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

A high performance parallel computing architecture for robust image features

NASA Astrophysics Data System (ADS)

Zhou, Renyan; Liu, Leibo; Wei, Shaojun

2014-03-01

A design of parallel architecture for image feature detection and description is proposed in this article. The major component of this architecture is a 2D cellular network composed of simple reprogrammable processors, enabling the Hessian Blob Detector and Haar Response Calculation, which are the most computing-intensive stage of the Speeded Up Robust Features (SURF) algorithm. Combining this 2D cellular network and dedicated hardware for SURF descriptors, this architecture achieves real-time image feature detection with minimal software in the host processor. A prototype FPGA implementation of the proposed architecture achieves 1318.9 GOPS general pixel processing @ 100 MHz clock and achieves up to 118 fps in VGA (640 × 480) image feature detection. The proposed architecture is stand-alone and scalable so it is easy to be migrated into VLSI implementation.

Investigation of Carbon Fiber Architecture in Braided Composites Using X-Ray CT Inspection

NASA Technical Reports Server (NTRS)

Rhoads, Daniel J.; Miller, Sandi G.; Roberts, Gary D.; Rauser, Richard W.; Golovaty, Dmitry; Wilber, J. Patrick; Espanol, Malena I.

2017-01-01

During the fabrication of braided carbon fiber composite materials, process variations occur which affect the fiber architecture. Quantitative measurements of local and global fiber architecture variations are needed to determine the potential effect of process variations on mechanical properties of the cured composite. Although non-destructive inspection via X-ray CT imaging is a promising approach, difficulties in quantitative analysis of the data arise due to the similar densities of the material constituents. In an effort to gain more quantitative information about features related to fiber architecture, methods have been explored to improve the details that can be captured by X-ray CT imaging. Metal-coated fibers and thin veils are used as inserts to extract detailed information about fiber orientations and inter-ply behavior from X-ray CT images.

Formal Foundations for the Specification of Software Architecture.

DTIC Science & Technology

1995-03-01

Architectures For- mally: A Case-Study Using KWIC." Kestrel Institute, Palo Alto, CA 94304, April 1994. 58. Kang, Kyo C. Feature-Oriented Domain Analysis ( FODA ...6.3.5 Constraint-Based Architectures ................. 6-60 6.4 Summary ......... ............................. 6-63 VII. Analysis of Process-Based...between these architec- ture theories were investigated. A feasibility analysis on an image processing application demonstrated that architecture theories

Remote hardware-reconfigurable robotic camera

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Torres-Huitzil, Cesar; Maya-Rueda, Selene E.

2001-10-01

In this work, a camera with integrated image processing capabilities is discussed. The camera is based on an imager coupled to an FPGA device (Field Programmable Gate Array) which contains an architecture for real-time computer vision low-level processing. The architecture can be reprogrammed remotely for application specific purposes. The system is intended for rapid modification and adaptation for inspection and recognition applications, with the flexibility of hardware and software reprogrammability. FPGA reconfiguration allows the same ease of upgrade in hardware as a software upgrade process. The camera is composed of a digital imager coupled to an FPGA device, two memory banks, and a microcontroller. The microcontroller is used for communication tasks and FPGA programming. The system implements a software architecture to handle multiple FPGA architectures in the device, and the possibility to download a software/hardware object from the host computer into its internal context memory. System advantages are: small size, low power consumption, and a library of hardware/software functionalities that can be exchanged during run time. The system has been validated with an edge detection and a motion processing architecture, which will be presented in the paper. Applications targeted are in robotics, mobile robotics, and vision based quality control.

Video image processing

NASA Technical Reports Server (NTRS)

Murray, N. D.

1985-01-01

Current technology projections indicate a lack of availability of special purpose computing for Space Station applications. Potential functions for video image special purpose processing are being investigated, such as smoothing, enhancement, restoration and filtering, data compression, feature extraction, object detection and identification, pixel interpolation/extrapolation, spectral estimation and factorization, and vision synthesis. Also, architectural approaches are being identified and a conceptual design generated. Computationally simple algorithms will be research and their image/vision effectiveness determined. Suitable algorithms will be implimented into an overall architectural approach that will provide image/vision processing at video rates that are flexible, selectable, and programmable. Information is given in the form of charts, diagrams and outlines.

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

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.

An energy efficient and high speed architecture for convolution computing based on binary resistive random access memory

NASA Astrophysics Data System (ADS)

Liu, Chen; Han, Runze; Zhou, Zheng; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

2018-04-01

In this work we present a novel convolution computing architecture based on metal oxide resistive random access memory (RRAM) to process the image data stored in the RRAM arrays. The proposed image storage architecture shows performances of better speed-device consumption efficiency compared with the previous kernel storage architecture. Further we improve the architecture for a high accuracy and low power computing by utilizing the binary storage and the series resistor. For a 28 × 28 image and 10 kernels with a size of 3 × 3, compared with the previous kernel storage approach, the newly proposed architecture shows excellent performances including: 1) almost 100% accuracy within 20% LRS variation and 90% HRS variation; 2) more than 67 times speed boost; 3) 71.4% energy saving.

