey (Conference Presentation)

NASA Astrophysics Data System (ADS)

Akil, Mohamed

2017-05-01

The real-time processing is getting more and more important in many image processing applications. Image segmentation is one of the most fundamental tasks image analysis. As a consequence, many different approaches for image segmentation have been proposed. The watershed transform is a well-known image segmentation tool. The watershed transform is a very data intensive task. To achieve acceleration and obtain real-time processing of watershed algorithms, parallel architectures and programming models for multicore computing have been developed. This paper focuses on the survey of the approaches for parallel implementation of sequential watershed algorithms on multicore general purpose CPUs: homogeneous multicore processor with shared memory. To achieve an efficient parallel implementation, it's necessary to explore different strategies (parallelization/distribution/distributed scheduling) combined with different acceleration and optimization techniques to enhance parallelism. In this paper, we give a comparison of various parallelization of sequential watershed algorithms on shared memory multicore architecture. We analyze the performance measurements of each parallel implementation and the impact of the different sources of overhead on the performance of the parallel implementations. In this comparison study, we also discuss the advantages and disadvantages of the parallel programming models. Thus, we compare the OpenMP (an application programming interface for multi-Processing) with Ptheads (POSIX Threads) to illustrate the impact of each parallel programming model on the performance of the parallel implementations.

Ongoing quality control in digital radiography: Report of AAPM Imaging Physics Committee Task Group 151

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, A. Kyle, E-mail: kyle.jones@mdanderson.org; Geiser, William; Heintz, Philip

Quality control (QC) in medical imaging is an ongoing process and not just a series of infrequent evaluations of medical imaging equipment. The QC process involves designing and implementing a QC program, collecting and analyzing data, investigating results that are outside the acceptance levels for the QC program, and taking corrective action to bring these results back to an acceptable level. The QC process involves key personnel in the imaging department, including the radiologist, radiologic technologist, and the qualified medical physicist (QMP). The QMP performs detailed equipment evaluations and helps with oversight of the QC program, the radiologic technologist ismore » responsible for the day-to-day operation of the QC program. The continued need for ongoing QC in digital radiography has been highlighted in the scientific literature. The charge of this task group was to recommend consistency tests designed to be performed by a medical physicist or a radiologic technologist under the direction of a medical physicist to identify problems with an imaging system that need further evaluation by a medical physicist, including a fault tree to define actions that need to be taken when certain fault conditions are identified. The focus of this final report is the ongoing QC process, including rejected image analysis, exposure analysis, and artifact identification. These QC tasks are vital for the optimal operation of a department performing digital radiography.« less

TU-B-19A-01: Image Registration II: TG132-Quality Assurance for Image Registration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brock, K; Mutic, S

2014-06-15

AAPM Task Group 132 was charged with a review of the current approaches and solutions for image registration in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes. As the results of image registration are always used as the input of another process for planning or delivery, it is important for the user to understand and document the uncertainty associate with the algorithm in general and the Result of a specific registration. The recommendations of this task group, which at the time of abstract submission are currently being reviewed by the AAPM, include themore » following components. The user should understand the basic image registration techniques and methods of visualizing image fusion. The disclosure of basic components of the image registration by commercial vendors is critical in this respect. The physicists should perform end-to-end tests of imaging, registration, and planning/treatment systems if image registration is performed on a stand-alone system. A comprehensive commissioning process should be performed and documented by the physicist prior to clinical use of the system. As documentation is important to the safe implementation of this process, a request and report system should be integrated into the clinical workflow. Finally, a patient specific QA practice should be established for efficient evaluation of image registration results. The implementation of these recommendations will be described and illustrated during this educational session. Learning Objectives: Highlight the importance of understanding the image registration techniques used in their clinic. Describe the end-to-end tests needed for stand-alone registration systems. Illustrate a comprehensive commissioning program using both phantom data and clinical images. Describe a request and report system to ensure communication and documentation. Demonstrate an clinically-efficient patient QA practice for efficient evaluation of image registration.« less

The use of vision-based image quality metrics to predict low-light performance of camera phones

NASA Astrophysics Data System (ADS)

Hultgren, B.; Hertel, D.

2010-01-01

Small digital camera modules such as those in mobile phones have become ubiquitous. Their low-light performance is of utmost importance since a high percentage of images are made under low lighting conditions where image quality failure may occur due to blur, noise, and/or underexposure. These modes of image degradation are not mutually exclusive: they share common roots in the physics of the imager, the constraints of image processing, and the general trade-off situations in camera design. A comprehensive analysis of failure modes is needed in order to understand how their interactions affect overall image quality. Low-light performance is reported for DSLR, point-and-shoot, and mobile phone cameras. The measurements target blur, noise, and exposure error. Image sharpness is evaluated from three different physical measurements: static spatial frequency response, handheld motion blur, and statistical information loss due to image processing. Visual metrics for sharpness, graininess, and brightness are calculated from the physical measurements, and displayed as orthogonal image quality metrics to illustrate the relative magnitude of image quality degradation as a function of subject illumination. The impact of each of the three sharpness measurements on overall sharpness quality is displayed for different light levels. The power spectrum of the statistical information target is a good representation of natural scenes, thus providing a defined input signal for the measurement of power-spectrum based signal-to-noise ratio to characterize overall imaging performance.

Performance of InGaAs short wave infrared avalanche photodetector for low flux imaging

NASA Astrophysics Data System (ADS)

Singh, Anand; Pal, Ravinder

2017-11-01

Opto-electronic performance of the InGaAs/i-InGaAs/InP short wavelength infrared focal plane array suitable for high resolution imaging under low flux conditions and ranging is presented. More than 85% quantum efficiency is achieved in the optimized detector structure. Isotropic nature of the wet etching process poses a challenge in maintaining the required control in the small pitch high density detector array. Etching process is developed to achieve low dark current density of 1 nA/cm2 in the detector array with 25 µm pitch at 298 K. Noise equivalent photon performance less than one is achievable showing single photon detection capability. The reported photodiode with low photon flux is suitable for active cum passive imaging, optical information processing and quantum computing applications.

Design and development of an ultrasound calibration phantom and system

NASA Astrophysics Data System (ADS)

Cheng, Alexis; Ackerman, Martin K.; Chirikjian, Gregory S.; Boctor, Emad M.

2014-03-01

Image-guided surgery systems are often used to provide surgeons with informational support. Due to several unique advantages such as ease of use, real-time image acquisition, and no ionizing radiation, ultrasound is a common medical imaging modality used in image-guided surgery systems. To perform advanced forms of guidance with ultrasound, such as virtual image overlays or automated robotic actuation, an ultrasound calibration process must be performed. This process recovers the rigid body transformation between a tracked marker attached to the ultrasound transducer and the ultrasound image. A phantom or model with known geometry is also required. In this work, we design and test an ultrasound calibration phantom and software. The two main considerations in this work are utilizing our knowledge of ultrasound physics to design the phantom and delivering an easy to use calibration process to the user. We explore the use of a three-dimensional printer to create the phantom in its entirety without need for user assembly. We have also developed software to automatically segment the three-dimensional printed rods from the ultrasound image by leveraging knowledge about the shape and scale of the phantom. In this work, we present preliminary results from using this phantom to perform ultrasound calibration. To test the efficacy of our method, we match the projection of the points segmented from the image to the known model and calculate a sum squared difference between each point for several combinations of motion generation and filtering methods. The best performing combination of motion and filtering techniques had an error of 1.56 mm and a standard deviation of 1.02 mm.

Calibration and Image Reconstruction for the Hurricane Imaging Radiometer (HIRAD)

NASA Technical Reports Server (NTRS)

Ruf, Christopher; Roberts, J. Brent; Biswas, Sayak; James, Mark W.; Miller, Timothy

2012-01-01

The Hurricane Imaging Radiometer (HIRAD) is a new airborne passive microwave synthetic aperture radiometer designed to provide wide swath images of ocean surface wind speed under heavy precipitation and, in particular, in tropical cyclones. It operates at 4, 5, 6 and 6.6 GHz and uses interferometric signal processing to synthesize a pushbroom imager in software from a low profile planar antenna with no mechanical scanning. HIRAD participated in NASA s Genesis and Rapid Intensification Processes (GRIP) mission during Fall 2010 as its first science field campaign. HIRAD produced images of upwelling brightness temperature over a aprox 70 km swath width with approx 3 km spatial resolution. From this, ocean surface wind speed and column averaged atmospheric liquid water content can be retrieved across the swath. The calibration and image reconstruction algorithms that were used to verify HIRAD functional performance during and immediately after GRIP were only preliminary and used a number of simplifying assumptions and approximations about the instrument design and performance. The development and performance of a more detailed and complete set of algorithms are reported here.

GUI for Coordinate Measurement of an Image for the Estimation of Geometric Distortion of an Opto-electronic Display System

NASA Astrophysics Data System (ADS)

Saini, Surender Singh; Sardana, Harish Kumar; Pattnaik, Shyam Sundar

2017-06-01

Conventional image editing software in combination with other techniques are not only difficult to apply to an image but also permits a user to perform some basic functions one at a time. However, image processing algorithms and photogrammetric systems are developed in the recent past for real-time pattern recognition applications. A graphical user interface (GUI) is developed which can perform multiple functions simultaneously for the analysis and estimation of geometric distortion in an image with reference to the corresponding distorted image. The GUI measure, record, and visualize the performance metric of X/Y coordinates of one image over the other. The various keys and icons provided in the utility extracts the coordinates of distortion free reference image and the image with geometric distortion. The error between these two corresponding points gives the measure of distortion and also used to evaluate the correction parameters for image distortion. As the GUI interface minimizes human interference in the process of geometric correction, its execution just requires use of icons and keys provided in the utility; this technique gives swift and accurate results as compared to other conventional methods for the measurement of the X/Y coordinates of an image.

Image Corruption Detection in Diffusion Tensor Imaging for Post-Processing and Real-Time Monitoring

PubMed Central

Li, Yue; Shea, Steven M.; Lorenz, Christine H.; Jiang, Hangyi; Chou, Ming-Chung; Mori, Susumu

2013-01-01

Due to the high sensitivity of diffusion tensor imaging (DTI) to physiological motion, clinical DTI scans often suffer a significant amount of artifacts. Tensor-fitting-based, post-processing outlier rejection is often used to reduce the influence of motion artifacts. Although it is an effective approach, when there are multiple corrupted data, this method may no longer correctly identify and reject the corrupted data. In this paper, we introduce a new criterion called “corrected Inter-Slice Intensity Discontinuity” (cISID) to detect motion-induced artifacts. We compared the performance of algorithms using cISID and other existing methods with regard to artifact detection. The experimental results show that the integration of cISID into fitting-based methods significantly improves the retrospective detection performance at post-processing analysis. The performance of the cISID criterion, if used alone, was inferior to the fitting-based methods, but cISID could effectively identify severely corrupted images with a rapid calculation time. In the second part of this paper, an outlier rejection scheme was implemented on a scanner for real-time monitoring of image quality and reacquisition of the corrupted data. The real-time monitoring, based on cISID and followed by post-processing, fitting-based outlier rejection, could provide a robust environment for routine DTI studies. PMID:24204551

Research and development on performance models of thermal imaging systems

NASA Astrophysics Data System (ADS)

Wang, Ji-hui; Jin, Wei-qi; Wang, Xia; Cheng, Yi-nan

2009-07-01

Traditional ACQUIRE models perform the discrimination tasks of detection (target orientation, recognition and identification) for military target based upon minimum resolvable temperature difference (MRTD) and Johnson criteria for thermal imaging systems (TIS). Johnson criteria is generally pessimistic for performance predict of sampled imager with the development of focal plane array (FPA) detectors and digital image process technology. Triangle orientation discrimination threshold (TOD) model, minimum temperature difference perceived (MTDP)/ thermal range model (TRM3) Model and target task performance (TTP) metric have been developed to predict the performance of sampled imager, especially TTP metric can provides better accuracy than the Johnson criteria. In this paper, the performance models above are described; channel width metrics have been presented to describe the synthesis performance including modulate translate function (MTF) channel width for high signal noise to ration (SNR) optoelectronic imaging systems and MRTD channel width for low SNR TIS; the under resolvable questions for performance assessment of TIS are indicated; last, the development direction of performance models for TIS are discussed.

Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform

PubMed Central

Wang, Min; Tian, Yun

2018-01-01

The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator's dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance. PMID:29861711

Numerical image manipulation and display in solar astronomy

NASA Technical Reports Server (NTRS)

Levine, R. H.; Flagg, J. C.

1977-01-01

The paper describes the system configuration and data manipulation capabilities of a solar image display system which allows interactive analysis of visual images and on-line manipulation of digital data. Image processing features include smoothing or filtering of images stored in the display, contrast enhancement, and blinking or flickering images. A computer with a core memory of 28,672 words provides the capacity to perform complex calculations based on stored images, including computing histograms, selecting subsets of images for further analysis, combining portions of images to produce images with physical meaning, and constructing mathematical models of features in an image. Some of the processing modes are illustrated by some image sequences from solar observations.

SkySat-1: very high-resolution imagery from a small satellite

NASA Astrophysics Data System (ADS)

Murthy, Kiran; Shearn, Michael; Smiley, Byron D.; Chau, Alexandra H.; Levine, Josh; Robinson, M. Dirk

2014-10-01

This paper presents details of the SkySat-1 mission, which is the first microsatellite-class commercial earth- observation system to generate sub-meter resolution panchromatic imagery, in addition to sub-meter resolution 4-band pan-sharpened imagery. SkySat-1 was built and launched for an order of magnitude lower cost than similarly performing missions. The low-cost design enables the deployment of a large imaging constellation that can provide imagery with both high temporal resolution and high spatial resolution. One key enabler of the SkySat-1 mission was simplifying the spacecraft design and instead relying on ground- based image processing to achieve high-performance at the system level. The imaging instrument consists of a custom-designed high-quality optical telescope and commercially-available high frame rate CMOS image sen- sors. While each individually captured raw image frame shows moderate quality, ground-based image processing algorithms improve the raw data by combining data from multiple frames to boost image signal-to-noise ratio (SNR) and decrease the ground sample distance (GSD) in a process Skybox calls "digital TDI". Careful qual-ity assessment and tuning of the spacecraft, payload, and algorithms was necessary to generate high-quality panchromatic, multispectral, and pan-sharpened imagery. Furthermore, the framing sensor configuration en- abled the first commercial High-Definition full-frame rate panchromatic video to be captured from space, with approximately 1 meter ground sample distance. Details of the SkySat-1 imaging instrument and ground-based image processing system are presented, as well as an overview of the work involved with calibrating and validating the system. Examples of raw and processed imagery are shown, and the raw imagery is compared to pre-launch simulated imagery used to tune the image processing algorithms.

[Development of a Text-Data Based Learning Tool That Integrates Image Processing and Displaying].

PubMed

Shinohara, Hiroyuki; Hashimoto, Takeyuki

2015-01-01

We developed a text-data based learning tool that integrates image processing and displaying by Excel. Knowledge required for programing this tool is limited to using absolute, relative, and composite cell references and learning approximately 20 mathematical functions available in Excel. The new tool is capable of resolution translation, geometric transformation, spatial-filter processing, Radon transform, Fourier transform, convolutions, correlations, deconvolutions, wavelet transform, mutual information, and simulation of proton density-, T1-, and T2-weighted MR images. The processed images of 128 x 128 pixels or 256 x 256 pixels are observed directly within Excel worksheets without using any particular image display software. The results of image processing using this tool were compared with those using C language and the new tool was judged to have sufficient accuracy to be practically useful. The images displayed on Excel worksheets were compared with images using binary-data display software. This comparison indicated that the image quality of the Excel worksheets was nearly equal to the latter in visual impressions. Since image processing is performed by using text-data, the process is visible and facilitates making contrasts by using mathematical equations within the program. We concluded that the newly developed tool is adequate as a computer-assisted learning tool for use in medical image processing.

Ultra-Rapid Categorization of Fourier-Spectrum Equalized Natural Images: Macaques and Humans Perform Similarly

PubMed Central

Girard, Pascal; Koenig-Robert, Roger

2011-01-01

Background Comparative studies of cognitive processes find similarities between humans and apes but also monkeys. Even high-level processes, like the ability to categorize classes of object from any natural scene under ultra-rapid time constraints, seem to be present in rhesus macaque monkeys (despite a smaller brain and the lack of language and a cultural background). An interesting and still open question concerns the degree to which the same images are treated with the same efficacy by humans and monkeys when a low level cue, the spatial frequency content, is controlled. Methodology/Principal Findings We used a set of natural images equalized in Fourier spectrum and asked whether it is still possible to categorize them as containing an animal and at what speed. One rhesus macaque monkey performed a forced-choice saccadic task with a good accuracy (67.5% and 76% for new and familiar images respectively) although performance was lower than with non-equalized images. Importantly, the minimum reaction time was still very fast (100 ms). We compared the performances of human subjects with the same setup and the same set of (new) images. Overall mean performance of humans was also lower than with original images (64% correct) but the minimum reaction time was still short (140 ms). Conclusion Performances on individual images (% correct but not reaction times) for both humans and the monkey were significantly correlated suggesting that both species use similar features to perform the task. A similar advantage for full-face images was seen for both species. The results also suggest that local low spatial frequency information could be important, a finding that fits the theory that fast categorization relies on a rapid feedforward magnocellular signal. PMID:21326600

Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising

PubMed Central

Lentini, Marianela; Paluszny, Marco

2014-01-01

The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T 2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek's algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T 2 MR images, and the filter is applied to each image before using the variant of the Prony method. PMID:24834108

Improving the performance of the prony method using a wavelet domain filter for MRI denoising.

PubMed

Jaramillo, Rodney; Lentini, Marianela; Paluszny, Marco

2014-01-01

The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T 2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek's algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T 2 MR images, and the filter is applied to each image before using the variant of the Prony method.

Construction of mammographic examination process ontology using bottom-up hierarchical task analysis.

PubMed

Yagahara, Ayako; Yokooka, Yuki; Jiang, Guoqian; Tsuji, Shintarou; Fukuda, Akihisa; Nishimoto, Naoki; Kurowarabi, Kunio; Ogasawara, Katsuhiko

2018-03-01

Describing complex mammography examination processes is important for improving the quality of mammograms. It is often difficult for experienced radiologic technologists to explain the process because their techniques depend on their experience and intuition. In our previous study, we analyzed the process using a new bottom-up hierarchical task analysis and identified key components of the process. Leveraging the results of the previous study, the purpose of this study was to construct a mammographic examination process ontology to formally describe the relationships between the process and image evaluation criteria to improve the quality of mammograms. First, we identified and created root classes: task, plan, and clinical image evaluation (CIE). Second, we described an "is-a" relation referring to the result of the previous study and the structure of the CIE. Third, the procedural steps in the ontology were described using the new properties: "isPerformedBefore," "isPerformedAfter," and "isPerformedAfterIfNecessary." Finally, the relationships between tasks and CIEs were described using the "isAffectedBy" property to represent the influence of the process on image quality. In total, there were 219 classes in the ontology. By introducing new properties related to the process flow, a sophisticated mammography examination process could be visualized. In relationships between tasks and CIEs, it became clear that the tasks affecting the evaluation criteria related to positioning were greater in number than those for image quality. We developed a mammographic examination process ontology that makes knowledge explicit for a comprehensive mammography process. Our research will support education and help promote knowledge sharing about mammography examination expertise.

The Hico Image Processing System: A Web-Accessible Hyperspectral Remote Sensing Toolbox

NASA Astrophysics Data System (ADS)

Harris, A. T., III; Goodman, J.; Justice, B.

2014-12-01

As the quantity of Earth-observation data increases, the use-case for hosting analytical tools in geospatial data centers becomes increasingly attractive. To address this need, HySpeed Computing and Exelis VIS have developed the HICO Image Processing System, a prototype cloud computing system that provides online, on-demand, scalable remote sensing image processing capabilities. The system provides a mechanism for delivering sophisticated image processing analytics and data visualization tools into the hands of a global user community, who will only need a browser and internet connection to perform analysis. Functionality of the HICO Image Processing System is demonstrated using imagery from the Hyperspectral Imager for the Coastal Ocean (HICO), an imaging spectrometer located on the International Space Station (ISS) that is optimized for acquisition of aquatic targets. Example applications include a collection of coastal remote sensing algorithms that are directed at deriving critical information on water and habitat characteristics of our vulnerable coastal environment. The project leverages the ENVI Services Engine as the framework for all image processing tasks, and can readily accommodate the rapid integration of new algorithms, datasets and processing tools.

Restoration of color in a remote sensing image and its quality evaluation

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Wang, Zhihe

2003-09-01

This paper is focused on the restoration of color remote sensing (including airborne photo). A complete approach is recommended. It propose that two main aspects should be concerned in restoring a remote sensing image, that are restoration of space information, restoration of photometric information. In this proposal, the restoration of space information can be performed by making the modulation transfer function (MTF) as degradation function, in which the MTF is obtained by measuring the edge curve of origin image. The restoration of photometric information can be performed by improved local maximum entropy algorithm. What's more, a valid approach in processing color remote sensing image is recommended. That is splits the color remote sensing image into three monochromatic images which corresponding three visible light bands and synthesizes the three images after being processed separately with psychological color vision restriction. Finally, three novel evaluation variables are obtained based on image restoration to evaluate the image restoration quality in space restoration quality and photometric restoration quality. An evaluation is provided at last.

Performance evaluation of image denoising developed using convolutional denoising autoencoders in chest radiography

NASA Astrophysics Data System (ADS)

Lee, Donghoon; Choi, Sunghoon; Kim, Hee-Joung

2018-03-01

When processing medical images, image denoising is an important pre-processing step. Various image denoising algorithms have been developed in the past few decades. Recently, image denoising using the deep learning method has shown excellent performance compared to conventional image denoising algorithms. In this study, we introduce an image denoising technique based on a convolutional denoising autoencoder (CDAE) and evaluate clinical applications by comparing existing image denoising algorithms. We train the proposed CDAE model using 3000 chest radiograms training data. To evaluate the performance of the developed CDAE model, we compare it with conventional denoising algorithms including median filter, total variation (TV) minimization, and non-local mean (NLM) algorithms. Furthermore, to verify the clinical effectiveness of the developed denoising model with CDAE, we investigate the performance of the developed denoising algorithm on chest radiograms acquired from real patients. The results demonstrate that the proposed denoising algorithm developed using CDAE achieves a superior noise-reduction effect in chest radiograms compared to TV minimization and NLM algorithms, which are state-of-the-art algorithms for image noise reduction. For example, the peak signal-to-noise ratio and structure similarity index measure of CDAE were at least 10% higher compared to conventional denoising algorithms. In conclusion, the image denoising algorithm developed using CDAE effectively eliminated noise without loss of information on anatomical structures in chest radiograms. It is expected that the proposed denoising algorithm developed using CDAE will be effective for medical images with microscopic anatomical structures, such as terminal bronchioles.

Real-time model-based vision system for object acquisition and tracking

NASA Technical Reports Server (NTRS)

Wilcox, Brian; Gennery, Donald B.; Bon, Bruce; Litwin, Todd

1987-01-01

A machine vision system is described which is designed to acquire and track polyhedral objects moving and rotating in space by means of two or more cameras, programmable image-processing hardware, and a general-purpose computer for high-level functions. The image-processing hardware is capable of performing a large variety of operations on images and on image-like arrays of data. Acquisition utilizes image locations and velocities of the features extracted by the image-processing hardware to determine the three-dimensional position, orientation, velocity, and angular velocity of the object. Tracking correlates edges detected in the current image with edge locations predicted from an internal model of the object and its motion, continually updating velocity information to predict where edges should appear in future frames. With some 10 frames processed per second, real-time tracking is possible.

A comparison of visual statistics for the image enhancement of FORESITE aerial images with those of major image classes

NASA Astrophysics Data System (ADS)

Jobson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

2006-05-01

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally within the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging-terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on the limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

A Comparison of Visual Statistics for the Image Enhancement of FORESITE Aerial Images with Those of Major Image Classes

NASA Technical Reports Server (NTRS)

Johnson, Daniel J.; Rahman, Zia-ur; Woodell, Glenn A.; Hines, Glenn D.

2006-01-01

Aerial images from the Follow-On Radar, Enhanced and Synthetic Vision Systems Integration Technology Evaluation (FORESITE) flight tests with the NASA Langley Research Center's research Boeing 757 were acquired during severe haze and haze/mixed clouds visibility conditions. These images were enhanced using the Visual Servo (VS) process that makes use of the Multiscale Retinex. The images were then quantified with visual quality metrics used internally with the VS. One of these metrics, the Visual Contrast Measure, has been computed for hundreds of FORESITE images, and for major classes of imaging--terrestrial (consumer), orbital Earth observations, orbital Mars surface imaging, NOAA aerial photographs, and underwater imaging. The metric quantifies both the degree of visual impairment of the original, un-enhanced images as well as the degree of visibility improvement achieved by the enhancement process. The large aggregate data exhibits trends relating to degree of atmospheric visibility attenuation, and its impact on limits of enhancement performance for the various image classes. Overall results support the idea that in most cases that do not involve extreme reduction in visibility, large gains in visual contrast are routinely achieved by VS processing. Additionally, for very poor visibility imaging, lesser, but still substantial, gains in visual contrast are also routinely achieved. Further, the data suggest that these visual quality metrics can be used as external standalone metrics for establishing performance parameters.

An Ibm PC/AT-Based Image Acquisition And Processing System For Quantitative Image Analysis

NASA Astrophysics Data System (ADS)

Kim, Yongmin; Alexander, Thomas

1986-06-01

In recent years, a large number of applications have been developed for image processing systems in the area of biological imaging. We have already finished the development of a dedicated microcomputer-based image processing and analysis system for quantitative microscopy. The system's primary function has been to facilitate and ultimately automate quantitative image analysis tasks such as the measurement of cellular DNA contents. We have recognized from this development experience, and interaction with system users, biologists and technicians, that the increasingly widespread use of image processing systems, and the development and application of new techniques for utilizing the capabilities of such systems, would generate a need for some kind of inexpensive general purpose image acquisition and processing system specially tailored for the needs of the medical community. We are currently engaged in the development and testing of hardware and software for a fairly high-performance image processing computer system based on a popular personal computer. In this paper, we describe the design and development of this system. Biological image processing computer systems have now reached a level of hardware and software refinement where they could become convenient image analysis tools for biologists. The development of a general purpose image processing system for quantitative image analysis that is inexpensive, flexible, and easy-to-use represents a significant step towards making the microscopic digital image processing techniques more widely applicable not only in a research environment as a biologist's workstation, but also in clinical environments as a diagnostic tool.

Astronomical Image Processing with Hadoop

NASA Astrophysics Data System (ADS)

Wiley, K.; Connolly, A.; Krughoff, S.; Gardner, J.; Balazinska, M.; Howe, B.; Kwon, Y.; Bu, Y.

2011-07-01

In the coming decade astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. With a requirement that these images be analyzed in real time to identify moving sources such as potentially hazardous asteroids or transient objects such as supernovae, these data streams present many computational challenges. In the commercial world, new techniques that utilize cloud computing have been developed to handle massive data streams. In this paper we describe how cloud computing, and in particular the map-reduce paradigm, can be used in astronomical data processing. We will focus on our experience implementing a scalable image-processing pipeline for the SDSS database using Hadoop (http://hadoop.apache.org). This multi-terabyte imaging dataset approximates future surveys such as those which will be conducted with the LSST. Our pipeline performs image coaddition in which multiple partially overlapping images are registered, integrated and stitched into a single overarching image. We will first present our initial implementation, then describe several critical optimizations that have enabled us to achieve high performance, and finally describe how we are incorporating a large in-house existing image processing library into our Hadoop system. The optimizations involve prefiltering of the input to remove irrelevant images from consideration, grouping individual FITS files into larger, more efficient indexed files, and a hybrid system in which a relational database is used to determine the input images relevant to the task. The incorporation of an existing image processing library, written in C++, presented difficult challenges since Hadoop is programmed primarily in Java. We will describe how we achieved this integration and the sophisticated image processing routines that were made feasible as a result. We will end by briefly describing the longer term goals of our work, namely detection and classification of transient objects and automated object classification.

Non-rigid ultrasound image registration using generalized relaxation labeling process

NASA Astrophysics Data System (ADS)

Lee, Jong-Ha; Seong, Yeong Kyeong; Park, MoonHo; Woo, Kyoung-Gu; Ku, Jeonghun; Park, Hee-Jun

2013-03-01

This research proposes a novel non-rigid registration method for ultrasound images. The most predominant anatomical features in medical images are tissue boundaries, which appear as edges. In ultrasound images, however, other features can be identified as well due to the specular reflections that appear as bright lines superimposed on the ideal edge location. In this work, an image's local phase information (via the frequency domain) is used to find the ideal edge location. The generalized relaxation labeling process is then formulated to align the feature points extracted from the ideal edge location. In this work, the original relaxation labeling method was generalized by taking n compatibility coefficient values to improve non-rigid registration performance. This contextual information combined with a relaxation labeling process is used to search for a correspondence. Then the transformation is calculated by the thin plate spline (TPS) model. These two processes are iterated until the optimal correspondence and transformation are found. We have tested our proposed method and the state-of-the-art algorithms with synthetic data and bladder ultrasound images of in vivo human subjects. Experiments show that the proposed method improves registration performance significantly, as compared to other state-of-the-art non-rigid registration algorithms.

Joint Processing of Envelope Alignment and Phase Compensation for Isar Imaging

NASA Astrophysics Data System (ADS)

Chen, Tao; Jin, Guanghu; Dong, Zhen

2018-04-01

Range envelope alignment and phase compensation are spilt into two isolated parts in the classical methods of translational motion compensation in Inverse Synthetic Aperture Radar (ISAR) imaging. In classic method of the rotating object imaging, the two reference points of the envelope alignment and the Phase Difference (PD) estimation are probably not the same point, making it difficult to uncouple the coupling term by conducting the correction of Migration Through Resolution Cell (MTRC). In this paper, an improved approach of joint processing which chooses certain scattering point as the sole reference point is proposed to perform with utilizing the Prominent Point Processing (PPP) method. With this end in view, we firstly get the initial image using classical methods from which a certain scattering point can be chose. The envelope alignment and phase compensation using the selected scattering point as the same reference point are subsequently conducted. The keystone transform is thus smoothly applied to further improve imaging quality. Both simulation experiments and real data processing are provided to demonstrate the performance of the proposed method compared with classical method.

An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

PubMed Central

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

PubMed

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

3D image restoration for confocal microscopy: toward a wavelet deconvolution for the study of complex biological structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, Jacques; Le Calvez, Sophie; Ulfendahl, Mats

2000-05-01

Image restoration algorithms provide efficient tools for recovering part of the information lost in the imaging process of a microscope. We describe recent progress in the application of deconvolution to confocal microscopy. The point spread function of a Biorad-MRC1024 confocal microscope was measured under various imaging conditions, and used to process 3D-confocal images acquired in an intact preparation of the inner ear developed at Karolinska Institutet. Using these experiments we investigate the application of denoising methods based on wavelet analysis as a natural regularization of the deconvolution process. Within the Bayesian approach to image restoration, we compare wavelet denoising with the use of a maximum entropy constraint as another natural regularization method. Numerical experiments performed with test images show a clear advantage of the wavelet denoising approach, allowing to `cool down' the image with respect to the signal, while suppressing much of the fine-scale artifacts appearing during deconvolution due to the presence of noise, incomplete knowledge of the point spread function, or undersampling problems. We further describe a natural development of this approach, which consists of performing the Bayesian inference directly in the wavelet domain.

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.

Psychophysical evaluation of the image quality of a dynamic flat-panel digital x-ray image detector using the threshold contrast detail detectability (TCDD) technique

NASA Astrophysics Data System (ADS)

Davies, Andrew G.; Cowen, Arnold R.; Bruijns, Tom J. C.

1999-05-01

We are currently in an era of active development of the digital X-ray imaging detectors that will serve the radiological communities in the new millennium. The rigorous comparative physical evaluations of such devices are therefore becoming increasingly important from both the technical and clinical perspectives. The authors have been actively involved in the evaluation of a clinical demonstration version of a flat-panel dynamic digital X-ray image detector (or FDXD). Results of objective physical evaluation of this device have been presented elsewhere at this conference. The imaging performance of FDXD under radiographic exposure conditions have been previously reported, and in this paper a psychophysical evaluation of the FDXD detector operating under continuous fluoroscopic conditions is presented. The evaluation technique employed was the threshold contrast detail detectability (TCDD) technique, which enables image quality to be measured on devices operating in the clinical environment. This approach addresses image quality in the context of both the image acquisition and display processes, and uses human observers to measure performance. The Leeds test objects TO[10] and TO[10+] were used to obtain comparative measurements of performance on the FDXD and two digital spot fluorography (DSF) systems, one utilizing a Plumbicon camera and the other a state of the art CCD camera. Measurements were taken at a range of detector entrance exposure rates, namely 6, 12, 25 and 50 (mu) R/s. In order to facilitate comparisons between the systems, all fluoroscopic image processing such as noise reduction algorithms, were disabled during the experiments. At the highest dose rate FDXD significantly outperformed the DSF comparison systems in the TCDD comparisons. At 25 and 12 (mu) R/s all three-systems performed in an equivalent manner and at the lowest exposure rate FDXD was inferior to the two DSF systems. At standard fluoroscopic exposures, FDXD performed in an equivalent manner to the DSF systems for the TCDD comparisons. This would suggest that FDXD would therefore perform adequately in a clinical fluoroscopic environment and our initial clinical experiences support this. Noise reduction processing of the fluoroscopic data acquired on FDXD was also found to further improve TCDD performance for FDXD. FDXD therefore combines acceptable fluoroscopic performance with excellent radiographic (snap shot) imaging fidelity, allowing the possibility of a universal x-ray detector to be developed, based on FDXD's technology. It is also envisaged that fluoroscopic performance will be improved by the development of digital image enhancement techniques specifically tailored to the characteristics of the FDXD detector.

A Study of Light Level Effect on the Accuracy of Image Processing-based Tomato Grading

NASA Astrophysics Data System (ADS)

Prijatna, D.; Muhaemin, M.; Wulandari, R. P.; Herwanto, T.; Saukat, M.; Sugandi, W. K.

2018-05-01

Image processing method has been used in non-destructive tests of agricultural products. Compared to manual method, image processing method may produce more objective and consistent results. Image capturing box installed in currently used tomato grading machine (TEP-4) is equipped with four fluorescence lamps to illuminate the processed tomatoes. Since the performance of any lamp will decrease if its service time has exceeded its lifetime, it is predicted that this will affect tomato classification. The objective of this study was to determine the minimum light levels which affect classification accuracy. This study was conducted by varying light level from minimum and maximum on tomatoes in image capturing boxes and then investigates its effects on image characteristics. Research results showed that light intensity affects two variables which are important for classification, for example, area and color of captured image. Image processing program was able to determine correctly the weight and classification of tomatoes when light level was 30 lx to 140 lx.

Improved Discrete Approximation of Laplacian of Gaussian

NASA Technical Reports Server (NTRS)

Shuler, Robert L., Jr.

2004-01-01

An improved method of computing a discrete approximation of the Laplacian of a Gaussian convolution of an image has been devised. The primary advantage of the method is that without substantially degrading the accuracy of the end result, it reduces the amount of information that must be processed and thus reduces the amount of circuitry needed to perform the Laplacian-of- Gaussian (LOG) operation. Some background information is necessary to place the method in context. The method is intended for application to the LOG part of a process of real-time digital filtering of digitized video data that represent brightnesses in pixels in a square array. The particular filtering process of interest is one that converts pixel brightnesses to binary form, thereby reducing the amount of information that must be performed in subsequent correlation processing (e.g., correlations between images in a stereoscopic pair for determining distances or correlations between successive frames of the same image for detecting motions). The Laplacian is often included in the filtering process because it emphasizes edges and textures, while the Gaussian is often included because it smooths out noise that might not be consistent between left and right images or between successive frames of the same image.

Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers

PubMed Central

Filipovic, Nenad D.

2017-01-01

Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of the region of interest from a breast image, followed by the identification of suspicious mass regions, their classification, and comparison with the existing image database. It is often the case that already existing image databases have large sets of data whose processing requires a lot of time, and thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. In this paper, the implementation of the already existing algorithm for region-of-interest based image segmentation for mammogram images on High-Performance Reconfigurable Dataflow Computers (HPRDCs) is proposed. As a dataflow engine (DFE) of such HPRDC, Maxeler's acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable Dataflow Computers (RDCs) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave a different acceleration value of algorithm execution. Those acceleration values are presented and experimental results showed good acceleration. PMID:28611851

Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers.

PubMed

Milankovic, Ivan L; Mijailovic, Nikola V; Filipovic, Nenad D; Peulic, Aleksandar S

2017-01-01

Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of the region of interest from a breast image, followed by the identification of suspicious mass regions, their classification, and comparison with the existing image database. It is often the case that already existing image databases have large sets of data whose processing requires a lot of time, and thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. In this paper, the implementation of the already existing algorithm for region-of-interest based image segmentation for mammogram images on High-Performance Reconfigurable Dataflow Computers (HPRDCs) is proposed. As a dataflow engine (DFE) of such HPRDC, Maxeler's acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable Dataflow Computers (RDCs) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave a different acceleration value of algorithm execution. Those acceleration values are presented and experimental results showed good acceleration.

High-performance computing in image registration

NASA Astrophysics Data System (ADS)

Zanin, Michele; Remondino, Fabio; Dalla Mura, Mauro

2012-10-01

Thanks to the recent technological advances, a large variety of image data is at our disposal with variable geometric, radiometric and temporal resolution. In many applications the processing of such images needs high performance computing techniques in order to deliver timely responses e.g. for rapid decisions or real-time actions. Thus, parallel or distributed computing methods, Digital Signal Processor (DSP) architectures, Graphical Processing Unit (GPU) programming and Field-Programmable Gate Array (FPGA) devices have become essential tools for the challenging issue of processing large amount of geo-data. The article focuses on the processing and registration of large datasets of terrestrial and aerial images for 3D reconstruction, diagnostic purposes and monitoring of the environment. For the image alignment procedure, sets of corresponding feature points need to be automatically extracted in order to successively compute the geometric transformation that aligns the data. The feature extraction and matching are ones of the most computationally demanding operations in the processing chain thus, a great degree of automation and speed is mandatory. The details of the implemented operations (named LARES) exploiting parallel architectures and GPU are thus presented. The innovative aspects of the implementation are (i) the effectiveness on a large variety of unorganized and complex datasets, (ii) capability to work with high-resolution images and (iii) the speed of the computations. Examples and comparisons with standard CPU processing are also reported and commented.

Matching rendered and real world images by digital image processing

NASA Astrophysics Data System (ADS)

Mitjà, Carles; Bover, Toni; Bigas, Miquel; Escofet, Jaume

2010-05-01

Recent advances in computer-generated images (CGI) have been used in commercial and industrial photography providing a broad scope in product advertising. Mixing real world images with those rendered from virtual space software shows a more or less visible mismatching between corresponding image quality performance. Rendered images are produced by software which quality performance is only limited by the resolution output. Real world images are taken with cameras with some amount of image degradation factors as lens residual aberrations, diffraction, sensor low pass anti aliasing filters, color pattern demosaicing, etc. The effect of all those image quality degradation factors can be characterized by the system Point Spread Function (PSF). Because the image is the convolution of the object by the system PSF, its characterization shows the amount of image degradation added to any taken picture. This work explores the use of image processing to degrade the rendered images following the parameters indicated by the real system PSF, attempting to match both virtual and real world image qualities. The system MTF is determined by the slanted edge method both in laboratory conditions and in the real picture environment in order to compare the influence of the working conditions on the device performance; an approximation to the system PSF is derived from the two measurements. The rendered images are filtered through a Gaussian filter obtained from the taking system PSF. Results with and without filtering are shown and compared measuring the contrast achieved in different final image regions.

Meta-analysis of the technical performance of an imaging procedure: guidelines and statistical methodology.

PubMed

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2015-02-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test-retest repeatability data for illustrative purposes. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Meta-analysis of the technical performance of an imaging procedure: Guidelines and statistical methodology

PubMed Central

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2017-01-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test–retest repeatability data for illustrative purposes. PMID:24872353

Model-based estimation of breast percent density in raw and processed full-field digital mammography images from image-acquisition physics and patient-image characteristics

NASA Astrophysics Data System (ADS)

Keller, Brad M.; Nathan, Diane L.; Conant, Emily F.; Kontos, Despina

2012-03-01

Breast percent density (PD%), as measured mammographically, is one of the strongest known risk factors for breast cancer. While the majority of studies to date have focused on PD% assessment from digitized film mammograms, digital mammography (DM) is becoming increasingly common, and allows for direct PD% assessment at the time of imaging. This work investigates the accuracy of a generalized linear model-based (GLM) estimation of PD% from raw and postprocessed digital mammograms, utilizing image acquisition physics, patient characteristics and gray-level intensity features of the specific image. The model is trained in a leave-one-woman-out fashion on a series of 81 cases for which bilateral, mediolateral-oblique DM images were available in both raw and post-processed format. Baseline continuous and categorical density estimates were provided by a trained breast-imaging radiologist. Regression analysis is performed and Pearson's correlation, r, and Cohen's kappa, κ, are computed. The GLM PD% estimation model performed well on both processed (r=0.89, p<0.001) and raw (r=0.75, p<0.001) images. Model agreement with radiologist assigned density categories was also high for processed (κ=0.79, p<0.001) and raw (κ=0.76, p<0.001) images. Model-based prediction of breast PD% could allow for a reproducible estimation of breast density, providing a rapid risk assessment tool for clinical practice.

FAST: framework for heterogeneous medical image computing and visualization.

PubMed

Smistad, Erik; Bozorgi, Mohammadmehdi; Lindseth, Frank

2015-11-01

Computer systems are becoming increasingly heterogeneous in the sense that they consist of different processors, such as multi-core CPUs and graphic processing units. As the amount of medical image data increases, it is crucial to exploit the computational power of these processors. However, this is currently difficult due to several factors, such as driver errors, processor differences, and the need for low-level memory handling. This paper presents a novel FrAmework for heterogeneouS medical image compuTing and visualization (FAST). The framework aims to make it easier to simultaneously process and visualize medical images efficiently on heterogeneous systems. FAST uses common image processing programming paradigms and hides the details of memory handling from the user, while enabling the use of all processors and cores on a system. The framework is open-source, cross-platform and available online. Code examples and performance measurements are presented to show the simplicity and efficiency of FAST. The results are compared to the insight toolkit (ITK) and the visualization toolkit (VTK) and show that the presented framework is faster with up to 20 times speedup on several common medical imaging algorithms. FAST enables efficient medical image computing and visualization on heterogeneous systems. Code examples and performance evaluations have demonstrated that the toolkit is both easy to use and performs better than existing frameworks, such as ITK and VTK.

Real-time acquisition and display of flow contrast using speckle variance optical coherence tomography in a graphics processing unit.