Computer vision camera with embedded FPGA processing

NASA Astrophysics Data System (ADS)

Lecerf, Antoine; Ouellet, Denis; Arias-Estrada, Miguel

2000-03-01

Traditional computer vision is based on a camera-computer system in which the image understanding algorithms are embedded in the computer. To circumvent the computational load of vision algorithms, low-level processing and imaging hardware can be integrated in a single compact module where a dedicated architecture is implemented. This paper presents a Computer Vision Camera based on an open architecture implemented in an FPGA. The system is targeted to real-time computer vision tasks where low level processing and feature extraction tasks can be implemented in the FPGA device. The camera integrates a CMOS image sensor, an FPGA device, two memory banks, and an embedded PC for communication and control tasks. The FPGA device is a medium size one equivalent to 25,000 logic gates. The device is connected to two high speed memory banks, an IS interface, and an imager interface. The camera can be accessed for architecture programming, data transfer, and control through an Ethernet link from a remote computer. A hardware architecture can be defined in a Hardware Description Language (like VHDL), simulated and synthesized into digital structures that can be programmed into the FPGA and tested on the camera. The architecture of a classical multi-scale edge detection algorithm based on a Laplacian of Gaussian convolution has been developed to show the capabilities of the system.

Image Processing Using a Parallel Architecture.

DTIC Science & Technology

1987-12-01

ENG/87D-25 Abstract This study developed a set o± low level image processing tools on a parallel computer that allows concurrent processing of images...environment, the set of tools offers a significant reduction in the time required to perform some commonly used image processing operations. vI IMAGE...step toward developing these systems, a structured set of image processing tools was implemented using a parallel computer. More important than

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.

A Electro-Optical Image Algebra Processing System for Automatic Target Recognition

NASA Astrophysics Data System (ADS)

Coffield, Patrick Cyrus

The proposed electro-optical image algebra processing system is designed specifically for image processing and other related computations. The design is a hybridization of an optical correlator and a massively paralleled, single instruction multiple data processor. The architecture of the design consists of three tightly coupled components: a spatial configuration processor (the optical analog portion), a weighting processor (digital), and an accumulation processor (digital). The systolic flow of data and image processing operations are directed by a control buffer and pipelined to each of the three processing components. The image processing operations are defined in terms of basic operations of an image algebra developed by the University of Florida. The algebra is capable of describing all common image-to-image transformations. The merit of this architectural design is how it implements the natural decomposition of algebraic functions into spatially distributed, point use operations. The effect of this particular decomposition allows convolution type operations to be computed strictly as a function of the number of elements in the template (mask, filter, etc.) instead of the number of picture elements in the image. Thus, a substantial increase in throughput is realized. The implementation of the proposed design may be accomplished in many ways. While a hybrid electro-optical implementation is of primary interest, the benefits and design issues of an all digital implementation are also discussed. The potential utility of this architectural design lies in its ability to control a large variety of the arithmetic and logic operations of the image algebra's generalized matrix product. The generalized matrix product is the most powerful fundamental operation in the algebra, thus allowing a wide range of applications. No other known device or design has made this claim of processing speed and general implementation of a heterogeneous image algebra.

a New Protocol for Texture Mapping Process and 2d Representation of Rupestrian Architecture

NASA Astrophysics Data System (ADS)

Carnevali, L.; Carpiceci, M.; Angelini, A.

2018-05-01

The development of the survey techniques for architecture and archaeology requires a general review in the methods used for the representation of numerical data. The possibilities offered by data processing allow to find new paths for studying issues connected to the drawing discipline. The research project aimed at experimenting different approaches for the representation of the rupestrian architecture and the texture mapping process. The nature of the rupestrian architecture does not allow a traditional representation of sections and projections of edges and outlines. The paper presents a method, the Equidistant Multiple Sections (EMS), inspired by cartography and based on the use of isohipses generated from different geometric plane. A specific paragraph is dedicated to the texture mapping process for unstructured surface models. One of the main difficulty in the image projection consists in the recognition of homologous points between image and point cloud, above all in the areas with most deformations. With the aid of the "virtual scan" tool a different procedure was developed for improving the correspondences of the image. The result show a sensible improvement of the entire process above all for the architectural vaults. A detailed study concerned the unfolding of the straight line surfaces; the barrel vault of the analyzed chapel has been unfolded for observing the paintings in the real shapes out of the morphological context.

Real-time traffic sign detection and recognition

NASA Astrophysics Data System (ADS)

Herbschleb, Ernst; de With, Peter H. N.

2009-01-01

The continuous growth of imaging databases increasingly requires analysis tools for extraction of features. In this paper, a new architecture for the detection of traffic signs is proposed. The architecture is designed to process a large database with tens of millions of images with a resolution up to 4,800x2,400 pixels. Because of the size of the database, a high reliability as well as a high throughput is required. The novel architecture consists of a three-stage algorithm with multiple steps per stage, combining both color and specific spatial information. The first stage contains an area-limitation step which is performance critical in both the detection rate as the overall processing time. The second stage locates suggestions for traffic signs using recently published feature processing. The third stage contains a validation step to enhance reliability of the algorithm. During this stage, the traffic signs are recognized. Experiments show a convincing detection rate of 99%. With respect to computational speed, the throughput for line-of-sight images of 800×600 pixels is 35 Hz and for panorama images it is 4 Hz. Our novel architecture outperforms existing algorithms, with respect to both detection rate and throughput

The Multimission Image Processing Laboratory's virtual frame buffer interface

NASA Technical Reports Server (NTRS)

Wolfe, T.

1984-01-01

Large image processing systems use multiple frame buffers with differing architectures and vendor supplied interfaces. This variety of architectures and interfaces creates software development, maintenance and portability problems for application programs. Several machine-dependent graphics standards such as ANSI Core and GKS are available, but none of them are adequate for image processing. Therefore, the Multimission Image Processing laboratory project has implemented a programmer level virtual frame buffer interface. This interface makes all frame buffers appear as a generic frame buffer with a specified set of characteristics. This document defines the virtual frame uffer interface and provides information such as FORTRAN subroutine definitions, frame buffer characteristics, sample programs, etc. It is intended to be used by application programmers and system programmers who are adding new frame buffers to a system.

Real time SAR processing

NASA Technical Reports Server (NTRS)

Premkumar, A. B.; Purviance, J. E.

1990-01-01

A simplified model for the SAR imaging problem is presented. The model is based on the geometry of the SAR system. Using this model an expression for the entire phase history of the received SAR signal is formulated. From the phase history, it is shown that the range and the azimuth coordinates for a point target image can be obtained by processing the phase information during the intrapulse and interpulse periods respectively. An architecture for a VLSI implementation for the SAR signal processor is presented which generates images in real time. The architecture uses a small number of chips, a new correlation processor, and an efficient azimuth correlation process.

Software architecture for intelligent image processing using Prolog

NASA Astrophysics Data System (ADS)

Jones, Andrew C.; Batchelor, Bruce G.

1994-10-01

We describe a prototype system for interactive image processing using Prolog, implemented by the first author on an Apple Macintosh computer. This system is inspired by Prolog+, but differs from it in two particularly important respects. The first is that whereas Prolog+ assumes the availability of dedicated image processing hardware, with which the Prolog system communicates, our present system implements image processing functions in software using the C programming language. The second difference is that although our present system supports Prolog+ commands, these are implemented in terms of lower-level Prolog predicates which provide a more flexible approach to image manipulation. We discuss the impact of the Apple Macintosh operating system upon the implementation of the image-processing functions, and the interface between these functions and the Prolog system. We also explain how the Prolog+ commands have been implemented. The system described in this paper is a fairly early prototype, and we outline how we intend to develop the system, a task which is expedited by the extensible architecture we have implemented.

Architecture and data processing alternatives for Tse computer. Volume 1: Tse logic design concepts and the development of image processing machine architectures

NASA Technical Reports Server (NTRS)

Rickard, D. A.; Bodenheimer, R. E.

1976-01-01

Digital computer components which perform two dimensional array logic operations (Tse logic) on binary data arrays are described. The properties of Golay transforms which make them useful in image processing are reviewed, and several architectures for Golay transform processors are presented with emphasis on the skeletonizing algorithm. Conventional logic control units developed for the Golay transform processors are described. One is a unique microprogrammable control unit that uses a microprocessor to control the Tse computer. The remaining control units are based on programmable logic arrays. Performance criteria are established and utilized to compare the various Golay transform machines developed. A critique of Tse logic is presented, and recommendations for additional research are included.

Quantitative imaging methods in osteoporosis.

PubMed

Oei, Ling; Koromani, Fjorda; Rivadeneira, Fernando; Zillikens, M Carola; Oei, Edwin H G

2016-12-01

Osteoporosis is characterized by a decreased bone mass and quality resulting in an increased fracture risk. Quantitative imaging methods are critical in the diagnosis and follow-up of treatment effects in osteoporosis. Prior radiographic vertebral fractures and bone mineral density (BMD) as a quantitative parameter derived from dual-energy X-ray absorptiometry (DXA) are among the strongest known predictors of future osteoporotic fractures. Therefore, current clinical decision making relies heavily on accurate assessment of these imaging features. Further, novel quantitative techniques are being developed to appraise additional characteristics of osteoporosis including three-dimensional bone architecture with quantitative computed tomography (QCT). Dedicated high-resolution (HR) CT equipment is available to enhance image quality. At the other end of the spectrum, by utilizing post-processing techniques such as the trabecular bone score (TBS) information on three-dimensional architecture can be derived from DXA images. Further developments in magnetic resonance imaging (MRI) seem promising to not only capture bone micro-architecture but also characterize processes at the molecular level. This review provides an overview of various quantitative imaging techniques based on different radiological modalities utilized in clinical osteoporosis care and research.