PubMed

Xu, Jing; Wong, Kevin; Jian, Yifan; Sarunic, Marinko V

2014-02-01

In this report, we describe a graphics processing unit (GPU)-accelerated processing platform for real-time acquisition and display of flow contrast images with Fourier domain optical coherence tomography (FDOCT) in mouse and human eyes in vivo. Motion contrast from blood flow is processed using the speckle variance OCT (svOCT) technique, which relies on the acquisition of multiple B-scan frames at the same location and tracking the change of the speckle pattern. Real-time mouse and human retinal imaging using two different custom-built OCT systems with processing and display performed on GPU are presented with an in-depth analysis of performance metrics. The display output included structural OCT data, en face projections of the intensity data, and the svOCT en face projections of retinal microvasculature; these results compare projections with and without speckle variance in the different retinal layers to reveal significant contrast improvements. As a demonstration, videos of real-time svOCT for in vivo human and mouse retinal imaging are included in our results. The capability of performing real-time svOCT imaging of the retinal vasculature may be a useful tool in a clinical environment for monitoring disease-related pathological changes in the microcirculation such as diabetic retinopathy.

Comparison of approaches for mobile document image analysis using server supported smartphones

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-03-01

With the recent advances in mobile technologies, new capabilities are emerging, such as mobile document image analysis. However, mobile phones are still less powerful than servers, and they have some resource limitations. One approach to overcome these limitations is performing resource-intensive processes of the application on remote servers. In mobile document image analysis, the most resource consuming process is the Optical Character Recognition (OCR) process, which is used to extract text in mobile phone captured images. In this study, our goal is to compare the in-phone and the remote server processing approaches for mobile document image analysis in order to explore their trade-offs. For the inphone approach, all processes required for mobile document image analysis run on the mobile phone. On the other hand, in the remote-server approach, core OCR process runs on the remote server and other processes run on the mobile phone. Results of the experiments show that the remote server approach is considerably faster than the in-phone approach in terms of OCR time, but adds extra delays such as network delay. Since compression and downscaling of images significantly reduce file sizes and extra delays, the remote server approach overall outperforms the in-phone approach in terms of selected speed and correct recognition metrics, if the gain in OCR time compensates for the extra delays. According to the results of the experiments, using the most preferable settings, the remote server approach performs better than the in-phone approach in terms of speed and acceptable correct recognition metrics.

Scalable, High-performance 3D Imaging Software Platform: System Architecture and Application to Virtual Colonoscopy

PubMed Central

Yoshida, Hiroyuki; Wu, Yin; Cai, Wenli; Brett, Bevin

2013-01-01

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. In this work, we have developed a software platform that is designed to support high-performance 3D medical image processing for a wide range of applications using increasingly available and affordable commodity computing systems: multi-core, clusters, and cloud computing systems. To achieve scalable, high-performance computing, our platform (1) employs size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D image processing algorithms; (2) supports task scheduling for efficient load distribution and balancing; and (3) consists of a layered parallel software libraries that allow a wide range of medical applications to share the same functionalities. We evaluated the performance of our platform by applying it to an electronic cleansing system in virtual colonoscopy, with initial experimental results showing a 10 times performance improvement on an 8-core workstation over the original sequential implementation of the system. PMID:23366803

Dynamic deformation image de-blurring and image processing for digital imaging correlation measurement

NASA Astrophysics Data System (ADS)

Guo, X.; Li, Y.; Suo, T.; Liu, H.; Zhang, C.

2017-11-01

This paper proposes a method for de-blurring of images captured in the dynamic deformation of materials. De-blurring is achieved based on the dynamic-based approach, which is used to estimate the Point Spread Function (PSF) during the camera exposure window. The deconvolution process involving iterative matrix calculations of pixels, is then performed on the GPU to decrease the time cost. Compared to the Gauss method and the Lucy-Richardson method, it has the best result of the image restoration. The proposed method has been evaluated by using the Hopkinson bar loading system. In comparison to the blurry image, the proposed method has successfully restored the image. It is also demonstrated from image processing applications that the de-blurring method can improve the accuracy and the stability of the digital imaging correlation measurement.

Implementation of total focusing method for phased array ultrasonic imaging on FPGA

NASA Astrophysics Data System (ADS)

Guo, JianQiang; Li, Xi; Gao, Xiaorong; Wang, Zeyong; Zhao, Quanke

2015-02-01

This paper describes a multi-FPGA imaging system dedicated for the real-time imaging using the Total Focusing Method (TFM) and Full Matrix Capture (FMC). The system was entirely described using Verilog HDL language and implemented on Altera Stratix IV GX FPGA development board. The whole algorithm process is to: establish a coordinate system of image and divide it into grids; calculate the complete acoustic distance of array element between transmitting array element and receiving array element, and transform it into index value; then index the sound pressure values from ROM and superimpose sound pressure values to get pixel value of one focus point; and calculate the pixel values of all focus points to get the final imaging. The imaging result shows that this algorithm has high SNR of defect imaging. And FPGA with parallel processing capability can provide high speed performance, so this system can provide the imaging interface, with complete function and good performance.

End-to-end performance analysis using engineering confidence models and a ground processor prototype

NASA Astrophysics Data System (ADS)

Kruse, Klaus-Werner; Sauer, Maximilian; Jäger, Thomas; Herzog, Alexandra; Schmitt, Michael; Huchler, Markus; Wallace, Kotska; Eisinger, Michael; Heliere, Arnaud; Lefebvre, Alain; Maher, Mat; Chang, Mark; Phillips, Tracy; Knight, Steve; de Goeij, Bryan T. G.; van der Knaap, Frits; Van't Hof, Adriaan

2015-10-01

The European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) are co-operating to develop the EarthCARE satellite mission with the fundamental objective of improving the understanding of the processes involving clouds, aerosols and radiation in the Earth's atmosphere. The EarthCARE Multispectral Imager (MSI) is relatively compact for a space borne imager. As a consequence, the immediate point-spread function (PSF) of the instrument will be mainly determined by the diffraction caused by the relatively small optical aperture. In order to still achieve a high contrast image, de-convolution processing is applied to remove the impact of diffraction on the PSF. A Lucy-Richardson algorithm has been chosen for this purpose. This paper will describe the system setup and the necessary data pre-processing and post-processing steps applied in order to compare the end-to-end image quality with the L1b performance required by the science community.

Optical Signal Processing: Poisson Image Restoration and Shearing Interferometry

NASA Technical Reports Server (NTRS)

Hong, Yie-Ming

1973-01-01

Optical signal processing can be performed in either digital or analog systems. Digital computers and coherent optical systems are discussed as they are used in optical signal processing. Topics include: image restoration; phase-object visualization; image contrast reversal; optical computation; image multiplexing; and fabrication of spatial filters. Digital optical data processing deals with restoration of images degraded by signal-dependent noise. When the input data of an image restoration system are the numbers of photoelectrons received from various areas of a photosensitive surface, the data are Poisson distributed with mean values proportional to the illuminance of the incoherently radiating object and background light. Optical signal processing using coherent optical systems is also discussed. Following a brief review of the pertinent details of Ronchi's diffraction grating interferometer, moire effect, carrier-frequency photography, and achromatic holography, two new shearing interferometers based on them are presented. Both interferometers can produce variable shear.

[Computer-assisted image processing for quantifying histopathologic variables in the healing of colonic anastomosis in dogs].

PubMed

Novelli, M D; Barreto, E; Matos, D; Saad, S S; Borra, R C

1997-01-01

The authors present the experimental results of the computerized quantifying of tissular structures involved in the reparative process of colonic anastomosis performed by manual suture and biofragmentable ring. The quantified variables in this study were: oedema fluid, myofiber tissue, blood vessel and cellular nuclei. An image processing software developed at Laboratório de Informática Dedicado à Odontologia (LIDO) was utilized to quantifying the pathognomonic alterations in the inflammatory process in colonic anastomosis performed in 14 dogs. The results were compared to those obtained through traditional way diagnosis by two pathologists in view of counterproof measures. The criteria for these diagnoses were defined in levels represented by absent, light, moderate and intensive which were compared to analysis performed by the computer. There was significant statistical difference between two techniques: the biofragmentable ring technique exhibited low oedema fluid, organized myofiber tissue and higher number of alongated cellular nuclei in relation to manual suture technique. The analysis of histometric variables through computational image processing was considered efficient and powerful to quantify the main tissular inflammatory and reparative changing.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform.

PubMed

Moutsatsos, Ioannis K; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J; Jenkins, Jeremy L; Holway, Nicholas; Tallarico, John; Parker, Christian N

2017-03-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an "off-the-shelf," open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community.

Jenkins-CI, an Open-Source Continuous Integration System, as a Scientific Data and Image-Processing Platform

PubMed Central

Moutsatsos, Ioannis K.; Hossain, Imtiaz; Agarinis, Claudia; Harbinski, Fred; Abraham, Yann; Dobler, Luc; Zhang, Xian; Wilson, Christopher J.; Jenkins, Jeremy L.; Holway, Nicholas; Tallarico, John; Parker, Christian N.

2016-01-01

High-throughput screening generates large volumes of heterogeneous data that require a diverse set of computational tools for management, processing, and analysis. Building integrated, scalable, and robust computational workflows for such applications is challenging but highly valuable. Scientific data integration and pipelining facilitate standardized data processing, collaboration, and reuse of best practices. We describe how Jenkins-CI, an “off-the-shelf,” open-source, continuous integration system, is used to build pipelines for processing images and associated data from high-content screening (HCS). Jenkins-CI provides numerous plugins for standard compute tasks, and its design allows the quick integration of external scientific applications. Using Jenkins-CI, we integrated CellProfiler, an open-source image-processing platform, with various HCS utilities and a high-performance Linux cluster. The platform is web-accessible, facilitates access and sharing of high-performance compute resources, and automates previously cumbersome data and image-processing tasks. Imaging pipelines developed using the desktop CellProfiler client can be managed and shared through a centralized Jenkins-CI repository. Pipelines and managed data are annotated to facilitate collaboration and reuse. Limitations with Jenkins-CI (primarily around the user interface) were addressed through the selection of helper plugins from the Jenkins-CI community. PMID:27899692

High Tech Aids Low Vision: A Review of Image Processing for the Visually Impaired.

PubMed

Moshtael, Howard; Aslam, Tariq; Underwood, Ian; Dhillon, Baljean

2015-08-01

Recent advances in digital image processing provide promising methods for maximizing the residual vision of the visually impaired. This paper seeks to introduce this field to the readership and describe its current state as found in the literature. A systematic search revealed 37 studies that measure the value of image processing techniques for subjects with low vision. The techniques used are categorized according to their effect and the principal findings are summarized. The majority of participants preferred enhanced images over the original for a wide range of enhancement types. Adapting the contrast and spatial frequency content often improved performance at object recognition and reading speed, as did techniques that attenuate the image background and a technique that induced jitter. A lack of consistency in preference and performance measures was found, as well as a lack of independent studies. Nevertheless, the promising results should encourage further research in order to allow their widespread use in low-vision aids.

A pipelined architecture for real time correction of non-uniformity in infrared focal plane arrays imaging system using multiprocessors

NASA Astrophysics Data System (ADS)

Zou, Liang; Fu, Zhuang; Zhao, YanZheng; Yang, JunYan

2010-07-01

This paper proposes a kind of pipelined electric circuit architecture implemented in FPGA, a very large scale integrated circuit (VLSI), which efficiently deals with the real time non-uniformity correction (NUC) algorithm for infrared focal plane arrays (IRFPA). Dual Nios II soft-core processors and a DSP with a 64+ core together constitute this image system. Each processor undertakes own systematic task, coordinating its work with each other's. The system on programmable chip (SOPC) in FPGA works steadily under the global clock frequency of 96Mhz. Adequate time allowance makes FPGA perform NUC image pre-processing algorithm with ease, which has offered favorable guarantee for the work of post image processing in DSP. And at the meantime, this paper presents a hardware (HW) and software (SW) co-design in FPGA. Thus, this systematic architecture yields an image processing system with multiprocessor, and a smart solution to the satisfaction with the performance of the system.

Mutual information-based template matching scheme for detection of breast masses: from mammography to digital breast tomosynthesis

PubMed Central

Mazurowski, Maciej A; Lo, Joseph Y; Harrawood, Brian P; Tourassi, Georgia D

2011-01-01

Development of a computational decision aid for a new medical imaging modality typically is a long and complicated process. It consists of collecting data in the form of images and annotations, development of image processing and pattern recognition algorithms for analysis of the new images and finally testing of the resulting system. Since new imaging modalities are developed more rapidly than ever before, any effort for decreasing the time and cost of this development process could result in maximizing the benefit of the new imaging modality to patients by making the computer aids quickly available to radiologists that interpret the images. In this paper, we make a step in this direction and investigate the possibility of translating the knowledge about the detection problem from one imaging modality to another. Specifically, we present a computer-aided detection (CAD) system for mammographic masses that uses a mutual information-based template matching scheme with intelligently selected templates. We presented principles of template matching with mutual information for mammography before. In this paper, we present an implementation of those principles in a complete computer-aided detection system. The proposed system, through an automatic optimization process, chooses the most useful templates (mammographic regions of interest) using a large database of previously collected and annotated mammograms. Through this process, the knowledge about the task of detecting masses in mammograms is incorporated in the system. Then we evaluate whether our system developed for screen-film mammograms can be successfully applied not only to other mammograms but also to digital breast tomosynthesis (DBT) reconstructed slices without adding any DBT cases for training. Our rationale is that since mutual information is known to be a robust intermodality image similarity measure, it has high potential of transferring knowledge between modalities in the context of the mass detection task. Experimental evaluation of the system on mammograms showed competitive performance compared to other mammography CAD systems recently published in the literature. When the system was applied “as-is” to DBT, its performance was notably worse than that for mammograms. However, with a simple additional preprocessing step, the performance of the system reached levels similar to that obtained for mammograms. In conclusion, the presented CAD system not only performed competitively on screen-film mammograms but it also performed robustly on DBT showing that direct transfer of knowledge across breast imaging modalities for mass detection is in fact possible. PMID:21554985

Processing Demands Impact 3-Year-Olds' Performance in a Spontaneous-Response Task: New Evidence for the Processing-Load Account of Early False-Belief Understanding.

PubMed

Scott, Rose M; Roby, Erin

2015-01-01

Prior to age four, children succeed in non-elicited-response false-belief tasks but fail elicited-response false-belief tasks. To explain this discrepancy, the processing-load account argues that the capacity to represent beliefs emerges in infancy, as indicated by early success on non-elicited-response tasks, but that children's ability to demonstrate this capacity depends on the processing demands of the task and children's processing skills. When processing demands exceed young children's processing abilities, such as in standard elicited-response tasks, children fail despite their capacity to represent beliefs. Support for this account comes from recent evidence that reducing processing demands improves young children's performance: when demands are sufficiently reduced, 2.5-year-olds succeed in elicited-response tasks. Here we sought complementary evidence for the processing-load account by examining whether increasing processing demands impeded children's performance in a non-elicited-response task. 3-year-olds were tested in a preferential-looking task in which they heard a change-of-location false-belief story accompanied by a picture book; across children, we manipulated the amount of linguistic ambiguity in the story. The final page of the book showed two images: one that was consistent with the main character's false belief and one that was consistent with reality. When the story was relatively unambiguous, children looked reliably longer at the false-belief-consistent image, successfully demonstrating their false-belief understanding. When the story was ambiguous, however, this undermined children's performance: looking times to the belief-consistent image were correlated with verbal ability, and only children with verbal skills in the upper quartile of the sample demonstrated a significant preference for the belief-consistent image. These results support the processing-load account by demonstrating that regardless of whether a task involves an elicited response, children's performance depends on the processing demands of the task and their processing skills. These findings also have implications for alternative, deflationary accounts of early false-belief understanding.

Processing Demands Impact 3-Year-Olds’ Performance in a Spontaneous-Response Task: New Evidence for the Processing-Load Account of Early False-Belief Understanding

PubMed Central

Scott, Rose M.; Roby, Erin

2015-01-01

Prior to age four, children succeed in non-elicited-response false-belief tasks but fail elicited-response false-belief tasks. To explain this discrepancy, the processing-load account argues that the capacity to represent beliefs emerges in infancy, as indicated by early success on non-elicited-response tasks, but that children’s ability to demonstrate this capacity depends on the processing demands of the task and children’s processing skills. When processing demands exceed young children’s processing abilities, such as in standard elicited-response tasks, children fail despite their capacity to represent beliefs. Support for this account comes from recent evidence that reducing processing demands improves young children’s performance: when demands are sufficiently reduced, 2.5-year-olds succeed in elicited-response tasks. Here we sought complementary evidence for the processing-load account by examining whether increasing processing demands impeded children’s performance in a non-elicited-response task. 3-year-olds were tested in a preferential-looking task in which they heard a change-of-location false-belief story accompanied by a picture book; across children, we manipulated the amount of linguistic ambiguity in the story. The final page of the book showed two images: one that was consistent with the main character’s false belief and one that was consistent with reality. When the story was relatively unambiguous, children looked reliably longer at the false-belief-consistent image, successfully demonstrating their false-belief understanding. When the story was ambiguous, however, this undermined children’s performance: looking times to the belief-consistent image were correlated with verbal ability, and only children with verbal skills in the upper quartile of the sample demonstrated a significant preference for the belief-consistent image. These results support the processing-load account by demonstrating that regardless of whether a task involves an elicited response, children’s performance depends on the processing demands of the task and their processing skills. These findings also have implications for alternative, deflationary accounts of early false-belief understanding. PMID:26562840

Coincident Extraction of Line Objects from Stereo Image Pairs.

DTIC Science & Technology

1983-09-01

4.4.3 Reconstruction of intersections 4.5 Final result processing 5. Presentation of the results 5.1 FIM image processing system 5.2 Extraction results in...image. To achieve this goal, the existing software system had to be modified and extended considerably. The following sections of this report will give...8000 pixels of each image without explicit loading of subimages could not yet be performed due to computer system software problems. m m n m -4- The

Image interpolation and denoising for division of focal plane sensors using Gaussian processes.

PubMed

Gilboa, Elad; Cunningham, John P; Nehorai, Arye; Gruev, Viktor

2014-06-16

Image interpolation and denoising are important techniques in image processing. These methods are inherent to digital image acquisition as most digital cameras are composed of a 2D grid of heterogeneous imaging sensors. Current polarization imaging employ four different pixelated polarization filters, commonly referred to as division of focal plane polarization sensors. The sensors capture only partial information of the true scene, leading to a loss of spatial resolution as well as inaccuracy of the captured polarization information. Interpolation is a standard technique to recover the missing information and increase the accuracy of the captured polarization information. Here we focus specifically on Gaussian process regression as a way to perform a statistical image interpolation, where estimates of sensor noise are used to improve the accuracy of the estimated pixel information. We further exploit the inherent grid structure of this data to create a fast exact algorithm that operates in ����(N(3/2)) (vs. the naive ���� (N³)), thus making the Gaussian process method computationally tractable for image data. This modeling advance and the enabling computational advance combine to produce significant improvements over previously published interpolation methods for polarimeters, which is most pronounced in cases of low signal-to-noise ratio (SNR). We provide the comprehensive mathematical model as well as experimental results of the GP interpolation performance for division of focal plane polarimeter.

Landsat-8 Operational Land Imager (OLI) radiometric performance on-orbit

USGS Publications Warehouse

Morfitt, Ron; Barsi, Julia A.; Levy, Raviv; Markham, Brian L.; Micijevic, Esad; Ong, Lawrence; Scaramuzza, Pat; Vanderwerff, Kelly

2015-01-01

Expectations of the Operational Land Imager (OLI) radiometric performance onboard Landsat-8 have been met or exceeded. The calibration activities that occurred prior to launch provided calibration parameters that enabled ground processing to produce imagery that met most requirements when data were transmitted to the ground. Since launch, calibration updates have improved the image quality even more, so that all requirements are met. These updates range from detector gain coefficients to reduce striping and banding to alignment parameters to improve the geometric accuracy. This paper concentrates on the on-orbit radiometric performance of the OLI, excepting the radiometric calibration performance. Topics discussed in this paper include: signal-to-noise ratios that are an order of magnitude higher than previous Landsat missions; radiometric uniformity that shows little residual banding and striping, and continues to improve; a dynamic range that limits saturation to extremely high radiance levels; extremely stable detectors; slight nonlinearity that is corrected in ground processing; detectors that are stable and 100% operable; and few image artifacts.

Youpi: YOUr processing PIpeline

NASA Astrophysics Data System (ADS)

Monnerville, Mathias; Sémah, Gregory

2012-03-01

Youpi is a portable, easy to use web application providing high level functionalities to perform data reduction on scientific FITS images. Built on top of various open source reduction tools released to the community by TERAPIX (http://terapix.iap.fr), Youpi can help organize data, manage processing jobs on a computer cluster in real time (using Condor) and facilitate teamwork by allowing fine-grain sharing of results and data. Youpi is modular and comes with plugins which perform, from within a browser, various processing tasks such as evaluating the quality of incoming images (using the QualityFITS software package), computing astrometric and photometric solutions (using SCAMP), resampling and co-adding FITS images (using SWarp) and extracting sources and building source catalogues from astronomical images (using SExtractor). Youpi is useful for small to medium-sized data reduction projects; it is free and is published under the GNU General Public License.

Real-time image dehazing using local adaptive neighborhoods and dark-channel-prior

NASA Astrophysics Data System (ADS)

Valderrama, Jesus A.; Díaz-Ramírez, Víctor H.; Kober, Vitaly; Hernandez, Enrique

2015-09-01

A real-time algorithm for single image dehazing is presented. The algorithm is based on calculation of local neighborhoods of a hazed image inside a moving window. The local neighborhoods are constructed by computing rank-order statistics. Next the dark-channel-prior approach is applied to the local neighborhoods to estimate the transmission function of the scene. By using the suggested approach there is no need for applying a refining algorithm to the estimated transmission such as the soft matting algorithm. To achieve high-rate signal processing the proposed algorithm is implemented exploiting massive parallelism on a graphics processing unit (GPU). Computer simulation results are carried out to test the performance of the proposed algorithm in terms of dehazing efficiency and speed of processing. These tests are performed using several synthetic and real images. The obtained results are analyzed and compared with those obtained with existing dehazing algorithms.

Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions.

PubMed

Jha, Abhinav K; Barrett, Harrison H; Frey, Eric C; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A

2015-09-21

Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and implemented for graphics processing units (GPUs). Further, this approach leverages another important advantage of PP systems, namely the possibility to perform photon-by-photon real-time reconstruction. We demonstrate the application of the approach to perform reconstruction in a simulated 2D SPECT system. The results help to validate and demonstrate the utility of the proposed method and show that PP systems can help overcome the aliasing artifacts that are otherwise intrinsically present in PC systems.

Singular value decomposition for photon-processing nuclear imaging systems and applications for reconstruction and computing null functions

NASA Astrophysics Data System (ADS)

Jha, Abhinav K.; Barrett, Harrison H.; Frey, Eric C.; Clarkson, Eric; Caucci, Luca; Kupinski, Matthew A.

2015-09-01

Recent advances in technology are enabling a new class of nuclear imaging systems consisting of detectors that use real-time maximum-likelihood (ML) methods to estimate the interaction position, deposited energy, and other attributes of each photon-interaction event and store these attributes in a list format. This class of systems, which we refer to as photon-processing (PP) nuclear imaging systems, can be described by a fundamentally different mathematical imaging operator that allows processing of the continuous-valued photon attributes on a per-photon basis. Unlike conventional photon-counting (PC) systems that bin the data into images, PP systems do not have any binning-related information loss. Mathematically, while PC systems have an infinite-dimensional null space due to dimensionality considerations, PP systems do not necessarily suffer from this issue. Therefore, PP systems have the potential to provide improved performance in comparison to PC systems. To study these advantages, we propose a framework to perform the singular-value decomposition (SVD) of the PP imaging operator. We use this framework to perform the SVD of operators that describe a general two-dimensional (2D) planar linear shift-invariant (LSIV) PP system and a hypothetical continuously rotating 2D single-photon emission computed tomography (SPECT) PP system. We then discuss two applications of the SVD framework. The first application is to decompose the object being imaged by the PP imaging system into measurement and null components. We compare these components to the measurement and null components obtained with PC systems. In the process, we also present a procedure to compute the null functions for a PC system. The second application is designing analytical reconstruction algorithms for PP systems. The proposed analytical approach exploits the fact that PP systems acquire data in a continuous domain to estimate a continuous object function. The approach is parallelizable and implemented for graphics processing units (GPUs). Further, this approach leverages another important advantage of PP systems, namely the possibility to perform photon-by-photon real-time reconstruction. We demonstrate the application of the approach to perform reconstruction in a simulated 2D SPECT system. The results help to validate and demonstrate the utility of the proposed method and show that PP systems can help overcome the aliasing artifacts that are otherwise intrinsically present in PC systems.

Delta-Doped Back-Illuminated CMOS Imaging Arrays: Progress and Prospects

NASA Technical Reports Server (NTRS)

Hoenk, Michael E.; Jones, Todd J.; Dickie, Matthew R.; Greer, Frank; Cunningham, Thomas J.; Blazejewski, Edward; Nikzad, Shouleh

2009-01-01

In this paper, we report the latest results on our development of delta-doped, thinned, back-illuminated CMOS imaging arrays. As with charge-coupled devices, thinning and back-illumination are essential to the development of high performance CMOS imaging arrays. Problems with back surface passivation have emerged as critical to the prospects for incorporating CMOS imaging arrays into high performance scientific instruments, just as they did for CCDs over twenty years ago. In the early 1990's, JPL developed delta-doped CCDs, in which low temperature molecular beam epitaxy was used to form an ideal passivation layer on the silicon back surface. Comprising only a few nanometers of highly-doped epitaxial silicon, delta-doping achieves the stability and uniformity that are essential for high performance imaging and spectroscopy. Delta-doped CCDs were shown to have high, stable, and uniform quantum efficiency across the entire spectral range from the extreme ultraviolet through the near infrared. JPL has recently bump-bonded thinned, delta-doped CMOS imaging arrays to a CMOS readout, and demonstrated imaging. Delta-doped CMOS devices exhibit the high quantum efficiency that has become the standard for scientific-grade CCDs. Together with new circuit designs for low-noise readout currently under development, delta-doping expands the potential scientific applications of CMOS imaging arrays, and brings within reach important new capabilities, such as fast, high-sensitivity imaging with parallel readout and real-time signal processing. It remains to demonstrate manufacturability of delta-doped CMOS imaging arrays. To that end, JPL has acquired a new silicon MBE and ancillary equipment for delta-doping wafers up to 200mm in diameter, and is now developing processes for high-throughput, high yield delta-doping of fully-processed wafers with CCD and CMOS imaging devices.

SAR processing using SHARC signal processing systems

NASA Astrophysics Data System (ADS)

Huxtable, Barton D.; Jackson, Christopher R.; Skaron, Steve A.

1998-09-01

Synthetic aperture radar (SAR) is uniquely suited to help solve the Search and Rescue problem since it can be utilized either day or night and through both dense fog or thick cloud cover. Other papers in this session, and in this session in 1997, describe the various SAR image processing algorithms that are being developed and evaluated within the Search and Rescue Program. All of these approaches to using SAR data require substantial amounts of digital signal processing: for the SAR image formation, and possibly for the subsequent image processing. In recognition of the demanding processing that will be required for an operational Search and Rescue Data Processing System (SARDPS), NASA/Goddard Space Flight Center and NASA/Stennis Space Center are conducting a technology demonstration utilizing SHARC multi-chip modules from Boeing to perform SAR image formation processing.

SSME propellant path leak detection real-time

NASA Technical Reports Server (NTRS)

Crawford, R. A.; Smith, L. M.

1994-01-01

Included are four documents that outline the technical aspects of the research performed on NASA Grant NAG8-140: 'A System for Sequential Step Detection with Application to Video Image Processing'; 'Leak Detection from the SSME Using Sequential Image Processing'; 'Digital Image Processor Specifications for Real-Time SSME Leak Detection'; and 'A Color Change Detection System for Video Signals with Applications to Spectral Analysis of Rocket Engine Plumes'.

Sensor image prediction techniques

NASA Astrophysics Data System (ADS)

Stenger, A. J.; Stone, W. R.; Berry, L.; Murray, T. J.

1981-02-01

The preparation of prediction imagery is a complex, costly, and time consuming process. Image prediction systems which produce a detailed replica of the image area require the extensive Defense Mapping Agency data base. The purpose of this study was to analyze the use of image predictions in order to determine whether a reduced set of more compact image features contains enough information to produce acceptable navigator performance. A job analysis of the navigator's mission tasks was performed. It showed that the cognitive and perceptual tasks he performs during navigation are identical to those performed for the targeting mission function. In addition, the results of the analysis of his performance when using a particular sensor can be extended to the analysis of this mission tasks using any sensor. An experimental approach was used to determine the relationship between navigator performance and the type of amount of information in the prediction image. A number of subjects were given image predictions containing varying levels of scene detail and different image features, and then asked to identify the predicted targets in corresponding dynamic flight sequences over scenes of cultural, terrain, and mixed (both cultural and terrain) content.

Computer-aided classification of breast microcalcification clusters: merging of features from image processing and radiologists

NASA Astrophysics Data System (ADS)

Lo, Joseph Y.; Gavrielides, Marios A.; Markey, Mia K.; Jesneck, Jonathan L.

2003-05-01

We developed an ensemble classifier for the task of computer-aided diagnosis of breast microcalcification clusters,which are very challenging to characterize for radiologists and computer models alike. The purpose of this study is to help radiologists identify whether suspicious calcification clusters are benign vs. malignant, such that they may potentially recommend fewer unnecessary biopsies for actually benign lesions. The data consists of mammographic features extracted by automated image processing algorithms as well as manually interpreted by radiologists according to a standardized lexicon. We used 292 cases from a publicly available mammography database. From each cases, we extracted 22 image processing features pertaining to lesion morphology, 5 radiologist features also pertaining to morphology, and the patient age. Linear discriminant analysis (LDA) models were designed using each of the three data types. Each local model performed poorly; the best was one based upon image processing features which yielded ROC area index AZ of 0.59 +/- 0.03 and partial AZ above 90% sensitivity of 0.08 +/- 0.03. We then developed ensemble models using different combinations of those data types, and these models all improved performance compared to the local models. The final ensemble model was based upon 5 features selected by stepwise LDA from all 28 available features. This ensemble performed with AZ of 0.69 +/- 0.03 and partial AZ of 0.21 +/- 0.04, which was statistically significantly better than the model based on the image processing features alone (p<0.001 and p=0.01 for full and partial AZ respectively). This demonstrated the value of the radiologist-extracted features as a source of information for this task. It also suggested there is potential for improved performance using this ensemble classifier approach to combine different sources of currently available data.

Fast perceptual image hash based on cascade algorithm

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly; Yavtushenko, Evgeniya

2017-09-01

In this paper, we propose a perceptual image hash algorithm based on cascade algorithm, which can be applied in image authentication, retrieval, and indexing. Image perceptual hash uses for image retrieval in sense of human perception against distortions caused by compression, noise, common signal processing and geometrical modifications. The main disadvantage of perceptual hash is high time expenses. In the proposed cascade algorithm of image retrieval initializes with short hashes, and then a full hash is applied to the processed results. Computer simulation results show that the proposed hash algorithm yields a good performance in terms of robustness, discriminability, and time expenses.

Restoration of motion blurred images

NASA Astrophysics Data System (ADS)

Gaxiola, Leopoldo N.; Juarez-Salazar, Rigoberto; Diaz-Ramirez, Victor H.

2017-08-01

Image restoration is a classic problem in image processing. Image degradations can occur due to several reasons, for instance, imperfections of imaging systems, quantization errors, atmospheric turbulence, relative motion between camera or objects, among others. Motion blur is a typical degradation in dynamic imaging systems. In this work, we present a method to estimate the parameters of linear motion blur degradation from a captured blurred image. The proposed method is based on analyzing the frequency spectrum of a captured image in order to firstly estimate the degradation parameters, and then, to restore the image with a linear filter. The performance of the proposed method is evaluated by processing synthetic and real-life images. The obtained results are characterized in terms of accuracy of image restoration given by an objective criterion.

Design of light-small high-speed image data processing system

NASA Astrophysics Data System (ADS)

Yang, Jinbao; Feng, Xue; Li, Fei

2015-10-01

A light-small high speed image data processing system was designed in order to meet the request of image data processing in aerospace. System was constructed of FPGA, DSP and MCU (Micro-controller), implementing a video compress of 3 million pixels@15frames and real-time return of compressed image to the upper system. Programmable characteristic of FPGA, high performance image compress IC and configurable MCU were made best use to improve integration. Besides, hard-soft board design was introduced and PCB layout was optimized. At last, system achieved miniaturization, light-weight and fast heat dispersion. Experiments show that, system's multifunction was designed correctly and worked stably. In conclusion, system can be widely used in the area of light-small imaging.

Intensity dependent spread theory

NASA Technical Reports Server (NTRS)

Holben, Richard

1990-01-01

The Intensity Dependent Spread (IDS) procedure is an image-processing technique based on a model of the processing which occurs in the human visual system. IDS processing is relevant to many aspects of machine vision and image processing. For quantum limited images, it produces an ideal trade-off between spatial resolution and noise averaging, performs edge enhancement thus requiring only mean-crossing detection for the subsequent extraction of scene edges, and yields edge responses whose amplitudes are independent of scene illumination, depending only upon the ratio of the reflectance on the two sides of the edge. These properties suggest that the IDS process may provide significant bandwidth reduction while losing only minimal scene information when used as a preprocessor at or near the image plane.

Applying and extending ISO/TC42 digital camera resolution standards to mobile imaging products

NASA Astrophysics Data System (ADS)

Williams, Don; Burns, Peter D.

2007-01-01

There are no fundamental differences between today's mobile telephone cameras and consumer digital still cameras that suggest many existing ISO imaging performance standards do not apply. To the extent that they have lenses, color filter arrays, detectors, apertures, image processing, and are hand held, there really are no operational or architectural differences. Despite this, there are currently differences in the levels of imaging performance. These are driven by physical and economic constraints, and image-capture conditions. Several ISO standards for resolution, well established for digital consumer digital cameras, require care when applied to the current generation of cell phone cameras. In particular, accommodation of optical flare, shading non-uniformity and distortion are recommended. We offer proposals for the application of existing ISO imaging resolution performance standards to mobile imaging products, and suggestions for extending performance standards to the characteristic behavior of camera phones.

Real-time image processing for non-contact monitoring of dynamic displacements using smartphone technologies

NASA Astrophysics Data System (ADS)

Min, Jae-Hong; Gelo, Nikolas J.; Jo, Hongki

2016-04-01

The newly developed smartphone application, named RINO, in this study allows measuring absolute dynamic displacements and processing them in real time using state-of-the-art smartphone technologies, such as high-performance graphics processing unit (GPU), in addition to already powerful CPU and memories, embedded high-speed/ resolution camera, and open-source computer vision libraries. A carefully designed color-patterned target and user-adjustable crop filter enable accurate and fast image processing, allowing up to 240fps for complete displacement calculation and real-time display. The performances of the developed smartphone application are experimentally validated, showing comparable accuracy with those of conventional laser displacement sensor.

A robust hidden Markov Gauss mixture vector quantizer for a noisy source.

PubMed

Pyun, Kyungsuk Peter; Lim, Johan; Gray, Robert M

2009-07-01

Noise is ubiquitous in real life and changes image acquisition, communication, and processing characteristics in an uncontrolled manner. Gaussian noise and Salt and Pepper noise, in particular, are prevalent in noisy communication channels, camera and scanner sensors, and medical MRI images. It is not unusual for highly sophisticated image processing algorithms developed for clean images to malfunction when used on noisy images. For example, hidden Markov Gauss mixture models (HMGMM) have been shown to perform well in image segmentation applications, but they are quite sensitive to image noise. We propose a modified HMGMM procedure specifically designed to improve performance in the presence of noise. The key feature of the proposed procedure is the adjustment of covariance matrices in Gauss mixture vector quantizer codebooks to minimize an overall minimum discrimination information distortion (MDI). In adjusting covariance matrices, we expand or shrink their elements based on the noisy image. While most results reported in the literature assume a particular noise type, we propose a framework without assuming particular noise characteristics. Without denoising the corrupted source, we apply our method directly to the segmentation of noisy sources. We apply the proposed procedure to the segmentation of aerial images with Salt and Pepper noise and with independent Gaussian noise, and we compare our results with those of the median filter restoration method and the blind deconvolution-based method, respectively. We show that our procedure has better performance than image restoration-based techniques and closely matches to the performance of HMGMM for clean images in terms of both visual segmentation results and error rate.

MOPEX: a software package for astronomical image processing and visualization

NASA Astrophysics Data System (ADS)

Makovoz, David; Roby, Trey; Khan, Iffat; Booth, Hartley

2006-06-01

We present MOPEX - a software package for astronomical image processing and display. The package is a combination of command-line driven image processing software written in C/C++ with a Java-based GUI. The main image processing capabilities include creating mosaic images, image registration, background matching, point source extraction, as well as a number of minor image processing tasks. The combination of the image processing and display capabilities allows for much more intuitive and efficient way of performing image processing. The GUI allows for the control over the image processing and display to be closely intertwined. Parameter setting, validation, and specific processing options are entered by the user through a set of intuitive dialog boxes. Visualization feeds back into further processing by providing a prompt feedback of the processing results. The GUI also allows for further analysis by accessing and displaying data from existing image and catalog servers using a virtual observatory approach. Even though originally designed for the Spitzer Space Telescope mission, a lot of functionalities are of general usefulness and can be used for working with existing astronomical data and for new missions. The software used in the package has undergone intensive testing and benefited greatly from effective software reuse. The visualization part has been used for observation planning for both the Spitzer and Herschel Space Telescopes as part the tool Spot. The visualization capabilities of Spot have been enhanced and integrated with the image processing functionality of the command-line driven MOPEX. The image processing software is used in the Spitzer automated pipeline processing, which has been in operation for nearly 3 years. The image processing capabilities have also been tested in off-line processing by numerous astronomers at various institutions around the world. The package is multi-platform and includes automatic update capabilities. The software package has been developed by a small group of software developers and scientists at the Spitzer Science Center. It is available for distribution at the Spitzer Science Center web page.

Graphical user interface for image acquisition and processing

DOEpatents

Goldberg, Kenneth A.

2002-01-01

An event-driven GUI-based image acquisition interface for the IDL programming environment designed for CCD camera control and image acquisition directly into the IDL environment where image manipulation and data analysis can be performed, and a toolbox of real-time analysis applications. Running the image acquisition hardware directly from IDL removes the necessity of first saving images in one program and then importing the data into IDL for analysis in a second step. Bringing the data directly into IDL creates an opportunity for the implementation of IDL image processing and display functions in real-time. program allows control over the available charge coupled device (CCD) detector parameters, data acquisition, file saving and loading, and image manipulation and processing, all from within IDL. The program is built using IDL's widget libraries to control the on-screen display and user interface.

The Vector, Signal, and Image Processing Library (VSIPL): an Open Standard for Astronomical Data Processing

NASA Astrophysics Data System (ADS)

Kepner, J. V.; Janka, R. S.; Lebak, J.; Richards, M. A.

1999-12-01

The Vector/Signal/Image Processing Library (VSIPL) is a DARPA initiated effort made up of industry, government and academic representatives who have defined an industry standard API for vector, signal, and image processing primitives for real-time signal processing on high performance systems. VSIPL supports a wide range of data types (int, float, complex, ...) and layouts (vectors, matrices and tensors) and is ideal for astronomical data processing. The VSIPL API is intended to serve as an open, vendor-neutral, industry standard interface. The object-based VSIPL API abstracts the memory architecture of the underlying machine by using the concept of memory blocks and views. Early experiments with VSIPL code conversions have been carried out by the High Performance Computing Program team at the UCSD. Commercially, several major vendors of signal processors are actively developing implementations. VSIPL has also been explicitly required as part of a recent Rome Labs teraflop procurement. This poster presents the VSIPL API, its functionality and the status of various implementations.

Fundamental performance differences between CMOS and CCD imagers: part III

NASA Astrophysics Data System (ADS)

Janesick, James; Pinter, Jeff; Potter, Robert; Elliott, Tom; Andrews, James; Tower, John; Cheng, John; Bishop, Jeanne

2009-08-01

This paper is a status report on recent scientific CMOS imager developments since when previous publications were written. Focus today is being given on CMOS design and process optimization because fundamental problems affecting performance are now reasonably well understood. Topics found in this paper include discussions on a low cost custom scientific CMOS fabrication approach, substrate bias for deep depletion imagers, near IR and x-ray point-spread performance, custom fabricated high resisitivity epitaxial and SOI silicon wafers for backside illuminated imagers, buried channel MOSFETs for ultra low noise performance, 1 e- charge transfer imagers, high speed transfer pixels, RTS/ flicker noise versus MOSFET geometry, pixel offset and gain non uniformity measurements, high S/N dCDS/aCDS signal processors, pixel thermal dark current sources, radiation damage topics, CCDs fabricated in CMOS and future large CMOS imagers planned at Sarnoff.

An array processing system for lunar geochemical and geophysical data

NASA Technical Reports Server (NTRS)

Eliason, E. M.; Soderblom, L. A.

1977-01-01

A computerized array processing system has been developed to reduce, analyze, display, and correlate a large number of orbital and earth-based geochemical, geophysical, and geological measurements of the moon on a global scale. The system supports the activities of a consortium of about 30 lunar scientists involved in data synthesis studies. The system was modeled after standard digital image-processing techniques but differs in that processing is performed with floating point precision rather than integer precision. Because of flexibility in floating-point image processing, a series of techniques that are impossible or cumbersome in conventional integer processing were developed to perform optimum interpolation and smoothing of data. Recently color maps of about 25 lunar geophysical and geochemical variables have been generated.

[Coupling AFM fluid imaging with micro-flocculation filtration process for the technological optimization].

PubMed

Zheng, Bei; Ge, Xiao-peng; Yu, Zhi-yong; Yuan, Sheng-guang; Zhang, Wen-jing; Sun, Jing-fang

2012-08-01

Atomic force microscope (AFM) fluid imaging was applied to the study of micro-flocculation filtration process and the optimization of micro-flocculation time and the agitation intensity of G values. It can be concluded that AFM fluid imaging proves to be a promising tool in the observation and characterization of floc morphology and the dynamic coagulation processes under aqueous environmental conditions. Through the use of AFM fluid imaging technique, optimized conditions for micro-flocculation time of 2 min and the agitation intensity (G value) of 100 s(-1) were obtained in the treatment of dye-printing industrial tailing wastewater by the micro-flocculation filtration process with a good performance.