Implementing An Image Understanding System Architecture Using Pipe

NASA Astrophysics Data System (ADS)

Luck, Randall L.

1988-03-01

This paper will describe PIPE and how it can be used to implement an image understanding system. Image understanding is the process of developing a description of an image in order to make decisions about its contents. The tasks of image understanding are generally split into low level vision and high level vision. Low level vision is performed by PIPE -a high performance parallel processor with an architecture specifically designed for processing video images at up to 60 fields per second. High level vision is performed by one of several types of serial or parallel computers - depending on the application. An additional processor called ISMAP performs the conversion from iconic image space to symbolic feature space. ISMAP plugs into one of PIPE's slots and is memory mapped into the high level processor. Thus it forms the high speed link between the low and high level vision processors. The mechanisms for bottom-up, data driven processing and top-down, model driven processing are discussed.

Scalable software architecture for on-line multi-camera video processing

NASA Astrophysics Data System (ADS)

Camplani, Massimo; Salgado, Luis

2011-03-01

In this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhead.

Hierarchical storage of large volume of multidector CT data using distributed servers

NASA Astrophysics Data System (ADS)

Ratib, Osman; Rosset, Antoine; Heuberger, Joris; Bandon, David

2006-03-01

Multidector scanners and hybrid multimodality scanners have the ability to generate large number of high-resolution images resulting in very large data sets. In most cases, these datasets are generated for the sole purpose of generating secondary processed images and 3D rendered images as well as oblique and curved multiplanar reformatted images. It is therefore not essential to archive the original images after they have been processed. We have developed an architecture of distributed archive servers for temporary storage of large image datasets for 3D rendering and image processing without the need for long term storage in PACS archive. With the relatively low cost of storage devices it is possible to configure these servers to hold several months or even years of data, long enough for allowing subsequent re-processing if required by specific clinical situations. We tested the latest generation of RAID servers provided by Apple computers with a capacity of 5 TBytes. We implemented a peer-to-peer data access software based on our Open-Source image management software called OsiriX, allowing remote workstations to directly access DICOM image files located on the server through a new technology called "bonjour". This architecture offers a seamless integration of multiple servers and workstations without the need for central database or complex workflow management tools. It allows efficient access to image data from multiple workstation for image analysis and visualization without the need for image data transfer. It provides a convenient alternative to centralized PACS architecture while avoiding complex and time-consuming data transfer and storage.

Hardware architecture design of image restoration based on time-frequency domain computation

NASA Astrophysics Data System (ADS)

Wen, Bo; Zhang, Jing; Jiao, Zipeng

2013-10-01

The image restoration algorithms based on time-frequency domain computation is high maturity and applied widely in engineering. To solve the high-speed implementation of these algorithms, the TFDC hardware architecture is proposed. Firstly, the main module is designed, by analyzing the common processing and numerical calculation. Then, to improve the commonality, the iteration control module is planed for iterative algorithms. In addition, to reduce the computational cost and memory requirements, the necessary optimizations are suggested for the time-consuming module, which include two-dimensional FFT/IFFT and the plural calculation. Eventually, the TFDC hardware architecture is adopted for hardware design of real-time image restoration system. The result proves that, the TFDC hardware architecture and its optimizations can be applied to image restoration algorithms based on TFDC, with good algorithm commonality, hardware realizability and high efficiency.

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.

Workflow-enabled distributed component-based information architecture for digital medical imaging enterprises.

PubMed

Wong, Stephen T C; Tjandra, Donny; Wang, Huili; Shen, Weimin

2003-09-01

Few information systems today offer a flexible means to define and manage the automated part of radiology processes, which provide clinical imaging services for the entire healthcare organization. Even fewer of them provide a coherent architecture that can easily cope with heterogeneity and inevitable local adaptation of applications and can integrate clinical and administrative information to aid better clinical, operational, and business decisions. We describe an innovative enterprise architecture of image information management systems to fill the needs. Such a system is based on the interplay of production workflow management, distributed object computing, Java and Web techniques, and in-depth domain knowledge in radiology operations. Our design adapts the approach of "4+1" architectural view. In this new architecture, PACS and RIS become one while the user interaction can be automated by customized workflow process. Clinical service applications are implemented as active components. They can be reasonably substituted by applications of local adaptations and can be multiplied for fault tolerance and load balancing. Furthermore, the workflow-enabled digital radiology system would provide powerful query and statistical functions for managing resources and improving productivity. This paper will potentially lead to a new direction of image information management. We illustrate the innovative design with examples taken from an implemented system.

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.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Single Input Multiple Output Technology.

PubMed

Chen, Shuo; Luo, Chenggao; Deng, Bin; Wang, Hongqiang; Cheng, Yongqiang; Zhuang, Zhaowen

2018-01-19

As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI) can achieve high-resolution, forward-looking, and staring imaging by producing spatiotemporal independent signals with coded apertures. In this paper, we propose a three-dimensional (3D) TCAI architecture based on single input multiple output (SIMO) technology, which can reduce the coding and sampling times sharply. The coded aperture applied in the proposed TCAI architecture loads either purposive or random phase modulation factor. In the transmitting process, the purposive phase modulation factor drives the terahertz beam to scan the divided 3D imaging cells. In the receiving process, the random phase modulation factor is adopted to modulate the terahertz wave to be spatiotemporally independent for high resolution. Considering human-scale targets, images of each 3D imaging cell are reconstructed one by one to decompose the global computational complexity, and then are synthesized together to obtain the complete high-resolution image. As for each imaging cell, the multi-resolution imaging method helps to reduce the computational burden on a large-scale reference-signal matrix. The experimental results demonstrate that the proposed architecture can achieve high-resolution imaging with much less time for 3D targets and has great potential in applications such as security screening, nondestructive detection, medical diagnosis, etc.

Developing a New Thesaurus for Art and Architecture.

ERIC Educational Resources Information Center

Petersen, Toni

1990-01-01

This description of the development of the Art and Architecture Thesaurus from 1979 to the present explains the processes and policies that were used to construct a language designed to represent knowledge in art and architecture, as well as to be a surrogate for the image and object being described. (EAM)

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.

A Versatile Image Processor For Digital Diagnostic Imaging And Its Application In Computed Radiography

NASA Astrophysics Data System (ADS)

Blume, H.; Alexandru, R.; Applegate, R.; Giordano, T.; Kamiya, K.; Kresina, R.

1986-06-01

In a digital diagnostic imaging department, the majority of operations for handling and processing of images can be grouped into a small set of basic operations, such as image data buffering and storage, image processing and analysis, image display, image data transmission and image data compression. These operations occur in almost all nodes of the diagnostic imaging communications network of the department. An image processor architecture was developed in which each of these functions has been mapped into hardware and software modules. The modular approach has advantages in terms of economics, service, expandability and upgradeability. The architectural design is based on the principles of hierarchical functionality, distributed and parallel processing and aims at real time response. Parallel processing and real time response is facilitated in part by a dual bus system: a VME control bus and a high speed image data bus, consisting of 8 independent parallel 16-bit busses, capable of handling combined up to 144 MBytes/sec. The presented image processor is versatile enough to meet the video rate processing needs of digital subtraction angiography, the large pixel matrix processing requirements of static projection radiography, or the broad range of manipulation and display needs of a multi-modality diagnostic work station. Several hardware modules are described in detail. For illustrating the capabilities of the image processor, processed 2000 x 2000 pixel computed radiographs are shown and estimated computation times for executing the processing opera-tions are presented.

Visual information processing II; Proceedings of the Meeting, Orlando, FL, Apr. 14-16, 1993

NASA Technical Reports Server (NTRS)

Huck, Friedrich O. (Editor); Juday, Richard D. (Editor)

1993-01-01

Various papers on visual information processing are presented. Individual topics addressed include: aliasing as noise, satellite image processing using a hammering neural network, edge-detetion method using visual perception, adaptive vector median filters, design of a reading test for low-vision image warping, spatial transformation architectures, automatic image-enhancement method, redundancy reduction in image coding, lossless gray-scale image compression by predictive GDF, information efficiency in visual communication, optimizing JPEG quantization matrices for different applications, use of forward error correction to maintain image fidelity, effect of peanoscanning on image compression. Also discussed are: computer vision for autonomous robotics in space, optical processor for zero-crossing edge detection, fractal-based image edge detection, simulation of the neon spreading effect by bandpass filtering, wavelet transform (WT) on parallel SIMD architectures, nonseparable 2D wavelet image representation, adaptive image halftoning based on WT, wavelet analysis of global warming, use of the WT for signal detection, perfect reconstruction two-channel rational filter banks, N-wavelet coding for pattern classification, simulation of image of natural objects, number-theoretic coding for iconic systems.

3-D System-on-System (SoS) Biomedical-Imaging Architecture for Health-Care Applications.