Accelerating image recognition on mobile devices using GPGPU

NASA Astrophysics Data System (ADS)

Bordallo López, Miguel; Nykänen, Henri; Hannuksela, Jari; Silvén, Olli; Vehviläinen, Markku

2011-01-01

The future multi-modal user interfaces of battery-powered mobile devices are expected to require computationally costly image analysis techniques. The use of Graphic Processing Units for computing is very well suited for parallel processing and the addition of programmable stages and high precision arithmetic provide for opportunities to implement energy-efficient complete algorithms. At the moment the first mobile graphics accelerators with programmable pipelines are available, enabling the GPGPU implementation of several image processing algorithms. In this context, we consider a face tracking approach that uses efficient gray-scale invariant texture features and boosting. The solution is based on the Local Binary Pattern (LBP) features and makes use of the GPU on the pre-processing and feature extraction phase. We have implemented a series of image processing techniques in the shader language of OpenGL ES 2.0, compiled them for a mobile graphics processing unit and performed tests on a mobile application processor platform (OMAP3530). In our contribution, we describe the challenges of designing on a mobile platform, present the performance achieved and provide measurement results for the actual power consumption in comparison to using the CPU (ARM) on the same platform.

Identifying regions of interest in medical images using self-organizing maps.

PubMed

Teng, Wei-Guang; Chang, Ping-Lin

2012-10-01

Advances in data acquisition, processing and visualization techniques have had a tremendous impact on medical imaging in recent years. However, the interpretation of medical images is still almost always performed by radiologists. Developments in artificial intelligence and image processing have shown the increasingly great potential of computer-aided diagnosis (CAD). Nevertheless, it has remained challenging to develop a general approach to process various commonly used types of medical images (e.g., X-ray, MRI, and ultrasound images). To facilitate diagnosis, we recommend the use of image segmentation to discover regions of interest (ROI) using self-organizing maps (SOM). We devise a two-stage SOM approach that can be used to precisely identify the dominant colors of a medical image and then segment it into several small regions. In addition, by appropriately conducting the recursive merging steps to merge smaller regions into larger ones, radiologists can usually identify one or more ROIs within a medical image.

PI2GIS: processing image to geographical information systems, a learning tool for QGIS

NASA Astrophysics Data System (ADS)

Correia, R.; Teodoro, A.; Duarte, L.

2017-10-01

To perform an accurate interpretation of remote sensing images, it is necessary to extract information using different image processing techniques. Nowadays, it became usual to use image processing plugins to add new capabilities/functionalities integrated in Geographical Information System (GIS) software. The aim of this work was to develop an open source application to automatically process and classify remote sensing images from a set of satellite input data. The application was integrated in a GIS software (QGIS), automating several image processing steps. The use of QGIS for this purpose is justified since it is easy and quick to develop new plugins, using Python language. This plugin is inspired in the Semi-Automatic Classification Plugin (SCP) developed by Luca Congedo. SCP allows the supervised classification of remote sensing images, the calculation of vegetation indices such as NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) and other image processing operations. When analysing SCP, it was realized that a set of operations, that are very useful in teaching classes of remote sensing and image processing tasks, were lacking, such as the visualization of histograms, the application of filters, different image corrections, unsupervised classification and several environmental indices computation. The new set of operations included in the PI2GIS plugin can be divided into three groups: pre-processing, processing, and classification procedures. The application was tested consider an image from Landsat 8 OLI from a North area of Portugal.

Survey: interpolation methods for whole slide image processing.

PubMed

Roszkowiak, L; Korzynska, A; Zak, J; Pijanowska, D; Swiderska-Chadaj, Z; Markiewicz, T

2017-02-01

Evaluating whole slide images of histological and cytological samples is used in pathology for diagnostics, grading and prognosis . It is often necessary to rescale whole slide images of a very large size. Image resizing is one of the most common applications of interpolation. We collect the advantages and drawbacks of nine interpolation methods, and as a result of our analysis, we try to select one interpolation method as the preferred solution. To compare the performance of interpolation methods, test images were scaled and then rescaled to the original size using the same algorithm. The modified image was compared to the original image in various aspects. The time needed for calculations and results of quantification performance on modified images were also compared. For evaluation purposes, we used four general test images and 12 specialized biological immunohistochemically stained tissue sample images. The purpose of this survey is to determine which method of interpolation is the best to resize whole slide images, so they can be further processed using quantification methods. As a result, the interpolation method has to be selected depending on the task involving whole slide images. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Neural Correlates of Symptom Dimensions in Pediatric Obsessive-Compulsive Disorder: A Functional Magnetic Resonance Imaging Study

ERIC Educational Resources Information Center

Gilbert, Andrew R.; Akkal, Dalila; Almeida, Jorge R. C.; Mataix-Cols, David; Kalas, Catherine; Devlin, Bernie; Birmaher, Boris; Phillips, Mary L.

2009-01-01

The use of functional magnetic resonance imaging on a group of pediatric subjects with obsessive compulsive disorder reveals that this group has reduced activity in neural regions underlying emotional processing, cognitive processing, and motor performance as compared to control subjects.

High speed multiphoton imaging

NASA Astrophysics Data System (ADS)

Li, Yongxiao; Brustle, Anne; Gautam, Vini; Cockburn, Ian; Gillespie, Cathy; Gaus, Katharina; Lee, Woei Ming

2016-12-01

Intravital multiphoton microscopy has emerged as a powerful technique to visualize cellular processes in-vivo. Real time processes revealed through live imaging provided many opportunities to capture cellular activities in living animals. The typical parameters that determine the performance of multiphoton microscopy are speed, field of view, 3D imaging and imaging depth; many of these are important to achieving data from in-vivo. Here, we provide a full exposition of the flexible polygon mirror based high speed laser scanning multiphoton imaging system, PCI-6110 card (National Instruments) and high speed analog frame grabber card (Matrox Solios eA/XA), which allows for rapid adjustments between frame rates i.e. 5 Hz to 50 Hz with 512 × 512 pixels. Furthermore, a motion correction algorithm is also used to mitigate motion artifacts. A customized control software called Pscan 1.0 is developed for the system. This is then followed by calibration of the imaging performance of the system and a series of quantitative in-vitro and in-vivo imaging in neuronal tissues and mice.

Applications of nonlocal means algorithm in low-dose X-ray CT image processing and reconstruction: a review

PubMed Central

Zhang, Hao; Zeng, Dong; Zhang, Hua; Wang, Jing; Liang, Zhengrong

2017-01-01

Low-dose X-ray computed tomography (LDCT) imaging is highly recommended for use in the clinic because of growing concerns over excessive radiation exposure. However, the CT images reconstructed by the conventional filtered back-projection (FBP) method from low-dose acquisitions may be severely degraded with noise and streak artifacts due to excessive X-ray quantum noise, or with view-aliasing artifacts due to insufficient angular sampling. In 2005, the nonlocal means (NLM) algorithm was introduced as a non-iterative edge-preserving filter to denoise natural images corrupted by additive Gaussian noise, and showed superior performance. It has since been adapted and applied to many other image types and various inverse problems. This paper specifically reviews the applications of the NLM algorithm in LDCT image processing and reconstruction, and explicitly demonstrates its improving effects on the reconstructed CT image quality from low-dose acquisitions. The effectiveness of these applications on LDCT and their relative performance are described in detail. PMID:28303644

UWGSP7: a real-time optical imaging workstation

NASA Astrophysics Data System (ADS)

Bush, John E.; Kim, Yongmin; Pennington, Stan D.; Alleman, Andrew P.

1995-04-01

With the development of UWGSP7, the University of Washington Image Computing Systems Laboratory has a real-time workstation for continuous-wave (cw) optical reflectance imaging. Recent discoveries in optical science and imaging research have suggested potential practical use of the technology as a medical imaging modality and identified the need for a machine to support these applications in real time. The UWGSP7 system was developed to provide researchers with a high-performance, versatile tool for use in optical imaging experiments with the eventual goal of bringing the technology into clinical use. One of several major applications of cw optical reflectance imaging is tumor imaging which uses a light-absorbing dye that preferentially sequesters in tumor tissue. This property could be used to locate tumors and to identify tumor margins intraoperatively. Cw optical reflectance imaging consists of illumination of a target with a band-limited light source and monitoring the light transmitted by or reflected from the target. While continuously illuminating the target, a control image is acquired and stored. A dye is injected into a subject and a sequence of data images are acquired and processed. The data images are aligned with the control image and then subtracted to obtain a signal representing the change in optical reflectance over time. This signal can be enhanced by digital image processing and displayed in pseudo-color. This type of emerging imaging technique requires a computer system that is versatile and adaptable. The UWGSP7 utilizes a VESA local bus PC as a host computer running the Windows NT operating system and includes ICSL developed add-on boards for image acquisition and processing. The image acquisition board is used to digitize and format the analog signal from the input device into digital frames and to the average frames into images. To accommodate different input devices, the camera interface circuitry is designed in a small mezzanine board that supports the RS-170 standard. The image acquisition board is connected to the image- processing board using a direct connect port which provides a 66 Mbytes/s channel independent of the system bus. The image processing board utilizes the Texas Instruments TMS320C80 Multimedia Video Processor chip. This chip is capable of 2 billion operations per second providing the UWGSP7 with the capability to perform real-time image processing functions like median filtering, convolution and contrast enhancement. This processing power allows interactive analysis of the experiments as compared to current practice of off-line processing and analysis. Due to its flexibility and programmability, the UWGSP7 can be adapted into various research needs in intraoperative optical imaging.

Simulation of digital mammography images

NASA Astrophysics Data System (ADS)

Workman, Adam

2005-04-01

A number of different technologies are available for digital mammography. However, it is not clear how differences in the physical performance aspects of the different imaging technologies affect clinical performance. Randomised controlled trials provide a means of gaining information on clinical performance however do not provide direct comparison of the different digital imaging technologies. This work describes a method of simulating the performance of different digital mammography systems. The method involves modifying the imaging performance parameters of images from a small field of view (SFDM), high resolution digital imaging system used for spot imaging. Under normal operating conditions this system produces images with higher signal-to-noise ratio (SNR) over a wide spatial frequency range than current full field digital mammography (FFDM) systems. The SFDM images can be 'degraded" by computer processing to simulate the characteristics of a FFDM system. Initial work characterised the physical performance (MTF, NPS) of the SFDM detector and developed a model and method for simulating signal transfer and noise properties of a FFDM system. It was found that the SNR properties of the simulated FFDM images were very similar to those measured from an actual FFDM system verifying the methodology used. The application of this technique to clinical images from the small field system will allow the clinical performance of different FFDM systems to be simulated and directly compared using the same clinical image datasets.

Natural language processing and visualization in the molecular imaging domain.

PubMed

Tulipano, P Karina; Tao, Ying; Millar, William S; Zanzonico, Pat; Kolbert, Katherine; Xu, Hua; Yu, Hong; Chen, Lifeng; Lussier, Yves A; Friedman, Carol

2007-06-01

Molecular imaging is at the crossroads of genomic sciences and medical imaging. Information within the molecular imaging literature could be used to link to genomic and imaging information resources and to organize and index images in a way that is potentially useful to researchers. A number of natural language processing (NLP) systems are available to automatically extract information from genomic literature. One existing NLP system, known as BioMedLEE, automatically extracts biological information consisting of biomolecular substances and phenotypic data. This paper focuses on the adaptation, evaluation, and application of BioMedLEE to the molecular imaging domain. In order to adapt BioMedLEE for this domain, we extend an existing molecular imaging terminology and incorporate it into BioMedLEE. BioMedLEE's performance is assessed with a formal evaluation study. The system's performance, measured as recall and precision, is 0.74 (95% CI: [.70-.76]) and 0.70 (95% CI [.63-.76]), respectively. We adapt a JAVA viewer known as PGviewer for the simultaneous visualization of images with NLP extracted information.

A Pipeline for 3D Digital Optical Phenotyping Plant Root System Architecture

NASA Astrophysics Data System (ADS)

Davis, T. W.; Shaw, N. M.; Schneider, D. J.; Shaff, J. E.; Larson, B. G.; Craft, E. J.; Liu, Z.; Kochian, L. V.; Piñeros, M. A.

2017-12-01

This work presents a new pipeline for digital optical phenotyping the root system architecture of agricultural crops. The pipeline begins with a 3D root-system imaging apparatus for hydroponically grown crop lines of interest. The apparatus acts as a self-containing dark room, which includes an imaging tank, motorized rotating bearing and digital camera. The pipeline continues with the Plant Root Imaging and Data Acquisition (PRIDA) software, which is responsible for image capturing and storage. Once root images have been captured, image post-processing is performed using the Plant Root Imaging Analysis (PRIA) command-line tool, which extracts root pixels from color images. Following the pre-processing binarization of digital root images, 3D trait characterization is performed using the next-generation RootReader3D software. RootReader3D measures global root system architecture traits, such as total root system volume and length, total number of roots, and maximum rooting depth and width. While designed to work together, the four stages of the phenotyping pipeline are modular and stand-alone, which provides flexibility and adaptability for various research endeavors.

Gen-2 hand-held optical imager towards cancer imaging: reflectance and transillumination phantom studies.

PubMed

Gonzalez, Jean; Roman, Manuela; Hall, Michael; Godavarty, Anuradha

2012-01-01

Hand-held near-infrared (NIR) optical imagers are developed by various researchers towards non-invasive clinical breast imaging. Unlike these existing imagers that can perform only reflectance imaging, a generation-2 (Gen-2) hand-held optical imager has been recently developed to perform both reflectance and transillumination imaging. The unique forked design of the hand-held probe head(s) allows for reflectance imaging (as in ultrasound) and transillumination or compressed imaging (as in X-ray mammography). Phantom studies were performed to demonstrate two-dimensional (2D) target detection via reflectance and transillumination imaging at various target depths (1-5 cm deep) and using simultaneous multiple point illumination approach. It was observed that 0.45 cc targets were detected up to 5 cm deep during transillumination, but limited to 2.5 cm deep during reflectance imaging. Additionally, implementing appropriate data post-processing techniques along with a polynomial fitting approach, to plot 2D surface contours of the detected signal, yields distinct target detectability and localization. The ability of the gen-2 imager to perform both reflectance and transillumination imaging allows its direct comparison to ultrasound and X-ray mammography results, respectively, in future clinical breast imaging studies.

Real-time co-registered ultrasound and photoacoustic imaging system based on FPGA and DSP architecture

NASA Astrophysics Data System (ADS)

Alqasemi, Umar; Li, Hai; Aguirre, Andres; Zhu, Quing

2011-03-01

Co-registering ultrasound (US) and photoacoustic (PA) imaging is a logical extension to conventional ultrasound because both modalities provide complementary information of tumor morphology, tumor vasculature and hypoxia for cancer detection and characterization. In addition, both modalities are capable of providing real-time images for clinical applications. In this paper, a Field Programmable Gate Array (FPGA) and Digital Signal Processor (DSP) module-based real-time US/PA imaging system is presented. The system provides real-time US/PA data acquisition and image display for up to 5 fps* using the currently implemented DSP board. It can be upgraded to 15 fps, which is the maximum pulse repetition rate of the used laser, by implementing an advanced DSP module. Additionally, the photoacoustic RF data for each frame is saved for further off-line processing. The system frontend consists of eight 16-channel modules made of commercial and customized circuits. Each 16-channel module consists of two commercial 8-channel receiving circuitry boards and one FPGA board from Analog Devices. Each receiving board contains an IC† that combines. 8-channel low-noise amplifiers, variable-gain amplifiers, anti-aliasing filters, and ADC's‡ in a single chip with sampling frequency of 40MHz. The FPGA board captures the LVDSξ Double Data Rate (DDR) digital output of the receiving board and performs data conditioning and subbeamforming. A customized 16-channel transmission circuitry is connected to the two receiving boards for US pulseecho (PE) mode data acquisition. A DSP module uses External Memory Interface (EMIF) to interface with the eight 16-channel modules through a customized adaptor board. The DSP transfers either sub-beamformed data (US pulse-echo mode or PAI imaging mode) or raw data from FPGA boards to its DDR-2 memory through the EMIF link, then it performs additional processing, after that, it transfer the data to the PC** for further image processing. The PC code performs image processing including demodulation, beam envelope detection and scan conversion. Additionally, the PC code pre-calculates the delay coefficients used for transmission focusing and receiving dynamic focusing for different types of transducers to speed up the imaging process. To further speed up the imaging process, a multi-threads technique is implemented in order to allow formation of previous image frame data and acquisition of the next one simultaneously. The system is also capable of doing semi-real-time automated SO2 imaging at 10 seconds per frame by changing the wavelength knob of the laser automatically using a stepper motor controlled by the system. Initial in vivo experiments were performed on animal tumors to map out its vasculature and hypoxia level, which were superimposed on co-registered US images. The real-time system allows capturing co-registered US/PA images free of motion artifacts and also provides dynamitic information when contrast agents are used.

Evaluation of a hyperspectral image database for demosaicking purposes

NASA Astrophysics Data System (ADS)

Larabi, Mohamed-Chaker; Süsstrunk, Sabine

2011-01-01

We present a study on the the applicability of hyperspectral images to evaluate color filter array (CFA) design and the performance of demosaicking algorithms. The aim is to simulate a typical digital still camera processing pipe-line and to compare two different scenarios: evaluate the performance of demosaicking algorithms applied to raw camera RGB values before color rendering to sRGB, and evaluate the performance of demosaicking algorithms applied on the final sRGB color rendered image. The second scenario is the most frequently used one in literature because CFA design and algorithms are usually tested on a set of existing images that are already rendered, such as the Kodak Photo CD set containing the well-known lighthouse image. We simulate the camera processing pipe-line with measured spectral sensitivity functions of a real camera. Modeling a Bayer CFA, we select three linear demosaicking techniques in order to perform the tests. The evaluation is done using CMSE, CPSNR, s-CIELAB and MSSIM metrics to compare demosaicking results. We find that the performance, and especially the difference between demosaicking algorithms, is indeed significant depending if the mosaicking/demosaicking is applied to camera raw values as opposed to already rendered sRGB images. We argue that evaluating the former gives a better indication how a CFA/demosaicking combination will work in practice, and that it is in the interest of the community to create a hyperspectral image dataset dedicated to that effect.

SU-E-J-91: FFT Based Medical Image Registration Using a Graphics Processing Unit (GPU).

PubMed

Luce, J; Hoggarth, M; Lin, J; Block, A; Roeske, J

2012-06-01

To evaluate the efficiency gains obtained from using a Graphics Processing Unit (GPU) to perform a Fourier Transform (FT) based image registration. Fourier-based image registration involves obtaining the FT of the component images, and analyzing them in Fourier space to determine the translations and rotations of one image set relative to another. An important property of FT registration is that by enlarging the images (adding additional pixels), one can obtain translations and rotations with sub-pixel resolution. The expense, however, is an increased computational time. GPUs may decrease the computational time associated with FT image registration by taking advantage of their parallel architecture to perform matrix computations much more efficiently than a Central Processor Unit (CPU). In order to evaluate the computational gains produced by a GPU, images with known translational shifts were utilized. A program was written in the Interactive Data Language (IDL; Exelis, Boulder, CO) to performCPU-based calculations. Subsequently, the program was modified using GPU bindings (Tech-X, Boulder, CO) to perform GPU-based computation on the same system. Multiple image sizes were used, ranging from 256×256 to 2304×2304. The time required to complete the full algorithm by the CPU and GPU were benchmarked and the speed increase was defined as the ratio of the CPU-to-GPU computational time. The ratio of the CPU-to- GPU time was greater than 1.0 for all images, which indicates the GPU is performing the algorithm faster than the CPU. The smallest improvement, a 1.21 ratio, was found with the smallest image size of 256×256, and the largest speedup, a 4.25 ratio, was observed with the largest image size of 2304×2304. GPU programming resulted in a significant decrease in computational time associated with a FT image registration algorithm. The inclusion of the GPU may provide near real-time, sub-pixel registration capability. © 2012 American Association of Physicists in Medicine.

Automated method for the rapid and precise estimation of adherent cell culture characteristics from phase contrast microscopy images.

PubMed

Jaccard, Nicolas; Griffin, Lewis D; Keser, Ana; Macown, Rhys J; Super, Alexandre; Veraitch, Farlan S; Szita, Nicolas

2014-03-01

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license. © 2013 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

Automated Method for the Rapid and Precise Estimation of Adherent Cell Culture Characteristics from Phase Contrast Microscopy Images

PubMed Central

Jaccard, Nicolas; Griffin, Lewis D; Keser, Ana; Macown, Rhys J; Super, Alexandre; Veraitch, Farlan S; Szita, Nicolas

2014-01-01

The quantitative determination of key adherent cell culture characteristics such as confluency, morphology, and cell density is necessary for the evaluation of experimental outcomes and to provide a suitable basis for the establishment of robust cell culture protocols. Automated processing of images acquired using phase contrast microscopy (PCM), an imaging modality widely used for the visual inspection of adherent cell cultures, could enable the non-invasive determination of these characteristics. We present an image-processing approach that accurately detects cellular objects in PCM images through a combination of local contrast thresholding and post hoc correction of halo artifacts. The method was thoroughly validated using a variety of cell lines, microscope models and imaging conditions, demonstrating consistently high segmentation performance in all cases and very short processing times (<1 s per 1,208 × 960 pixels image). Based on the high segmentation performance, it was possible to precisely determine culture confluency, cell density, and the morphology of cellular objects, demonstrating the wide applicability of our algorithm for typical microscopy image processing pipelines. Furthermore, PCM image segmentation was used to facilitate the interpretation and analysis of fluorescence microscopy data, enabling the determination of temporal and spatial expression patterns of a fluorescent reporter. We created a software toolbox (PHANTAST) that bundles all the algorithms and provides an easy to use graphical user interface. Source-code for MATLAB and ImageJ is freely available under a permissive open-source license. Biotechnol. Bioeng. 2014;111: 504–517. © 2013 Wiley Periodicals, Inc. PMID:24037521

Image flows and one-liner graphical image representation.

PubMed

Makhervaks, Vadim; Barequet, Gill; Bruckstein, Alfred

2002-10-01

This paper introduces a novel graphical image representation consisting of a single curve-the one-liner. The first step of the algorithm involves the detection and ranking of image edges. A new edge exploration technique is used to perform both tasks simultaneously. This process is based on image flows. It uses a gradient vector field and a new operator to explore image edges. Estimation of the derivatives of the image is performed by using local Taylor expansions in conjunction with a weighted least-squares method. This process finds all the possible image edges without any pruning, and collects information that allows the edges found to be prioritized. This enables the most important edges to be selected to form a skeleton of the representation sought. The next step connects the selected edges into one continuous curve-the one-liner. It orders the selected edges and determines the curves connecting them. These two problems are solved separately. Since the abstract graph setting of the first problem is NP-complete, we reduce it to a variant of the traveling salesman problem and compute an approximate solution to it. We solve the second problem by using Dijkstra's shortest-path algorithm. The full software implementation for the entire one-liner determination process is available.

Watch your step! A frustrated total internal reflection approach to forensic footwear imaging

NASA Astrophysics Data System (ADS)

Needham, J. A.; Sharp, J. S.

2016-02-01

Forensic image retrieval and processing are vital tools in the fight against crime e.g. during fingerprint capture. However, despite recent advances in machine vision technology and image processing techniques (and contrary to the claims of popular fiction) forensic image retrieval is still widely being performed using outdated practices involving inkpads and paper. Ongoing changes in government policy, increasing crime rates and the reduction of forensic service budgets increasingly require that evidence be gathered and processed more rapidly and efficiently. A consequence of this is that new, low-cost imaging technologies are required to simultaneously increase the quality and throughput of the processing of evidence. This is particularly true in the burgeoning field of forensic footwear analysis, where images of shoe prints are being used to link individuals to crime scenes. Here we describe one such approach based upon frustrated total internal reflection imaging that can be used to acquire images of regions where shoes contact rigid surfaces.

Watch your step! A frustrated total internal reflection approach to forensic footwear imaging.

PubMed

Needham, J A; Sharp, J S

2016-02-16

Forensic image retrieval and processing are vital tools in the fight against crime e.g. during fingerprint capture. However, despite recent advances in machine vision technology and image processing techniques (and contrary to the claims of popular fiction) forensic image retrieval is still widely being performed using outdated practices involving inkpads and paper. Ongoing changes in government policy, increasing crime rates and the reduction of forensic service budgets increasingly require that evidence be gathered and processed more rapidly and efficiently. A consequence of this is that new, low-cost imaging technologies are required to simultaneously increase the quality and throughput of the processing of evidence. This is particularly true in the burgeoning field of forensic footwear analysis, where images of shoe prints are being used to link individuals to crime scenes. Here we describe one such approach based upon frustrated total internal reflection imaging that can be used to acquire images of regions where shoes contact rigid surfaces.

Using fuzzy fractal features of digital images for the material surface analisys

NASA Astrophysics Data System (ADS)

Privezentsev, D. G.; Zhiznyakov, A. L.; Astafiev, A. V.; Pugin, E. V.

2018-01-01

Edge detection is an important task in image processing. There are a lot of approaches in this area: Sobel, Canny operators and others. One of the perspective techniques in image processing is the use of fuzzy logic and fuzzy sets theory. They allow us to increase processing quality by representing information in its fuzzy form. Most of the existing fuzzy image processing methods switch to fuzzy sets on very late stages, so this leads to some useful information loss. In this paper, a novel method of edge detection based on fuzzy image representation and fuzzy pixels is proposed. With this approach, we convert the image to fuzzy form on the first step. Different approaches to this conversion are described. Several membership functions for fuzzy pixel description and requirements for their form and view are given. A novel approach to edge detection based on Sobel operator and fuzzy image representation is proposed. Experimental testing of developed method was performed on remote sensing images.

Research of real-time video processing system based on 6678 multi-core DSP

NASA Astrophysics Data System (ADS)

Li, Xiangzhen; Xie, Xiaodan; Yin, Xiaoqiang

2017-10-01

In the information age, the rapid development in the direction of intelligent video processing, complex algorithm proposed the powerful challenge on the performance of the processor. In this article, through the FPGA + TMS320C6678 frame structure, the image to fog, merge into an organic whole, to stabilize the image enhancement, its good real-time, superior performance, break through the traditional function of video processing system is simple, the product defects such as single, solved the video application in security monitoring, video, etc. Can give full play to the video monitoring effectiveness, improve enterprise economic benefits.

Corpus callosum segmentation using deep neural networks with prior information from multi-atlas images

NASA Astrophysics Data System (ADS)

Park, Gilsoon; Hong, Jinwoo; Lee, Jong-Min

2018-03-01

In human brain, Corpus Callosum (CC) is the largest white matter structure, connecting between right and left hemispheres. Structural features such as shape and size of CC in midsagittal plane are of great significance for analyzing various neurological diseases, for example Alzheimer's disease, autism and epilepsy. For quantitative and qualitative studies of CC in brain MR images, robust segmentation of CC is important. In this paper, we present a novel method for CC segmentation. Our approach is based on deep neural networks and the prior information generated from multi-atlas images. Deep neural networks have recently shown good performance in various image processing field. Convolutional neural networks (CNN) have shown outstanding performance for classification and segmentation in medical image fields. We used convolutional neural networks for CC segmentation. Multi-atlas based segmentation model have been widely used in medical image segmentation because atlas has powerful information about the target structure we want to segment, consisting of MR images and corresponding manual segmentation of the target structure. We combined the prior information, such as location and intensity distribution of target structure (i.e. CC), made from multi-atlas images in CNN training process for more improving training. The CNN with prior information showed better segmentation performance than without.

Stable image acquisition for mobile image processing applications

NASA Astrophysics Data System (ADS)

Henning, Kai-Fabian; Fritze, Alexander; Gillich, Eugen; Mönks, Uwe; Lohweg, Volker

2015-02-01

Today, mobile devices (smartphones, tablets, etc.) are widespread and of high importance for their users. Their performance as well as versatility increases over time. This leads to the opportunity to use such devices for more specific tasks like image processing in an industrial context. For the analysis of images requirements like image quality (blur, illumination, etc.) as well as a defined relative position of the object to be inspected are crucial. Since mobile devices are handheld and used in constantly changing environments the challenge is to fulfill these requirements. We present an approach to overcome the obstacles and stabilize the image capturing process such that image analysis becomes significantly improved on mobile devices. Therefore, image processing methods are combined with sensor fusion concepts. The approach consists of three main parts. First, pose estimation methods are used to guide a user moving the device to a defined position. Second, the sensors data and the pose information are combined for relative motion estimation. Finally, the image capturing process is automated. It is triggered depending on the alignment of the device and the object as well as the image quality that can be achieved under consideration of motion and environmental effects.

Digital image processing using parallel computing based on CUDA technology

NASA Astrophysics Data System (ADS)

Skirnevskiy, I. P.; Pustovit, A. V.; Abdrashitova, M. O.

2017-01-01

This article describes expediency of using a graphics processing unit (GPU) in big data processing in the context of digital images processing. It provides a short description of a parallel computing technology and its usage in different areas, definition of the image noise and a brief overview of some noise removal algorithms. It also describes some basic requirements that should be met by certain noise removal algorithm in the projection to computer tomography. It provides comparison of the performance with and without using GPU as well as with different percentage of using CPU and GPU.

Bit error rate performance of Image Processing Facility high density tape recorders

NASA Technical Reports Server (NTRS)

Heffner, P.

1981-01-01

The Image Processing Facility at the NASA/Goddard Space Flight Center uses High Density Tape Recorders (HDTR's) to transfer high volume image data and ancillary information from one system to another. For ancillary information, it is required that very low bit error rates (BER's) accompany the transfers. The facility processes about 10 to the 11th bits of image data per day from many sensors, involving 15 independent processing systems requiring the use of HDTR's. When acquired, the 16 HDTR's offered state-of-the-art performance of 1 x 10 to the -6th BER as specified. The BER requirement was later upgraded in two steps: (1) incorporating data randomizing circuitry to yield a BER of 2 x 10 to the -7th and (2) further modifying to include a bit error correction capability to attain a BER of 2 x 10 to the -9th. The total improvement factor was 500 to 1. Attention is given here to the background, technical approach, and final results of these modifications. Also discussed are the format of the data recorded by the HDTR, the magnetic tape format, the magnetic tape dropout characteristics as experienced in the Image Processing Facility, the head life history, and the reliability of the HDTR's.

Smartphones as image processing systems for prosthetic vision.

PubMed

Zapf, Marc P; Matteucci, Paul B; Lovell, Nigel H; Suaning, Gregg J

2013-01-01

The feasibility of implants for prosthetic vision has been demonstrated by research and commercial organizations. In most devices, an essential forerunner to the internal stimulation circuit is an external electronics solution for capturing, processing and relaying image information as well as extracting useful features from the scene surrounding the patient. The capabilities and multitude of image processing algorithms that can be performed by the device in real-time plays a major part in the final quality of the prosthetic vision. It is therefore optimal to use powerful hardware yet to avoid bulky, straining solutions. Recent publications have reported of portable single-board computers fast enough for computationally intensive image processing. Following the rapid evolution of commercial, ultra-portable ARM (Advanced RISC machine) mobile devices, the authors investigated the feasibility of modern smartphones running complex face detection as external processing devices for vision implants. The role of dedicated graphics processors in speeding up computation was evaluated while performing a demanding noise reduction algorithm (image denoising). The time required for face detection was found to decrease by 95% from 2.5 year old to recent devices. In denoising, graphics acceleration played a major role, speeding up denoising by a factor of 18. These results demonstrate that the technology has matured sufficiently to be considered as a valid external electronics platform for visual prosthetic research.

Calibration-free quantification of interior properties of porous media with x-ray computed tomography.

PubMed

Hussein, Esam M A; Agbogun, H M D; Al, Tom A

2015-03-01

A method is presented for interpreting the values of x-ray attenuation coefficients reconstructed in computed tomography of porous media, while overcoming the ambiguity caused by the multichromatic nature of x-rays, dilution by void, and material heterogeneity. The method enables determination of porosity without relying on calibration or image segmentation or thresholding to discriminate pores from solid material. It distinguishes between solution-accessible and inaccessible pores, and provides the spatial and frequency distributions of solid-matrix material in a heterogeneous medium. This is accomplished by matching an image of a sample saturated with a contrast solution with that saturated with a transparent solution. Voxels occupied with solid-material and inaccessible pores are identified by the fact that they maintain the same location and image attributes in both images, with voxels containing inaccessible pores appearing empty in both images. Fully porous and accessible voxels exhibit the maximum contrast, while the rest are porous voxels containing mixtures of pore solutions and solid. This matching process is performed with an image registration computer code, and image processing software that requires only simple subtraction and multiplication (scaling) processes. The process is demonstrated in dolomite (non-uniform void distribution, homogeneous solid matrix) and sandstone (nearly uniform void distribution, heterogeneous solid matrix) samples, and its overall performance is shown to compare favorably with a method based on calibration and thresholding. Copyright © 2014 Elsevier Ltd. All rights reserved.

Man-machine interactive imaging and data processing using high-speed digital mass storage

NASA Technical Reports Server (NTRS)

Alsberg, H.; Nathan, R.

1975-01-01

The role of vision in teleoperation has been recognized as an important element in the man-machine control loop. In most applications of remote manipulation, direct vision cannot be used. To overcome this handicap, the human operator's control capabilities are augmented by a television system. This medium provides a practical and useful link between workspace and the control station from which the operator perform his tasks. Human performance deteriorates when the images are degraded as a result of instrumental and transmission limitations. Image enhancement is used to bring out selected qualities in a picture to increase the perception of the observer. A general purpose digital computer, an extensive special purpose software system is used to perform an almost unlimited repertoire of processing operations.

Karyotyping human chromosomes by optical and x-ray ptychography methods

DOE PAGES

Shemilt, Laura; Verbanis, Ephanielle; Schwenke, Joerg; ...

2015-02-01

Sorting and identifying chromosomes, a process known as karyotyping, is widely used to detect changes in chromosome shapes and gene positions. In a karyotype the chromosomes are identified by their size and therefore this process can be performed by measuring macroscopic structural variables. Chromosomes contain a specific number of basepairs that linearly correlate with their size; therefore, it is possible to perform a karyotype on chromosomes using their mass as an identifying factor. Here, we obtain the first images, to our knowledge, of chromosomes using the novel imaging method of ptychography. We can use the images to measure the massmore » of chromosomes and perform a partial karyotype from the results. Lastly, we also obtain high spatial resolution using this technique with synchrotron source x-rays.« less

Karyotyping human chromosomes by optical and x-ray ptychography methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shemilt, Laura; Verbanis, Ephanielle; Schwenke, Joerg

Sorting and identifying chromosomes, a process known as karyotyping, is widely used to detect changes in chromosome shapes and gene positions. In a karyotype the chromosomes are identified by their size and therefore this process can be performed by measuring macroscopic structural variables. Chromosomes contain a specific number of basepairs that linearly correlate with their size; therefore, it is possible to perform a karyotype on chromosomes using their mass as an identifying factor. Here, we obtain the first images, to our knowledge, of chromosomes using the novel imaging method of ptychography. We can use the images to measure the massmore » of chromosomes and perform a partial karyotype from the results. Lastly, we also obtain high spatial resolution using this technique with synchrotron source x-rays.« less

iMAGE cloud: medical image processing as a service for regional healthcare in a hybrid cloud environment.

PubMed

Liu, Li; Chen, Weiping; Nie, Min; Zhang, Fengjuan; Wang, Yu; He, Ailing; Wang, Xiaonan; Yan, Gen

2016-11-01

To handle the emergence of the regional healthcare ecosystem, physicians and surgeons in various departments and healthcare institutions must process medical images securely, conveniently, and efficiently, and must integrate them with electronic medical records (EMRs). In this manuscript, we propose a software as a service (SaaS) cloud called the iMAGE cloud. A three-layer hybrid cloud was created to provide medical image processing services in the smart city of Wuxi, China, in April 2015. In the first step, medical images and EMR data were received and integrated via the hybrid regional healthcare network. Then, traditional and advanced image processing functions were proposed and computed in a unified manner in the high-performance cloud units. Finally, the image processing results were delivered to regional users using the virtual desktop infrastructure (VDI) technology. Security infrastructure was also taken into consideration. Integrated information query and many advanced medical image processing functions-such as coronary extraction, pulmonary reconstruction, vascular extraction, intelligent detection of pulmonary nodules, image fusion, and 3D printing-were available to local physicians and surgeons in various departments and healthcare institutions. Implementation results indicate that the iMAGE cloud can provide convenient, efficient, compatible, and secure medical image processing services in regional healthcare networks. The iMAGE cloud has been proven to be valuable in applications in the regional healthcare system, and it could have a promising future in the healthcare system worldwide.

21 CFR 892.2050 - Picture archiving and communications system.

Code of Federal Regulations, 2014 CFR

2014-04-01

... processing of medical images. Its hardware components may include workstations, digitizers, communications... hardcopy devices. The software components may provide functions for performing operations related to image...

21 CFR 892.2050 - Picture archiving and communications system.

Code of Federal Regulations, 2011 CFR

2011-04-01

... processing of medical images. Its hardware components may include workstations, digitizers, communications... hardcopy devices. The software components may provide functions for performing operations related to image...

21 CFR 892.2050 - Picture archiving and communications system.

Code of Federal Regulations, 2012 CFR

2012-04-01

... processing of medical images. Its hardware components may include workstations, digitizers, communications... hardcopy devices. The software components may provide functions for performing operations related to image...

21 CFR 892.2050 - Picture archiving and communications system.

Code of Federal Regulations, 2013 CFR

2013-04-01

... processing of medical images. Its hardware components may include workstations, digitizers, communications... hardcopy devices. The software components may provide functions for performing operations related to image...

Effect of software manipulation (Photoshop) of digitised retinal images on the grading of diabetic retinopathy.

PubMed

George, L D; Lusty, J; Owens, D R; Ollerton, R L

1999-08-01

To determine whether software processing of digitised retinal images using a "sharpen" filter improves the ability to grade diabetic retinopathy. 150 macula centred retinal images were taken as 35 mm colour transparencies representing a spectrum of diabetic retinopathy, digitised, and graded in random order before and after the application of a sharpen filter (Adobe Photoshop). Digital enhancement of contrast and brightness was performed and a X2 digital zoom was utilised. The grades from the unenhanced and enhanced digitised images were compared with the same retinal fields viewed as slides. Overall agreement in retinopathy grade from the digitised images improved from 83.3% (125/150) to 94.0% (141/150) with sight threatening diabetic retinopathy (STDR) correctly identified in 95.5% (84/88) and 98.9% (87/88) of cases when using unenhanced and enhanced images respectively. In total, five images were overgraded and four undergraded from the enhanced images compared with 17 and eight images respectively when using unenhanced images. This study demonstrates that the already good agreement in grading performance can be further improved by software manipulation or processing of digitised retinal images.

Effect of software manipulation (Photoshop) of digitised retinal images on the grading of diabetic retinopathy

PubMed Central

George, L; Lusty, J; Owens, D; Ollerton, R

1999-01-01

AIMS—To determine whether software processing of digitised retinal images using a "sharpen" filter improves the ability to grade diabetic retinopathy.
METHODS—150 macula centred retinal images were taken as 35 mm colour transparencies representing a spectrum of diabetic retinopathy, digitised, and graded in random order before and after the application of a sharpen filter (Adobe Photoshop). Digital enhancement of contrast and brightness was performed and a X2 digital zoom was utilised. The grades from the unenhanced and enhanced digitised images were compared with the same retinal fields viewed as slides.
RESULTS—Overall agreement in retinopathy grade from the digitised images improved from 83.3% (125/150) to 94.0% (141/150) with sight threatening diabetic retinopathy (STDR) correctly identified in 95.5% (84/88) and 98.9% (87/88) of cases when using unenhanced and enhanced images respectively. In total, five images were overgraded and four undergraded from the enhanced images compared with 17 and eight images respectively when using unenhanced images.
CONCLUSION—This study demonstrates that the already good agreement in grading performance can be further improved by software manipulation or processing of digitised retinal images.

 PMID:10413691

GaAs Supercomputing: Architecture, Language, And Algorithms For Image Processing

NASA Astrophysics Data System (ADS)

Johl, John T.; Baker, Nick C.

1988-10-01

The application of high-speed GaAs processors in a parallel system matches the demanding computational requirements of image processing. The architecture of the McDonnell Douglas Astronautics Company (MDAC) vector processor is described along with the algorithms and language translator. Most image and signal processing algorithms can utilize parallel processing and show a significant performance improvement over sequential versions. The parallelization performed by this system is within each vector instruction. Since each vector has many elements, each requiring some computation, useful concurrent arithmetic operations can easily be performed. Balancing the memory bandwidth with the computation rate of the processors is an important design consideration for high efficiency and utilization. The architecture features a bus-based execution unit consisting of four to eight 32-bit GaAs RISC microprocessors running at a 200 MHz clock rate for a peak performance of 1.6 BOPS. The execution unit is connected to a vector memory with three buses capable of transferring two input words and one output word every 10 nsec. The address generators inside the vector memory perform different vector addressing modes and feed the data to the execution unit. The functions discussed in this paper include basic MATRIX OPERATIONS, 2-D SPATIAL CONVOLUTION, HISTOGRAM, and FFT. For each of these algorithms, assembly language programs were run on a behavioral model of the system to obtain performance figures.

High performance embedded system for real-time pattern matching

NASA Astrophysics Data System (ADS)

Sotiropoulou, C.-L.; Luciano, P.; Gkaitatzis, S.; Citraro, S.; Giannetti, P.; Dell'Orso, M.

2017-02-01

In this paper we present an innovative and high performance embedded system for real-time pattern matching. This system is based on the evolution of hardware and algorithms developed for the field of High Energy Physics and more specifically for the execution of extremely fast pattern matching for tracking of particles produced by proton-proton collisions in hadron collider experiments. A miniaturized version of this complex system is being developed for pattern matching in generic image processing applications. The system works as a contour identifier able to extract the salient features of an image. It is based on the principles of cognitive image processing, which means that it executes fast pattern matching and data reduction mimicking the operation of the human brain. The pattern matching can be executed by a custom designed Associative Memory chip. The reference patterns are chosen by a complex training algorithm implemented on an FPGA device. Post processing algorithms (e.g. pixel clustering) are also implemented on the FPGA. The pattern matching can be executed on a 2D or 3D space, on black and white or grayscale images, depending on the application and thus increasing exponentially the processing requirements of the system. We present the firmware implementation of the training and pattern matching algorithm, performance and results on a latest generation Xilinx Kintex Ultrascale FPGA device.

Particle sizing in rocket motor studies utilizing hologram image processing

NASA Technical Reports Server (NTRS)

Netzer, David; Powers, John

1987-01-01

A technique of obtaining particle size information from holograms of combustion products is described. The holograms are obtained with a pulsed ruby laser through windows in a combustion chamber. The reconstruction is done with a krypton laser with the real image being viewed through a microscope. The particle size information is measured with a Quantimet 720 image processing system which can discriminate various features and perform measurements of the portions of interest in the image. Various problems that arise in the technique are discussed, especially those that are a consequence of the speckle due to the diffuse illumination used in the recording process.

Digital Imaging

NASA Technical Reports Server (NTRS)

1986-01-01

Digital Imaging is the computer processed numerical representation of physical images. Enhancement of images results in easier interpretation. Quantitative digital image analysis by Perceptive Scientific Instruments, locates objects within an image and measures them to extract quantitative information. Applications are CAT scanners, radiography, microscopy in medicine as well as various industrial and manufacturing uses. The PSICOM 327 performs all digital image analysis functions. It is based on Jet Propulsion Laboratory technology, is accurate and cost efficient.

Optical Processing of Speckle Images with Bacteriorhodopsin for Pattern Recognition

NASA Technical Reports Server (NTRS)

Downie, John D.; Tucker, Deanne (Technical Monitor)

1994-01-01

Logarithmic processing of images with multiplicative noise characteristics can be utilized to transform the image into one with an additive noise distribution. This simplifies subsequent image processing steps for applications such as image restoration or correlation for pattern recognition. One particularly common form of multiplicative noise is speckle, for which the logarithmic operation not only produces additive noise, but also makes it of constant variance (signal-independent). We examine the optical transmission properties of some bacteriorhodopsin films here and find them well suited to implement such a pointwise logarithmic transformation optically in a parallel fashion. We present experimental results of the optical conversion of speckle images into transformed images with additive, signal-independent noise statistics using the real-time photochromic properties of bacteriorhodopsin. We provide an example of improved correlation performance in terms of correlation peak signal-to-noise for such a transformed speckle image.

Use of discrete chromatic space to tune the image tone in a color image mosaic

NASA Astrophysics Data System (ADS)

Zhang, Zuxun; Li, Zhijiang; Zhang, Jianqing; Zheng, Li

2003-09-01

Color image process is a very important problem. However, the main approach presently of them is to transfer RGB colour space into another colour space, such as HIS (Hue, Intensity and Saturation). YIQ, LUV and so on. Virutally, it may not be a valid way to process colour airborne image just in one colour space. Because the electromagnetic wave is physically altered in every wave band, while the color image is perceived based on psychology vision. Therefore, it's necessary to propose an approach accord with physical transformation and psychological perception. Then, an analysis on how to use relative colour spaces to process colour airborne photo is discussed and an application on how to tune the image tone in colour airborne image mosaic is introduced. As a practice, a complete approach to perform the mosaic on color airborne images via taking full advantage of relative color spaces is discussed in the application.

Corner-point criterion for assessing nonlinear image processing imagers

NASA Astrophysics Data System (ADS)

Landeau, Stéphane; Pigois, Laurent; Foing, Jean-Paul; Deshors, Gilles; Swiathy, Greggory

2017-10-01

Range performance modeling of optronics imagers attempts to characterize the ability to resolve details in the image. Today, digital image processing is systematically used in conjunction with the optoelectronic system to correct its defects or to exploit tiny detection signals to increase performance. In order to characterize these processing having adaptive and non-linear properties, it becomes necessary to stimulate the imagers with test patterns whose properties are similar to the actual scene image ones, in terms of dynamic range, contours, texture and singular points. This paper presents an approach based on a Corner-Point (CP) resolution criterion, derived from the Probability of Correct Resolution (PCR) of binary fractal patterns. The fundamental principle lies in the respectful perception of the CP direction of one pixel minority value among the majority value of a 2×2 pixels block. The evaluation procedure considers the actual image as its multi-resolution CP transformation, taking the role of Ground Truth (GT). After a spatial registration between the degraded image and the original one, the degradation is statistically measured by comparing the GT with the degraded image CP transformation, in terms of localized PCR at the region of interest. The paper defines this CP criterion and presents the developed evaluation techniques, such as the measurement of the number of CP resolved on the target, the transformation CP and its inverse transform that make it possible to reconstruct an image of the perceived CPs. Then, this criterion is compared with the standard Johnson criterion, in the case of a linear blur and noise degradation. The evaluation of an imaging system integrating an image display and a visual perception is considered, by proposing an analysis scheme combining two methods: a CP measurement for the highly non-linear part (imaging) with real signature test target and conventional methods for the more linear part (displaying). The application to color imaging is proposed, with a discussion about the choice of the working color space depending on the type of image enhancement processing used.

Visually enhanced CCTV digital surveillance utilizing Intranet and Internet.

PubMed

Ozaki, Nobuyuki

2002-07-01

This paper describes a solution for integrated plant supervision utilizing closed circuit television (CCTV) digital surveillance. Three basic requirements are first addressed as the platform of the system, with discussion on the suitable video compression. The system configuration is described in blocks. The system provides surveillance functionality: real-time monitoring, and process analysis functionality: a troubleshooting tool. This paper describes the formulation of practical performance design for determining various encoder parameters. It also introduces image processing techniques for enhancing the original CCTV digital image to lessen the burden on operators. Some screenshots are listed for the surveillance functionality. For the process analysis, an image searching filter supported by image processing techniques is explained with screenshots. Multimedia surveillance, which is the merger with process data surveillance, or the SCADA system, is also explained.

Acousto-optic time- and space-integrating spotlight-mode SAR processor

NASA Astrophysics Data System (ADS)

Haney, Michael W.; Levy, James J.; Michael, Robert R., Jr.

1993-09-01

The technical approach and recent experimental results for the acousto-optic time- and space- integrating real-time SAR image formation processor program are reported. The concept overcomes the size and power consumption limitations of electronic approaches by using compact, rugged, and low-power analog optical signal processing techniques for the most computationally taxing portions of the SAR imaging problem. Flexibility and performance are maintained by the use of digital electronics for the critical low-complexity filter generation and output image processing functions. The results include a demonstration of the processor's ability to perform high-resolution spotlight-mode SAR imaging by simultaneously compensating for range migration and range/azimuth coupling in the analog optical domain, thereby avoiding a highly power-consuming digital interpolation or reformatting operation usually required in all-electronic approaches.

High-performance web viewer for cardiac images

NASA Astrophysics Data System (ADS)

dos Santos, Marcelo; Furuie, Sergio S.

2004-04-01

With the advent of the digital devices for medical diagnosis the use of the regular films in radiology has decreased. Thus, the management and handling of medical images in digital format has become an important and critical task. In Cardiology, for example, the main difficulty is to display dynamic images with the appropriated color palette and frame rate used on acquisition process by Cath, Angio and Echo systems. In addition, other difficulty is handling large images in memory by any existing personal computer, including thin clients. In this work we present a web-based application that carries out these tasks with robustness and excellent performance, without burdening the server and network. This application provides near-diagnostic quality display of cardiac images stored as DICOM 3.0 files via a web browser and provides a set of resources that allows the viewing of still and dynamic images. It can access image files from the local disks, or network connection. Its features include: allows real-time playback, dynamic thumbnails image viewing during loading, access to patient database information, image processing tools, linear and angular measurements, on-screen annotations, image printing and exporting DICOM images to other image formats, and many others, all characterized by a pleasant user-friendly interface, inside a Web browser by means of a Java application. This approach offers some advantages over the most of medical images viewers, such as: facility of installation, integration with other systems by means of public and standardized interfaces, platform independence, efficient manipulation and display of medical images, all with high performance.

Research based on the SoPC platform of feature-based image registration

NASA Astrophysics Data System (ADS)

Shi, Yue-dong; Wang, Zhi-hui

2015-12-01

This paper focuses on the study of implementing feature-based image registration by System on a Programmable Chip (SoPC) hardware platform. We solidify the image registration algorithm on the FPGA chip, in which embedded soft core processor Nios II can speed up the image processing system. In this way, we can make image registration technology get rid of the PC. And, consequently, this kind of technology will be got an extensive use. The experiment result indicates that our system shows stable performance, particularly in terms of matching processing which noise immunity is good. And feature points of images show a reasonable distribution.

An Approach for Stitching Satellite Images in a Bigdata Mapreduce Framework

NASA Astrophysics Data System (ADS)

Sarı, H.; Eken, S.; Sayar, A.

2017-11-01

In this study we present a two-step map/reduce framework to stitch satellite mosaic images. The proposed system enable recognition and extraction of objects whose parts falling in separate satellite mosaic images. However this is a time and resource consuming process. The major aim of the study is improving the performance of the image stitching processes by utilizing big data framework. To realize this, we first convert the images into bitmaps (first mapper) and then String formats in the forms of 255s and 0s (second mapper), and finally, find the best possible matching position of the images by a reduce function.

A new automated assessment method for contrast-detail images by applying support vector machine and its robustness to nonlinear image processing.

PubMed

Takei, Takaaki; Ikeda, Mitsuru; Imai, Kuniharu; Yamauchi-Kawaura, Chiyo; Kato, Katsuhiko; Isoda, Haruo

2013-09-01

The automated contrast-detail (C-D) analysis methods developed so-far cannot be expected to work well on images processed with nonlinear methods, such as noise reduction methods. Therefore, we have devised a new automated C-D analysis method by applying support vector machine (SVM), and tested for its robustness to nonlinear image processing. We acquired the CDRAD (a commercially available C-D test object) images at a tube voltage of 120 kV and a milliampere-second product (mAs) of 0.5-5.0. A partial diffusion equation based technique was used as noise reduction method. Three radiologists and three university students participated in the observer performance study. The training data for our SVM method was the classification data scored by the one radiologist for the CDRAD images acquired at 1.6 and 3.2 mAs and their noise-reduced images. We also compared the performance of our SVM method with the CDRAD Analyser algorithm. The mean C-D diagrams (that is a plot of the mean of the smallest visible hole diameter vs. hole depth) obtained from our devised SVM method agreed well with the ones averaged across the six human observers for both original and noise-reduced CDRAD images, whereas the mean C-D diagrams from the CDRAD Analyser algorithm disagreed with the ones from the human observers for both original and noise-reduced CDRAD images. In conclusion, our proposed SVM method for C-D analysis will work well for the images processed with the non-linear noise reduction method as well as for the original radiographic images.

Effects of image processing on the detective quantum efficiency

NASA Astrophysics Data System (ADS)

Park, Hye-Suk; Kim, Hee-Joung; Cho, Hyo-Min; Lee, Chang-Lae; Lee, Seung-Wan; Choi, Yu-Na

2010-04-01

Digital radiography has gained popularity in many areas of clinical practice. This transition brings interest in advancing the methodologies for image quality characterization. However, as the methodologies for such characterizations have not been standardized, the results of these studies cannot be directly compared. The primary objective of this study was to standardize methodologies for image quality characterization. The secondary objective was to evaluate affected factors to Modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE) according to image processing algorithm. Image performance parameters such as MTF, NPS, and DQE were evaluated using the international electro-technical commission (IEC 62220-1)-defined RQA5 radiographic techniques. Computed radiography (CR) images of hand posterior-anterior (PA) for measuring signal to noise ratio (SNR), slit image for measuring MTF, white image for measuring NPS were obtained and various Multi-Scale Image Contrast Amplification (MUSICA) parameters were applied to each of acquired images. In results, all of modified images were considerably influence on evaluating SNR, MTF, NPS, and DQE. Modified images by the post-processing had higher DQE than the MUSICA=0 image. This suggests that MUSICA values, as a post-processing, have an affect on the image when it is evaluating for image quality. In conclusion, the control parameters of image processing could be accounted for evaluating characterization of image quality in same way. The results of this study could be guided as a baseline to evaluate imaging systems and their imaging characteristics by measuring MTF, NPS, and DQE.

Smart CMOS image sensor for lightning detection and imaging.

PubMed

Rolando, Sébastien; Goiffon, Vincent; Magnan, Pierre; Corbière, Franck; Molina, Romain; Tulet, Michel; Bréart-de-Boisanger, Michel; Saint-Pé, Olivier; Guiry, Saïprasad; Larnaudie, Franck; Leone, Bruno; Perez-Cuevas, Leticia; Zayer, Igor

2013-03-01

We present a CMOS image sensor dedicated to lightning detection and imaging. The detector has been designed to evaluate the potentiality of an on-chip lightning detection solution based on a smart sensor. This evaluation is performed in the frame of the predevelopment phase of the lightning detector that will be implemented in the Meteosat Third Generation Imager satellite for the European Space Agency. The lightning detection process is performed by a smart detector combining an in-pixel frame-to-frame difference comparison with an adjustable threshold and on-chip digital processing allowing an efficient localization of a faint lightning pulse on the entire large format array at a frequency of 1 kHz. A CMOS prototype sensor with a 256×256 pixel array and a 60 μm pixel pitch has been fabricated using a 0.35 μm 2P 5M technology and tested to validate the selected detection approach.

Use of laser range finders and range image analysis in automated assembly tasks

NASA Technical Reports Server (NTRS)

Alvertos, Nicolas; Dcunha, Ivan

1990-01-01

A proposition to study the effect of filtering processes on range images and to evaluate the performance of two different laser range mappers is made. Median filtering was utilized to remove noise from the range images. First and second order derivatives are then utilized to locate the similarities and dissimilarities between the processed and the original images. Range depth information is converted into spatial coordinates, and a set of coefficients which describe 3-D objects is generated using the algorithm developed in the second phase of this research. Range images of spheres and cylinders are used for experimental purposes. An algorithm was developed to compare the performance of two different laser range mappers based upon the range depth information of surfaces generated by each of the mappers. Furthermore, an approach based on 2-D analytic geometry is also proposed which serves as a basis for the recognition of regular 3-D geometric objects.

Fluorescent screens and image processing for the APS linac test stand

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berg, W.; Ko, K.

A fluorescent screen was used to monitor relative beam position and spot size of a 56-MeV electron beam in the linac test stand. A chromium doped alumina ceramic screen inserted into the beam was monitored by a video camera. The resulting image was captured using a frame grabber and stored into memory. Reconstruction and analysis of the stored image was performed using PV-WAVE. This paper will discuss the hardware and software implementation of the fluorescent screen and imaging system. Proposed improvements for the APS linac fluorescent screens and image processing will also be discussed.

A fast and fully automatic registration approach based on point features for multi-source remote-sensing images

NASA Astrophysics Data System (ADS)

Yu, Le; Zhang, Dengrong; Holden, Eun-Jung

2008-07-01

Automatic registration of multi-source remote-sensing images is a difficult task as it must deal with the varying illuminations and resolutions of the images, different perspectives and the local deformations within the images. This paper proposes a fully automatic and fast non-rigid image registration technique that addresses those issues. The proposed technique performs a pre-registration process that coarsely aligns the input image to the reference image by automatically detecting their matching points by using the scale invariant feature transform (SIFT) method and an affine transformation model. Once the coarse registration is completed, it performs a fine-scale registration process based on a piecewise linear transformation technique using feature points that are detected by the Harris corner detector. The registration process firstly finds in succession, tie point pairs between the input and the reference image by detecting Harris corners and applying a cross-matching strategy based on a wavelet pyramid for a fast search speed. Tie point pairs with large errors are pruned by an error-checking step. The input image is then rectified by using triangulated irregular networks (TINs) to deal with irregular local deformations caused by the fluctuation of the terrain. For each triangular facet of the TIN, affine transformations are estimated and applied for rectification. Experiments with Quickbird, SPOT5, SPOT4, TM remote-sensing images of the Hangzhou area in China demonstrate the efficiency and the accuracy of the proposed technique for multi-source remote-sensing image registration.

Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

NASA Astrophysics Data System (ADS)

Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

2010-02-01

Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

Predicting cotton yield of small field plots in a cotton breeding program using UAV imagery data

NASA Astrophysics Data System (ADS)

Maja, Joe Mari J.; Campbell, Todd; Camargo Neto, Joao; Astillo, Philip

2016-05-01

One of the major criteria used for advancing experimental lines in a breeding program is yield performance. Obtaining yield performance data requires machine picking each plot with a cotton picker, modified to weigh individual plots. Harvesting thousands of small field plots requires a great deal of time and resources. The efficiency of cotton breeding could be increased significantly while the cost could be decreased with the availability of accurate methods to predict yield performance. This work is investigating the feasibility of using an image processing technique using a commercial off-the-shelf (COTS) camera mounted on a small Unmanned Aerial Vehicle (sUAV) to collect normal RGB images in predicting cotton yield on small plot. An orthonormal image was generated from multiple images and used to process multiple, segmented plots. A Gaussian blur was used to eliminate the high frequency component of the images, which corresponds to the cotton pixels, and used image subtraction technique to generate high frequency pixel images. The cotton pixels were then separated using k-means cluster with 5 classes. Based on the current work, the calculated percentage cotton area was computed using the generated high frequency image (cotton pixels) divided by the total area of the plot. Preliminary results showed (five flights, 3 altitudes) that cotton cover on multiple pre-selected 227 sq. m. plots produce an average of 8% which translate to approximately 22.3 kgs. of cotton. The yield prediction equation generated from the test site was then use on a separate validation site and produced a prediction error of less than 10%. In summary, the results indicate that a COTS camera with an appropriate image processing technique can produce results that are comparable to expensive sensors.

Application of an enhanced fuzzy algorithm for MR brain tumor image segmentation

NASA Astrophysics Data System (ADS)

Hemanth, D. Jude; Vijila, C. Kezi Selva; Anitha, J.

2010-02-01

Image segmentation is one of the significant digital image processing techniques commonly used in the medical field. One of the specific applications is tumor detection in abnormal Magnetic Resonance (MR) brain images. Fuzzy approaches are widely preferred for tumor segmentation which generally yields superior results in terms of accuracy. But most of the fuzzy algorithms suffer from the drawback of slow convergence rate which makes the system practically non-feasible. In this work, the application of modified Fuzzy C-means (FCM) algorithm to tackle the convergence problem is explored in the context of brain image segmentation. This modified FCM algorithm employs the concept of quantization to improve the convergence rate besides yielding excellent segmentation efficiency. This algorithm is experimented on real time abnormal MR brain images collected from the radiologists. A comprehensive feature vector is extracted from these images and used for the segmentation technique. An extensive feature selection process is performed which reduces the convergence time period and improve the segmentation efficiency. After segmentation, the tumor portion is extracted from the segmented image. Comparative analysis in terms of segmentation efficiency and convergence rate is performed between the conventional FCM and the modified FCM. Experimental results show superior results for the modified FCM algorithm in terms of the performance measures. Thus, this work highlights the application of the modified algorithm for brain tumor detection in abnormal MR brain images.

Bit-level plane image encryption based on coupled map lattice with time-varying delay

NASA Astrophysics Data System (ADS)

Lv, Xiupin; Liao, Xiaofeng; Yang, Bo

2018-04-01

Most of the existing image encryption algorithms had two basic properties: confusion and diffusion in a pixel-level plane based on various chaotic systems. Actually, permutation in a pixel-level plane could not change the statistical characteristics of an image, and many of the existing color image encryption schemes utilized the same method to encrypt R, G and B components, which means that the three color components of a color image are processed three times independently. Additionally, dynamical performance of a single chaotic system degrades greatly with finite precisions in computer simulations. In this paper, a novel coupled map lattice with time-varying delay therefore is applied in color images bit-level plane encryption to solve the above issues. Spatiotemporal chaotic system with both much longer period in digitalization and much excellent performances in cryptography is recommended. Time-varying delay embedded in coupled map lattice enhances dynamical behaviors of the system. Bit-level plane image encryption algorithm has greatly reduced the statistical characteristics of an image through the scrambling processing. The R, G and B components cross and mix with one another, which reduces the correlation among the three components. Finally, simulations are carried out and all the experimental results illustrate that the proposed image encryption algorithm is highly secure, and at the same time, also demonstrates superior performance.

A new method of cardiographic image segmentation based on grammar

NASA Astrophysics Data System (ADS)

Hamdi, Salah; Ben Abdallah, Asma; Bedoui, Mohamed H.; Alimi, Adel M.

2011-10-01

The measurement of the most common ultrasound parameters, such as aortic area, mitral area and left ventricle (LV) volume, requires the delineation of the organ in order to estimate the area. In terms of medical image processing this translates into the need to segment the image and define the contours as accurately as possible. The aim of this work is to segment an image and make an automated area estimation based on grammar. The entity "language" will be projected to the entity "image" to perform structural analysis and parsing of the image. We will show how the idea of segmentation and grammar-based area estimation is applied to real problems of cardio-graphic image processing.

Strength of Perceptual Experience Predicts Word Processing Performance Better than Concreteness or Imageability

ERIC Educational Resources Information Center

Connell, Louise; Lynott, Dermot

2012-01-01

Abstract concepts are traditionally thought to differ from concrete concepts by their lack of perceptual information, which causes them to be processed more slowly and less accurately than perceptually-based concrete concepts. In two studies, we examined this assumption by comparing concreteness and imageability ratings to a set of perceptual…

Display management subsystem, version 1: A user's eye view

NASA Technical Reports Server (NTRS)

Parker, Dolores

1986-01-01

The structure and application functions of the Display Management Subsystem (DMS) are described. The DMS, a subsystem of the Transportable Applications Executive (TAE), was designed to provide a device-independent interface for an image processing and display environment. The system is callable by C and FORTRAN applications, portable to accommodate different image analysis terminals, and easily expandable to meet local needs. Generic applications are also available for performing many image processing tasks.

Processing Translational Motion Sequences.

DTIC Science & Technology

1982-10-01

the initial ROADSIGN image using a (del)**2g mask with a width of 5 pixels The distinctiveness values were computed using features which were 5x5 pixel...the initial step size of the local search quite large. 34 4. EX P R g NTg The following experiments were performed using the roadsign and industrial...the initial image of the sequence. The third experiment involves processing the roadsign image sequence using the features extracted at the positions

Hybrid imaging: a quantum leap in scientific imaging

NASA Astrophysics Data System (ADS)

Atlas, Gene; Wadsworth, Mark V.

2004-01-01

ImagerLabs has advanced its patented next generation imaging technology called the Hybrid Imaging Technology (HIT) that offers scientific quality performance. The key to the HIT is the merging of the CCD and CMOS technologies through hybridization rather than process integration. HIT offers exceptional QE, fill factor, broad spectral response and very low noise properties of the CCD. In addition, it provides the very high-speed readout, low power, high linearity and high integration capability of CMOS sensors. In this work, we present the benefits, and update the latest advances in the performance of this exciting technology.

A report on the ST ScI optical disk workstation

NASA Technical Reports Server (NTRS)

1985-01-01

The STScI optical disk project was designed to explore the options, opportunities and problems presented by the optical disk technology, and to see if optical disks are a viable, and inexpensive, means of storing the large amount of data which are found in astronomical digital imagery. A separate workstation was purchased on which the development can be done and serves as an astronomical image processing computer, incorporating the optical disks into the solution of standard image processing tasks. It is indicated that small workstations can be powerful tools for image processing, and that astronomical image processing may be more conveniently and cost-effectively performed on microcomputers than on the mainframe and super-minicomputers. The optical disks provide unique capabilities in data storage.

Automatic Image Processing Workflow for the Keck/NIRC2 Vortex Coronagraph

NASA Astrophysics Data System (ADS)

Xuan, Wenhao; Cook, Therese; Ngo, Henry; Zawol, Zoe; Ruane, Garreth; Mawet, Dimitri

2018-01-01

The Keck/NIRC2 camera, equipped with the vortex coronagraph, is an instrument targeted at the high contrast imaging of extrasolar planets. To uncover a faint planet signal from the overwhelming starlight, we utilize the Vortex Image Processing (VIP) library, which carries out principal component analysis to model and remove the stellar point spread function. To bridge the gap between data acquisition and data reduction, we implement a workflow that 1) downloads, sorts, and processes data with VIP, 2) stores the analysis products into a database, and 3) displays the reduced images, contrast curves, and auxiliary information on a web interface. Both angular differential imaging and reference star differential imaging are implemented in the analysis module. A real-time version of the workflow runs during observations, allowing observers to make educated decisions about time distribution on different targets, hence optimizing science yield. The post-night version performs a standardized reduction after the observation, building up a valuable database that not only helps uncover new discoveries, but also enables a statistical study of the instrument itself. We present the workflow, and an examination of the contrast performance of the NIRC2 vortex with respect to factors including target star properties and observing conditions.

Benchmarking image fusion system design parameters

NASA Astrophysics Data System (ADS)

Howell, Christopher L.

2013-06-01

A clear and absolute method for discriminating between image fusion algorithm performances is presented. This method can effectively be used to assist in the design and modeling of image fusion systems. Specifically, it is postulated that quantifying human task performance using image fusion should be benchmarked to whether the fusion algorithm, at a minimum, retained the performance benefit achievable by each independent spectral band being fused. The established benchmark would then clearly represent the threshold that a fusion system should surpass to be considered beneficial to a particular task. A genetic algorithm is employed to characterize the fused system parameters using a Matlab® implementation of NVThermIP as the objective function. By setting the problem up as a mixed-integer constraint optimization problem, one can effectively look backwards through the image acquisition process: optimizing fused system parameters by minimizing the difference between modeled task difficulty measure and the benchmark task difficulty measure. The results of an identification perception experiment are presented, where human observers were asked to identify a standard set of military targets, and used to demonstrate the effectiveness of the benchmarking process.

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

NASA Astrophysics Data System (ADS)

Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

Real-time photoacoustic and ultrasound dual-modality imaging system facilitated with graphics processing unit and code parallel optimization.

PubMed

Yuan, Jie; Xu, Guan; Yu, Yao; Zhou, Yu; Carson, Paul L; Wang, Xueding; Liu, Xiaojun

2013-08-01

Photoacoustic tomography (PAT) offers structural and functional imaging of living biological tissue with highly sensitive optical absorption contrast and excellent spatial resolution comparable to medical ultrasound (US) imaging. We report the development of a fully integrated PAT and US dual-modality imaging system, which performs signal scanning, image reconstruction, and display for both photoacoustic (PA) and US imaging all in a truly real-time manner. The back-projection (BP) algorithm for PA image reconstruction is optimized to reduce the computational cost and facilitate parallel computation on a state of the art graphics processing unit (GPU) card. For the first time, PAT and US imaging of the same object can be conducted simultaneously and continuously, at a real-time frame rate, presently limited by the laser repetition rate of 10 Hz. Noninvasive PAT and US imaging of human peripheral joints in vivo were achieved, demonstrating the satisfactory image quality realized with this system. Another experiment, simultaneous PAT and US imaging of contrast agent flowing through an artificial vessel, was conducted to verify the performance of this system for imaging fast biological events. The GPU-based image reconstruction software code for this dual-modality system is open source and available for download from http://sourceforge.net/projects/patrealtime.

Multispectral image enhancement processing for microsat-borne imager

NASA Astrophysics Data System (ADS)

Sun, Jianying; Tan, Zheng; Lv, Qunbo; Pei, Linlin

2017-10-01

With the rapid development of remote sensing imaging technology, the micro satellite, one kind of tiny spacecraft, appears during the past few years. A good many studies contribute to dwarfing satellites for imaging purpose. Generally speaking, micro satellites weigh less than 100 kilograms, even less than 50 kilograms, which are slightly larger or smaller than the common miniature refrigerators. However, the optical system design is hard to be perfect due to the satellite room and weight limitation. In most cases, the unprocessed data captured by the imager on the microsatellite cannot meet the application need. Spatial resolution is the key problem. As for remote sensing applications, the higher spatial resolution of images we gain, the wider fields we can apply them. Consequently, how to utilize super resolution (SR) and image fusion to enhance the quality of imagery deserves studying. Our team, the Key Laboratory of Computational Optical Imaging Technology, Academy Opto-Electronics, is devoted to designing high-performance microsat-borne imagers and high-efficiency image processing algorithms. This paper addresses a multispectral image enhancement framework for space-borne imagery, jointing the pan-sharpening and super resolution techniques to deal with the spatial resolution shortcoming of microsatellites. We test the remote sensing images acquired by CX6-02 satellite and give the SR performance. The experiments illustrate the proposed approach provides high-quality images.

SU-E-I-37: Low-Dose Real-Time Region-Of-Interest X-Ray Fluoroscopic Imaging with a GPU-Accelerated Spatially Different Bilateral Filtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chung, H; Lee, J; Pua, R

2014-06-01

Purpose: The purpose of our study is to reduce imaging radiation dose while maintaining image quality of region of interest (ROI) in X-ray fluoroscopy. A low-dose real-time ROI fluoroscopic imaging technique which includes graphics-processing-unit- (GPU-) accelerated image processing for brightness compensation and noise filtering was developed in this study. Methods: In our ROI fluoroscopic imaging, a copper filter is placed in front of the X-ray tube. The filter contains a round aperture to reduce radiation dose to outside of the aperture. To equalize the brightness difference between inner and outer ROI regions, brightness compensation was performed by use of amore » simple weighting method that applies selectively to the inner ROI, the outer ROI, and the boundary zone. A bilateral filtering was applied to the images to reduce relatively high noise in the outer ROI images. To speed up the calculation of our technique for real-time application, the GPU-acceleration was applied to the image processing algorithm. We performed a dosimetric measurement using an ion-chamber dosimeter to evaluate the amount of radiation dose reduction. The reduction of calculation time compared to a CPU-only computation was also measured, and the assessment of image quality in terms of image noise and spatial resolution was conducted. Results: More than 80% of dose was reduced by use of the ROI filter. The reduction rate depended on the thickness of the filter and the size of ROI aperture. The image noise outside the ROI was remarkably reduced by the bilateral filtering technique. The computation time for processing each frame image was reduced from 3.43 seconds with single CPU to 9.85 milliseconds with GPU-acceleration. Conclusion: The proposed technique for X-ray fluoroscopy can substantially reduce imaging radiation dose to the patient while maintaining image quality particularly in the ROI region in real-time.« less

Nonlocal means-based speckle filtering for ultrasound images

PubMed Central

Coupé, Pierrick; Hellier, Pierre; Kervrann, Charles; Barillot, Christian

2009-01-01

In image processing, restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques. In this paper, an adaptation of the Non Local (NL-) means filter is proposed for speckle reduction in ultrasound (US) images. Originally developed for additive white Gaussian noise, we propose to use a Bayesian framework to derive a NL-means filter adapted to a relevant ultrasound noise model. Quantitative results on synthetic data show the performances of the proposed method compared to well-established and state-of-the-art methods. Results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image. PMID:19482578

Rotation and scale change invariant point pattern relaxation matching by the Hopfield neural network

NASA Astrophysics Data System (ADS)

Sang, Nong; Zhang, Tianxu

1997-12-01

Relaxation matching is one of the most relevant methods for image matching. The original relaxation matching technique using point patterns is sensitive to rotations and scale changes. We improve the original point pattern relaxation matching technique to be invariant to rotations and scale changes. A method that makes the Hopfield neural network perform this matching process is discussed. An advantage of this is that the relaxation matching process can be performed in real time with the neural network's massively parallel capability to process information. Experimental results with large simulated images demonstrate the effectiveness and feasibility of the method to perform point patten relaxation matching invariant to rotations and scale changes and the method to perform this matching by the Hopfield neural network. In addition, we show that the method presented can be tolerant to small random error.

Differential Shift Estimation in the Absence of Coherence: Performance Analysis and Benefits of Polarimetry

NASA Astrophysics Data System (ADS)

Villano, Michelangelo; Papathanassiou, Konstantinos P.

2011-03-01

The estimation of the local differential shift between synthetic aperture radar (SAR) images has proven to be an effective technique for monitoring glacier surface motion. As images acquired over glaciers by short wavelength SAR systems, such as TerraSAR-X, often suffer from a lack of coherence, image features have to be exploited for the shift estimation (feature-tracking).The present paper addresses feature-tracking with special attention to the feasibility requirements and the achievable accuracy of the shift estimation. In particular, the dependence of the performance on image characteristics, such as texture parameters, signal-to-noise ratio (SNR) and resolution, as well as on processing techniques (despeckling, normalised cross-correlation versus maximum likelihood estimation) is analysed by means of Monte-Carlo simulations. TerraSAR-X data acquired over the Helheim glacier, Greenland, and the Aletsch glacier, Switzerland, have been processed to validate the simulation results.Feature-tracking can benefit of the availability of fully-polarimetric data. As some image characteristics, in fact, are polarisation-dependent, the selection of an optimum polarisation leads to improved performance. Furthermore, fully-polarimetric SAR images can be despeckled without degrading the resolution, so that additional (smaller-scale) features can be exploited.

Hyperspectral imaging for food processing automation

NASA Astrophysics Data System (ADS)

Park, Bosoon; Lawrence, Kurt C.; Windham, William R.; Smith, Doug P.; Feldner, Peggy W.

2002-11-01

This paper presents the research results that demonstrates hyperspectral imaging could be used effectively for detecting feces (from duodenum, ceca, and colon) and ingesta on the surface of poultry carcasses, and potential application for real-time, on-line processing of poultry for automatic safety inspection. The hyperspectral imaging system included a line scan camera with prism-grating-prism spectrograph, fiber optic line lighting, motorized lens control, and hyperspectral image processing software. Hyperspectral image processing algorithms, specifically band ratio of dual-wavelength (565/517) images and thresholding were effective on the identification of fecal and ingesta contamination of poultry carcasses. A multispectral imaging system including a common aperture camera with three optical trim filters (515.4 nm with 8.6- nm FWHM), 566.4 nm with 8.8-nm FWHM, and 631 nm with 10.2-nm FWHM), which were selected and validated by a hyperspectral imaging system, was developed for a real-time, on-line application. A total image processing time required to perform the current multispectral images captured by a common aperture camera was approximately 251 msec or 3.99 frames/sec. A preliminary test shows that the accuracy of real-time multispectral imaging system to detect feces and ingesta on corn/soybean fed poultry carcasses was 96%. However, many false positive spots that cause system errors were also detected.

A Computer-Aided Type-II Fuzzy Image Processing for Diagnosis of Meniscus Tear.

PubMed

Zarandi, M H Fazel; Khadangi, A; Karimi, F; Turksen, I B

2016-12-01

Meniscal tear is one of the prevalent knee disorders among young athletes and the aging population, and requires correct diagnosis and surgical intervention, if necessary. Not only the errors followed by human intervention but also the obstacles of manual meniscal tear detection highlight the need for automatic detection techniques. This paper presents a type-2 fuzzy expert system for meniscal tear diagnosis using PD magnetic resonance images (MRI). The scheme of the proposed type-2 fuzzy image processing model is composed of three distinct modules: Pre-processing, Segmentation, and Classification. λ-nhancement algorithm is used to perform the pre-processing step. For the segmentation step, first, Interval Type-2 Fuzzy C-Means (IT2FCM) is applied to the images, outputs of which are then employed by Interval Type-2 Possibilistic C-Means (IT2PCM) to perform post-processes. Second stage concludes with re-estimation of "η" value to enhance IT2PCM. Finally, a Perceptron neural network with two hidden layers is used for Classification stage. The results of the proposed type-2 expert system have been compared with a well-known segmentation algorithm, approving the superiority of the proposed system in meniscal tear recognition.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132.

PubMed

Brock, Kristy K; Mutic, Sasa; McNutt, Todd R; Li, Hua; Kessler, Marc L

2017-07-01

Image registration and fusion algorithms exist in almost every software system that creates or uses images in radiotherapy. Most treatment planning systems support some form of image registration and fusion to allow the use of multimodality and time-series image data and even anatomical atlases to assist in target volume and normal tissue delineation. Treatment delivery systems perform registration and fusion between the planning images and the in-room images acquired during the treatment to assist patient positioning. Advanced applications are beginning to support daily dose assessment and enable adaptive radiotherapy using image registration and fusion to propagate contours and accumulate dose between image data taken over the course of therapy to provide up-to-date estimates of anatomical changes and delivered dose. This information aids in the detection of anatomical and functional changes that might elicit changes in the treatment plan or prescription. As the output of the image registration process is always used as the input of another process for planning or delivery, it is important to understand and communicate the uncertainty associated with the software in general and the result of a specific registration. Unfortunately, there is no standard mathematical formalism to perform this for real-world situations where noise, distortion, and complex anatomical variations can occur. Validation of the software systems performance is also complicated by the lack of documentation available from commercial systems leading to use of these systems in undesirable 'black-box' fashion. In view of this situation and the central role that image registration and fusion play in treatment planning and delivery, the Therapy Physics Committee of the American Association of Physicists in Medicine commissioned Task Group 132 to review current approaches and solutions for image registration (both rigid and deformable) in radiotherapy and to provide recommendations for quality assurance and quality control of these clinical processes. © 2017 American Association of Physicists in Medicine.

Platform for Postprocessing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Don

2008-01-01

Taking advantage of the similarities that exist among all waveform-based non-destructive evaluation (NDE) methods, a common software platform has been developed containing multiple- signal and image-processing techniques for waveforms and images. The NASA NDE Signal and Image Processing software has been developed using the latest versions of LabVIEW, and its associated Advanced Signal Processing and Vision Toolkits. The software is useable on a PC with Windows XP and Windows Vista. The software has been designed with a commercial grade interface in which two main windows, Waveform Window and Image Window, are displayed if the user chooses a waveform file to display. Within these two main windows, most actions are chosen through logically conceived run-time menus. The Waveform Window has plots for both the raw time-domain waves and their frequency- domain transformations (fast Fourier transform and power spectral density). The Image Window shows the C-scan image formed from information of the time-domain waveform (such as peak amplitude) or its frequency-domain transformation at each scan location. The user also has the ability to open an image, or series of images, or a simple set of X-Y paired data set in text format. Each of the Waveform and Image Windows contains menus from which to perform many user actions. An option exists to use raw waves obtained directly from scan, or waves after deconvolution if system wave response is provided. Two types of deconvolution, time-based subtraction or inverse-filter, can be performed to arrive at a deconvolved wave set. Additionally, the menu on the Waveform Window allows preprocessing of waveforms prior to image formation, scaling and display of waveforms, formation of different types of images (including non-standard types such as velocity), gating of portions of waves prior to image formation, and several other miscellaneous and specialized operations. The menu available on the Image Window allows many further image processing and analysis operations, some of which are found in commercially-available image-processing software programs (such as Adobe Photoshop), and some that are not (removing outliers, Bscan information, region-of-interest analysis, line profiles, and precision feature measurements).

New Developments in Observer Performance Methodology in Medical Imaging

PubMed Central

Chakraborty, Dev P.

2011-01-01

A common task in medical imaging is assessing whether a new imaging system, or a variant of an existing one, is an improvement over an existing imaging technology. Imaging systems are generally quite complex, consisting of several components – e.g., image acquisition hardware, image processing and display hardware and software, and image interpretation by radiologists– each of which can affect performance. While it may appear odd to include the radiologist as a “component” of the imaging chain, since the radiologist’s decision determines subsequent patient care, the effect of the human interpretation has to be included. Physical measurements like modulation transfer function, signal to noise ratio, etc., are useful for characterizing the non-human parts of the imaging chain under idealized and often unrealistic conditions, such as uniform background phantoms, target objects with sharp edges, etc. Measuring the effect on performance of the entire imaging chain, including the radiologist, and using real clinical images, requires different methods that fall under the rubric of observer performance methods or “ROC analysis”. The purpose of this paper is to review recent developments in this field, particularly with respect to the free-response method. PMID:21978444

Sparse representations via learned dictionaries for x-ray angiogram image denoising

NASA Astrophysics Data System (ADS)

Shang, Jingfan; Huang, Zhenghua; Li, Qian; Zhang, Tianxu

2018-03-01

X-ray angiogram image denoising is always an active research topic in the field of computer vision. In particular, the denoising performance of many existing methods had been greatly improved by the widely use of nonlocal similar patches. However, the only nonlocal self-similar (NSS) patch-based methods can be still be improved and extended. In this paper, we propose an image denoising model based on the sparsity of the NSS patches to obtain high denoising performance and high-quality image. In order to represent the sparsely NSS patches in every location of the image well and solve the image denoising model more efficiently, we obtain dictionaries as a global image prior by the K-SVD algorithm over the processing image; Then the single and effectively alternating directions method of multipliers (ADMM) method is used to solve the image denoising model. The results of widely synthetic experiments demonstrate that, owing to learned dictionaries by K-SVD algorithm, a sparsely augmented lagrangian image denoising (SALID) model, which perform effectively, obtains a state-of-the-art denoising performance and better high-quality images. Moreover, we also give some denoising results of clinical X-ray angiogram images.

Detecting Moving Sources in Astronomical Images (Abstract)

NASA Astrophysics Data System (ADS)

Block, A.

2018-06-01

(Abstract only) Source detection in images is an important part of analyzing astronomical data. This project discusses an implementation of image detection in python, as well as processes for performing photometry in python. Application of these tools to looking for moving sources is also discussed.

Distortion correction and cross-talk compensation algorithm for use with an imaging spectrometer based spatially resolved diffuse reflectance system

NASA Astrophysics Data System (ADS)

Cappon, Derek J.; Farrell, Thomas J.; Fang, Qiyin; Hayward, Joseph E.

2016-12-01

Optical spectroscopy of human tissue has been widely applied within the field of biomedical optics to allow rapid, in vivo characterization and analysis of the tissue. When designing an instrument of this type, an imaging spectrometer is often employed to allow for simultaneous analysis of distinct signals. This is especially important when performing spatially resolved diffuse reflectance spectroscopy. In this article, an algorithm is presented that allows for the automated processing of 2-dimensional images acquired from an imaging spectrometer. The algorithm automatically defines distinct spectrometer tracks and adaptively compensates for distortion introduced by optical components in the imaging chain. Crosstalk resulting from the overlap of adjacent spectrometer tracks in the image is detected and subtracted from each signal. The algorithm's performance is demonstrated in the processing of spatially resolved diffuse reflectance spectra recovered from an Intralipid and ink liquid phantom and is shown to increase the range of wavelengths over which usable data can be recovered.

Limitations of contrast enhancement for infrared target identification

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Fanning, Jonathan D.

2009-05-01

Contrast enhancement and dynamic range compression are currently being used to improve the performance of infrared imagers by increasing the contrast between the target and the scene content. Automatic contrast enhancement techniques do not always achieve this improvement. In some cases, the contrast can increase to a level of target saturation. This paper assesses the range-performance effects of contrast enhancement for target identification as a function of image saturation. Human perception experiments were performed to determine field performance using contrast enhancement on the U.S. Army RDECOM CERDEC NVESD standard military eight target set using an un-cooled LWIR camera. The experiments compare the identification performance of observers viewing contrast enhancement processed images at various levels of saturation. Contrast enhancement is modeled in the U.S. Army thermal target acquisition model (NVThermIP) by changing the scene contrast temperature. The model predicts improved performance based on any improved target contrast, regardless of specific feature saturation or enhancement. The measured results follow the predicted performance based on the target task difficulty metric used in NVThermIP for the non-saturated cases. The saturated images reduce the information contained in the target and performance suffers. The model treats the contrast of the target as uniform over spatial frequency. As the contrast is enhanced, the model assumes that the contrast is enhanced uniformly over the spatial frequencies. After saturation, the spatial cues that differentiate one tank from another are located in a limited band of spatial frequencies. A frequency dependent treatment of target contrast is needed to predict performance of over-processed images.

Performance assessment of a compressive sensing single-pixel imaging system

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Preece, Bradley L.

2017-04-01

Conventional sensors measure the light incident at each pixel in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process to recover the image. CS has the potential to acquire imagery with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations, reconstruction accuracy, and reconstruction speed to meet operational requirements. Performance modeling of CS imagers is challenging due to the complexity and nonlinearity of the system and reconstruction algorithm. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of a two-handheld object target set was collected using an shortwave infrared single-pixel CS camera for various ranges and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques are discussed.

Real-time speckle variance swept-source optical coherence tomography using a graphics processing unit.