PubMed

Sang-Jin Lee; Kavehei, O; Yoon-Ki Hong; Tae Won Cho; Younggap You; Kyoungrok Cho; Eshraghian, K

2010-12-01

This paper presents the implementation of a 3-D architecture for a biomedical-imaging system based on a multilayered system-on-system structure. The architecture consists of a complementary metal-oxide semiconductor image sensor layer, memory, 3-D discrete wavelet transform (3D-DWT), 3-D Advanced Encryption Standard (3D-AES), and an RF transmitter as an add-on layer. Multilayer silicon (Si) stacking permits fabrication and optimization of individual layers by different processing technology to achieve optimal performance. Utilization of through silicon via scheme can address required low-power operation as well as high-speed performance. Potential benefits of 3-D vertical integration include an improved form factor as well as a reduction in the total wiring length, multifunctionality, power efficiency, and flexible heterogeneous integration. The proposed imaging architecture was simulated by using Cadence Spectre and Synopsys HSPICE while implementation was carried out by Cadence Virtuoso and Mentor Graphic Calibre.

The microcomputer workstation - An alternate hardware architecture for remotely sensed image analysis

NASA Technical Reports Server (NTRS)

Erickson, W. K.; Hofman, L. B.; Donovan, W. E.

1984-01-01

Difficulties regarding the digital image analysis of remotely sensed imagery can arise in connection with the extensive calculations required. In the past, an expensive large to medium mainframe computer system was needed for performing these calculations. For image-processing applications smaller minicomputer-based systems are now used by many organizations. The costs for such systems are still in the range from $100K to $300K. Recently, as a result of new developments, the use of low-cost microcomputers for image processing and display systems appeared to have become feasible. These developments are related to the advent of the 16-bit microprocessor and the concept of the microcomputer workstation. Earlier 8-bit microcomputer-based image processing systems are briefly examined, and a computer workstation architecture is discussed. Attention is given to a microcomputer workstation developed by Stanford University, and the design and implementation of a workstation network.

Local wavelet transform: a cost-efficient custom processor for space image compression

NASA Astrophysics Data System (ADS)

Masschelein, Bart; Bormans, Jan G.; Lafruit, Gauthier

2002-11-01

Thanks to its intrinsic scalability features, the wavelet transform has become increasingly popular as decorrelator in image compression applications. Throuhgput, memory requirements and complexity are important parameters when developing hardware image compression modules. An implementation of the classical, global wavelet transform requires large memory sizes and implies a large latency between the availability of the input image and the production of minimal data entities for entropy coding. Image tiling methods, as proposed by JPEG2000, reduce the memory sizes and the latency, but inevitably introduce image artefacts. The Local Wavelet Transform (LWT), presented in this paper, is a low-complexity wavelet transform architecture using a block-based processing that results in the same transformed images as those obtained by the global wavelet transform. The architecture minimizes the processing latency with a limited amount of memory. Moreover, as the LWT is an instruction-based custom processor, it can be programmed for specific tasks, such as push-broom processing of infinite-length satelite images. The features of the LWT makes it appropriate for use in space image compression, where high throughput, low memory sizes, low complexity, low power and push-broom processing are important requirements.

Noise-Coupled Image Rejection Architecture of Complex Bandpass ΔΣAD Modulator

NASA Astrophysics Data System (ADS)

San, Hao; Kobayashi, Haruo

This paper proposes a new realization technique of image rejection function by noise-coupling architecture, which is used for a complex bandpass ΔΣAD modulator. The complex bandpass ΔΣAD modulator processes just input I and Q signals, not image signals, and the AD conversion can be realized with low power dissipation. It realizes an asymmetric noise-shaped spectra, which is desirable for such low-IF receiver applications. However, the performance of the complex bandpass ΔΣAD modulator suffers from the mismatch between internal analog I and Q paths. I/Q path mismatch causes an image signal, and the quantization noise of the mirror image band aliases into the desired signal band, which degrades the SQNDR (Signal to Quantization Noise and Distortion Ratio) of the modulator. In our proposed modulator architecture, an extra notch for image rejection is realized by noise-coupled topology. We just add some passive capacitors and switches to the modulator; the additional integrator circuit composed of an operational amplifier in the conventional image rejection realization is not necessary. Therefore, the performance of the complex modulator can be effectively raised without additional power dissipation. We have performed simulation with MATLAB to confirm the validity of the proposed architecture. The simulation results show that the proposed architecture can achieve the realization of image-rejection effectively, and improve the SQNDR of the complex bandpass ΔΣAD modulator.

Image processing for navigation on a mobile embedded platform

NASA Astrophysics Data System (ADS)

Preuss, Thomas; Gentsch, Lars; Rambow, Mark

2006-02-01

Mobile computing devices such as PDAs or cellular phones may act as "Personal Multimedia Exchanges", but they are limited in their processing power as well as in their connectivity. Sensors as well as cellular phones and PDAs are able to gather multimedia data, e. g. images, but leak computing power to process that data on their own. Therefore, it is necessary, that these devices connect to devices with more performance, which provide e.g. image processing services. In this paper, a generic approach is presented that connects different kinds of clients with each other and allows them to interact with more powerful devices. This architecture, called BOSPORUS, represents a communication framework for dynamic peer-to-peer computing. Each peer offers and uses services in this network and communicates loosely coupled and asynchronously with the others. These features make BOSPORUS a service oriented network architecture (SONA). A mobile embedded system, which uses external services for image processing based on the BOSPORUS Framework is shown as an application of the BOSPORUS framework.