PubMed

Lee, Kenneth K C; Mariampillai, Adrian; Yu, Joe X Z; Cadotte, David W; Wilson, Brian C; Standish, Beau A; Yang, Victor X D

2012-07-01

Advances in swept source laser technology continues to increase the imaging speed of swept-source optical coherence tomography (SS-OCT) systems. These fast imaging speeds are ideal for microvascular detection schemes, such as speckle variance (SV), where interframe motion can cause severe imaging artifacts and loss of vascular contrast. However, full utilization of the laser scan speed has been hindered by the computationally intensive signal processing required by SS-OCT and SV calculations. Using a commercial graphics processing unit that has been optimized for parallel data processing, we report a complete high-speed SS-OCT platform capable of real-time data acquisition, processing, display, and saving at 108,000 lines per second. Subpixel image registration of structural images was performed in real-time prior to SV calculations in order to reduce decorrelation from stationary structures induced by the bulk tissue motion. The viability of the system was successfully demonstrated in a high bulk tissue motion scenario of human fingernail root imaging where SV images (512 × 512 pixels, n = 4) were displayed at 54 frames per second.

Sinus Meridiani: uncontrolled Mars Global Surveyor (MGS) Mars Orbital Camera (MOC): digital context photomosaic (250 megapixel resolution)

USGS Publications Warehouse

Noreen, Eric

2000-01-01

These images were processed from a raw format using Integrated Software for Images and Spectrometers (ISIS) to perform radiometric corrections and projection. All the images were projected in sinusoidal using a center longitude of 0 degrees. There are two versions of the mosaic, one unfiltered (sinusmos.tif), and one produced with all images processed through a box filter with an averaged pixel tone of 7.5 (sinusmosflt.tif). Both mosaics are ArcView-ArcInfo(2) ready in TIF format with associated world files (*.tfw).

Central Valles Marineris: uncontrolled Mars Global Surveyor (MGS) Mars Orbital Camera (MOC) digital context photomosaic (250 megapixel resolution)

USGS Publications Warehouse

Noreen, Eric

2000-01-01

These images were processed from a raw format using Integrated Software for Images and Spectrometers (ISIS) to perform radiometric corrections and projection. All the images were projected in sinusoidal using a center longitude of 70 degrees. There are two versions of the mosaic, one unfiltered (vallesmos.tif), and one produced with all images processed through a box filter with an averaged pixel tone of 7.699 (vallesmosflt.tif). Both mosaics are ArcView-ArcInfo ready in TIF format with associated world files (*.tfw).

Privacy Protection by Masking Moving Objects for Security Cameras

NASA Astrophysics Data System (ADS)

Yabuta, Kenichi; Kitazawa, Hitoshi; Tanaka, Toshihisa

Because of an increasing number of security cameras, it is crucial to establish a system that protects the privacy of objects in the recorded images. To this end, we propose a framework of image processing and data hiding for security monitoring and privacy protection. First, we state the requirements of the proposed monitoring systems and suggest possible implementation that satisfies those requirements. The underlying concept of our proposed framework is as follows: (1) in the recorded images, the objects whose privacy should be protected are deteriorated by appropriate image processing; (2) the original objects are encrypted and watermarked into the output image, which is encoded using an image compression standard; (3) real-time processing is performed such that no future frame is required to generate on output bitstream. It should be noted that in this framework, anyone can observe the decoded image that includes the deteriorated objects that are unrecognizable or invisible. On the other hand, for crime investigation, this system allows a limited number of users to observe the original objects by using a special viewer that decrypts and decodes the watermarked objects with a decoding password. Moreover, the special viewer allows us to select the objects to be decoded and displayed. We provide an implementation example, experimental results, and performance evaluations to support our proposed framework.

Comprehensive optimization process of paranasal sinus radiography.

PubMed

Saarakkala, S; Nironen, K; Hermunen, H; Aarnio, J; Heikkinen, J O

2009-04-01

The optimization of radiological examinations is important in order to reduce unnecessary patient radiation exposure. To perform a comprehensive optimization process for paranasal sinus radiography at Mikkeli Central Hospital, Finland. Patients with suspicion of acute sinusitis were imaged with a Kodak computed radiography (CR) system (n=20) and with a Philips digital radiography (DR) system (n=30) using focus-detector distances (FDDs) of 110 cm, 150 cm, or 200 cm. Patients' radiation exposure was determined in terms of entrance surface dose and dose-area product. Furthermore, an anatomical phantom was used for the estimation of point doses inside the head. Clinical image quality was evaluated by an experienced radiologist, and physical image quality was evaluated from the digital radiography phantom. Patient doses were significantly lower and image quality better with the DR system compared to the CR system. The differences in patient dose and physical image quality were small with varying FDD. Clinical image quality of the DR system was lowest with FDD of 200 cm. Further, imaging with FDD of 150 cm was technically easier for the technologist to perform than with FDD of 110 cm. After optimization, it was recommended that the DR system with FDD of 150 cm should always be used at Mikkeli Central Hospital. We recommend this kind of comprehensive approach in all optimization processes of radiological examinations.

Real-time FPGA architectures for computer vision

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Torres-Huitzil, Cesar

2000-03-01

This paper presents an architecture for real-time generic convolution of a mask and an image. The architecture is intended for fast low level image processing. The FPGA-based architecture takes advantage of the availability of registers in FPGAs to implement an efficient and compact module to process the convolutions. The architecture is designed to minimize the number of accesses to the image memory and is based on parallel modules with internal pipeline operation in order to improve its performance. The architecture is prototyped in a FPGA, but it can be implemented on a dedicated VLSI to reach higher clock frequencies. Complexity issues, FPGA resources utilization, FPGA limitations, and real time performance are discussed. Some results are presented and discussed.

Experiments with recursive estimation in astronomical image processing

NASA Technical Reports Server (NTRS)

Busko, I.

1992-01-01

Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

PubMed

Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

PubMed Central

Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

Computational analysis of Pelton bucket tip erosion using digital image processing

NASA Astrophysics Data System (ADS)

Shrestha, Bim Prasad; Gautam, Bijaya; Bajracharya, Tri Ratna

2008-03-01

Erosion of hydro turbine components through sand laden river is one of the biggest problems in Himalayas. Even with sediment trapping systems, complete removal of fine sediment from water is impossible and uneconomical; hence most of the turbine components in Himalayan Rivers are exposed to sand laden water and subject to erode. Pelton bucket which are being wildly used in different hydropower generation plant undergoes erosion on the continuous presence of sand particles in water. The subsequent erosion causes increase in splitter thickness, which is supposed to be theoretically zero. This increase in splitter thickness gives rise to back hitting of water followed by decrease in turbine efficiency. This paper describes the process of measurement of sharp edges like bucket tip using digital image processing. Image of each bucket is captured and allowed to run for 72 hours; sand concentration in water hitting the bucket is closely controlled and monitored. Later, the image of the test bucket is taken in the same condition. The process is repeated for 10 times. In this paper digital image processing which encompasses processes that performs image enhancement in both spatial and frequency domain. In addition, the processes that extract attributes from images, up to and including the measurement of splitter's tip. Processing of image has been done in MATLAB 6.5 platform. The result shows that quantitative measurement of edge erosion of sharp edges could accurately be detected and the erosion profile could be generated using image processing technique.

Performance assessment of a data processing chain for THz imaging

NASA Astrophysics Data System (ADS)

Catapano, Ilaria; Ludeno, Giovanni; Soldovieri, Francesco

2017-04-01

Nowadays, TeraHertz (THz) imaging is deserving huge attention as very high resolution diagnostic tool in many applicative fields, among which security, cultural heritage, material characterization and civil engineering diagnostics. This widespread use of THz waves is due to their non-ionizing nature, their capability of penetrating into non-metallic opaque materials, as well as to the technological advances, which have allowed the commercialization of compact, flexible and portable systems. However, the effectiveness of THz imaging depends strongly on the adopted data processing aimed at improving the imaging performance of the hardware device. In particular, data processing is required to mitigate detrimental and unavoidable effects like noise, signal attenuation, as well as to correct the sample surface topography. With respect to data processing, we have proposed recently a strategy involving three different steps aimed at reducing noise, filtering out undesired signal introduced by the adopted THz system and performing surface topography correction [1]. The first step regards noise filtering and exploits a procedure based on the Singular Value Decomposition (SVD) [2] of the data matrix, which does not require knowledge of noise level and it does not involve the use of a reference signal. The second step aims at removing the undesired signal that we have experienced to be introduced by the adopted Z-Omega Fiber-Coupled Terahertz Time Domain (FICO) system. Indeed, when the system works in a high-speed mode, an undesired low amplitude peak occurs always at the same time instant from the beginning of the observation time window and needs to be removed from the useful data matrix in order to avoid a wrong interpretation of the imaging results. The third step of the considered data processing chain is a topographic correction, which needs in order to image properly the samples surface and its inner structure. Such a procedure performs an automatic alignment of the first peak of the measured waveforms by exploiting the a-priori information on the focus distance at which the specimen under test must be located during the measurement phase. The usefulness of the proposed data processing chain has been widely assessed in the last few months by surveying several specimens made by different materials and representative of objects of interest for civil engineering and cultural heritage diagnostics. At the conference, we will show in detail the signal processing chain and present several achieved results. REFERENCES [1] I. Catapano, F. Soldovieri, "A Data Processing Chain for Terahertz Imaging and Its Use in Artwork Diagnostics". J Infrared Milli Terahz Waves, pp.13, Nov. 2016. [2] M. Bertero and P. Boccacci (1998), Introduction to Inverse Problems in Imaging, Bristol: Institute of Physics Publishing.

Influence of Averaging Preprocessing on Image Analysis with a Markov Random Field Model

NASA Astrophysics Data System (ADS)

Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato

2018-02-01

This paper describes our investigations into the influence of averaging preprocessing on the performance of image analysis. Averaging preprocessing involves a trade-off: image averaging is often undertaken to reduce noise while the number of image data available for image analysis is decreased. We formulated a process of generating image data by using a Markov random field (MRF) model to achieve image analysis tasks such as image restoration and hyper-parameter estimation by a Bayesian approach. According to the notions of Bayesian inference, posterior distributions were analyzed to evaluate the influence of averaging. There are three main results. First, we found that the performance of image restoration with a predetermined value for hyper-parameters is invariant regardless of whether averaging is conducted. We then found that the performance of hyper-parameter estimation deteriorates due to averaging. Our analysis of the negative logarithm of the posterior probability, which is called the free energy based on an analogy with statistical mechanics, indicated that the confidence of hyper-parameter estimation remains higher without averaging. Finally, we found that when the hyper-parameters are estimated from the data, the performance of image restoration worsens as averaging is undertaken. We conclude that averaging adversely influences the performance of image analysis through hyper-parameter estimation.

An Automated Measurement of Ciliary Beating Frequency using a Combined Optical Flow and Peak Detection.

PubMed

Kim, Woojae; Han, Tae Hwa; Kim, Hyun Jun; Park, Man Young; Kim, Ku Sang; Park, Rae Woong

2011-06-01

The mucociliary transport system is a major defense mechanism of the respiratory tract. The performance of mucous transportation in the nasal cavity can be represented by a ciliary beating frequency (CBF). This study proposes a novel method to measure CBF by using optical flow. To obtain objective estimates of CBF from video images, an automated computer-based image processing technique is developed. This study proposes a new method based on optical flow for image processing and peak detection for signal processing. We compare the measuring accuracy of the method in various combinations of image processing (optical flow versus difference image) and signal processing (fast Fourier transform [FFT] vs. peak detection [PD]). The digital high-speed video method with a manual count of CBF in slow motion video play, is the gold-standard in CBF measurement. We obtained a total of fifty recorded ciliated sinonasal epithelium images to measure CBF from the Department of Otolaryngology. The ciliated sinonasal epithelium images were recorded at 50-100 frames per second using a charge coupled device camera with an inverted microscope at a magnification of ×1,000. The mean square errors and variance for each method were 1.24, 0.84 Hz; 11.8, 2.63 Hz; 3.22, 1.46 Hz; and 3.82, 1.53 Hz for optical flow (OF) + PD, OF + FFT, difference image [DI] + PD, and DI + FFT, respectively. Of the four methods, PD using optical flow showed the best performance for measuring the CBF of nasal mucosa. The proposed method was able to measure CBF more objectively and efficiently than what is currently possible.

A novel x-ray imaging system and its imaging performance

NASA Astrophysics Data System (ADS)

Yu, Chunyu; Chang, Benkang; Wang, Shiyun; Zhang, Junju; Yao, Xiao

2006-09-01

Since x-ray was discovered and applied to the imaging technology, the x-ray imaging techniques have experienced several improvements, from film-screen, x-ray image intensifier, CR to DR. To store and transmit the image information conveniently, the digital imaging is necessary for the imaging techniques in medicine and biology. Usually as the intensifying screen technique as for concerned, to get the digital image signals, the CCD was lens coupled directly to the screen, but which suffers from a loss of x-ray signal and resulted in the poor x-ray image perfonnance. Therefore, to improve the image performance, we joined the brightness intensifier, which, was named the Low Light Level (LLL) image intensifier in military affairs, between the intensifying screen and the CCD and designed the novel x-ray imaging system. This design method improved the image performance of the whole system thus decreased the x-ray dose. Comparison between two systems with and without the brightness intensifier was given in detail in this paper. Moreover, the main noise source of the image produced by the novel system was analyzed, and in this paper, the original images produced by the novel x-ray imaging system and the processed images were given respectively. It was clear that the image performance was satisfied and the x-ray imaging system can be used in security checking and many other nondestructive checking fields.

Measuring the complexity of design in real-time imaging software

NASA Astrophysics Data System (ADS)

Sangwan, Raghvinder S.; Vercellone-Smith, Pamela; Laplante, Phillip A.

2007-02-01

Due to the intricacies in the algorithms involved, the design of imaging software is considered to be more complex than non-image processing software (Sangwan et al, 2005). A recent investigation (Larsson and Laplante, 2006) examined the complexity of several image processing and non-image processing software packages along a wide variety of metrics, including those postulated by McCabe (1976), Chidamber and Kemerer (1994), and Martin (2003). This work found that it was not always possible to quantitatively compare the complexity between imaging applications and nonimage processing systems. Newer research and an accompanying tool (Structure 101, 2006), however, provides a greatly simplified approach to measuring software complexity. Therefore it may be possible to definitively quantify the complexity differences between imaging and non-imaging software, between imaging and real-time imaging software, and between software programs of the same application type. In this paper, we review prior results and describe the methodology for measuring complexity in imaging systems. We then apply a new complexity measurement methodology to several sets of imaging and non-imaging code in order to compare the complexity differences between the two types of applications. The benefit of such quantification is far reaching, for example, leading to more easily measured performance improvement and quality in real-time imaging code.

Demosaiced pixel super-resolution in digital holography for multiplexed computational color imaging on-a-chip (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wu, Yichen; Zhang, Yibo; Luo, Wei; Ozcan, Aydogan

2017-03-01

Digital holographic on-chip microscopy achieves large space-bandwidth-products (e.g., >1 billion) by making use of pixel super-resolution techniques. To synthesize a digital holographic color image, one can take three sets of holograms representing the red (R), green (G) and blue (B) parts of the spectrum and digitally combine them to synthesize a color image. The data acquisition efficiency of this sequential illumination process can be improved by 3-fold using wavelength-multiplexed R, G and B illumination that simultaneously illuminates the sample, and using a Bayer color image sensor with known or calibrated transmission spectra to digitally demultiplex these three wavelength channels. This demultiplexing step is conventionally used with interpolation-based Bayer demosaicing methods. However, because the pixels of different color channels on a Bayer image sensor chip are not at the same physical location, conventional interpolation-based demosaicing process generates strong color artifacts, especially at rapidly oscillating hologram fringes, which become even more pronounced through digital wave propagation and phase retrieval processes. Here, we demonstrate that by merging the pixel super-resolution framework into the demultiplexing process, such color artifacts can be greatly suppressed. This novel technique, termed demosaiced pixel super-resolution (D-PSR) for digital holographic imaging, achieves very similar color imaging performance compared to conventional sequential R,G,B illumination, with 3-fold improvement in image acquisition time and data-efficiency. We successfully demonstrated the color imaging performance of this approach by imaging stained Pap smears. The D-PSR technique is broadly applicable to high-throughput, high-resolution digital holographic color microscopy techniques that can be used in resource-limited-settings and point-of-care offices.

Graphical user interface to optimize image contrast parameters used in object segmentation - biomed 2009.

PubMed

Anderson, Jeffrey R; Barrett, Steven F

2009-01-01

Image segmentation is the process of isolating distinct objects within an image. Computer algorithms have been developed to aid in the process of object segmentation, but a completely autonomous segmentation algorithm has yet to be developed [1]. This is because computers do not have the capability to understand images and recognize complex objects within the image. However, computer segmentation methods [2], requiring user input, have been developed to quickly segment objects in serial sectioned images, such as magnetic resonance images (MRI) and confocal laser scanning microscope (CLSM) images. In these cases, the segmentation process becomes a powerful tool in visualizing the 3D nature of an object. The user input is an important part of improving the performance of many segmentation methods. A double threshold segmentation method has been investigated [3] to separate objects in gray scaled images, where the gray level of the object is among the gray levels of the background. In order to best determine the threshold values for this segmentation method the image must be manipulated for optimal contrast. The same is true of other segmentation and edge detection methods as well. Typically, the better the image contrast, the better the segmentation results. This paper describes a graphical user interface (GUI) that allows the user to easily change image contrast parameters that will optimize the performance of subsequent object segmentation. This approach makes use of the fact that the human brain is extremely effective in object recognition and understanding. The GUI provides the user with the ability to define the gray scale range of the object of interest. These lower and upper bounds of this range are used in a histogram stretching process to improve image contrast. Also, the user can interactively modify the gamma correction factor that provides a non-linear distribution of gray scale values, while observing the corresponding changes to the image. This interactive approach gives the user the power to make optimal choices in the contrast enhancement parameters.

A novel parallel architecture for local histogram equalization

NASA Astrophysics Data System (ADS)

Ohannessian, Mesrob I.; Choueiter, Ghinwa F.; Diab, Hassan

2005-07-01

Local histogram equalization is an image enhancement algorithm that has found wide application in the pre-processing stage of areas such as computer vision, pattern recognition and medical imaging. The computationally intensive nature of the procedure, however, is a main limitation when real time interactive applications are in question. This work explores the possibility of performing parallel local histogram equalization, using an array of special purpose elementary processors, through an HDL implementation that targets FPGA or ASIC platforms. A novel parallelization scheme is presented and the corresponding architecture is derived. The algorithm is reduced to pixel-level operations. Processing elements are assigned image blocks, to maintain a reasonable performance-cost ratio. To further simplify both processor and memory organizations, a bit-serial access scheme is used. A brief performance assessment is provided to illustrate and quantify the merit of the approach.

A Computer-Aided Diagnosis System for Measuring Carotid Artery Intima-Media Thickness (IMT) Using Quaternion Vectors.

PubMed

Kutbay, Uğurhan; Hardalaç, Fırat; Akbulut, Mehmet; Akaslan, Ünsal; Serhatlıoğlu, Selami

2016-06-01

This study aims investigating adjustable distant fuzzy c-means segmentation on carotid Doppler images, as well as quaternion-based convolution filters and saliency mapping procedures. We developed imaging software that will simplify the measurement of carotid artery intima-media thickness (IMT) on saliency mapping images. Additionally, specialists evaluated the present images and compared them with saliency mapping images. In the present research, we conducted imaging studies of 25 carotid Doppler images obtained by the Department of Cardiology at Fırat University. After implementing fuzzy c-means segmentation and quaternion-based convolution on all Doppler images, we obtained a model that can be analyzed easily by the doctors using a bottom-up saliency model. These methods were applied to 25 carotid Doppler images and then interpreted by specialists. In the present study, we used color-filtering methods to obtain carotid color images. Saliency mapping was performed on the obtained images, and the carotid artery IMT was detected and interpreted on the obtained images from both methods and the raw images are shown in Results. Also these results were investigated by using Mean Square Error (MSE) for the raw IMT images and the method which gives the best performance is the Quaternion Based Saliency Mapping (QBSM). 0,0014 and 0,000191 mm(2) MSEs were obtained for artery lumen diameters and plaque diameters in carotid arteries respectively. We found that computer-based image processing methods used on carotid Doppler could aid doctors' in their decision-making process. We developed software that could ease the process of measuring carotid IMT for cardiologists and help them to evaluate their findings.

Evaluation and testing of image quality of the Space Solar Extreme Ultraviolet Telescope

NASA Astrophysics Data System (ADS)

Peng, Jilong; Yi, Zhong; Zhou, Shuhong; Yu, Qian; Hou, Yinlong; Wang, Shanshan

2018-01-01

For the space solar extreme ultraviolet telescope, the star point test can not be performed in the x-ray band (19.5nm band) as there is not light source of bright enough. In this paper, the point spread function of the optical system is calculated to evaluate the imaging performance of the telescope system. Combined with the actual processing surface error, such as small grinding head processing and magnetorheological processing, the optical design software Zemax and data analysis software Matlab are used to directly calculate the system point spread function of the space solar extreme ultraviolet telescope. Matlab codes are programmed to generate the required surface error grid data. These surface error data is loaded to the specified surface of the telescope system by using the communication technique of DDE (Dynamic Data Exchange), which is used to connect Zemax and Matlab. As the different processing methods will lead to surface error with different size, distribution and spatial frequency, the impact of imaging is also different. Therefore, the characteristics of the surface error of different machining methods are studied. Combining with its position in the optical system and simulation its influence on the image quality, it is of great significance to reasonably choose the processing technology. Additionally, we have also analyzed the relationship between the surface error and the image quality evaluation. In order to ensure the final processing of the mirror to meet the requirements of the image quality, we should choose one or several methods to evaluate the surface error according to the different spatial frequency characteristics of the surface error.

Comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Sullivan, Malcolm N.; Chan, Kam Wai Clifford; Boyd, Robert W.

2010-11-15

We present a theoretical comparison of the signal-to-noise characteristics of quantum versus thermal ghost imaging. We first calculate the signal-to-noise ratio of each process in terms of its controllable experimental conditions. We show that a key distinction is that a thermal ghost image always resides on top of a large background; the fluctuations in this background constitutes an intrinsic noise source for thermal ghost imaging. In contrast, there is a negligible intrinsic background to a quantum ghost image. However, for practical reasons involving achievable illumination levels, acquisition times for thermal ghost images are often much shorter than those for quantummore » ghost images. We provide quantitative predictions for the conditions under which each process provides superior performance. Our conclusion is that each process can provide useful functionality, although under complementary conditions.« less

Automatic DNA Diagnosis for 1D Gel Electrophoresis Images using Bio-image Processing Technique.

PubMed

Intarapanich, Apichart; Kaewkamnerd, Saowaluck; Shaw, Philip J; Ukosakit, Kittipat; Tragoonrung, Somvong; Tongsima, Sissades

2015-01-01

DNA gel electrophoresis is a molecular biology technique for separating different sizes of DNA fragments. Applications of DNA gel electrophoresis include DNA fingerprinting (genetic diagnosis), size estimation of DNA, and DNA separation for Southern blotting. Accurate interpretation of DNA banding patterns from electrophoretic images can be laborious and error prone when a large number of bands are interrogated manually. Although many bio-imaging techniques have been proposed, none of them can fully automate the typing of DNA owing to the complexities of migration patterns typically obtained. We developed an image-processing tool that automatically calls genotypes from DNA gel electrophoresis images. The image processing workflow comprises three main steps: 1) lane segmentation, 2) extraction of DNA bands and 3) band genotyping classification. The tool was originally intended to facilitate large-scale genotyping analysis of sugarcane cultivars. We tested the proposed tool on 10 gel images (433 cultivars) obtained from polyacrylamide gel electrophoresis (PAGE) of PCR amplicons for detecting intron length polymorphisms (ILP) on one locus of the sugarcanes. These gel images demonstrated many challenges in automated lane/band segmentation in image processing including lane distortion, band deformity, high degree of noise in the background, and bands that are very close together (doublets). Using the proposed bio-imaging workflow, lanes and DNA bands contained within are properly segmented, even for adjacent bands with aberrant migration that cannot be separated by conventional techniques. The software, called GELect, automatically performs genotype calling on each lane by comparing with an all-banding reference, which was created by clustering the existing bands into the non-redundant set of reference bands. The automated genotype calling results were verified by independent manual typing by molecular biologists. This work presents an automated genotyping tool from DNA gel electrophoresis images, called GELect, which was written in Java and made available through the imageJ framework. With a novel automated image processing workflow, the tool can accurately segment lanes from a gel matrix, intelligently extract distorted and even doublet bands that are difficult to identify by existing image processing tools. Consequently, genotyping from DNA gel electrophoresis can be performed automatically allowing users to efficiently conduct large scale DNA fingerprinting via DNA gel electrophoresis. The software is freely available from http://www.biotec.or.th/gi/tools/gelect.

Active point out-of-plane ultrasound calibration

NASA Astrophysics Data System (ADS)

Cheng, Alexis; Guo, Xiaoyu; Zhang, Haichong K.; Kang, Hyunjae; Etienne-Cummings, Ralph; Boctor, Emad M.

2015-03-01

Image-guided surgery systems are often used to provide surgeons with informational support. Due to several unique advantages such as ease of use, real-time image acquisition, and no ionizing radiation, ultrasound is a common intraoperative medical imaging modality used in image-guided surgery systems. To perform advanced forms of guidance with ultrasound, such as virtual image overlays or automated robotic actuation, an ultrasound calibration process must be performed. This process recovers the rigid body transformation between a tracked marker attached to the transducer and the ultrasound image. Point-based phantoms are considered to be accurate, but their calibration framework assumes that the point is in the image plane. In this work, we present the use of an active point phantom and a calibration framework that accounts for the elevational uncertainty of the point. Given the lateral and axial position of the point in the ultrasound image, we approximate a circle in the axial-elevational plane with a radius equal to the axial position. The standard approach transforms all of the imaged points to be a single physical point. In our approach, we minimize the distances between the circular subsets of each image, with them ideally intersecting at a single point. We simulated in noiseless and noisy cases, presenting results on out-of-plane estimation errors, calibration estimation errors, and point reconstruction precision. We also performed an experiment using a robot arm as the tracker, resulting in a point reconstruction precision of 0.64mm.

Combined Acquisition/Processing For Data Reduction

NASA Astrophysics Data System (ADS)

Kruger, Robert A.

1982-01-01

Digital image processing systems necessarily consist of three components: acquisition, storage/retrieval and processing. The acquisition component requires the greatest data handling rates. By coupling together the acquisition witn some online hardwired processing, data rates and capacities for short term storage can be reduced. Furthermore, long term storage requirements can be reduced further by appropriate processing and editing of image data contained in short term memory. The net result could be reduced performance requirements for mass storage, processing and communication systems. Reduced amounts of data also snouid speed later data analysis and diagnostic decision making.

A new tool for supervised classification of satellite images available on web servers: Google Maps as a case study

NASA Astrophysics Data System (ADS)

García-Flores, Agustín.; Paz-Gallardo, Abel; Plaza, Antonio; Li, Jun

2016-10-01

This paper describes a new web platform dedicated to the classification of satellite images called Hypergim. The current implementation of this platform enables users to perform classification of satellite images from any part of the world thanks to the worldwide maps provided by Google Maps. To perform this classification, Hypergim uses unsupervised algorithms like Isodata and K-means. Here, we present an extension of the original platform in which we adapt Hypergim in order to use supervised algorithms to improve the classification results. This involves a significant modification of the user interface, providing the user with a way to obtain samples of classes present in the images to use in the training phase of the classification process. Another main goal of this development is to improve the runtime of the image classification process. To achieve this goal, we use a parallel implementation of the Random Forest classification algorithm. This implementation is a modification of the well-known CURFIL software package. The use of this type of algorithms to perform image classification is widespread today thanks to its precision and ease of training. The actual implementation of Random Forest was developed using CUDA platform, which enables us to exploit the potential of several models of NVIDIA graphics processing units using them to execute general purpose computing tasks as image classification algorithms. As well as CUDA, we use other parallel libraries as Intel Boost, taking advantage of the multithreading capabilities of modern CPUs. To ensure the best possible results, the platform is deployed in a cluster of commodity graphics processing units (GPUs), so that multiple users can use the tool in a concurrent way. The experimental results indicate that this new algorithm widely outperform the previous unsupervised algorithms implemented in Hypergim, both in runtime as well as precision of the actual classification of the images.

Design and implementation of non-linear image processing functions for CMOS image sensor

NASA Astrophysics Data System (ADS)

Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

2012-11-01

Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images

PubMed Central

Lahmiri, Salim; Boukadoum, Mounir

2013-01-01

A new methodology for automatic feature extraction from biomedical images and subsequent classification is presented. The approach exploits the spatial orientation of high-frequency textural features of the processed image as determined by a two-step process. First, the two-dimensional discrete wavelet transform (DWT) is applied to obtain the HH high-frequency subband image. Then, a Gabor filter bank is applied to the latter at different frequencies and spatial orientations to obtain new Gabor-filtered image whose entropy and uniformity are computed. Finally, the obtained statistics are fed to a support vector machine (SVM) binary classifier. The approach was validated on mammograms, retina, and brain magnetic resonance (MR) images. The obtained classification accuracies show better performance in comparison to common approaches that use only the DWT or Gabor filter banks for feature extraction. PMID:27006906

Finite grade pheromone ant colony optimization for image segmentation

NASA Astrophysics Data System (ADS)

Yuanjing, F.; Li, Y.; Liangjun, K.

2008-06-01

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

The PICWidget

NASA Technical Reports Server (NTRS)

Norris, Jeffrey; Fox, Jason; Rabe, Kenneth; Shu, I-Hsiang; Powell, Mark

2007-01-01

The Plug-in Image Component Widget (PICWidget) is a software component for building digital imaging applications. The component is part of a methodology described in GIS Methodology for Planning Planetary-Rover Operations (NPO-41812), which appears elsewhere in this issue of NASA Tech Briefs. Planetary rover missions return a large number and wide variety of image data products that vary in complexity in many ways. Supported by a powerful, flexible image-data-processing pipeline, the PICWidget can process and render many types of imagery, including (but not limited to) thumbnail, subframed, downsampled, stereoscopic, and mosaic images; images coregistred with orbital data; and synthetic red/green/blue images. The PICWidget is capable of efficiently rendering images from data representing many more pixels than are available at a computer workstation where the images are to be displayed. The PICWidget is implemented as an Eclipse plug-in using the Standard Widget Toolkit, which provides a straightforward interface for re-use of the PICWidget in any number of application programs built upon the Eclipse application framework. Because the PICWidget is tile-based and performs aggressive tile caching, it has flexibility to perform faster or slower, depending whether more or less memory is available.

The AAPM/RSNA physics tutorial for residents: digital fluoroscopy.

PubMed

Pooley, R A; McKinney, J M; Miller, D A

2001-01-01

A digital fluoroscopy system is most commonly configured as a conventional fluoroscopy system (tube, table, image intensifier, video system) in which the analog video signal is converted to and stored as digital data. Other methods of acquiring the digital data (eg, digital or charge-coupled device video and flat-panel detectors) will become more prevalent in the future. Fundamental concepts related to digital imaging in general include binary numbers, pixels, and gray levels. Digital image data allow the convenient use of several image processing techniques including last image hold, gray-scale processing, temporal frame averaging, and edge enhancement. Real-time subtraction of digital fluoroscopic images after injection of contrast material has led to widespread use of digital subtraction angiography (DSA). Additional image processing techniques used with DSA include road mapping, image fade, mask pixel shift, frame summation, and vessel size measurement. Peripheral angiography performed with an automatic moving table allows imaging of the peripheral vasculature with a single contrast material injection.

Open framework for management and processing of multi-modality and multidimensional imaging data for analysis and modelling muscular function

NASA Astrophysics Data System (ADS)

García Juan, David; Delattre, Bénédicte M. A.; Trombella, Sara; Lynch, Sean; Becker, Matthias; Choi, Hon Fai; Ratib, Osman

2014-03-01

Musculoskeletal disorders (MSD) are becoming a big healthcare economical burden in developed countries with aging population. Classical methods like biopsy or EMG used in clinical practice for muscle assessment are invasive and not accurately sufficient for measurement of impairments of muscular performance. Non-invasive imaging techniques can nowadays provide effective alternatives for static and dynamic assessment of muscle function. In this paper we present work aimed toward the development of a generic data structure for handling n-dimensional metabolic and anatomical data acquired from hybrid PET/MR scanners. Special static and dynamic protocols were developed for assessment of physical and functional images of individual muscles of the lower limb. In an initial stage of the project a manual segmentation of selected muscles was performed on high-resolution 3D static images and subsequently interpolated to full dynamic set of contours from selected 2D dynamic images across different levels of the leg. This results in a full set of 4D data of lower limb muscles at rest and during exercise. These data can further be extended to a 5D data by adding metabolic data obtained from PET images. Our data structure and corresponding image processing extension allows for better evaluation of large volumes of multidimensional imaging data that are acquired and processed to generate dynamic models of the moving lower limb and its muscular function.

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). A description of the sensor, ground data processing facility, laboratory calibration, and first results

NASA Technical Reports Server (NTRS)

Vane, Gregg (Editor)

1987-01-01

The papers in this document were presented at the Imaging Spectroscopy 2 Conference of the 31st International Symposium on Optical and Optoelectronic Applied Science and Engineering, in San Diego, California, on 20 and 21 August 1987. They describe the design and performance of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor and its subsystems, the ground data processing facility, laboratory calibration, and first results.

SPARX, a new environment for Cryo-EM image processing.

PubMed

Hohn, Michael; Tang, Grant; Goodyear, Grant; Baldwin, P R; Huang, Zhong; Penczek, Pawel A; Yang, Chao; Glaeser, Robert M; Adams, Paul D; Ludtke, Steven J

2007-01-01

SPARX (single particle analysis for resolution extension) is a new image processing environment with a particular emphasis on transmission electron microscopy (TEM) structure determination. It includes a graphical user interface that provides a complete graphical programming environment with a novel data/process-flow infrastructure, an extensive library of Python scripts that perform specific TEM-related computational tasks, and a core library of fundamental C++ image processing functions. In addition, SPARX relies on the EMAN2 library and cctbx, the open-source computational crystallography library from PHENIX. The design of the system is such that future inclusion of other image processing libraries is a straightforward task. The SPARX infrastructure intelligently handles retention of intermediate values, even those inside programming structures such as loops and function calls. SPARX and all dependencies are free for academic use and available with complete source.

The occipital face area is causally involved in the formation of identity-specific face representations.

PubMed

Ambrus, Géza Gergely; Dotzer, Maria; Schweinberger, Stefan R; Kovács, Gyula

2017-12-01

Transcranial magnetic stimulation (TMS) and neuroimaging studies suggest a role of the right occipital face area (rOFA) in early facial feature processing. However, the degree to which rOFA is necessary for the encoding of facial identity has been less clear. Here we used a state-dependent TMS paradigm, where stimulation preferentially facilitates attributes encoded by less active neural populations, to investigate the role of the rOFA in face perception and specifically in image-independent identity processing. Participants performed a familiarity decision task for famous and unknown target faces, preceded by brief (200 ms) or longer (3500 ms) exposures to primes which were either an image of a different identity (DiffID), another image of the same identity (SameID), the same image (SameIMG), or a Fourier-randomized noise pattern (NOISE) while either the rOFA or the vertex as control was stimulated by single-pulse TMS. Strikingly, TMS to the rOFA eliminated the advantage of SameID over DiffID condition, thereby disrupting identity-specific priming, while leaving image-specific priming (better performance for SameIMG vs. SameID) unaffected. Our results suggest that the role of rOFA is not limited to low-level feature processing, and emphasize its role in image-independent facial identity processing and the formation of identity-specific memory traces.

Segmentation of pomegranate MR images using spatial fuzzy c-means (SFCM) algorithm

NASA Astrophysics Data System (ADS)

Moradi, Ghobad; Shamsi, Mousa; Sedaaghi, M. H.; Alsharif, M. R.

2011-10-01

Segmentation is one of the fundamental issues of image processing and machine vision. It plays a prominent role in a variety of image processing applications. In this paper, one of the most important applications of image processing in MRI segmentation of pomegranate is explored. Pomegranate is a fruit with pharmacological properties such as being anti-viral and anti-cancer. Having a high quality product in hand would be critical factor in its marketing. The internal quality of the product is comprehensively important in the sorting process. The determination of qualitative features cannot be manually made. Therefore, the segmentation of the internal structures of the fruit needs to be performed as accurately as possible in presence of noise. Fuzzy c-means (FCM) algorithm is noise-sensitive and pixels with noise are classified inversely. As a solution, in this paper, the spatial FCM algorithm in pomegranate MR images' segmentation is proposed. The algorithm is performed with setting the spatial neighborhood information in FCM and modification of fuzzy membership function for each class. The segmentation algorithm results on the original and the corrupted Pomegranate MR images by Gaussian, Salt Pepper and Speckle noises show that the SFCM algorithm operates much more significantly than FCM algorithm. Also, after diverse steps of qualitative and quantitative analysis, we have concluded that the SFCM algorithm with 5×5 window size is better than the other windows.

Transform- and multi-domain deep learning for single-frame rapid autofocusing in whole slide imaging.

PubMed

Jiang, Shaowei; Liao, Jun; Bian, Zichao; Guo, Kaikai; Zhang, Yongbing; Zheng, Guoan

2018-04-01

A whole slide imaging (WSI) system has recently been approved for primary diagnostic use in the US. The image quality and system throughput of WSI is largely determined by the autofocusing process. Traditional approaches acquire multiple images along the optical axis and maximize a figure of merit for autofocusing. Here we explore the use of deep convolution neural networks (CNNs) to predict the focal position of the acquired image without axial scanning. We investigate the autofocusing performance with three illumination settings: incoherent Kohler illumination, partially coherent illumination with two plane waves, and one-plane-wave illumination. We acquire ~130,000 images with different defocus distances as the training data set. Different defocus distances lead to different spatial features of the captured images. However, solely relying on the spatial information leads to a relatively bad performance of the autofocusing process. It is better to extract defocus features from transform domains of the acquired image. For incoherent illumination, the Fourier cutoff frequency is directly related to the defocus distance. Similarly, autocorrelation peaks are directly related to the defocus distance for two-plane-wave illumination. In our implementation, we use the spatial image, the Fourier spectrum, the autocorrelation of the spatial image, and combinations thereof as the inputs for the CNNs. We show that the information from the transform domains can improve the performance and robustness of the autofocusing process. The resulting focusing error is ~0.5 µm, which is within the 0.8-µm depth-of-field range. The reported approach requires little hardware modification for conventional WSI systems and the images can be captured on the fly without focus map surveying. It may find applications in WSI and time-lapse microscopy. The transform- and multi-domain approaches may also provide new insights for developing microscopy-related deep-learning networks. We have made our training and testing data set (~12 GB) open-source for the broad research community.

Rapid Disaster Damage Estimation

NASA Astrophysics Data System (ADS)

Vu, T. T.

2012-07-01

The experiences from recent disaster events showed that detailed information derived from high-resolution satellite images could accommodate the requirements from damage analysts and disaster management practitioners. Richer information contained in such high-resolution images, however, increases the complexity of image analysis. As a result, few image analysis solutions can be practically used under time pressure in the context of post-disaster and emergency responses. To fill the gap in employment of remote sensing in disaster response, this research develops a rapid high-resolution satellite mapping solution built upon a dual-scale contextual framework to support damage estimation after a catastrophe. The target objects are building (or building blocks) and their condition. On the coarse processing level, statistical region merging deployed to group pixels into a number of coarse clusters. Based on majority rule of vegetation index, water and shadow index, it is possible to eliminate the irrelevant clusters. The remaining clusters likely consist of building structures and others. On the fine processing level details, within each considering clusters, smaller objects are formed using morphological analysis. Numerous indicators including spectral, textural and shape indices are computed to be used in a rule-based object classification. Computation time of raster-based analysis highly depends on the image size or number of processed pixels in order words. Breaking into 2 level processing helps to reduce the processed number of pixels and the redundancy of processing irrelevant information. In addition, it allows a data- and tasks- based parallel implementation. The performance is demonstrated with QuickBird images captured a disaster-affected area of Phanga, Thailand by the 2004 Indian Ocean tsunami are used for demonstration of the performance. The developed solution will be implemented in different platforms as well as a web processing service for operational uses.

JADA: a graphical user interface for comprehensive internal dose assessment in nuclear medicine.

PubMed

Grimes, Joshua; Uribe, Carlos; Celler, Anna

2013-07-01

The main objective of this work was to design a comprehensive dosimetry package that would keep all aspects of internal dose calculation within the framework of a single software environment and that would be applicable for a variety of dose calculation approaches. Our MATLAB-based graphical user interface (GUI) can be used for processing data obtained using pure planar, pure SPECT, or hybrid planar/SPECT imaging. Time-activity data for source regions are obtained using a set of tools that allow the user to reconstruct SPECT images, load images, coregister a series of planar images, and to perform two-dimensional and three-dimensional image segmentation. Curve fits are applied to the acquired time-activity data to construct time-activity curves, which are then integrated to obtain time-integrated activity coefficients. Subsequently, dose estimates are made using one of three methods. The organ level dose calculation subGUI calculates mean organ doses that are equivalent to dose assessment performed by OLINDA/EXM. Voxelized dose calculation options, which include the voxel S value approach and Monte Carlo simulation using the EGSnrc user code DOSXYZnrc, are available within the process 3D image data subGUI. The developed internal dosimetry software package provides an assortment of tools for every step in the dose calculation process, eliminating the need for manual data transfer between programs. This saves times and minimizes user errors, while offering a versatility that can be used to efficiently perform patient-specific internal dose calculations in a variety of clinical situations.

Time-resolved 3D MR velocity mapping at 3T: improved navigator-gated assessment of vascular anatomy and blood flow.

PubMed

Markl, Michael; Harloff, Andreas; Bley, Thorsten A; Zaitsev, Maxim; Jung, Bernd; Weigang, Ernst; Langer, Mathias; Hennig, Jürgen; Frydrychowicz, Alex

2007-04-01

To evaluate an improved image acquisition and data-processing strategy for assessing aortic vascular geometry and 3D blood flow at 3T. In a study with five normal volunteers and seven patients with known aortic pathology, prospectively ECG-gated cine three-dimensional (3D) MR velocity mapping with improved navigator gating, real-time adaptive k-space ordering and dynamic adjustment of the navigator acceptance criteria was performed. In addition to morphological information and three-directional blood flow velocities, phase-contrast (PC)-MRA images were derived from the same data set, which permitted 3D isosurface rendering of vascular boundaries in combination with visualization of blood-flow patterns. Analysis of navigator performance and image quality revealed improved scan efficiencies of 63.6%+/-10.5% and temporal resolution (<50 msec) compared to previous implementations. Semiquantitative evaluation of image quality by three independent observers demonstrated excellent general image appearance with moderate blurring and minor ghosting artifacts. Results from volunteer and patient examinations illustrate the potential of the improved image acquisition and data-processing strategy for identifying normal and pathological blood-flow characteristics. Navigator-gated time-resolved 3D MR velocity mapping at 3T in combination with advanced data processing is a powerful tool for performing detailed assessments of global and local blood-flow characteristics in the aorta to describe or exclude vascular alterations. Copyright (c) 2007 Wiley-Liss, Inc.