DREAMS and IMAGE: A Model and Computer Implementation for Concurrent, Life-Cycle Design of Complex Systems

NASA Technical Reports Server (NTRS)

Hale, Mark A.; Craig, James I.; Mistree, Farrokh; Schrage, Daniel P.

1995-01-01

Computing architectures are being assembled that extend concurrent engineering practices by providing more efficient execution and collaboration on distributed, heterogeneous computing networks. Built on the successes of initial architectures, requirements for a next-generation design computing infrastructure can be developed. These requirements concentrate on those needed by a designer in decision-making processes from product conception to recycling and can be categorized in two areas: design process and design information management. A designer both designs and executes design processes throughout design time to achieve better product and process capabilities while expanding fewer resources. In order to accomplish this, information, or more appropriately design knowledge, needs to be adequately managed during product and process decomposition as well as recomposition. A foundation has been laid that captures these requirements in a design architecture called DREAMS (Developing Robust Engineering Analysis Models and Specifications). In addition, a computing infrastructure, called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment), is being developed that satisfies design requirements defined in DREAMS and incorporates enabling computational technologies.

Adaptive neuro-heuristic hybrid model for fruit peel defects detection.

PubMed

Woźniak, Marcin; Połap, Dawid

2018-02-01

Fusion of machine learning methods benefits in decision support systems. A composition of approaches gives a possibility to use the most efficient features composed into one solution. In this article we would like to present an approach to the development of adaptive method based on fusion of proposed novel neural architecture and heuristic search into one co-working solution. We propose a developed neural network architecture that adapts to processed input co-working with heuristic method used to precisely detect areas of interest. Input images are first decomposed into segments. This is to make processing easier, since in smaller images (decomposed segments) developed Adaptive Artificial Neural Network (AANN) processes less information what makes numerical calculations more precise. For each segment a descriptor vector is composed to be presented to the proposed AANN architecture. Evaluation is run adaptively, where the developed AANN adapts to inputs and their features by composed architecture. After evaluation, selected segments are forwarded to heuristic search, which detects areas of interest. As a result the system returns the image with pixels located over peel damages. Presented experimental research results on the developed solution are discussed and compared with other commonly used methods to validate the efficacy and the impact of the proposed fusion in the system structure and training process on classification results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of two interpolation methods for empirical mode decomposition based evaluation of radiographic femur bone images.

PubMed

Udhayakumar, Ganesan; Sujatha, Chinnaswamy Manoharan; Ramakrishnan, Swaminathan

2013-01-01

Analysis of bone strength in radiographic images is an important component of estimation of bone quality in diseases such as osteoporosis. Conventional radiographic femur bone images are used to analyze its architecture using bi-dimensional empirical mode decomposition method. Surface interpolation of local maxima and minima points of an image is a crucial part of bi-dimensional empirical mode decomposition method and the choice of appropriate interpolation depends on specific structure of the problem. In this work, two interpolation methods of bi-dimensional empirical mode decomposition are analyzed to characterize the trabecular femur bone architecture of radiographic images. The trabecular bone regions of normal and osteoporotic femur bone images (N = 40) recorded under standard condition are used for this study. The compressive and tensile strength regions of the images are delineated using pre-processing procedures. The delineated images are decomposed into their corresponding intrinsic mode functions using interpolation methods such as Radial basis function multiquadratic and hierarchical b-spline techniques. Results show that bi-dimensional empirical mode decomposition analyses using both interpolations are able to represent architectural variations of femur bone radiographic images. As the strength of the bone depends on architectural variation in addition to bone mass, this study seems to be clinically useful.

Resource Efficient Hardware Architecture for Fast Computation of Running Max/Min Filters

PubMed Central

Torres-Huitzil, Cesar

2013-01-01

Running max/min filters on rectangular kernels are widely used in many digital signal and image processing applications. Filtering with a k × k kernel requires of k 2 − 1 comparisons per sample for a direct implementation; thus, performance scales expensively with the kernel size k. Faster computations can be achieved by kernel decomposition and using constant time one-dimensional algorithms on custom hardware. This paper presents a hardware architecture for real-time computation of running max/min filters based on the van Herk/Gil-Werman (HGW) algorithm. The proposed architecture design uses less computation and memory resources than previously reported architectures when targeted to Field Programmable Gate Array (FPGA) devices. Implementation results show that the architecture is able to compute max/min filters, on 1024 × 1024 images with up to 255 × 255 kernels, in around 8.4 milliseconds, 120 frames per second, at a clock frequency of 250 MHz. The implementation is highly scalable for the kernel size with good performance/area tradeoff suitable for embedded applications. The applicability of the architecture is shown for local adaptive image thresholding. PMID:24288456