Laterality in Metaphor Processing: Lack of Evidence from Functional Magnetic Resonance Imaging for the Right Hemisphere Theory

ERIC Educational Resources Information Center

Rapp, Alexander M.; Leube, Dirk T.; Erb, Michael; Grodd, Wolfgang; Kircher, Tilo T. J.

2007-01-01

We investigated processing of metaphoric sentences using event-related functional magnetic resonance imaging (fMRI). Seventeen healthy subjects (6 female, 11 male) read 60 novel short German sentence pairs with either metaphoric or literal meaning and performed two different tasks: judging the metaphoric content and judging whether the sentence…

MMX-I: A data-processing software for multi-modal X-ray imaging and tomography

NASA Astrophysics Data System (ADS)

Bergamaschi, A.; Medjoubi, K.; Messaoudi, C.; Marco, S.; Somogyi, A.

2017-06-01

Scanning hard X-ray imaging allows simultaneous acquisition of multimodal information, including X-ray fluorescence, absorption, phase and dark-field contrasts, providing structural and chemical details of the samples. Combining these scanning techniques with the infrastructure developed for fast data acquisition at Synchrotron Soleil permits to perform multimodal imaging and tomography during routine user experiments at the Nanoscopium beamline. A main challenge of such imaging techniques is the online processing and analysis of the generated very large volume (several hundreds of Giga Bytes) multimodal data-sets. This is especially important for the wide user community foreseen at the user oriented Nanoscopium beamline (e.g. from the fields of Biology, Life Sciences, Geology, Geobiology), having no experience in such data-handling. MMX-I is a new multi-platform open-source freeware for the processing and reconstruction of scanning multi-technique X-ray imaging and tomographic datasets. The MMX-I project aims to offer, both expert users and beginners, the possibility of processing and analysing raw data, either on-site or off-site. Therefore we have developed a multi-platform (Mac, Windows and Linux 64bit) data processing tool, which is easy to install, comprehensive, intuitive, extendable and user-friendly. MMX-I is now routinely used by the Nanoscopium user community and has demonstrated its performance in treating big data.

A new visual feedback-based magnetorheological haptic master for robot-assisted minimally invasive surgery

NASA Astrophysics Data System (ADS)

Choi, Seung-Hyun; Kim, Soomin; Kim, Pyunghwa; Park, Jinhyuk; Choi, Seung-Bok

2015-06-01

In this study, we developed a novel four-degrees-of-freedom haptic master using controllable magnetorheological (MR) fluid. We also integrated the haptic master with a vision device with image processing for robot-assisted minimally invasive surgery (RMIS). The proposed master can be used in RMIS as a haptic interface to provide the surgeon with a sense of touch by using both kinetic and kinesthetic information. The slave robot, which is manipulated with a proportional-integrative-derivative controller, uses a force sensor to obtain the desired forces from tissue contact, and these desired repulsive forces are then embodied through the MR haptic master. To verify the effectiveness of the haptic master, the desired force and actual force are compared in the time domain. In addition, a visual feedback system is implemented in the RMIS experiment to distinguish between the tumor and organ more clearly and provide better visibility to the operator. The hue-saturation-value color space is adopted for the image processing since it is often more intuitive than other color spaces. The image processing and haptic feedback are realized on surgery performance. In this work, tumor-cutting experiments are conducted under four different operating conditions: haptic feedback on, haptic feedback off, image processing on, and image processing off. The experimental realization shows that the performance index, which is a function of pixels, is different in the four operating conditions.

Low-cost, high-speed back-end processing system for high-frequency ultrasound B-mode imaging.

PubMed

Chang, Jin Ho; Sun, Lei; Yen, Jesse T; Shung, K Kirk

2009-07-01

For real-time visualization of the mouse heart (6 to 13 beats per second), a back-end processing system involving high-speed signal processing functions to form and display images has been developed. This back-end system was designed with new signal processing algorithms to achieve a frame rate of more than 400 images per second. These algorithms were implemented in a simple and cost-effective manner with a single field-programmable gate array (FPGA) and software programs written in C++. The operating speed of the back-end system was investigated by recording the time required for transferring an image to a personal computer. Experimental results showed that the back-end system is capable of producing 433 images per second. To evaluate the imaging performance of the back-end system, a complete imaging system was built. This imaging system, which consisted of a recently reported high-speed mechanical sector scanner assembled with the back-end system, was tested by imaging a wire phantom, a pig eye (in vitro), and a mouse heart (in vivo). It was shown that this system is capable of providing high spatial resolution images with fast temporal resolution.

Low-Cost, High-Speed Back-End Processing System for High-Frequency Ultrasound B-Mode Imaging

PubMed Central

Chang, Jin Ho; Sun, Lei; Yen, Jesse T.; Shung, K. Kirk

2009-01-01

For real-time visualization of the mouse heart (6 to 13 beats per second), a back-end processing system involving high-speed signal processing functions to form and display images has been developed. This back-end system was designed with new signal processing algorithms to achieve a frame rate of more than 400 images per second. These algorithms were implemented in a simple and cost-effective manner with a single field-programmable gate array (FPGA) and software programs written in C++. The operating speed of the back-end system was investigated by recording the time required for transferring an image to a personal computer. Experimental results showed that the back-end system is capable of producing 433 images per second. To evaluate the imaging performance of the back-end system, a complete imaging system was built. This imaging system, which consisted of a recently reported high-speed mechanical sector scanner assembled with the back-end system, was tested by imaging a wire phantom, a pig eye (in vitro), and a mouse heart (in vivo). It was shown that this system is capable of providing high spatial resolution images with fast temporal resolution. PMID:19574160

Detecting tympanostomy tubes from otoscopic images via offline and online training.

PubMed

Wang, Xin; Valdez, Tulio A; Bi, Jinbo

2015-06-01

Tympanostomy tube placement has been commonly used nowadays as a surgical treatment for otitis media. Following the placement, regular scheduled follow-ups for checking the status of the tympanostomy tubes are important during the treatment. The complexity of performing the follow up care mainly lies on identifying the presence and patency of the tympanostomy tube. An automated tube detection program will largely reduce the care costs and enhance the clinical efficiency of the ear nose and throat specialists and general practitioners. In this paper, we develop a computer vision system that is able to automatically detect a tympanostomy tube in an otoscopic image of the ear drum. The system comprises an offline classifier training process followed by a real-time refinement stage performed at the point of care. The offline training process constructs a three-layer cascaded classifier with each layer reflecting specific characteristics of the tube. The real-time refinement process enables the end users to interact and adjust the system over time based on their otoscopic images and patient care. The support vector machine (SVM) algorithm has been applied to train all of the classifiers. Empirical evaluation of the proposed system on both high quality hospital images and low quality internet images demonstrates the effectiveness of the system. The offline classifier trained using 215 images could achieve a 90% accuracy in terms of classifying otoscopic images with and without a tympanostomy tube, and then the real-time refinement process could improve the classification accuracy by 3-5% based on additional 20 images. Copyright © 2015 Elsevier Ltd. All rights reserved.

Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

NASA Technical Reports Server (NTRS)

Decker, Arthur J.

2004-01-01

Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

Embedded real-time image processing hardware for feature extraction and clustering

NASA Astrophysics Data System (ADS)

Chiu, Lihu; Chang, Grant

2003-08-01

Printronix, Inc. uses scanner-based image systems to perform print quality measurements for line-matrix printers. The size of the image samples and image definition required make commercial scanners convenient to use. The image processing is relatively well defined, and we are able to simplify many of the calculations into hardware equations and "c" code. The process of rapidly prototyping the system using DSP based "c" code gets the algorithms well defined early in the development cycle. Once a working system is defined, the rest of the process involves splitting the task up for the FPGA and the DSP implementation. Deciding which of the two to use, the DSP or the FPGA, is a simple matter of trial benchmarking. There are two kinds of benchmarking: One for speed, and the other for memory. The more memory intensive algorithms should run in the DSP, and the simple real time tasks can use the FPGA most effectively. Once the task is split, we can decide which platform the algorithm should be executed. This involves prototyping all the code in the DSP, then timing various blocks of the algorithm. Slow routines can be optimized using the compiler tools, and if further reduction in time is needed, into tasks that the FPGA can perform.

Fetal brain volumetry through MRI volumetric reconstruction and segmentation

PubMed Central

Estroff, Judy A.; Barnewolt, Carol E.; Connolly, Susan A.; Warfield, Simon K.

2013-01-01

Purpose Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested. Materials and methods The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation. Results Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses. Conclusion The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation. PMID:20625848

Image Display and Manipulation System (IDAMS) program documentation, Appendixes A-D. [including routines, convolution filtering, image expansion, and fast Fourier transformation

NASA Technical Reports Server (NTRS)

Cecil, R. W.; White, R. A.; Szczur, M. R.

1972-01-01

The IDAMS Processor is a package of task routines and support software that performs convolution filtering, image expansion, fast Fourier transformation, and other operations on a digital image tape. A unique task control card for that program, together with any necessary parameter cards, selects each processing technique to be applied to the input image. A variable number of tasks can be selected for execution by including the proper task and parameter cards in the input deck. An executive maintains control of the run; it initiates execution of each task in turn and handles any necessary error processing.

Automatic Welding System of Aluminum Pipe by Monitoring Backside Image of Molten Pool Using Vision Sensor

NASA Astrophysics Data System (ADS)

Baskoro, Ario Sunar; Kabutomori, Masashi; Suga, Yasuo

An automatic welding system using Tungsten Inert Gas (TIG) welding with vision sensor for welding of aluminum pipe was constructed. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position and moving welding torch with the AC welding machine. The monitoring system consists of a vision sensor using a charge-coupled device (CCD) camera to monitor backside image of molten pool. The captured image was processed to recognize the edge of molten pool by image processing algorithm. Neural network model for welding speed control were constructed to perform the process automatically. From the experimental results it shows the effectiveness of the control system confirmed by good detection of molten pool and sound weld of experimental result.

High quality image-pair-based deblurring method using edge mask and improved residual deconvolution

NASA Astrophysics Data System (ADS)

Cui, Guangmang; Zhao, Jufeng; Gao, Xiumin; Feng, Huajun; Chen, Yueting

2017-04-01

Image deconvolution problem is a challenging task in the field of image process. Using image pairs could be helpful to provide a better restored image compared with the deblurring method from a single blurred image. In this paper, a high quality image-pair-based deblurring method is presented using the improved RL algorithm and the gain-controlled residual deconvolution technique. The input image pair includes a non-blurred noisy image and a blurred image captured for the same scene. With the estimated blur kernel, an improved RL deblurring method based on edge mask is introduced to obtain the preliminary deblurring result with effective ringing suppression and detail preservation. Then the preliminary deblurring result is served as the basic latent image and the gain-controlled residual deconvolution is utilized to recover the residual image. A saliency weight map is computed as the gain map to further control the ringing effects around the edge areas in the residual deconvolution process. The final deblurring result is obtained by adding the preliminary deblurring result with the recovered residual image. An optical experimental vibration platform is set up to verify the applicability and performance of the proposed algorithm. Experimental results demonstrate that the proposed deblurring framework obtains a superior performance in both subjective and objective assessments and has a wide application in many image deblurring fields.

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing

PubMed Central

Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

2016-01-01

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate. PMID:27070606

Accelerating Spaceborne SAR Imaging Using Multiple CPU/GPU Deep Collaborative Computing.

PubMed

Zhang, Fan; Li, Guojun; Li, Wei; Hu, Wei; Hu, Yuxin

2016-04-07

With the development of synthetic aperture radar (SAR) technologies in recent years, the huge amount of remote sensing data brings challenges for real-time imaging processing. Therefore, high performance computing (HPC) methods have been presented to accelerate SAR imaging, especially the GPU based methods. In the classical GPU based imaging algorithm, GPU is employed to accelerate image processing by massive parallel computing, and CPU is only used to perform the auxiliary work such as data input/output (IO). However, the computing capability of CPU is ignored and underestimated. In this work, a new deep collaborative SAR imaging method based on multiple CPU/GPU is proposed to achieve real-time SAR imaging. Through the proposed tasks partitioning and scheduling strategy, the whole image can be generated with deep collaborative multiple CPU/GPU computing. In the part of CPU parallel imaging, the advanced vector extension (AVX) method is firstly introduced into the multi-core CPU parallel method for higher efficiency. As for the GPU parallel imaging, not only the bottlenecks of memory limitation and frequent data transferring are broken, but also kinds of optimized strategies are applied, such as streaming, parallel pipeline and so on. Experimental results demonstrate that the deep CPU/GPU collaborative imaging method enhances the efficiency of SAR imaging on single-core CPU by 270 times and realizes the real-time imaging in that the imaging rate outperforms the raw data generation rate.

Real-time optical image processing techniques

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang

1988-01-01

Nonlinear real-time optical processing on spatial pulse frequency modulation has been pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the modification of micro-channel spatial light modulators (MSLMs). Micro-channel spatial light modulators are modified via the Fabry-Perot method to achieve the high gamma operation required for non-linear operation. Real-time nonlinear processing was performed using the halftone screen and MSLM. The experiments showed the effectiveness of the thresholding and also showed the needs of higher SBP for image processing. The Hughes LCLV has been characterized and found to yield high gamma (about 1.7) when operated in low frequency and low bias mode. Cascading of two LCLVs should also provide enough gamma for nonlinear processing. In this case, the SBP of the LCLV is sufficient but the uniformity of the LCLV needs improvement. These include image correlation, computer generation of holograms, pseudo-color image encoding for image enhancement, and associative-retrieval in neural processing. The discovery of the only known optical method for dynamic range compression of an input image in real-time by using GaAs photorefractive crystals is reported. Finally, a new architecture for non-linear multiple sensory, neural processing has been suggested.

Advanced processing for high-bandwidth sensor systems

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Blain, Phil C.; Bloch, Jeffrey J.; Brislawn, Christopher M.; Brumby, Steven P.; Cafferty, Maureen M.; Dunham, Mark E.; Frigo, Janette R.; Gokhale, Maya; Harvey, Neal R.; Kenyon, Garrett; Kim, Won-Ha; Layne, J.; Lavenier, Dominique D.; McCabe, Kevin P.; Mitchell, Melanie; Moore, Kurt R.; Perkins, Simon J.; Porter, Reid B.; Robinson, S.; Salazar, Alfonso; Theiler, James P.; Young, Aaron C.

2000-11-01

Compute performance and algorithm design are key problems of image processing and scientific computing in general. For example, imaging spectrometers are capable of producing data in hundreds of spectral bands with millions of pixels. These data sets show great promise for remote sensing applications, but require new and computationally intensive processing. The goal of the Deployable Adaptive Processing Systems (DAPS) project at Los Alamos National Laboratory is to develop advanced processing hardware and algorithms for high-bandwidth sensor applications. The project has produced electronics for processing multi- and hyper-spectral sensor data, as well as LIDAR data, while employing processing elements using a variety of technologies. The project team is currently working on reconfigurable computing technology and advanced feature extraction techniques, with an emphasis on their application to image and RF signal processing. This paper presents reconfigurable computing technology and advanced feature extraction algorithm work and their application to multi- and hyperspectral image processing. Related projects on genetic algorithms as applied to image processing will be introduced, as will the collaboration between the DAPS project and the DARPA Adaptive Computing Systems program. Further details are presented in other talks during this conference and in other conferences taking place during this symposium.

A biological phantom for evaluation of CT image reconstruction algorithms

NASA Astrophysics Data System (ADS)

Cammin, J.; Fung, G. S. K.; Fishman, E. K.; Siewerdsen, J. H.; Stayman, J. W.; Taguchi, K.

2014-03-01

In recent years, iterative algorithms have become popular in diagnostic CT imaging to reduce noise or radiation dose to the patient. The non-linear nature of these algorithms leads to non-linearities in the imaging chain. However, the methods to assess the performance of CT imaging systems were developed assuming the linear process of filtered backprojection (FBP). Those methods may not be suitable any longer when applied to non-linear systems. In order to evaluate the imaging performance, a phantom is typically scanned and the image quality is measured using various indices. For reasons of practicality, cost, and durability, those phantoms often consist of simple water containers with uniform cylinder inserts. However, these phantoms do not represent the rich structure and patterns of real tissue accurately. As a result, the measured image quality or detectability performance for lesions may not reflect the performance on clinical images. The discrepancy between estimated and real performance may be even larger for iterative methods which sometimes produce "plastic-like", patchy images with homogeneous patterns. Consequently, more realistic phantoms should be used to assess the performance of iterative algorithms. We designed and constructed a biological phantom consisting of porcine organs and tissue that models a human abdomen, including liver lesions. We scanned the phantom on a clinical CT scanner and compared basic image quality indices between filtered backprojection and an iterative reconstruction algorithm.

Platform-independent software for medical image processing on the Internet

NASA Astrophysics Data System (ADS)

Mancuso, Michael E.; Pathak, Sayan D.; Kim, Yongmin

1997-05-01

We have developed a software tool for image processing over the Internet. The tool is a general purpose, easy to use, flexible, platform independent image processing software package with functions most commonly used in medical image processing.It provides for processing of medical images located wither remotely on the Internet or locally. The software was written in Java - the new programming language developed by Sun Microsystems. It was compiled and tested using Microsoft's Visual Java 1.0 and Microsoft's Just in Time Compiler 1.00.6211. The software is simple and easy to use. In order to use the tool, the user needs to download the software from our site before he/she runs it using any Java interpreter, such as those supplied by Sun, Symantec, Borland or Microsoft. Future versions of the operating systems supplied by Sun, Microsoft, Apple, IBM, and others will include Java interpreters. The software is then able to access and process any image on the iNternet or on the local computer. Using a 512 X 512 X 8-bit image, a 3 X 3 convolution took 0.88 seconds on an Intel Pentium Pro PC running at 200 MHz with 64 Mbytes of memory. A window/level operation took 0.38 seconds while a 3 X 3 median filter took 0.71 seconds. These performance numbers demonstrate the feasibility of using this software interactively on desktop computes. Our software tool supports various image processing techniques commonly used in medical image processing and can run without the need of any specialized hardware. It can become an easily accessible resource over the Internet to promote the learning and of understanding image processing algorithms. Also, it could facilitate sharing of medical image databases and collaboration amongst researchers and clinicians, regardless of location.

Digital techniques for processing Landsat imagery

NASA Technical Reports Server (NTRS)

Green, W. B.

1978-01-01

An overview of the basic techniques used to process Landsat images with a digital computer, and the VICAR image processing software developed at JPL and available to users through the NASA sponsored COSMIC computer program distribution center is presented. Examples of subjective processing performed to improve the information display for the human observer, such as contrast enhancement, pseudocolor display and band rationing, and of quantitative processing using mathematical models, such as classification based on multispectral signatures of different areas within a given scene and geometric transformation of imagery into standard mapping projections are given. Examples are illustrated by Landsat scenes of the Andes mountains and Altyn-Tagh fault zone in China before and after contrast enhancement and classification of land use in Portland, Oregon. The VICAR image processing software system which consists of a language translator that simplifies execution of image processing programs and provides a general purpose format so that imagery from a variety of sources can be processed by the same basic set of general applications programs is described.

High-Performance 3D Image Processing Architectures for Image-Guided Interventions

DTIC Science & Technology

2008-01-01

Parallel architectures and algorithms for image understanding. Boston: Academic Press, 1991. [99] A. Bruhn, T. Jakob, M. Fischer, T. Kohlberger , J...Symposium on Pattern Recognition, vol. 2449(pp. 290-297, 2002. [100] A. Bruhn, T. Jakob, M. Fischer, T. Kohlberger , J. Weickert, U. Bruning, and C

High-volume image quality assessment systems: tuning performance with an interactive data visualization tool

NASA Astrophysics Data System (ADS)

Bresnahan, Patricia A.; Pukinskis, Madeleine; Wiggins, Michael

1999-03-01

Image quality assessment systems differ greatly with respect to the number and types of mags they need to evaluate, and their overall architectures. Managers of these systems, however, all need to be able to tune and evaluate system performance, requirements often overlooked or under-designed during project planning. Performance tuning tools allow users to define acceptable quality standards for image features and attributes by adjusting parameter settings. Performance analysis tools allow users to evaluate and/or predict how well a system performs in a given parameter state. While image assessment algorithms are becoming quite sophisticated, duplicating or surpassing the human decision making process in their speed and reliability, they often require a greater investment in 'training' or fine tuning of parameters in order to achieve optimum performance. This process may involve the analysis of hundreds or thousands of images, generating a large database of files and statistics that can be difficult to sort through and interpret. Compounding the difficulty is the fact that personnel charged with tuning and maintaining the production system may not have the statistical or analytical background required for the task. Meanwhile, hardware innovations have greatly increased the volume of images that can be handled in a given time frame, magnifying the consequences of running a production site with an inadequately tuned system. In this paper, some general requirements for a performance evaluation and tuning data visualization system are discussed. A custom engineered solution to the tuning and evaluation problem is then presented, developed within the context of a high volume image quality assessment, data entry, OCR, and image archival system. A key factor influencing the design of the system was the context-dependent definition of image quality, as perceived by a human interpreter. This led to the development of a five-level, hierarchical approach to image quality evaluation. Lower-level pass-fail conditions and decision rules were coded into the system. Higher-level image quality states were defined by allowing the users to interactively adjust the system's sensitivity to various image attributes by manipulating graphical controls. Results were presented in easily interpreted bar graphs. These graphs were mouse- sensitive, allowing the user to more fully explore the subsets of data indicated by various color blocks. In order to simplify the performance evaluation and tuning process, users could choose to view the results of (1) the existing system parameter state, (2) the results of any arbitrary parameter values they chose, or (3) the results of a quasi-optimum parameter state, derived by applying a decision rule to a large set of possible parameter states. Giving managers easy- to-use tools for defining the more subjective aspects of quality resulted in a system that responded to contextual cues that are difficult to hard-code. It had the additional advantage of allowing the definition of quality to evolve over time, as users became more knowledgeable as to the strengths and limitations of an automated quality inspection system.

A new scanning electron microscopy approach to image aerogels at the nanoscale

NASA Astrophysics Data System (ADS)

Solá, F.; Hurwitz, F.; Yang, J.

2011-04-01

A new scanning electron microscopy (SEM) technique to image poor electrically conductive aerogels is presented. The process can be performed by non-expert SEM users. We showed that negative charging effects on aerogels can be minimized significantly by inserting dry nitrogen gas close to the region of interest. The process involves the local recombination of accumulated negative charges with positive ions generated from ionization processes. This new technique made possible the acquisition of images of aerogels with pores down to approximately 3 nm in diameter using a positively biased Everhart-Thornley (ET) detector.

Target recognition for ladar range image using slice image

NASA Astrophysics Data System (ADS)

Xia, Wenze; Han, Shaokun; Wang, Liang

2015-12-01

A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

Real-time Enhancement, Registration, and Fusion for a Multi-Sensor Enhanced Vision System

NASA Technical Reports Server (NTRS)

Hines, Glenn D.; Rahman, Zia-ur; Jobson, Daniel J.; Woodell, Glenn A.

2006-01-01

Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in real-time and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than- human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for real-time performance. We are using a real-time implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests. Keywords: enhanced vision system, image enhancement, retinex, digital signal processing, sensor fusion

Liver CT image processing: a short introduction of the technical elements.

PubMed

Masutani, Y; Uozumi, K; Akahane, Masaaki; Ohtomo, Kuni

2006-05-01

In this paper, we describe the technical aspects of image analysis for liver diagnosis and treatment, including the state-of-the-art of liver image analysis and its applications. After discussion on modalities for liver image analysis, various technical elements for liver image analysis such as registration, segmentation, modeling, and computer-assisted detection are covered with examples performed with clinical data sets. Perspective in the imaging technologies is also reviewed and discussed.

Emotion Modulation of Visual Attention: Categorical and Temporal Characteristics

PubMed Central

Ciesielski, Bethany G.; Armstrong, Thomas; Zald, David H.; Olatunji, Bunmi O.

2010-01-01

Background Experimental research has shown that emotional stimuli can either enhance or impair attentional performance. However, the relative effects of specific emotional stimuli and the specific time course of these differential effects are unclear. Methodology/Principal Findings In the present study, participants (n = 50) searched for a single target within a rapid serial visual presentation of images. Irrelevant fear, disgust, erotic or neutral images preceded the target by two, four, six, or eight items. At lag 2, erotic images induced the greatest deficits in subsequent target processing compared to other images, consistent with a large emotional attentional blink. Fear and disgust images also produced a larger attentional blinks at lag 2 than neutral images. Erotic, fear, and disgust images continued to induce greater deficits than neutral images at lag 4 and 6. However, target processing deficits induced by erotic, fear, and disgust images at intermediate lags (lag 4 and 6) did not consistently differ from each other. In contrast to performance at lag 2, 4, and 6, enhancement in target processing for emotional stimuli was observed in comparison to neutral stimuli at lag 8. Conclusions/Significance These findings suggest that task-irrelevant emotion information, particularly erotica, impairs intentional allocation of attention at early temporal stages, but at later temporal stages, emotional stimuli can have an enhancing effect on directed attention. These data suggest that the effects of emotional stimuli on attention can be both positive and negative depending upon temporal factors. PMID:21079773

Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue

NASA Astrophysics Data System (ADS)

Sawyer, Travis W.; Rice, Photini F. S.; Sawyer, David M.; Koevary, Jennifer W.; Barton, Jennifer K.

2018-02-01

Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depthresolved, high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must rst be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluated a set of algorithms to segment OCT images of mouse ovaries. We examined ve preprocessing techniques and six segmentation algorithms. While all pre-processing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of 32% +/- 1.2%. Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 0.948 +/- 0.012 compared with manual segmentation (1.0 being identical). Nonetheless, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.

Photogrammetric Processing of Planetary Linear Pushbroom Images Based on Approximate Orthophotos

NASA Astrophysics Data System (ADS)

Geng, X.; Xu, Q.; Xing, S.; Hou, Y. F.; Lan, C. Z.; Zhang, J. J.

2018-04-01

It is still a great challenging task to efficiently produce planetary mapping products from orbital remote sensing images. There are many disadvantages in photogrammetric processing of planetary stereo images, such as lacking ground control information and informative features. Among which, image matching is the most difficult job in planetary photogrammetry. This paper designs a photogrammetric processing framework for planetary remote sensing images based on approximate orthophotos. Both tie points extraction for bundle adjustment and dense image matching for generating digital terrain model (DTM) are performed on approximate orthophotos. Since most of planetary remote sensing images are acquired by linear scanner cameras, we mainly deal with linear pushbroom images. In order to improve the computational efficiency of orthophotos generation and coordinates transformation, a fast back-projection algorithm of linear pushbroom images is introduced. Moreover, an iteratively refined DTM and orthophotos scheme was adopted in the DTM generation process, which is helpful to reduce search space of image matching and improve matching accuracy of conjugate points. With the advantages of approximate orthophotos, the matching results of planetary remote sensing images can be greatly improved. We tested the proposed approach with Mars Express (MEX) High Resolution Stereo Camera (HRSC) and Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) images. The preliminary experimental results demonstrate the feasibility of the proposed approach.

Overlay metrology for double patterning processes

NASA Astrophysics Data System (ADS)

Leray, Philippe; Cheng, Shaunee; Laidler, David; Kandel, Daniel; Adel, Mike; Dinu, Berta; Polli, Marco; Vasconi, Mauro; Salski, Bartlomiej

2009-03-01

The double patterning (DPT) process is foreseen by the industry to be the main solution for the 32 nm technology node and even beyond. Meanwhile process compatibility has to be maintained and the performance of overlay metrology has to improve. To achieve this for Image Based Overlay (IBO), usually the optics of overlay tools are improved. It was also demonstrated that these requirements are achievable with a Diffraction Based Overlay (DBO) technique named SCOLTM [1]. In addition, we believe that overlay measurements with respect to a reference grid are required to achieve the required overlay control [2]. This induces at least a three-fold increase in the number of measurements (2 for double patterned layers to the reference grid and 1 between the double patterned layers). The requirements of process compatibility, enhanced performance and large number of measurements make the choice of overlay metrology for DPT very challenging. In this work we use different flavors of the standard overlay metrology technique (IBO) as well as the new technique (SCOL) to address these three requirements. The compatibility of the corresponding overlay targets with double patterning processes (Litho-Etch-Litho-Etch (LELE); Litho-Freeze-Litho-Etch (LFLE), Spacer defined) is tested. The process impact on different target types is discussed (CD bias LELE, Contrast for LFLE). We compare the standard imaging overlay metrology with non-standard imaging techniques dedicated to double patterning processes (multilayer imaging targets allowing one overlay target instead of three, very small imaging targets). In addition to standard designs already discussed [1], we investigate SCOL target designs specific to double patterning processes. The feedback to the scanner is determined using the different techniques. The final overlay results obtained are compared accordingly. We conclude with the pros and cons of each technique and suggest the optimal metrology strategy for overlay control in double patterning processes.

Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing

NASA Technical Reports Server (NTRS)

Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.

2012-01-01

As imagery is collected from an airborne platform, an individual viewing the images wants to know from where on the Earth the images were collected. To do this, some information about the camera needs to be known, such as its position and orientation relative to the Earth. This can be provided by common inertial navigation systems (INS). Once the location of the camera is known, it is useful to project an image onto some representation of the Earth. Due to the non-smooth terrain of the Earth (mountains, valleys, etc.), this projection is highly non-linear. Thus, to ensure accurate projection, one needs to project onto a digital elevation map (DEM). This allows one to view the images overlaid onto a representation of the Earth. A code has been developed that takes an image, a model of the camera used to acquire that image, the pose of the camera during acquisition (as provided by an INS), and a DEM, and outputs an image that has been geo-rectified. The world coordinate of the bounds of the image are provided for viewing purposes. The code finds a mapping from points on the ground (DEM) to pixels in the image. By performing this process for all points on the ground, one can "paint" the ground with the image, effectively performing a projection of the image onto the ground. In order to make this process efficient, a method was developed for finding a region of interest (ROI) on the ground to where the image will project. This code is useful in any scenario involving an aerial imaging platform that moves and rotates over time. Many other applications are possible in processing aerial and satellite imagery.

Transportable and vibration-free full-field low-coherent quantitative phase microscope

NASA Astrophysics Data System (ADS)

Yamauchi, Toyohiko; Yamada, Hidenao; Goto, Kentaro; Matsui, Hisayuki; Yasuhiko, Osamu; Ueda, Yukio

2018-02-01

We developed a transportable Linnik-type full-field low-coherent quantitative phase microscope that is able to compensate for optical path length (OPL) disturbance due to environmental mechanical noises. Though two-beam interferometers such as Linnik ones suffer from unstable OPL difference, we overcame this problem with a mechanical feedback system based on digital signal-processing that controls the OPL difference in sub-nanometer resolution precisely with a feedback bandwidth of 4 kHz. The developed setup has a footprint of 200 mm by 200 mm, a height of 500 mm, and a weight of 4.5 kilograms. In the transmission imaging mode, cells were cultured on a reflection-enhanced glass-bottom dish, and we obtained interference images sequentially while performing stepwise quarter-wavelength phase-shifting. Real-time image processing, including retrieval of the unwrapped phase from interference images and its background correction, along with the acquisition of interference images, was performed on a laptop computer. Emulation of the phase contrast (PhC) images and the differential interference contrast (DIC) images was also performed in real time. Moreover, our setup was applied for full-field cell membrane imaging in the reflection mode, where the cells were cultured on an anti-reflection (AR)-coated glass-bottom dish. The phase and intensity of the light reflected by the membrane revealed the outer shape of the cells independent of the refractive index. In this paper, we show imaging results on cultured cells in both transmission and reflection modes.

Millimeter-wave Imaging Radiometer (MIR) data processing and development of water vapor retrieval algorithms

NASA Technical Reports Server (NTRS)

Chang, L. Aron

1995-01-01

This document describes the progress of the task of the Millimeter-wave Imaging Radiometer (MIR) data processing and the development of water vapor retrieval algorithms, for the second six-month performing period. Aircraft MIR data from two 1995 field experiments were collected and processed with a revised data processing software. Two revised versions of water vapor retrieval algorithm were developed, one for the execution of retrieval on a supercomputer platform, and one for using pressure as the vertical coordinate. Two implementations of incorporating products from other sensors into the water vapor retrieval system, one from the Special Sensor Microwave Imager (SSM/I), the other from the High-resolution Interferometer Sounder (HIS). Water vapor retrievals were performed for both airborne MIR data and spaceborne SSM/T-2 data, during field experiments of TOGA/COARE, CAMEX-1, and CAMEX-2. The climatology of water vapor during TOGA/COARE was examined by SSM/T-2 soundings and conventional rawinsonde.

Optical correlators for automated rendezvous and capture

NASA Technical Reports Server (NTRS)

Juday, Richard D.

1991-01-01

The paper begins with a description of optical correlation. In this process, the propagation physics of coherent light is used to process images and extract information. The processed image is operated on as an area, rather than as a collection of points. An essentially instantaneous convolution is performed on that image to provide the sensory data. In this process, an image is sensed and encoded onto a coherent wavefront, and the propagation is arranged to create a bright spot of the image to match a model of the desired object. The brightness of the spot provides an indication of the degree of resemblance of the viewed image to the mode, and the location of the bright spot provides pointing information. The process can be utilized for AR&C to achieve the capability to identify objects among known reference types, estimate the object's location and orientation, and interact with the control system. System characteristics (speed, robustness, accuracy, small form factors) are adequate to meet most requirements. The correlator exploits the fact that Bosons and Fermions pass through each other. Since the image source is input as an electronic data set, conventional imagers can be used. In systems where the image is input directly, the correlating element must be at the sensing location.

An image processing pipeline to detect and segment nuclei in muscle fiber microscopic images.

PubMed

Guo, Yanen; Xu, Xiaoyin; Wang, Yuanyuan; Wang, Yaming; Xia, Shunren; Yang, Zhong

2014-08-01

Muscle fiber images play an important role in the medical diagnosis and treatment of many muscular diseases. The number of nuclei in skeletal muscle fiber images is a key bio-marker of the diagnosis of muscular dystrophy. In nuclei segmentation one primary challenge is to correctly separate the clustered nuclei. In this article, we developed an image processing pipeline to automatically detect, segment, and analyze nuclei in microscopic image of muscle fibers. The pipeline consists of image pre-processing, identification of isolated nuclei, identification and segmentation of clustered nuclei, and quantitative analysis. Nuclei are initially extracted from background by using local Otsu's threshold. Based on analysis of morphological features of the isolated nuclei, including their areas, compactness, and major axis lengths, a Bayesian network is trained and applied to identify isolated nuclei from clustered nuclei and artifacts in all the images. Then a two-step refined watershed algorithm is applied to segment clustered nuclei. After segmentation, the nuclei can be quantified for statistical analysis. Comparing the segmented results with those of manual analysis and an existing technique, we find that our proposed image processing pipeline achieves good performance with high accuracy and precision. The presented image processing pipeline can therefore help biologists increase their throughput and objectivity in analyzing large numbers of nuclei in muscle fiber images. © 2014 Wiley Periodicals, Inc.

Evaluation of computed tomography post-processing images in postoperative assessment of Lisfranc injuries compared with plain radiographs.

PubMed

Li, Haobo; Chen, Yanxi; Qiang, Minfei; Zhang, Kun; Jiang, Yuchen; Zhang, Yijie; Jia, Xiaoyang

2017-06-14

The objective of this study is to evaluate the value of computed tomography (CT) post-processing images in postoperative assessment of Lisfranc injuries compared with plain radiographs. A total of 79 cases with closed Lisfranc injuries that were treated with conventional open reduction and internal fixation from January 2010 to June 2016 were analyzed. Postoperative assessment was performed by two independent orthopedic surgeons with both plain radiographs and CT post-processing images. Inter- and intra-observer agreement were analyzed by kappa statistics while the differences between the two postoperative imaging assessments were assessed using the χ 2 test (McNemar's test). Significance was assumed when p < 0.05. Inter- and intra-observer agreement of CT post-processing images was much higher than that of plain radiographs. Non-anatomic reduction was more easily identified in patients with injuries of Myerson classifications A, B1, B2, and C1 using CT post-processing images with overall groups (p < 0.05), and poor internal fixation was also more easily detected in patients with injuries of Myerson classifications A, B1, B2, and C2 using CT post-processing images with overall groups (p < 0.05). CT post-processing images can be more reliable than plain radiographs in the postoperative assessment of reduction and implant placement for Lisfranc injuries.

A Tentative Application Of Morphological Filters To Time-Varying Images

NASA Astrophysics Data System (ADS)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

CSAM Metrology Software Tool

NASA Technical Reports Server (NTRS)

Vu, Duc; Sandor, Michael; Agarwal, Shri

2005-01-01

CSAM Metrology Software Tool (CMeST) is a computer program for analysis of false-color CSAM images of plastic-encapsulated microcircuits. (CSAM signifies C-mode scanning acoustic microscopy.) The colors in the images indicate areas of delamination within the plastic packages. Heretofore, the images have been interpreted by human examiners. Hence, interpretations have not been entirely consistent and objective. CMeST processes the color information in image-data files to detect areas of delamination without incurring inconsistencies of subjective judgement. CMeST can be used to create a database of baseline images of packages acquired at given times for comparison with images of the same packages acquired at later times. Any area within an image can be selected for analysis, which can include examination of different delamination types by location. CMeST can also be used to perform statistical analyses of image data. Results of analyses are available in a spreadsheet format for further processing. The results can be exported to any data-base-processing software.

Rapid data processing for ultrafast X-ray computed tomography using scalable and modular CUDA based pipelines

NASA Astrophysics Data System (ADS)

Frust, Tobias; Wagner, Michael; Stephan, Jan; Juckeland, Guido; Bieberle, André

2017-10-01

Ultrafast X-ray tomography is an advanced imaging technique for the study of dynamic processes basing on the principles of electron beam scanning. A typical application case for this technique is e.g. the study of multiphase flows, that is, flows of mixtures of substances such as gas-liquidflows in pipelines or chemical reactors. At Helmholtz-Zentrum Dresden-Rossendorf (HZDR) a number of such tomography scanners are operated. Currently, there are two main points limiting their application in some fields. First, after each CT scan sequence the data of the radiation detector must be downloaded from the scanner to a data processing machine. Second, the current data processing is comparably time-consuming compared to the CT scan sequence interval. To enable online observations or use this technique to control actuators in real-time, a modular and scalable data processing tool has been developed, consisting of user-definable stages working independently together in a so called data processing pipeline, that keeps up with the CT scanner's maximal frame rate of up to 8 kHz. The newly developed data processing stages are freely programmable and combinable. In order to achieve the highest processing performance all relevant data processing steps, which are required for a standard slice image reconstruction, were individually implemented in separate stages using Graphics Processing Units (GPUs) and NVIDIA's CUDA programming language. Data processing performance tests on different high-end GPUs (Tesla K20c, GeForce GTX 1080, Tesla P100) showed excellent performance. Program Files doi:http://dx.doi.org/10.17632/65sx747rvm.1 Licensing provisions: LGPLv3 Programming language: C++/CUDA Supplementary material: Test data set, used for the performance analysis. Nature of problem: Ultrafast computed tomography is performed with a scan rate of up to 8 kHz. To obtain cross-sectional images from projection data computer-based image reconstruction algorithms must be applied. The objective of the presented program is to reconstruct a data stream of around 1.3 GB s-1 in a minimum time period. Thus, the program allows to go into new fields of application and to use in the future even more compute-intensive algorithms, especially for data post-processing, to improve the quality of data analysis. Solution method: The program solves the given problem using a two-step process: first, by a generic, expandable and widely applicable template library implementing the streaming paradigm (GLADOS); second, by optimized processing stages for ultrafast computed tomography implementing the required algorithms in a performance-oriented way using CUDA (RISA). Thereby, task-parallelism between the processing stages as well as data parallelism within one processing stage is realized.

Performance of a Method to Standardize Breast Ultrasound Interpretation Using Image Processing and Case-Based Reasoning

NASA Astrophysics Data System (ADS)

André, M. P.; Galperin, M.; Berry, A.; Ojeda-Fournier, H.; O'Boyle, M.; Olson, L.; Comstock, C.; Taylor, A.; Ledgerwood, M.

Our computer-aided diagnostic (CADx) tool uses advanced image processing and artificial intelligence to analyze findings on breast sonography images. The goal is to standardize reporting of such findings using well-defined descriptors and to improve accuracy and reproducibility of interpretation of breast ultrasound by radiologists. This study examined several factors that may impact accuracy and reproducibility of the CADx software, which proved to be highly accurate and stabile over several operating conditions.

Towards real-time remote processing of laparoscopic video

NASA Astrophysics Data System (ADS)

Ronaghi, Zahra; Duffy, Edward B.; Kwartowitz, David M.

2015-03-01

Laparoscopic surgery is a minimally invasive surgical technique where surgeons insert a small video camera into the patient's body to visualize internal organs and small tools to perform surgical procedures. However, the benefit of small incisions has a drawback of limited visualization of subsurface tissues, which can lead to navigational challenges in the delivering of therapy. Image-guided surgery (IGS) uses images to map subsurface structures and can reduce the limitations of laparoscopic surgery. One particular laparoscopic camera system of interest is the vision system of the daVinci-Si robotic surgical system (Intuitive Surgical, Sunnyvale, CA, USA). The video streams generate approximately 360 megabytes of data per second, demonstrating a trend towards increased data sizes in medicine, primarily due to higher-resolution video cameras and imaging equipment. Processing this data on a bedside PC has become challenging and a high-performance computing (HPC) environment may not always be available at the point of care. To process this data on remote HPC clusters at the typical 30 frames per second (fps) rate, it is required that each 11.9 MB video frame be processed by a server and returned within 1/30th of a second. The ability to acquire, process and visualize data in real-time is essential for performance of complex tasks as well as minimizing risk to the patient. As a result, utilizing high-speed networks to access computing clusters will lead to real-time medical image processing and improve surgical experiences by providing real-time augmented laparoscopic data. We aim to develop a medical video processing system using an OpenFlow software defined network that is capable of connecting to multiple remote medical facilities and HPC servers.

Automation of image data processing. (Polish Title: Automatyzacja proces u przetwarzania danych obrazowych)

NASA Astrophysics Data System (ADS)

Preuss, R.

2014-12-01

This article discusses the current capabilities of automate processing of the image data on the example of using PhotoScan software by Agisoft. At present, image data obtained by various registration systems (metric and non - metric cameras) placed on airplanes, satellites, or more often on UAVs is used to create photogrammetric products. Multiple registrations of object or land area (large groups of photos are captured) are usually performed in order to eliminate obscured area as well as to raise the final accuracy of the photogrammetric product. Because of such a situation t he geometry of the resulting image blocks is far from the typical configuration of images. For fast images georeferencing automatic image matching algorithms are currently applied. They can create a model of a block in the local coordinate system or using initial exterior orientation and measured control points can provide image georeference in an external reference frame. In the case of non - metric image application, it is also possible to carry out self - calibration process at this stage. Image matching algorithm is also used in generation of dense point clouds reconstructing spatial shape of the object (area). In subsequent processing steps it is possible to obtain typical photogrammetric products such as orthomosaic, DSM or DTM and a photorealistic solid model of an object . All aforementioned processing steps are implemented in a single program in contrary to standard commercial software dividing all steps into dedicated modules. Image processing leading to final geo referenced products can be fully automated including sequential implementation of the processing steps at predetermined control parameters. The paper presents the practical results of the application fully automatic generation of othomosaic for both images obtained by a metric Vexell camera and a block of images acquired by a non - metric UAV system

Parallel Processing of Images in Mobile Devices using BOINC

NASA Astrophysics Data System (ADS)

Curiel, Mariela; Calle, David F.; Santamaría, Alfredo S.; Suarez, David F.; Flórez, Leonardo

2018-04-01

Medical image processing helps health professionals make decisions for the diagnosis and treatment of patients. Since some algorithms for processing images require substantial amounts of resources, one could take advantage of distributed or parallel computing. A mobile grid can be an adequate computing infrastructure for this problem. A mobile grid is a grid that includes mobile devices as resource providers. In a previous step of this research, we selected BOINC as the infrastructure to build our mobile grid. However, parallel processing of images in mobile devices poses at least two important challenges: the execution of standard libraries for processing images and obtaining adequate performance when compared to desktop computers grids. By the time we started our research, the use of BOINC in mobile devices also involved two issues: a) the execution of programs in mobile devices required to modify the code to insert calls to the BOINC API, and b) the division of the image among the mobile devices as well as its merging required additional code in some BOINC components. This article presents answers to these four challenges.

An optimized digital watermarking algorithm in wavelet domain based on differential evolution for color image.

PubMed

Cui, Xinchun; Niu, Yuying; Zheng, Xiangwei; Han, Yingshuai

2018-01-01

In this paper, a new color watermarking algorithm based on differential evolution is proposed. A color host image is first converted from RGB space to YIQ space, which is more suitable for the human visual system. Then, apply three-level discrete wavelet transformation to luminance component Y and generate four different frequency sub-bands. After that, perform singular value decomposition on these sub-bands. In the watermark embedding process, apply discrete wavelet transformation to a watermark image after the scrambling encryption processing. Our new algorithm uses differential evolution algorithm with adaptive optimization to choose the right scaling factors. Experimental results show that the proposed algorithm has a better performance in terms of invisibility and robustness.

Assessing the Performance of Medical Personnel Involved in the Diagnostic Imaging Processes in Mulago Hospital, Kampala, Uganda

PubMed Central

Kawooya, Michael G.; Pariyo, George; Malwadde, Elsie Kiguli; Byanyima, Rosemary; Kisembo, Harrient

2012-01-01

Objectives: Uganda, has limited health resources and improving performance of personnel involved in imaging is necessary for efficiency. The objectives of the study were to develop and pilot imaging user performance indices, document non-tangible aspects of performance, and propose ways of improving performance. Materials and Methods: This was a cross-sectional survey employing triangulation methodology, conducted in Mulago National Referral Hospital over a period of 3 years from 2005 to 2008. The qualitative study used in-depth interviews, focus group discussions, and self-administered questionnaires, to explore clinicians’ and radiologists’ performancerelated views. Results: The study came up with following indices: appropriate service utilization (ASU), appropriateness of clinician's nonimaging decisions (ANID), and clinical utilization of imaging results (CUI). The ASU, ANID, and CUI were: 94%, 80%, and 97%, respectively. The clinician's requisitioning validity was high (positive likelihood ratio of 10.6) contrasting with a poor validity for detecting those patients not needing imaging (negative likelihood ratio of 0.16). Some requisitions were inappropriate and some requisition and reports lacked detail, clarity, and precision. Conclusion: Clinicians perform well at imaging requisition-decisions but there are issues in imaging requisitioning and reporting that need to be addressed to improve performance. PMID:23230543

Next Generation UAS Based Spectral Systems for Environmental Monitoring

NASA Technical Reports Server (NTRS)

Campbell, P.; Townsend, P.; Mandl, D.; Kingdon, C.; Ly, V.; Sohlberg, R.; Corp, L.; Cappelaere, P.; Frye, S.; Handy, M.;

Radiometric and Geometric Accuracy Analysis of Rasat Pan Imagery

NASA Astrophysics Data System (ADS)

Kocaman, S.; Yalcin, I.; Guler, M.

2016-06-01

RASAT is the second Turkish Earth Observation satellite which was launched in 2011. It operates with pushbroom principle and acquires panchromatic and MS images with 7.5 m and 15 m resolutions, respectively. The swath width of the sensor is 30 km. The main aim of this study is to analyse the radiometric and geometric quality of RASAT images. A systematic validation approach for the RASAT imagery and its products is being applied. RASAT image pair acquired over Kesan city in Edirne province of Turkey are used for the investigations. The raw RASAT data (L0) are processed by Turkish Space Agency (TUBITAK-UZAY) to produce higher level image products. The image products include radiometrically processed (L1), georeferenced (L2) and orthorectified (L3) data, as well as pansharpened images. The image quality assessments include visual inspections, noise, MTF and histogram analyses. The geometric accuracy assessment results are only preliminary and the assessment is performed using the raw images. The geometric accuracy potential is investigated using 3D ground control points extracted from road intersections, which were measured manually in stereo from aerial images with 20 cm resolution and accuracy. The initial results of the study, which were performed using one RASAT panchromatic image pair, are presented in this paper.

Efficient image acquisition design for a cancer detection system

NASA Astrophysics Data System (ADS)

Nguyen, Dung; Roehrig, Hans; Borders, Marisa H.; Fitzpatrick, Kimberly A.; Roveda, Janet

2013-09-01

Modern imaging modalities, such as Computed Tomography (CT), Digital Breast Tomosynthesis (DBT) or Magnetic Resonance Tomography (MRT) are able to acquire volumetric images with an isotropic resolution in micrometer (um) or millimeter (mm) range. When used in interactive telemedicine applications, these raw images need a huge storage unit, thereby necessitating the use of high bandwidth data communication link. To reduce the cost of transmission and enable archiving, especially for medical applications, image compression is performed. Recent advances in compression algorithms have resulted in a vast array of data compression techniques, but because of the characteristics of these images, there are challenges to overcome to transmit these images efficiently. In addition, the recent studies raise the low dose mammography risk on high risk patient. Our preliminary studies indicate that by bringing the compression before the analog-to-digital conversion (ADC) stage is more efficient than other compression techniques after the ADC. The linearity characteristic of the compressed sensing and ability to perform the digital signal processing (DSP) during data conversion open up a new area of research regarding the roles of sparsity in medical image registration, medical image analysis (for example, automatic image processing algorithm to efficiently extract the relevant information for the clinician), further Xray dose reduction for mammography, and contrast enhancement.

Novel optical scanning cryptography using Fresnel telescope imaging.

PubMed

Yan, Aimin; Sun, Jianfeng; Hu, Zhijuan; Zhang, Jingtao; Liu, Liren

2015-07-13

We propose a new method called modified optical scanning cryptography using Fresnel telescope imaging technique for encryption and decryption of remote objects. An image or object can be optically encrypted on the fly by Fresnel telescope scanning system together with an encryption key. For image decryption, the encrypted signals are received and processed with an optical coherent heterodyne detection system. The proposed method has strong performance through use of secure Fresnel telescope scanning with orthogonal polarized beams and efficient all-optical information processing. The validity of the proposed method is demonstrated by numerical simulations and experimental results.

The highs and lows of object impossibility: effects of spatial frequency on holistic processing of impossible objects.

PubMed

Freud, Erez; Avidan, Galia; Ganel, Tzvi

2015-02-01

Holistic processing, the decoding of a stimulus as a unified whole, is a basic characteristic of object perception. Recent research using Garner's speeded classification task has shown that this processing style is utilized even for impossible objects that contain an inherent spatial ambiguity. In particular, similar Garner interference effects were found for possible and impossible objects, indicating similar holistic processing styles for the two object categories. In the present study, we further investigated the perceptual mechanisms that mediate such holistic representation of impossible objects. We relied on the notion that, whereas information embedded in the high-spatial-frequency (HSF) content supports fine-detailed processing of object features, the information conveyed by low spatial frequencies (LSF) is more crucial for the emergence of a holistic shape representation. To test the effects of image frequency on the holistic processing of impossible objects, participants performed the Garner speeded classification task on images of possible and impossible cubes filtered for their LSF and HSF information. For images containing only LSF, similar interference effects were observed for possible and impossible objects, indicating that the two object categories were processed in a holistic manner. In contrast, for the HSF images, Garner interference was obtained only for possible, but not for impossible objects. Importantly, we provided evidence to show that this effect could not be attributed to a lack of sensitivity to object possibility in the LSF images. Particularly, even for full-spectrum images, Garner interference was still observed for both possible and impossible objects. Additionally, performance in an object classification task revealed high sensitivity to object possibility, even for LSF images. Taken together, these findings suggest that the visual system can tolerate the spatial ambiguity typical to impossible objects by relying on information embedded in LSF, whereas HSF information may underlie the visual system's susceptibility to distortions in objects' spatial layouts.

Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

NASA Astrophysics Data System (ADS)

Gnyawali, Surya C.; Blum, Kevin; Pal, Durba; Ghatak, Subhadip; Khanna, Savita; Roy, Sashwati; Sen, Chandan K.

2017-01-01

Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system.

Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

PubMed Central

Gnyawali, Surya C.; Blum, Kevin; Pal, Durba; Ghatak, Subhadip; Khanna, Savita; Roy, Sashwati; Sen, Chandan K.

2017-01-01

Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system. PMID:28106129

Utilization of a balanced steady state free precession signal model for improved fat/water decomposition.

PubMed

Henze Bancroft, Leah C; Strigel, Roberta M; Hernando, Diego; Johnson, Kevin M; Kelcz, Frederick; Kijowski, Richard; Block, Walter F

2016-03-01

Chemical shift based fat/water decomposition methods such as IDEAL are frequently used in challenging imaging environments with large B0 inhomogeneity. However, they do not account for the signal modulations introduced by a balanced steady state free precession (bSSFP) acquisition. Here we demonstrate improved performance when the bSSFP frequency response is properly incorporated into the multipeak spectral fat model used in the decomposition process. Balanced SSFP allows for rapid imaging but also introduces a characteristic frequency response featuring periodic nulls and pass bands. Fat spectral components in adjacent pass bands will experience bulk phase offsets and magnitude modulations that change the expected constructive and destructive interference between the fat spectral components. A bSSFP signal model was incorporated into the fat/water decomposition process and used to generate images of a fat phantom, and bilateral breast and knee images in four normal volunteers at 1.5 Tesla. Incorporation of the bSSFP signal model into the decomposition process improved the performance of the fat/water decomposition. Incorporation of this model allows rapid bSSFP imaging sequences to use robust fat/water decomposition methods such as IDEAL. While only one set of imaging parameters were presented, the method is compatible with any field strength or repetition time. © 2015 Wiley Periodicals, Inc.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

PubMed Central

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

An efficient approach to integrated MeV ion imaging.

PubMed

Nikbakht, T; Kakuee, O; Solé, V A; Vosuoghi, Y; Lamehi-Rachti, M

2018-03-01

An ionoluminescence (IL) spectral imaging system, besides the common MeV ion imaging facilities such as µ-PIXE and µ-RBS, is implemented at the Van de Graaff laboratory of Tehran. A versatile processing software is required to handle the large amount of data concurrently collected in µ-IL and common MeV ion imaging measurements through the respective methodologies. The open-source freeware PyMca, with image processing and multivariate analysis capabilities, is employed to simultaneously process common MeV ion imaging and µ-IL data. Herein, the program was adapted to support the OM_DAQ listmode data format. The appropriate performance of the µ-IL data acquisition system is confirmed through a case study. Moreover, the capabilities of the software for simultaneous analysis of µ-PIXE and µ-RBS experimental data are presented. Copyright © 2017 Elsevier B.V. All rights reserved.

Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

2018-04-01

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

An automated image processing method for classification of diabetic retinopathy stages from conjunctival microvasculature images

NASA Astrophysics Data System (ADS)

Khansari, Maziyar M.; O'Neill, William; Penn, Richard; Blair, Norman P.; Chau, Felix; Shahidi, Mahnaz

2017-03-01

The conjunctiva is a densely vascularized tissue of the eye that provides an opportunity for imaging of human microcirculation. In the current study, automated fine structure analysis of conjunctival microvasculature images was performed to discriminate stages of diabetic retinopathy (DR). The study population consisted of one group of nondiabetic control subjects (NC) and 3 groups of diabetic subjects, with no clinical DR (NDR), non-proliferative DR (NPDR), or proliferative DR (PDR). Ordinary least square regression and Fisher linear discriminant analyses were performed to automatically discriminate images between group pairs of subjects. Human observers who were masked to the grouping of subjects performed image discrimination between group pairs. Over 80% and 70% of images of subjects with clinical and non-clinical DR were correctly discriminated by the automated method, respectively. The discrimination rates of the automated method were higher than human observers. The fine structure analysis of conjunctival microvasculature images provided discrimination of DR stages and can be potentially useful for DR screening and monitoring.

Fundamental performance differences of CMOS and CCD imagers: part V

NASA Astrophysics Data System (ADS)

Janesick, James R.; Elliott, Tom; Andrews, James; Tower, John; Pinter, Jeff

2013-02-01

Previous papers delivered over the last decade have documented developmental progress made on large pixel scientific CMOS imagers that match or surpass CCD performance. New data and discussions presented in this paper include: 1) a new buried channel CCD fabricated on a CMOS process line, 2) new data products generated by high performance custom scientific CMOS 4T/5T/6T PPD pixel imagers, 3) ultimate CTE and speed limits for large pixel CMOS imagers, 4) fabrication and test results of a flight 4k x 4k CMOS imager for NRL's SoloHi Solar Orbiter Mission, 5) a progress report on ultra large stitched Mk x Nk CMOS imager, 6) data generated by on-chip sub-electron CDS signal chain circuitry used in our imagers, 7) CMOS and CMOSCCD proton and electron radiation damage data for dose levels up to 10 Mrd, 8) discussions and data for a new class of PMOS pixel CMOS imagers and 9) future CMOS development work planned.

Self-Organizing Neural Network Map for the Purpose of Visualizing the Concept Images of Students on Angles

ERIC Educational Resources Information Center

Kaya, Deniz

2017-01-01

The purpose of the study is to perform a less-dimensional thorough visualization process for the purpose of determining the images of the students on the concept of angle. The Ward clustering analysis combined with Self-Organizing Neural Network Map (SOM) has been used for the dimension process. The Conceptual Understanding Tool, which consisted…

A methodology for evaluation of an interactive multispectral image processing system

NASA Technical Reports Server (NTRS)

Kovalick, William M.; Newcomer, Jeffrey A.; Wharton, Stephen W.

1987-01-01

Because of the considerable cost of an interactive multispectral image processing system, an evaluation of a prospective system should be performed to ascertain if it will be acceptable to the anticipated users. Evaluation of a developmental system indicated that the important system elements include documentation, user friendliness, image processing capabilities, and system services. The criteria and evaluation procedures for these elements are described herein. The following factors contributed to the success of the evaluation of the developmental system: (1) careful review of documentation prior to program development, (2) construction and testing of macromodules representing typical processing scenarios, (3) availability of other image processing systems for referral and verification, and (4) use of testing personnel with an applications perspective and experience with other systems. This evaluation was done in addition to and independently of program testing by the software developers of the system.

Possibility Study of Scale Invariant Feature Transform (SIFT) Algorithm Application to Spine Magnetic Resonance Imaging

PubMed Central

Lee, Dong-Hoon; Lee, Do-Wan; Han, Bong-Soo

2016-01-01

The purpose of this study is an application of scale invariant feature transform (SIFT) algorithm to stitch the cervical-thoracic-lumbar (C-T-L) spine magnetic resonance (MR) images to provide a view of the entire spine in a single image. All MR images were acquired with fast spin echo (FSE) pulse sequence using two MR scanners (1.5 T and 3.0 T). The stitching procedures for each part of spine MR image were performed and implemented on a graphic user interface (GUI) configuration. Moreover, the stitching process is performed in two categories; manual point-to-point (mPTP) selection that performed by user specified corresponding matching points, and automated point-to-point (aPTP) selection that performed by SIFT algorithm. The stitched images using SIFT algorithm showed fine registered results and quantitatively acquired values also indicated little errors compared with commercially mounted stitching algorithm in MRI systems. Our study presented a preliminary validation of the SIFT algorithm application to MRI spine images, and the results indicated that the proposed approach can be performed well for the improvement of diagnosis. We believe that our approach can be helpful for the clinical application and extension of other medical imaging modalities for image stitching. PMID:27064404

Platform for intraoperative analysis of video streams

NASA Astrophysics Data System (ADS)

Clements, Logan; Galloway, Robert L., Jr.

2004-05-01

Interactive, image-guided surgery (IIGS) has proven to increase the specificity of a variety of surgical procedures. However, current IIGS systems do not compensate for changes that occur intraoperatively and are not reflected in preoperative tomograms. Endoscopes and intraoperative ultrasound, used in minimally invasive surgery, provide real-time (RT) information in a surgical setting. Combining the information from RT imaging modalities with traditional IIGS techniques will further increase surgical specificity by providing enhanced anatomical information. In order to merge these techniques and obtain quantitative data from RT imaging modalities, a platform was developed to allow both the display and processing of video streams in RT. Using a Bandit-II CV frame grabber board (Coreco Imaging, St. Laurent, Quebec) and the associated library API, a dynamic link library was created in Microsoft Visual C++ 6.0 such that the platform could be incorporated into the IIGS system developed at Vanderbilt University. Performance characterization, using two relatively inexpensive host computers, has shown the platform capable of performing simple image processing operations on frames captured from a CCD camera and displaying the processed video data at near RT rates both independent of and while running the IIGS system.

The relationship between three-dimensional imaging and group decision making: an exploratory study.

PubMed

Litynski, D M; Grabowski, M; Wallace, W A

1997-07-01

This paper describes an empirical investigation of the effect of three dimensional (3-D) imaging on group performance in a tactical planning task. The objective of the study is to examine the role that stereoscopic imaging can play in supporting face-to-face group problem solving and decision making-in particular, the alternative generation and evaluation processes in teams. It was hypothesized that with the stereoscopic display, group members would better visualize the information concerning the task environment, producing open communication and information exchanges. The experimental setting was a tactical command and control task, and the quality of the decisions and nature of the group decision process were investigated with three treatments: 1) noncomputerized, i.e., topographic maps with depth cues; 2) two-dimensional (2-D) imaging; and 3) stereoscopic imaging. The results were mixed on group performance. However, those groups with the stereoscopic displays generated more alternatives and spent less time on evaluation. In addition, the stereoscopic decision aid did not interfere with the group problem solving and decision-making processes. The paper concludes with a discussion of potential benefits, and the need to resolve demonstrated weaknesses of the technology.

Working memory and decision processes in visual area v4.

PubMed

Hayden, Benjamin Y; Gallant, Jack L

2013-01-01

Recognizing and responding to a remembered stimulus requires the coordination of perception, working memory, and decision-making. To investigate the role of visual cortex in these processes, we recorded responses of single V4 neurons during performance of a delayed match-to-sample task that incorporates rapid serial visual presentation of natural images. We found that neuronal activity during the delay period after the cue but before the images depends on the identity of the remembered image and that this change persists while distractors appear. This persistent response modulation has been identified as a diagnostic criterion for putative working memory signals; our data thus suggest that working memory may involve reactivation of sensory neurons. When the remembered image reappears in the neuron's receptive field, visually evoked responses are enhanced; this match enhancement is a diagnostic criterion for decision. One model that predicts these data is the matched filter hypothesis, which holds that during search V4 neurons change their tuning so as to match the remembered cue, and thus become detectors for that image. More generally, these results suggest that V4 neurons participate in the perceptual, working memory, and decision processes that are needed to perform memory-guided decision-making.

Fusing Image Data for Calculating Position of an Object

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Cheng, Yang; Liebersbach, Robert; Trebi-Ollenu, Ashitey

2007-01-01

A computer program has been written for use in maintaining the calibration, with respect to the positions of imaged objects, of a stereoscopic pair of cameras on each of the Mars Explorer Rovers Spirit and Opportunity. The program identifies and locates a known object in the images. The object in question is part of a Moessbauer spectrometer located at the tip of a robot arm, the kinematics of which are known. In the program, the images are processed through a module that extracts edges, combines the edges into line segments, and then derives ellipse centroids from the line segments. The images are also processed by a feature-extraction algorithm that performs a wavelet analysis, then performs a pattern-recognition operation in the wavelet-coefficient space to determine matches to a texture feature measure derived from the horizontal, vertical, and diagonal coefficients. The centroids from the ellipse finder and the wavelet feature matcher are then fused to determine co-location. In the event that a match is found, the centroid (or centroids if multiple matches are present) is reported. If no match is found, the process reports the results of the analyses for further examination by human experts.

Real-time thermal imaging of solid oxide fuel cell cathode activity in working condition.

PubMed

Montanini, Roberto; Quattrocchi, Antonino; Piccolo, Sebastiano A; Amato, Alessandra; Trocino, Stefano; Zignani, Sabrina C; Faro, Massimiliano Lo; Squadrito, Gaetano

2016-09-01

Electrochemical methods such as voltammetry and electrochemical impedance spectroscopy are effective for quantifying solid oxide fuel cell (SOFC) operational performance, but not for identifying and monitoring the chemical processes that occur on the electrodes' surface, which are thought to be strictly related to the SOFCs' efficiency. Because of their high operating temperature, mechanical failure or cathode delamination is a common shortcoming of SOFCs that severely affects their reliability. Infrared thermography may provide a powerful tool for probing in situ SOFC electrode processes and the materials' structural integrity, but, due to the typical design of pellet-type cells, a complete optical access to the electrode surface is usually prevented. In this paper, a specially designed SOFC is introduced, which allows temperature distribution to be measured over all the cathode area while still preserving the electrochemical performance of the device. Infrared images recorded under different working conditions are then processed by means of a dedicated image processing algorithm for quantitative data analysis. Results reported in the paper highlight the effectiveness of infrared thermal imaging in detecting the onset of cell failure during normal operation and in monitoring cathode activity when the cell is fed with different types of fuels.

Super-Resolution for “Jilin-1” Satellite Video Imagery via a Convolutional Network

PubMed Central

Wang, Zhongyuan; Wang, Lei; Ren, Yexian

2018-01-01

Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method’s practicality. Experimental results on “Jilin-1” satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods. PMID:29652838

Super-Resolution for "Jilin-1" Satellite Video Imagery via a Convolutional Network.

PubMed

Xiao, Aoran; Wang, Zhongyuan; Wang, Lei; Ren, Yexian

2018-04-13

Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method's practicality. Experimental results on "Jilin-1" satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

In-Line Monitoring of a Pharmaceutical Pan Coating Process by Optical Coherence Tomography.

PubMed

Markl, Daniel; Hannesschläger, Günther; Sacher, Stephan; Leitner, Michael; Buchsbaum, Andreas; Pescod, Russel; Baele, Thomas; Khinast, Johannes G

2015-08-01

This work demonstrates a new in-line measurement technique for monitoring the coating growth of randomly moving tablets in a pan coating process. In-line quality control is performed by an optical coherence tomography (OCT) sensor allowing nondestructive and contact-free acquisition of cross-section images of film coatings in real time. The coating thickness can be determined directly from these OCT images and no chemometric calibration models are required for quantification. Coating thickness measurements are extracted from the images by a fully automated algorithm. Results of the in-line measurements are validated using off-line OCT images, thickness calculations from tablet dimension measurements, and weight gain measurements. Validation measurements are performed on sample tablets periodically removed from the process during production. Reproducibility of the results is demonstrated by three batches produced under the same process conditions. OCT enables a multiple direct measurement of the coating thickness on individual tablets rather than providing the average coating thickness of a large number of tablets. This gives substantially more information about the coating quality, that is, intra- and intertablet coating variability, than standard quality control methods. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

Attitude-error compensation for airborne down-looking synthetic-aperture imaging lidar

NASA Astrophysics Data System (ADS)

Li, Guang-yuan; Sun, Jian-feng; Zhou, Yu; Lu, Zhi-yong; Zhang, Guo; Cai, Guang-yu; Liu, Li-ren

2017-11-01

Target-coordinate transformation in the lidar spot of the down-looking synthetic-aperture imaging lidar (SAIL) was performed, and the attitude errors were deduced in the process of imaging, according to the principle of the airborne down-looking SAIL. The influence of the attitude errors on the imaging quality was analyzed theoretically. A compensation method for the attitude errors was proposed and theoretically verified. An airborne down-looking SAIL experiment was performed and yielded the same results. A point-by-point error-compensation method for solving the azimuthal-direction space-dependent attitude errors was also proposed.

Grayscale image segmentation for real-time traffic sign recognition: the hardware point of view

NASA Astrophysics Data System (ADS)

Cao, Tam P.; Deng, Guang; Elton, Darrell

2009-02-01

In this paper, we study several grayscale-based image segmentation methods for real-time road sign recognition applications on an FPGA hardware platform. The performance of different image segmentation algorithms in different lighting conditions are initially compared using PC simulation. Based on these results and analysis, suitable algorithms are implemented and tested on a real-time FPGA speed sign detection system. Experimental results show that the system using segmented images uses significantly less hardware resources on an FPGA while maintaining comparable system's performance. The system is capable of processing 60 live video frames per second.

Performance comparison of ISAR imaging method based on time frequency transforms

NASA Astrophysics Data System (ADS)

Xie, Chunjian; Guo, Chenjiang; Xu, Jiadong

2013-03-01

Inverse synthetic aperture radar (ISAR) can image the moving target, especially the target in the air, so it is important in the air defence and missile defence system. Time-frequency Transform was applied to ISAR imaging process widely. Several time frequency transforms were introduced. Noise jamming methods were analysed, and when these noise jamming were added to the echo of the ISAR receiver, the image can become blur even can't to be identify. But the effect is different to the different time frequency analysis. The results of simulation experiment show the Performance Comparison of the method.

Enhancing hyperspectral spatial resolution using multispectral image fusion: A wavelet approach

NASA Astrophysics Data System (ADS)

Jazaeri, Amin

High spectral and spatial resolution images have a significant impact in remote sensing applications. Because both spatial and spectral resolutions of spaceborne sensors are fixed by design and it is not possible to further increase the spatial or spectral resolution, techniques such as image fusion must be applied to achieve such goals. This dissertation introduces the concept of wavelet fusion between hyperspectral and multispectral sensors in order to enhance the spectral and spatial resolution of a hyperspectral image. To test the robustness of this concept, images from Hyperion (hyperspectral sensor) and Advanced Land Imager (multispectral sensor) were first co-registered and then fused using different wavelet algorithms. A regression-based fusion algorithm was also implemented for comparison purposes. The results show that the fused images using a combined bi-linear wavelet-regression algorithm have less error than other methods when compared to the ground truth. In addition, a combined regression-wavelet algorithm shows more immunity to misalignment of the pixels due to the lack of proper registration. The quantitative measures of average mean square error show that the performance of wavelet-based methods degrades when the spatial resolution of hyperspectral images becomes eight times less than its corresponding multispectral image. Regardless of what method of fusion is utilized, the main challenge in image fusion is image registration, which is also a very time intensive process. Because the combined regression wavelet technique is computationally expensive, a hybrid technique based on regression and wavelet methods was also implemented to decrease computational overhead. However, the gain in faster computation was offset by the introduction of more error in the outcome. The secondary objective of this dissertation is to examine the feasibility and sensor requirements for image fusion for future NASA missions in order to be able to perform onboard image fusion. In this process, the main challenge of image registration was resolved by registering the input images using transformation matrices of previously acquired data. The composite image resulted from the fusion process remarkably matched the ground truth, indicating the possibility of real time onboard fusion processing.

Automation of Cassini Support Imaging Uplink Command Development

NASA Technical Reports Server (NTRS)

Ly-Hollins, Lisa; Breneman, Herbert H.; Brooks, Robert

2010-01-01

"Support imaging" is imagery requested by other Cassini science teams to aid in the interpretation of their data. The generation of the spacecraft command sequences for these images is performed by the Cassini Instrument Operations Team. The process initially established for doing this was very labor-intensive, tedious and prone to human error. Team management recognized this process as one that could easily benefit from automation. Team members were tasked to document the existing manual process, develop a plan and strategy to automate the process, implement the plan and strategy, test and validate the new automated process, and deliver the new software tools and documentation to Flight Operations for use during the Cassini extended mission. In addition to the goals of higher efficiency and lower risk in the processing of support imaging requests, an effort was made to maximize adaptability of the process to accommodate uplink procedure changes and the potential addition of new capabilities outside the scope of the initial effort.

On-demand server-side image processing for web-based DICOM image display

NASA Astrophysics Data System (ADS)

Sakusabe, Takaya; Kimura, Michio; Onogi, Yuzo

2000-04-01

Low cost image delivery is needed in modern networked hospitals. If a hospital has hundreds of clients, cost of client systems is a big problem. Naturally, a Web-based system is the most effective solution. But a Web browser could not display medical images with certain image processing such as a lookup table transformation. We developed a Web-based medical image display system using Web browser and on-demand server-side image processing. All images displayed on a Web page are generated from DICOM files on a server, delivered on-demand. User interaction on the Web page is handled by a client-side scripting technology such as JavaScript. This combination makes a look-and-feel of an imaging workstation not only for its functionality but also for its speed. Real time update of images with tracing mouse motion is achieved on Web browser without any client-side image processing which may be done by client-side plug-in technology such as Java Applets or ActiveX. We tested performance of the system in three cases. Single client, small number of clients in a fast speed network, and large number of clients in a normal speed network. The result shows that there are very slight overhead for communication and very scalable in number of clients.

Image processing can cause some malignant soft-tissue lesions to be missed in digital mammography images.

PubMed

Warren, L M; Halling-Brown, M D; Looney, P T; Dance, D R; Wallis, M G; Given-Wilson, R M; Wilkinson, L; McAvinchey, R; Young, K C

2017-09-01

To investigate the effect of image processing on cancer detection in mammography. An observer study was performed using 349 digital mammography images of women with normal breasts, calcification clusters, or soft-tissue lesions including 191 subtle cancers. Images underwent two types of processing: FlavourA (standard) and FlavourB (added enhancement). Six observers located features in the breast they suspected to be cancerous (4,188 observations). Data were analysed using jackknife alternative free-response receiver operating characteristic (JAFROC) analysis. Characteristics of the cancers detected with each image processing type were investigated. For calcifications, the JAFROC figure of merit (FOM) was equal to 0.86 for both types of image processing. For soft-tissue lesions, the JAFROC FOM were better for FlavourA (0.81) than FlavourB (0.78); this difference was significant (p=0.001). Using FlavourA a greater number of cancers of all grades and sizes were detected than with FlavourB. FlavourA improved soft-tissue lesion detection in denser breasts (p=0.04 when volumetric density was over 7.5%) CONCLUSIONS: The detection of malignant soft-tissue lesions (which were primarily invasive) was significantly better with FlavourA than FlavourB image processing. This is despite FlavourB having a higher contrast appearance often preferred by radiologists. It is important that clinical choice of image processing is based on objective measures. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Block-based scalable wavelet image codec

NASA Astrophysics Data System (ADS)

Bao, Yiliang; Kuo, C.-C. Jay

1999-10-01

This paper presents a high performance block-based wavelet image coder which is designed to be of very low implementational complexity yet with rich features. In this image coder, the Dual-Sliding Wavelet Transform (DSWT) is first applied to image data to generate wavelet coefficients in fixed-size blocks. Here, a block only consists of wavelet coefficients from a single subband. The coefficient blocks are directly coded with the Low Complexity Binary Description (LCBiD) coefficient coding algorithm. Each block is encoded using binary context-based bitplane coding. No parent-child correlation is exploited in the coding process. There is also no intermediate buffering needed in between DSWT and LCBiD. The compressed bit stream generated by the proposed coder is both SNR and resolution scalable, as well as highly resilient to transmission errors. Both DSWT and LCBiD process the data in blocks whose size is independent of the size of the original image. This gives more flexibility in the implementation. The codec has a very good coding performance even the block size is (16,16).

Application of the EM algorithm to radiographic images.

PubMed

Brailean, J C; Little, D; Giger, M L; Chen, C T; Sullivan, B J

1992-01-01

The expectation maximization (EM) algorithm has received considerable attention in the area of positron emitted tomography (PET) as a restoration and reconstruction technique. In this paper, the restoration capabilities of the EM algorithm when applied to radiographic images is investigated. This application does not involve reconstruction. The performance of the EM algorithm is quantitatively evaluated using a "perceived" signal-to-noise ratio (SNR) as the image quality metric. This perceived SNR is based on statistical decision theory and includes both the observer's visual response function and a noise component internal to the eye-brain system. For a variety of processing parameters, the relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to compare quantitatively the effects of the EM algorithm with two other image enhancement techniques: global contrast enhancement (windowing) and unsharp mask filtering. The results suggest that the EM algorithm's performance is superior when compared to unsharp mask filtering and global contrast enhancement for radiographic images which contain objects smaller than 4 mm.

The effects of gray scale image processing on digital mammography interpretation performance.

PubMed

Cole, Elodia B; Pisano, Etta D; Zeng, Donglin; Muller, Keith; Aylward, Stephen R; Park, Sungwook; Kuzmiak, Cherie; Koomen, Marcia; Pavic, Dag; Walsh, Ruth; Baker, Jay; Gimenez, Edgardo I; Freimanis, Rita

2005-05-01

To determine the effects of three image-processing algorithms on diagnostic accuracy of digital mammography in comparison with conventional screen-film mammography. A total of 201 cases consisting of nonprocessed soft copy versions of the digital mammograms acquired from GE, Fischer, and Trex digital mammography systems (1997-1999) and conventional screen-film mammograms of the same patients were interpreted by nine radiologists. The raw digital data were processed with each of three different image-processing algorithms creating three presentations-manufacturer's default (applied and laser printed to film by each of the manufacturers), MUSICA, and PLAHE-were presented in soft copy display. There were three radiologists per presentation. Area under the receiver operating characteristic curve for GE digital mass cases was worse than screen-film for all digital presentations. The area under the receiver operating characteristic for Trex digital mass cases was better, but only with images processed with the manufacturer's default algorithm. Sensitivity for GE digital mass cases was worse than screen film for all digital presentations. Specificity for Fischer digital calcifications cases was worse than screen film for images processed in default and PLAHE algorithms. Specificity for Trex digital calcifications cases was worse than screen film for images processed with MUSICA. Specific image-processing algorithms may be necessary for optimal presentation for interpretation based on machine and lesion type.

High-performance floating-point image computing workstation for medical applications

NASA Astrophysics Data System (ADS)

Mills, Karl S.; Wong, Gilman K.; Kim, Yongmin

1990-07-01

The medical imaging field relies increasingly on imaging and graphics techniques in diverse applications with needs similar to (or more stringent than) those of the military, industrial and scientific communities. However, most image processing and graphics systems available for use in medical imaging today are either expensive, specialized, or in most cases both. High performance imaging and graphics workstations which can provide real-time results for a number of applications, while maintaining affordability and flexibility, can facilitate the application of digital image computing techniques in many different areas. This paper describes the hardware and software architecture of a medium-cost floating-point image processing and display subsystem for the NeXT computer, and its applications as a medical imaging workstation. Medical imaging applications of the workstation include use in a Picture Archiving and Communications System (PACS), in multimodal image processing and 3-D graphics workstation for a broad range of imaging modalities, and as an electronic alternator utilizing its multiple monitor display capability and large and fast frame buffer. The subsystem provides a 2048 x 2048 x 32-bit frame buffer (16 Mbytes of image storage) and supports both 8-bit gray scale and 32-bit true color images. When used to display 8-bit gray scale images, up to four different 256-color palettes may be used for each of four 2K x 2K x 8-bit image frames. Three of these image frames can be used simultaneously to provide pixel selectable region of interest display. A 1280 x 1024 pixel screen with 1: 1 aspect ratio can be windowed into the frame buffer for display of any portion of the processed image or images. In addition, the system provides hardware support for integer zoom and an 82-color cursor. This subsystem is implemented on an add-in board occupying a single slot in the NeXT computer. Up to three boards may be added to the NeXT for multiple display capability (e.g., three 1280 x 1024 monitors, each with a 16-Mbyte frame buffer). Each add-in board provides an expansion connector to which an optional image computing coprocessor board may be added. Each coprocessor board supports up to four processors for a peak performance of 160 MFLOPS. The coprocessors can execute programs from external high-speed microcode memory as well as built-in internal microcode routines. The internal microcode routines provide support for 2-D and 3-D graphics operations, matrix and vector arithmetic, and image processing in integer, IEEE single-precision floating point, or IEEE double-precision floating point. In addition to providing a library of C functions which links the NeXT computer to the add-in board and supports its various operational modes, algorithms and medical imaging application programs are being developed and implemented for image display and enhancement. As an extension to the built-in algorithms of the coprocessors, 2-D Fast Fourier Transform (FF1), 2-D Inverse FFF, convolution, warping and other algorithms (e.g., Discrete Cosine Transform) which exploit the parallel architecture of the coprocessor board are being implemented.

Performance of different reflectance and diffuse optical imaging tomographic approaches in fluorescence molecular imaging of small animals

NASA Astrophysics Data System (ADS)

Dinten, Jean-Marc; Petié, Philippe; da Silva, Anabela; Boutet, Jérôme; Koenig, Anne; Hervé, Lionel; Berger, Michel; Laidevant, Aurélie; Rizo, Philippe

2006-03-01

Optical imaging of fluorescent probes is an essential tool for investigation of molecular events in small animals for drug developments. In order to get localization and quantification information of fluorescent labels, CEA-LETI has developed efficient approaches in classical reflectance imaging as well as in diffuse optical tomographic imaging with continuous and temporal signals. This paper presents an overview of the different approaches investigated and their performances. High quality fluorescence reflectance imaging is obtained thanks to the development of an original "multiple wavelengths" system. The uniformity of the excitation light surface area is better than 15%. Combined with the use of adapted fluorescent probes, this system enables an accurate detection of pathological tissues, such as nodules, beneath the animal's observed area. Performances for the detection of ovarian nodules on a nude mouse are shown. In order to investigate deeper inside animals and get 3D localization, diffuse optical tomography systems are being developed for both slab and cylindrical geometries. For these two geometries, our reconstruction algorithms are based on analytical expression of light diffusion. Thanks to an accurate introduction of light/matter interaction process in the algorithms, high quality reconstructions of tumors in mice have been obtained. Reconstruction of lung tumors on mice are presented. By the use of temporal diffuse optical imaging, localization and quantification performances can be improved at the price of a more sophisticated acquisition system and more elaborate information processing methods. Such a system based on a pulsed laser diode and a time correlated single photon counting system has been set up. Performances of this system for localization and quantification of fluorescent probes are presented.

PyDBS: an automated image processing workflow for deep brain stimulation surgery.

PubMed

D'Albis, Tiziano; Haegelen, Claire; Essert, Caroline; Fernández-Vidal, Sara; Lalys, Florent; Jannin, Pierre

2015-02-01

Deep brain stimulation (DBS) is a surgical procedure for treating motor-related neurological disorders. DBS clinical efficacy hinges on precise surgical planning and accurate electrode placement, which in turn call upon several image processing and visualization tasks, such as image registration, image segmentation, image fusion, and 3D visualization. These tasks are often performed by a heterogeneous set of software tools, which adopt differing formats and geometrical conventions and require patient-specific parameterization or interactive tuning. To overcome these issues, we introduce in this article PyDBS, a fully integrated and automated image processing workflow for DBS surgery. PyDBS consists of three image processing pipelines and three visualization modules assisting clinicians through the entire DBS surgical workflow, from the preoperative planning of electrode trajectories to the postoperative assessment of electrode placement. The system's robustness, speed, and accuracy were assessed by means of a retrospective validation, based on 92 clinical cases. The complete PyDBS workflow achieved satisfactory results in 92 % of tested cases, with a median processing time of 28 min per patient. The results obtained are compatible with the adoption of PyDBS in clinical practice.

A configurable distributed high-performance computing framework for satellite's TDI-CCD imaging simulation

NASA Astrophysics Data System (ADS)

Xue, Bo; Mao, Bingjing; Chen, Xiaomei; Ni, Guoqiang

2010-11-01

This paper renders a configurable distributed high performance computing(HPC) framework for TDI-CCD imaging simulation. It uses strategy pattern to adapt multi-algorithms. Thus, this framework help to decrease the simulation time with low expense. Imaging simulation for TDI-CCD mounted on satellite contains four processes: 1) atmosphere leads degradation, 2) optical system leads degradation, 3) electronic system of TDI-CCD leads degradation and re-sampling process, 4) data integration. Process 1) to 3) utilize diversity data-intensity algorithms such as FFT, convolution and LaGrange Interpol etc., which requires powerful CPU. Even uses Intel Xeon X5550 processor, regular series process method takes more than 30 hours for a simulation whose result image size is 1500 * 1462. With literature study, there isn't any mature distributing HPC framework in this field. Here we developed a distribute computing framework for TDI-CCD imaging simulation, which is based on WCF[1], uses Client/Server (C/S) layer and invokes the free CPU resources in LAN. The server pushes the process 1) to 3) tasks to those free computing capacity. Ultimately we rendered the HPC in low cost. In the computing experiment with 4 symmetric nodes and 1 server , this framework reduced about 74% simulation time. Adding more asymmetric nodes to the computing network, the time decreased namely. In conclusion, this framework could provide unlimited computation capacity in condition that the network and task management server are affordable. And this is the brand new HPC solution for TDI-CCD imaging simulation and similar applications.

GPU accelerated optical coherence tomography angiography using strip-based registration (Conference Presentation)

NASA Astrophysics Data System (ADS)

Heisler, Morgan; Lee, Sieun; Mammo, Zaid; Jian, Yifan; Ju, Myeong Jin; Miao, Dongkai; Raposo, Eric; Wahl, Daniel J.; Merkur, Andrew; Navajas, Eduardo; Balaratnasingam, Chandrakumar; Beg, Mirza Faisal; Sarunic, Marinko V.

2017-02-01

High quality visualization of the retinal microvasculature can improve our understanding of the onset and development of retinal vascular diseases, which are a major cause of visual morbidity and are increasing in prevalence. Optical Coherence Tomography Angiography (OCT-A) images are acquired over multiple seconds and are particularly susceptible to motion artifacts, which are more prevalent when imaging patients with pathology whose ability to fixate is limited. The acquisition of multiple OCT-A images sequentially can be performed for the purpose of removing motion artifact and increasing the contrast of the vascular network through averaging. Due to the motion artifacts, a robust registration pipeline is needed before feature preserving image averaging can be performed. In this report, we present a novel method for a GPU-accelerated pipeline for acquisition, processing, segmentation, and registration of multiple, sequentially acquired OCT-A images to correct for the motion artifacts in individual images for the purpose of averaging. High performance computing, blending CPU and GPU, was introduced to accelerate processing in order to provide high quality visualization of the retinal microvasculature and to enable a more accurate quantitative analysis in a clinically useful time frame. Specifically, image discontinuities caused by rapid micro-saccadic movements and image warping due to smoother reflex movements were corrected by strip-wise affine registration estimated using Scale Invariant Feature Transform (SIFT) keypoints and subsequent local similarity-based non-rigid registration. These techniques improve the image quality, increasing the value for clinical diagnosis and increasing the range of patients for whom high quality OCT-A images can be acquired.

Interactive degraded document enhancement and ground truth generation

NASA Astrophysics Data System (ADS)

Bal, G.; Agam, G.; Frieder, O.; Frieder, G.

2008-01-01

Degraded documents are frequently obtained in various situations. Examples of degraded document collections include historical document depositories, document obtained in legal and security investigations, and legal and medical archives. Degraded document images are hard to to read and are hard to analyze using computerized techniques. There is hence a need for systems that are capable of enhancing such images. We describe a language-independent semi-automated system for enhancing degraded document images that is capable of exploiting inter- and intra-document coherence. The system is capable of processing document images with high levels of degradations and can be used for ground truthing of degraded document images. Ground truthing of degraded document images is extremely important in several aspects: it enables quantitative performance measurements of enhancement systems and facilitates model estimation that can be used to improve performance. Performance evaluation is provided using the historical Frieder diaries collection.1

[Image fusion: use in the control of the distribution of prostatic biopsies].

PubMed

Mozer, Pierre; Baumann, Michaël; Chevreau, Grégoire; Troccaz, Jocelyne

2008-02-01

Prostate biopsies are performed under 2D TransRectal UltraSound (US) guidance by sampling the prostate according to a predefined pattern. Modern image processing tools allow better control of biopsy distribution. We evaluated the accuracy of a single operator performing a pattern of 12 ultrasound-guided biopsies by registering 3D ultrasound control images acquired after each biopsy. For each patient, prostate image alignment was performed automatically with a voxel-based registration algorithm allowing visualization of each biopsy trajectory in a single ultrasound reference volume. On average, the operator reached the target in 60% of all cases. This study shows that it is difficult to accurately reach targets in the prostate using 2D ultrasound. In the near future, real-time fusion of MRI and US images will allow selection of a target in previously acquired MR images and biopsy of this target by US guidance.

IR CMOS: near infrared enhanced digital imaging (Presentation Recording)

NASA Astrophysics Data System (ADS)

Pralle, Martin U.; Carey, James E.; Joy, Thomas; Vineis, Chris J.; Palsule, Chintamani

2015-08-01

SiOnyx has demonstrated imaging at light levels below 1 mLux (moonless starlight) at video frame rates with a 720P CMOS image sensor in a compact, low latency camera. Low light imaging is enabled by the combination of enhanced quantum efficiency in the near infrared together with state of the art low noise image sensor design. The quantum efficiency enhancements are achieved by applying Black Silicon, SiOnyx's proprietary ultrafast laser semiconductor processing technology. In the near infrared, silicon's native indirect bandgap results in low absorption coefficients and long absorption lengths. The Black Silicon nanostructured layer fundamentally disrupts this paradigm by enhancing the absorption of light within a thin pixel layer making 5 microns of silicon equivalent to over 300 microns of standard silicon. This results in a demonstrate 10 fold improvements in near infrared sensitivity over incumbent imaging technology while maintaining complete compatibility with standard CMOS image sensor process flows. Applications include surveillance, nightvision, and 1064nm laser see spot. Imaging performance metrics will be discussed. Demonstrated performance characteristics: Pixel size : 5.6 and 10 um Array size: 720P/1.3Mpix Frame rate: 60 Hz Read noise: 2 ele/pixel Spectral sensitivity: 400 to 1200 nm (with 10x QE at 1064nm) Daytime imaging: color (Bayer pattern) Nighttime imaging: moonless starlight conditions 1064nm laser imaging: daytime imaging out to 2Km

Fuzzy Matching Based on Gray-scale Difference for Quantum Images

NASA Astrophysics Data System (ADS)

Luo, GaoFeng; Zhou, Ri-Gui; Liu, XingAo; Hu, WenWen; Luo, Jia

2018-05-01

Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.

Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera

PubMed Central

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation. PMID:22368479

Point cloud generation from aerial image data acquired by a quadrocopter type micro unmanned aerial vehicle and a digital still camera.

PubMed

Rosnell, Tomi; Honkavaara, Eija

2012-01-01

The objective of this investigation was to develop and investigate methods for point cloud generation by image matching using aerial image data collected by quadrocopter type micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point clouds from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point cloud generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point cloud generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point clouds fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point clouds that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point clouds from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point cloud generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point cloud generation.

High-performance electronic image stabilisation for shift and rotation correction

NASA Astrophysics Data System (ADS)

Parker, Steve C. J.; Hickman, D. L.; Wu, F.

2014-06-01

A novel low size, weight and power (SWaP) video stabiliser called HALO™ is presented that uses a SoC to combine the high processing bandwidth of an FPGA, with the signal processing flexibility of a CPU. An image based architecture is presented that can adapt the tiling of frames to cope with changing scene dynamics. A real-time implementation is then discussed that can generate several hundred optical flow vectors per video frame, to accurately calculate the unwanted rigid body translation and rotation of camera shake. The performance of the HALO™ stabiliser is comprehensively benchmarked against the respected Deshaker 3.0 off-line stabiliser plugin to VirtualDub. Eight different videos are used for benchmarking, simulating: battlefield, surveillance, security and low-level flight applications in both visible and IR wavebands. The results show that HALO™ rivals the performance of Deshaker within its operating envelope. Furthermore, HALO™ may be easily reconfigured to adapt to changing operating conditions or requirements; and can be used to host other video processing functionality like image distortion correction, fusion and contrast enhancement.

Radiography for intensive care: participatory process analysis in a PACS-equipped and film/screen environment

NASA Astrophysics Data System (ADS)

Peer, Regina; Peer, Siegfried; Sander, Heike; Marsolek, Ingo; Koller, Wolfgang; Pappert, Dirk; Hierholzer, Johannes

2002-05-01

If new technology is introduced into medical practice it must prove to make a difference. However traditional approaches of outcome analysis failed to show a direct benefit of PACS on patient care and economical benefits are still in debate. A participatory process analysis was performed to compare workflow in a film based hospital and a PACS environment. This included direct observation of work processes, interview of involved staff, structural analysis and discussion of observations with staff members. After definition of common structures strong and weak workflow steps were evaluated. With a common workflow structure in both hospitals, benefits of PACS were revealed in workflow steps related to image reporting with simultaneous image access for ICU-physicians and radiologists, archiving of images as well as image and report distribution. However PACS alone is not able to cover the complete process of 'radiography for intensive care' from ordering of an image till provision of the final product equals image + report. Interference of electronic workflow with analogue process steps such as paper based ordering reduces the potential benefits of PACS. In this regard workflow modeling proved to be very helpful for the evaluation of complex work processes linking radiology and the ICU.

Fission gas bubble identification using MATLAB's image processing toolbox

DOE Office of Scientific and Technical Information (OSTI.GOV)

Collette, R.; King, J.; Keiser, Jr., D.

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

Fission gas bubble identification using MATLAB's image processing toolbox

DOE PAGES

Collette, R.; King, J.; Keiser, Jr., D.; ...

2016-06-08

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. In addition, this study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding provedmore » to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods.« less

The WIYN One Degree Imager - Status and Performance

NASA Astrophysics Data System (ADS)

Boroson, Todd A.

2013-06-01

A preliminary version of the WIYN One Degree Imager (ODI) has been commissioned and put into scientific operation. ODI was designed to take advantage of the excellent image quality and wide field of view of the WIYN 3.5m telescope. It will do this by covering a one square degree focal plane with orthogonal transfer array (OTA) detectors, which have the capability to correct for image motion during the exposure in regions approximately the size of the isokinetic patch. The partial ODI (pODI) differs from the complete ODI in two ways - only 13 of the 64 OTAs populate the focal plane, and only coherent image motion correction is enabled. However, this implementation has allowed the commissioning of the instrument with all subsystems except the additional detectors in place. The 13 OTAs are configured as a 24 X 24 arcminute “science field”, plus 4 outer OTAs, allowing the sampling of all radii within the one square degree field. pODI is now in use for science observations as we prepare to upgrade the focal plane. The performance of pODI is excellent. Image quality is site seeing limited, and, on good seeing nights, we can achieve images around 0.4 arcsec FWHM over the entire field. The guide signal, from selected regions in the outer OTAs, can be passed to the telescope exclusively, or the high frequency component can be applied as a global shift to the OTAs. We are still in the process of characterizing the gains from this coherent correction, but the detectors perform well in this mode. Data are immediately transferred to an archive at Indiana University, where they are pipeline-processed to remove instrumental signature. The OTA detectors perform adequately in terms of read noise, full well, sensitivity, and dark current. They show 2 anomalies: (1) regions in the circuitry outside the imaging area glow under certain circumstances, and (2) a low level degradation of charge transfer efficiency is present between the imaging area and the serial registers. We have found ways to address both of these effects in operation, calibration, and post-processing, and the instrument is producing valuable scientific observations.

A data colocation grid framework for big data medical image processing: backend design

NASA Astrophysics Data System (ADS)

Bao, Shunxing; Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-03-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework's performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop and HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available.

A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design.

PubMed

Bao, Shunxing; Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A

2018-03-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework's performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available.

A Data Colocation Grid Framework for Big Data Medical Image Processing: Backend Design

PubMed Central

Huo, Yuankai; Parvathaneni, Prasanna; Plassard, Andrew J.; Bermudez, Camilo; Yao, Yuang; Lyu, Ilwoo; Gokhale, Aniruddha; Landman, Bennett A.

2018-01-01

When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging. Our target design criteria are (1) improving the framework’s performance in a heterogeneous cluster, (2) performing population based summary statistics on large datasets, and (3) introducing a table design scheme for rapid NoSQL query. In this paper, we present a heuristic backend interface application program interface (API) design for Hadoop & HBase for Medical Image Processing (HadoopBase-MIP). The API includes: Upload, Retrieve, Remove, Load balancer (for heterogeneous cluster) and MapReduce templates. A dataset summary statistic model is discussed and implemented by MapReduce paradigm. We introduce a HBase table scheme for fast data query to better utilize the MapReduce model. Briefly, 5153 T1 images were retrieved from a university secure, shared web database and used to empirically access an in-house grid with 224 heterogeneous CPU cores. Three empirical experiments results are presented and discussed: (1) load balancer wall-time improvement of 1.5-fold compared with a framework with built-in data allocation strategy, (2) a summary statistic model is empirically verified on grid framework and is compared with the cluster when deployed with a standard Sun Grid Engine (SGE), which reduces 8-fold of wall clock time and 14-fold of resource time, and (3) the proposed HBase table scheme improves MapReduce computation with 7 fold reduction of wall time compare with a naïve scheme when datasets are relative small. The source code and interfaces have been made publicly available. PMID:29887668

Fuzzy Reasoning to More Accurately Determine Void Areas on Optical Micrographs of Composite Structures

NASA Technical Reports Server (NTRS)

Dominquez, Jesus A.; Tate, Lanetra C.; Wright, M. Clara; Caraccio, Anne

2013-01-01

Accomplishing the best-performing composite matrix (resin) requires that not only the processing method but also the cure cycle generate low-void-content structures. If voids are present, the performance of the composite matrix will be significantly reduced. This is usually noticed by significant reductions in matrix-dominated properties, such as compression and shear strength. Voids in composite materials are areas that are absent of the composite components: matrix and fibers. The characteristics of the voids and their accurate estimation are critical to determine for high performance composite structures. One widely used method of performing void analysis on a composite structure sample is acquiring optical micrographs or Scanning Electron Microscope (SEM) images of lateral sides of the sample and retrieving the void areas within the micrographs/images using an image analysis technique. Segmentation for the retrieval and subsequent computation of void areas within the micrographs/images is challenging as the gray-scaled values of the void areas are close to the gray-scaled values of the matrix leading to the need of manually performing the segmentation based on the histogram of the micrographs/images to retrieve the void areas. The use of an algorithm developed by NASA and based on Fuzzy Reasoning (FR) proved to overcome the difficulty of suitably differentiate void and matrix image areas with similar gray-scaled values leading not only to a more accurate estimation of void areas on composite matrix micrographs but also to a faster void analysis process as the algorithm is fully autonomous.

SU-E-J-42: Motion Adaptive Image Filter for Low Dose X-Ray Fluoroscopy in the Real-Time Tumor-Tracking Radiotherapy System.

PubMed

Miyamoto, N; Ishikawa, M; Sutherland, K; Suzuki, R; Matsuura, T; Takao, S; Toramatsu, C; Nihongi, H; Shimizu, S; Onimaru, R; Umegaki, K; Shirato, H

2012-06-01

In the real-time tumor-tracking radiotherapy system, fiducial markers are detected by X-ray fluoroscopy. The fluoroscopic parameters should be optimized as low as possible in order to reduce unnecessary imaging dose. However, the fiducial markers could not be recognized due to effect of statistical noise in low dose imaging. Image processing is envisioned to be a solution to improve image quality and to maintain tracking accuracy. In this study, a recursive image filter adapted to target motion is proposed. A fluoroscopy system was used for the experiment. A spherical gold marker was used as a fiducial marker. About 450 fluoroscopic images of the marker were recorded. In order to mimic respiratory motion of the marker, the images were shifted sequentially. The tube voltage, current and exposure duration were fixed at 65 kV, 50 mA and 2.5 msec as low dose imaging condition, respectively. The tube current was 100 mA as high dose imaging. A pattern recognition score (PRS) ranging from 0 to 100 and image registration error were investigated by performing template pattern matching to each sequential image. The results with and without image processing were compared. In low dose imaging, theimage registration error and the PRS without the image processing were 2.15±1.21 pixel and 46.67±6.40, respectively. Those with the image processing were 1.48±0.82 pixel and 67.80±4.51, respectively. There was nosignificant difference in the image registration error and the PRS between the results of low dose imaging with the image processing and that of high dose imaging without the image processing. The results showed that the recursive filter was effective in order to maintain marker tracking stability and accuracy in low dose fluoroscopy. © 2012 American Association of Physicists in Medicine.

Modular Scanning Confocal Microscope with Digital Image Processing.

PubMed

Ye, Xianjun; McCluskey, Matthew D

2016-01-01

In conventional confocal microscopy, a physical pinhole is placed at the image plane prior to the detector to limit the observation volume. In this work, we present a modular design of a scanning confocal microscope which uses a CCD camera to replace the physical pinhole for materials science applications. Experimental scans were performed on a microscope resolution target, a semiconductor chip carrier, and a piece of etched silicon wafer. The data collected by the CCD were processed to yield images of the specimen. By selecting effective pixels in the recorded CCD images, a virtual pinhole is created. By analyzing the image moments of the imaging data, a lateral resolution enhancement is achieved by using a 20 × / NA = 0.4 microscope objective at 532 nm laser wavelength.

42 CFR 37.44 - Approval of radiographic facilities that use digital radiography systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... effective management, safety, and proper performance of chest image acquisition, digitization, processing... digital chest radiographs by submitting to NIOSH digital radiographic image files of a test object (e.g... radiographic image files from six or more sample chest radiographs that are of acceptable quality to one or...

Local spatio-temporal analysis in vision systems

NASA Astrophysics Data System (ADS)

Geisler, Wilson S.; Bovik, Alan; Cormack, Lawrence; Ghosh, Joydeep; Gildeen, David

1994-07-01

The aims of this project are the following: (1) develop a physiologically and psychophysically based model of low-level human visual processing (a key component of which are local frequency coding mechanisms); (2) develop image models and image-processing methods based upon local frequency coding; (3) develop algorithms for performing certain complex visual tasks based upon local frequency representations, (4) develop models of human performance in certain complex tasks based upon our understanding of low-level processing; and (5) develop a computational testbed for implementing, evaluating and visualizing the proposed models and algorithms, using a massively parallel computer. Progress has been substantial on all aims. The highlights include the following: (1) completion of a number of psychophysical and physiological experiments revealing new, systematic and exciting properties of the primate (human and monkey) visual system; (2) further development of image models that can accurately represent the local frequency structure in complex images; (3) near completion in the construction of the Texas Active Vision Testbed; (4) development and testing of several new computer vision algorithms dealing with shape-from-texture, shape-from-stereo, and depth-from-focus; (5) implementation and evaluation of several new models of human visual performance; and (6) evaluation, purchase and installation of a MasPar parallel computer.

Inspection design using 2D phased array, TFM and cueMAP software

DOE Office of Scientific and Technical Information (OSTI.GOV)

McGilp, Ailidh; Dziewierz, Jerzy; Lardner, Tim

2014-02-18

A simulation suite, cueMAP, has been developed to facilitate the design of inspection processes and sparse 2D array configurations. At the core of cueMAP is a Total Focusing Method (TFM) imaging algorithm that enables computer assisted design of ultrasonic inspection scenarios, including the design of bespoke array configurations to match the inspection criteria. This in-house developed TFM code allows for interactive evaluation of image quality indicators of ultrasonic imaging performance when utilizing a 2D phased array working in FMC/TFM mode. The cueMAP software uses a series of TFM images to build a map of resolution, contrast and sensitivity of imagingmore » performance of a simulated reflector, swept across the inspection volume. The software takes into account probe properties, wedge or water standoff, and effects of specimen curvature. In the validation process of this new software package, two 2D arrays have been evaluated on 304n stainless steel samples, typical of the primary circuit in nuclear plants. Thick section samples have been inspected using a 1MHz 2D matrix array. Due to the processing efficiency of the software, the data collected from these array configurations has been used to investigate the influence sub-aperture operation on inspection performance.« less

The performance analysis of three-dimensional track-before-detect algorithm based on Fisher-Tippett-Gnedenko theorem

NASA Astrophysics Data System (ADS)

Cho, Hoonkyung; Chun, Joohwan; Song, Sungchan

2016-09-01

The dim moving target tracking from the infrared image sequence in the presence of high clutter and noise has been recently under intensive investigation. The track-before-detect (TBD) algorithm processing the image sequence over a number of frames before decisions on the target track and existence is known to be especially attractive in very low SNR environments (⩽ 3 dB). In this paper, we shortly present a three-dimensional (3-D) TBD with dynamic programming (TBD-DP) algorithm using multiple IR image sensors. Since traditional two-dimensional TBD algorithm cannot track and detect the along the viewing direction, we use 3-D TBD with multiple sensors and also strictly analyze the detection performance (false alarm and detection probabilities) based on Fisher-Tippett-Gnedenko theorem. The 3-D TBD-DP algorithm which does not require a separate image registration step uses the pixel intensity values jointly read off from multiple image frames to compute the merit function required in the DP process. Therefore, we also establish the relationship between the pixel coordinates of image frame and the reference coordinates.

A data distributed parallel algorithm for ray-traced volume rendering

NASA Technical Reports Server (NTRS)

Ma, Kwan-Liu; Painter, James S.; Hansen, Charles D.; Krogh, Michael F.

1993-01-01

This paper presents a divide-and-conquer ray-traced volume rendering algorithm and a parallel image compositing method, along with their implementation and performance on the Connection Machine CM-5, and networked workstations. This algorithm distributes both the data and the computations to individual processing units to achieve fast, high-quality rendering of high-resolution data. The volume data, once distributed, is left intact. The processing nodes perform local ray tracing of their subvolume concurrently. No communication between processing units is needed during this locally ray-tracing process. A subimage is generated by each processing unit and the final image is obtained by compositing subimages in the proper order, which can be determined a priori. Test results on both the CM-5 and a group of networked workstations demonstrate the practicality of our rendering algorithm and compositing method.

Plenoptic Ophthalmoscopy: A Novel Imaging Technique.

PubMed

Adam, Murtaza K; Aenchbacher, Weston; Kurzweg, Timothy; Hsu, Jason

2016-11-01

This prospective retinal imaging case series was designed to establish feasibility of plenoptic ophthalmoscopy (PO), a novel mydriatic fundus imaging technique. A custom variable intensity LED array light source adapter was created for the Lytro Gen1 light-field camera (Lytro, Mountain View, CA). Initial PO testing was performed on a model eye and rabbit fundi. PO image acquisition was then performed on dilated human subjects with a variety of retinal pathology and images were subjected to computational enhancement. The Lytro Gen1 light-field camera with custom LED array captured fundus images of eyes with diabetic retinopathy, age-related macular degeneration, retinal detachment, and other diagnoses. Post-acquisition computational processing allowed for refocusing and perspective shifting of retinal PO images, resulting in improved image quality. The application of PO to image the ocular fundus is feasible. Additional studies are needed to determine its potential clinical utility. [Ophthalmic Surg Lasers Imaging Retina. 2016;47:1038-1043.]. Copyright 2016, SLACK Incorporated.

A similarity-based data warehousing environment for medical images.

PubMed

Teixeira, Jefferson William; Annibal, Luana Peixoto; Felipe, Joaquim Cezar; Ciferri, Ricardo Rodrigues; Ciferri, Cristina Dutra de Aguiar

2015-11-01

A core issue of the decision-making process in the medical field is to support the execution of analytical (OLAP) similarity queries over images in data warehousing environments. In this paper, we focus on this issue. We propose imageDWE, a non-conventional data warehousing environment that enables the storage of intrinsic features taken from medical images in a data warehouse and supports OLAP similarity queries over them. To comply with this goal, we introduce the concept of perceptual layer, which is an abstraction used to represent an image dataset according to a given feature descriptor in order to enable similarity search. Based on this concept, we propose the imageDW, an extended data warehouse with dimension tables specifically designed to support one or more perceptual layers. We also detail how to build an imageDW and how to load image data into it. Furthermore, we show how to process OLAP similarity queries composed of a conventional predicate and a similarity search predicate that encompasses the specification of one or more perceptual layers. Moreover, we introduce an index technique to improve the OLAP query processing over images. We carried out performance tests over a data warehouse environment that consolidated medical images from exams of several modalities. The results demonstrated the feasibility and efficiency of our proposed imageDWE to manage images and to process OLAP similarity queries. The results also demonstrated that the use of the proposed index technique guaranteed a great improvement in query processing. Copyright © 2015 Elsevier Ltd. All rights reserved.

A discrepancy within primate spatial vision and its bearing on the definition of edge detection processes in machine vision

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1990-01-01

The visual perception of form information is considered to be based on the functioning of simple and complex neurons in the primate striate cortex. However, a review of the physiological data on these brain cells cannot be harmonized with either the perceptual spatial frequency performance of primates or the performance which is necessary for form perception in humans. This discrepancy together with recent interest in cortical-like and perceptual-like processing in image coding and machine vision prompted a series of image processing experiments intended to provide some definition of the selection of image operators. The experiments were aimed at determining operators which could be used to detect edges in a computational manner consistent with the visual perception of structure in images. Fundamental issues were the selection of size (peak spatial frequency) and circular versus oriented operators (or some combination). In a previous study, circular difference-of-Gaussian (DOG) operators, with peak spatial frequency responses at about 11 and 33 cyc/deg were found to capture the primary structural information in images. Here larger scale circular DOG operators were explored and led to severe loss of image structure and introduced spatial dislocations (due to blur) in structure which is not consistent with visual perception. Orientation sensitive operators (akin to one class of simple cortical neurons) introduced ambiguities of edge extent regardless of the scale of the operator. For machine vision schemes which are functionally similar to natural vision form perception, two circularly symmetric very high spatial frequency channels appear to be necessary and sufficient for a wide range of natural images. Such a machine vision scheme is most similar to the physiological performance of the primate lateral geniculate nucleus rather than the striate cortex.

A New Vegetation Segmentation Approach for Cropped Fields Based on Threshold Detection from Hue Histograms

PubMed Central

Hassanein, Mohamed; El-Sheimy, Naser

2018-01-01

Over the last decade, the use of unmanned aerial vehicle (UAV) technology has evolved significantly in different applications as it provides a special platform capable of combining the benefits of terrestrial and aerial remote sensing. Therefore, such technology has been established as an important source of data collection for different precision agriculture (PA) applications such as crop health monitoring and weed management. Generally, these PA applications depend on performing a vegetation segmentation process as an initial step, which aims to detect the vegetation objects in collected agriculture fields’ images. The main result of the vegetation segmentation process is a binary image, where vegetations are presented in white color and the remaining objects are presented in black. Such process could easily be performed using different vegetation indexes derived from multispectral imagery. Recently, to expand the use of UAV imagery systems for PA applications, it was important to reduce the cost of such systems through using low-cost RGB cameras Thus, developing vegetation segmentation techniques for RGB images is a challenging problem. The proposed paper introduces a new vegetation segmentation methodology for low-cost UAV RGB images, which depends on using Hue color channel. The proposed methodology follows the assumption that the colors in any agriculture field image can be distributed into vegetation and non-vegetations colors. Therefore, four main steps are developed to detect five different threshold values using the hue histogram of the RGB image, these thresholds are capable to discriminate the dominant color, either vegetation or non-vegetation, within the agriculture field image. The achieved results for implementing the proposed methodology showed its ability to generate accurate and stable vegetation segmentation performance with mean accuracy equal to 87.29% and standard deviation as 12.5%. PMID:29670055

Development of real-time extensometer based on image processing

NASA Astrophysics Data System (ADS)

Adinanta, H.; Puranto, P.; Suryadi

2017-04-01

An extensometer system was developed by using high definition web camera as main sensor to track object position. The developed system applied digital image processing techniques. The image processing was used to measure the change of object position. The position measurement was done in real-time so that the system can directly showed the actual position in both x and y-axis. In this research, the relation between pixel and object position changes had been characterized. The system was tested by moving the target in a range of 20 cm in interval of 1 mm. To verify the long run performance, the stability and linearity of continuous measurements on both x and y-axis, this measurement had been conducted for 83 hours. The results show that this image processing-based extensometer had both good stability and linearity.

GPU computing in medical physics: a review.

PubMed

Pratx, Guillem; Xing, Lei

2011-05-01

The graphics processing unit (GPU) has emerged as a competitive platform for computing massively parallel problems. Many computing applications in medical physics can be formulated as data-parallel tasks that exploit the capabilities of the GPU for reducing processing times. The authors review the basic principles of GPU computing as well as the main performance optimization techniques, and survey existing applications in three areas of medical physics, namely image reconstruction, dose calculation and treatment plan optimization, and image processing.

Original non-stationary eddy current imaging process for the evaluation of defects in metallic structures

NASA Astrophysics Data System (ADS)

Placko, Dominique; Bore, Thierry; Rivollet, Alain; Joubert, Pierre-Yves

2015-10-01

This paper deals with the problem of imaging defects in metallic structures through eddy current (EC) inspections, and proposes an original process for a possible tomographical crack evaluation. This process is based on a semi analytical modeling, called "distributed point source method" (DPSM) which is used to describe and equate the interactions between the implemented EC probes and the structure under test. Several steps will be successively described, illustrating the feasibility of this new imaging process dedicated to the quantitative evaluation of defects. The basic principles of this imaging process firstly consist in creating a 3D grid by meshing the volume potentially inspected by the sensor. As a result, a given number of elemental volumes (called voxels) are obtained. Secondly, the DPSM modeling is used to compute an image for all occurrences in which only one of the voxels has a different conductivity among all the other ones. The assumption consists to consider that a real defect may be truly represented by a superimposition of elemental voxels: the resulting accuracy will naturally depend on the density of space sampling. On other hand, the excitation device of the EC imager has the capability to be oriented in several directions, and driven by an excitation current at variable frequency. So, the simulation will be performed for several frequencies and directions of the eddy currents induced in the structure, which increases the signal entropy. All these results are merged in a so-called "observation matrix" containing all the probe/structure interaction configurations. This matrix is then used in an inversion scheme in order to perform the evaluation of the defect location and geometry. The modeled EC data provided by the DPSM are compared to the experimental images provided by an eddy current imager (ECI), implemented on aluminum plates containing some buried defects. In order to validate the proposed inversion process, we feed it with computed images of various acquisition configurations. Additive noise was added to the images so that they are more representative of actual EC data. In the case of simple notch type defects, for which the relative conductivity may only take two extreme values (1 or 0), a threshold was introduced on the inverted images, in a post processing step, taking advantage of a priori knowledge of the statistical properties of the restored images. This threshold allowed to enhance the image contrast and has contributed to eliminate both the residual noise and the pixels showing non-realistic values.

The near real time image navigation of pictures returned by Voyager 2 at Neptune

NASA Technical Reports Server (NTRS)

Underwood, Ian M.; Bachman, Nathaniel J.; Taber, William L.; Wang, Tseng-Chan; Acton, Charles H.

1990-01-01

The development of a process for performing image navigation in near real time is described. The process was used to accurately determine the camera pointing for pictures returned by the Voyager 2 spacecraft at Neptune Encounter. Image navigation improves knowledge of the pointing of an imaging instrument at a particular epoch by correlating the spacecraft-relative locations of target bodies in inertial space with the locations of their images in a picture taken at that epoch. More than 8,500 pictures returned by Voyager 2 at Neptune were processed in near real time. The results were used in several applications, including improving pointing knowledge for nonimaging instruments ('C-smithing'), making 'Neptune, the Movie', and providing immediate access to geometrical quantities similar to those traditionally supplied in the Supplementary Experiment Data Record.

funcLAB/G-service-oriented architecture for standards-based analysis of functional magnetic resonance imaging in HealthGrids.

PubMed

Erberich, Stephan G; Bhandekar, Manasee; Chervenak, Ann; Kesselman, Carl; Nelson, Marvin D

2007-01-01

Functional MRI is successfully being used in clinical and research applications including preoperative planning, language mapping, and outcome monitoring. However, clinical use of fMRI is less widespread due to its complexity of imaging, image workflow, post-processing, and lack of algorithmic standards hindering result comparability. As a consequence, wide-spread adoption of fMRI as clinical tool is low contributing to the uncertainty of community physicians how to integrate fMRI into practice. In addition, training of physicians with fMRI is in its infancy and requires clinical and technical understanding. Therefore, many institutions which perform fMRI have a team of basic researchers and physicians to perform fMRI as a routine imaging tool. In order to provide fMRI as an advanced diagnostic tool to the benefit of a larger patient population, image acquisition and image post-processing must be streamlined, standardized, and available at any institution which does not have these resources available. Here we describe a software architecture, the functional imaging laboratory (funcLAB/G), which addresses (i) standardized image processing using Statistical Parametric Mapping and (ii) its extension to secure sharing and availability for the community using standards-based Grid technology (Globus Toolkit). funcLAB/G carries the potential to overcome the limitations of fMRI in clinical use and thus makes standardized fMRI available to the broader healthcare enterprise utilizing the Internet and HealthGrid Web Services technology.

Evaluation of clinical image processing algorithms used in digital mammography.

PubMed

Zanca, Federica; Jacobs, Jurgen; Van Ongeval, Chantal; Claus, Filip; Celis, Valerie; Geniets, Catherine; Provost, Veerle; Pauwels, Herman; Marchal, Guy; Bosmans, Hilde

2009-03-01

Screening is the only proven approach to reduce the mortality of breast cancer, but significant numbers of breast cancers remain undetected even when all quality assurance guidelines are implemented. With the increasing adoption of digital mammography systems, image processing may be a key factor in the imaging chain. Although to our knowledge statistically significant effects of manufacturer-recommended image processings have not been previously demonstrated, the subjective experience of our radiologists, that the apparent image quality can vary considerably between different algorithms, motivated this study. This article addresses the impact of five such algorithms on the detection of clusters of microcalcifications. A database of unprocessed (raw) images of 200 normal digital mammograms, acquired with the Siemens Novation DR, was collected retrospectively. Realistic simulated microcalcification clusters were inserted in half of the unprocessed images. All unprocessed images were subsequently processed with five manufacturer-recommended image processing algorithms (Agfa Musica 1, IMS Raffaello Mammo 1.2, Sectra Mamea AB Sigmoid, Siemens OPVIEW v2, and Siemens OPVIEW v1). Four breast imaging radiologists were asked to locate and score the clusters in each image on a five point rating scale. The free-response data were analyzed by the jackknife free-response receiver operating characteristic (JAFROC) method and, for comparison, also with the receiver operating characteristic (ROC) method. JAFROC analysis revealed highly significant differences between the image processings (F = 8.51, p < 0.0001), suggesting that image processing strongly impacts the detectability of clusters. Siemens OPVIEW2 and Siemens OPVIEW1 yielded the highest and lowest performances, respectively. ROC analysis of the data also revealed significant differences between the processing but at lower significance (F = 3.47, p = 0.0305) than JAFROC. Both statistical analysis methods revealed that the same six pairs of modalities were significantly different, but the JAFROC confidence intervals were about 32% smaller than ROC confidence intervals. This study shows that image processing has a significant impact on the detection of microcalcifications in digital mammograms. Objective measurements, such as described here, should be used by the manufacturers to select the optimal image processing algorithm.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT.

PubMed

Schenk, Andreas D; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-05-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library and Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. Copyright © 2013 Elsevier Inc. All rights reserved.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT

PubMed Central

Schenk, Andreas D.; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-01-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library & Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. PMID:23500887

Varying face occlusion detection and iterative recovery for face recognition

NASA Astrophysics Data System (ADS)

Wang, Meng; Hu, Zhengping; Sun, Zhe; Zhao, Shuhuan; Sun, Mei

2017-05-01

In most sparse representation methods for face recognition (FR), occlusion problems were usually solved via removing the occlusion part of both query samples and training samples to perform the recognition process. This practice ignores the global feature of facial image and may lead to unsatisfactory results due to the limitation of local features. Considering the aforementioned drawback, we propose a method called varying occlusion detection and iterative recovery for FR. The main contributions of our method are as follows: (1) to detect an accurate occlusion area of facial images, an image processing and intersection-based clustering combination method is used for occlusion FR; (2) according to an accurate occlusion map, the new integrated facial images are recovered iteratively and put into a recognition process; and (3) the effectiveness on recognition accuracy of our method is verified by comparing it with three typical occlusion map detection methods. Experiments show that the proposed method has a highly accurate detection and recovery performance and that it outperforms several similar state-of-the-art methods against partial contiguous occlusion.

Control Software for Advanced Video Guidance Sensor

NASA Technical Reports Server (NTRS)

Howard, Richard T.; Book, Michael L.; Bryan, Thomas C.

2006-01-01

Embedded software has been developed specifically for controlling an Advanced Video Guidance Sensor (AVGS). A Video Guidance Sensor is an optoelectronic system that provides guidance for automated docking of two vehicles. Such a system includes pulsed laser diodes and a video camera, the output of which is digitized. From the positions of digitized target images and known geometric relationships, the relative position and orientation of the vehicles are computed. The present software consists of two subprograms running in two processors that are parts of the AVGS. The subprogram in the first processor receives commands from an external source, checks the commands for correctness, performs commanded non-image-data-processing control functions, and sends image data processing parts of commands to the second processor. The subprogram in the second processor processes image data as commanded. Upon power-up, the software performs basic tests of functionality, then effects a transition to a standby mode. When a command is received, the software goes into one of several operational modes (e.g. acquisition or tracking). The software then returns, to the external source, the data appropriate to the command.

Activity in the fusiform face area supports expert perception in radiologists and does not depend upon holistic processing of images

NASA Astrophysics Data System (ADS)

Engel, Stephen A.; Harley, Erin M.; Pope, Whitney B.; Villablanca, J. Pablo; Mazziotta, John C.; Enzmann, Dieter

2009-02-01

Training in radiology dramatically changes observers' ability to process images, but the neural bases of this visual expertise remain unexplored. Prior imaging work has suggested that the fusiform face area (FFA), normally selectively responsive to faces, becomes responsive to images in observers' area of expertise. The FFA has been hypothesized to be important for "holistic" processing that integrates information across the entire image. Here, we report a cross-sectional study of radiologists that used functional magnetic resonance imaging to measure neural activity in first-year radiology residents, fourth-year radiology residents, and practicing radiologists as they detected abnormalities in chest radiographs. Across subjects, activity in the FFA correlated with visual expertise, measured as behavioral performance during scanning. To test whether processing in the FFA was holistic, we measured its responses both to intact radiographs and radiographs that had been divided into 25 square pieces whose locations were scrambled. Activity in the FFA was equal in magnitude for intact and scrambled images, and responses to both kinds of stimuli correlated reliably with expertise. These results suggest that the FFA is one of the cortical regions that provides the basis of expertise in radiology, but that its contribution is not holistic processing of images.

FPGA-Based Reconfigurable Processor for Ultrafast Interlaced Ultrasound and Photoacoustic Imaging

PubMed Central

Alqasemi, Umar; Li, Hai; Aguirre, Andrés; Zhu, Quing

2016-01-01

In this paper, we report, to the best of our knowledge, a unique field-programmable gate array (FPGA)-based reconfigurable processor for real-time interlaced co-registered ultrasound and photoacoustic imaging and its application in imaging tumor dynamic response. The FPGA is used to control, acquire, store, delay-and-sum, and transfer the data for real-time co-registered imaging. The FPGA controls the ultrasound transmission and ultrasound and photoacoustic data acquisition process of a customized 16-channel module that contains all of the necessary analog and digital circuits. The 16-channel module is one of multiple modules plugged into a motherboard; their beamformed outputs are made available for a digital signal processor (DSP) to access using an external memory interface (EMIF). The FPGA performs a key role through ultrafast reconfiguration and adaptation of its structure to allow real-time switching between the two imaging modes, including transmission control, laser synchronization, internal memory structure, beamforming, and EMIF structure and memory size. It performs another role by parallel accessing of internal memories and multi-thread processing to reduce the transfer of data and the processing load on the DSP. Furthermore, because the laser will be pulsing even during ultrasound pulse-echo acquisition, the FPGA ensures that the laser pulses are far enough from the pulse-echo acquisitions by appropriate time-division multiplexing (TDM). A co-registered ultrasound and photoacoustic imaging system consisting of four FPGA modules (64-channels) is constructed, and its performance is demonstrated using phantom targets and in vivo mouse tumor models. PMID:22828830

FPGA-based reconfigurable processor for ultrafast interlaced ultrasound and photoacoustic imaging.

PubMed

Alqasemi, Umar; Li, Hai; Aguirre, Andrés; Zhu, Quing

2012-07-01

In this paper, we report, to the best of our knowledge, a unique field-programmable gate array (FPGA)-based reconfigurable processor for real-time interlaced co-registered ultrasound and photoacoustic imaging and its application in imaging tumor dynamic response. The FPGA is used to control, acquire, store, delay-and-sum, and transfer the data for real-time co-registered imaging. The FPGA controls the ultrasound transmission and ultrasound and photoacoustic data acquisition process of a customized 16-channel module that contains all of the necessary analog and digital circuits. The 16-channel module is one of multiple modules plugged into a motherboard; their beamformed outputs are made available for a digital signal processor (DSP) to access using an external memory interface (EMIF). The FPGA performs a key role through ultrafast reconfiguration and adaptation of its structure to allow real-time switching between the two imaging modes, including transmission control, laser synchronization, internal memory structure, beamforming, and EMIF structure and memory size. It performs another role by parallel accessing of internal memories and multi-thread processing to reduce the transfer of data and the processing load on the DSP. Furthermore, because the laser will be pulsing even during ultrasound pulse-echo acquisition, the FPGA ensures that the laser pulses are far enough from the pulse-echo acquisitions by appropriate time-division multiplexing (TDM). A co-registered ultrasound and photoacoustic imaging system consisting of four FPGA modules (64-channels) is constructed, and its performance is demonstrated using phantom targets and in vivo mouse tumor models.

Terahertz multistatic reflection imaging.

PubMed

Dorney, Timothy D; Symes, William W; Baraniuk, Richard G; Mittleman, Daniel M

2002-07-01

We describe a new imaging method using single-cycle pulses of terahertz (THz) radiation. This technique emulates the data collection and image processing procedures developed for geophysical prospecting and is made possible by the availability of fiber-coupled THz receiver antennas. We use a migration procedure to solve the inverse problem; this permits us to reconstruct the location, the shape, and the refractive index of targets. We show examples for both metallic and dielectric model targets, and we perform velocity analysis on dielectric targets to estimate the refractive indices of imaged components. These results broaden the capabilities of THz imaging systems and also demonstrate the viability of the THz system as a test bed for the exploration of new seismic processing methods.

Highly curved image sensors: a practical approach for improved optical performance

NASA Astrophysics Data System (ADS)

Guenter, Brian; Joshi, Neel; Stoakley, Richard; Keefe, Andrew; Geary, Kevin; Freeman, Ryan; Hundley, Jake; Patterson, Pamela; Hammon, David; Herrera, Guillermo; Sherman, Elena; Nowak, Andrew; Schubert, Randall; Brewer, Peter; Yang, Louis; Mott, Russell; McKnight, Geoff

2017-06-01

The significant optical and size benefits of using a curved focal surface for imaging systems have been well studied yet never brought to market for lack of a high-quality, mass-producible, curved image sensor. In this work we demonstrate that commercial silicon CMOS image sensors can be thinned and formed into accurate, highly curved optical surfaces with undiminished functionality. Our key development is a pneumatic forming process that avoids rigid mechanical constraints and suppresses wrinkling instabilities. A combination of forming-mold design, pressure membrane elastic properties, and controlled friction forces enables us to gradually contact the die at the corners and smoothly press the sensor into a spherical shape. Allowing the die to slide into the concave target shape enables a threefold increase in the spherical curvature over prior approaches having mechanical constraints that resist deformation, and create a high-stress, stretch-dominated state. Our process creates a bridge between the high precision and low-cost but planar CMOS process, and ideal non-planar component shapes such as spherical imagers for improved optical systems. We demonstrate these curved sensors in prototype cameras with custom lenses, measuring exceptional resolution of 3220 line-widths per picture height at an aperture of f/1.2 and nearly 100% relative illumination across the field. Though we use a 1/2.3" format image sensor in this report, we also show this process is generally compatible with many state of the art imaging sensor formats. By example, we report photogrammetry test data for an APS-C sized silicon die formed to a 30$^\\circ$ subtended spherical angle. These gains in sharpness and relative illumination enable a new generation of ultra-high performance, manufacturable, digital imaging systems for scientific, industrial, and artistic use.

GPU-based prompt gamma ray imaging from boron neutron capture therapy.

PubMed

Yoon, Do-Kun; Jung, Joo-Young; Jo Hong, Key; Sil Lee, Keum; Suk Suh, Tae

2015-01-01

The purpose of this research is to perform the fast reconstruction of a prompt gamma ray image using a graphics processing unit (GPU) computation from boron neutron capture therapy (BNCT) simulations. To evaluate the accuracy of the reconstructed image, a phantom including four boron uptake regions (BURs) was used in the simulation. After the Monte Carlo simulation of the BNCT, the modified ordered subset expectation maximization reconstruction algorithm using the GPU computation was used to reconstruct the images with fewer projections. The computation times for image reconstruction were compared between the GPU and the central processing unit (CPU). Also, the accuracy of the reconstructed image was evaluated by a receiver operating characteristic (ROC) curve analysis. The image reconstruction time using the GPU was 196 times faster than the conventional reconstruction time using the CPU. For the four BURs, the area under curve values from the ROC curve were 0.6726 (A-region), 0.6890 (B-region), 0.7384 (C-region), and 0.8009 (D-region). The tomographic image using the prompt gamma ray event from the BNCT simulation was acquired using the GPU computation in order to perform a fast reconstruction during treatment. The authors verified the feasibility of the prompt gamma ray image reconstruction using the GPU computation for BNCT simulations.