Visual communications and image processing '92; Proceedings of the Meeting, Boston, MA, Nov. 18-20, 1992

NASA Astrophysics Data System (ADS)

Maragos, Petros

The topics discussed at the conference include hierarchical image coding, motion analysis, feature extraction and image restoration, video coding, and morphological and related nonlinear filtering. Attention is also given to vector quantization, morphological image processing, fractals and wavelets, architectures for image and video processing, image segmentation, biomedical image processing, and model-based analysis. Papers are presented on affine models for motion and shape recovery, filters for directly detecting surface orientation in an image, tracking of unresolved targets in infrared imagery using a projection-based method, adaptive-neighborhood image processing, and regularized multichannel restoration of color images using cross-validation. (For individual items see A93-20945 to A93-20951)

Application of a distributed systems architecture for increased speed in image processing on an autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Wright, Adam A.; Momin, Orko; Shin, Young Ho; Shakya, Rahul; Nepal, Kumud; Ahlgren, David J.

2010-01-01

This paper presents the application of a distributed systems architecture to an autonomous ground vehicle, Q, that participates in both the autonomous and navigation challenges of the Intelligent Ground Vehicle Competition. In the autonomous challenge the vehicle is required to follow a course, while avoiding obstacles and staying within the course boundaries, which are marked by white lines. For the navigation challenge, the vehicle is required to reach a set of target destinations, known as way points, with given GPS coordinates and avoid obstacles that it encounters in the process. Previously the vehicle utilized a single laptop to execute all processing activities including image processing, sensor interfacing and data processing, path planning and navigation algorithms and motor control. National Instruments' (NI) LabVIEW served as the programming language for software implementation. As an upgrade to last year's design, a NI compact Reconfigurable Input/Output system (cRIO) was incorporated to the system architecture. The cRIO is NI's solution for rapid prototyping that is equipped with a real time processor, an FPGA and modular input/output. Under the current system, the real time processor handles the path planning and navigation algorithms, the FPGA gathers and processes sensor data. This setup leaves the laptop to focus on running the image processing algorithm. Image processing as previously presented by Nepal et. al. is a multi-step line extraction algorithm and constitutes the largest processor load. This distributed approach results in a faster image processing algorithm which was previously Q's bottleneck. Additionally, the path planning and navigation algorithms are executed more reliably on the real time processor due to the deterministic nature of operation. The implementation of this architecture required exploration of various inter-system communication techniques. Data transfer between the laptop and the real time processor using UDP packets was established as the most reliable protocol after testing various options. Improvement can be made to the system by migrating more algorithms to the hardware based FPGA to further speed up the operations of the vehicle.

Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey

NASA Astrophysics Data System (ADS)

Wang, Jason J.; Perrin, Marshall D.; Savransky, Dmitry; Arriaga, Pauline; Chilcote, Jeffrey K.; De Rosa, Robert J.; Millar-Blanchaer, Maxwell A.; Marois, Christian; Rameau, Julien; Wolff, Schuyler G.; Shapiro, Jacob; Ruffio, Jean-Baptiste; Maire, Jérôme; Marchis, Franck; Graham, James R.; Macintosh, Bruce; Ammons, S. Mark; Bailey, Vanessa P.; Barman, Travis S.; Bruzzone, Sebastian; Bulger, Joanna; Cotten, Tara; Doyon, René; Duchêne, Gaspard; Fitzgerald, Michael P.; Follette, Katherine B.; Goodsell, Stephen; Greenbaum, Alexandra Z.; Hibon, Pascale; Hung, Li-Wei; Ingraham, Patrick; Kalas, Paul; Konopacky, Quinn M.; Larkin, James E.; Marley, Mark S.; Metchev, Stanimir; Nielsen, Eric L.; Oppenheimer, Rebecca; Palmer, David W.; Patience, Jennifer; Poyneer, Lisa A.; Pueyo, Laurent; Rajan, Abhijith; Rantakyrö, Fredrik T.; Schneider, Adam C.; Sivaramakrishnan, Anand; Song, Inseok; Soummer, Remi; Thomas, Sandrine; Wallace, J. Kent; Ward-Duong, Kimberly; Wiktorowicz, Sloane J.

2018-01-01

The Gemini Planet Imager Exoplanet Survey (GPIES) is a multiyear direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the Data Cruncher, combines multiple data reduction pipelines (DRPs) together to process all spectroscopic, polarimetric, and calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow up on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our DRPs. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.

Comments on `Area and power efficient DCT architecture for image compression' by Dhandapani and Ramachandran

NASA Astrophysics Data System (ADS)

Cintra, Renato J.; Bayer, Fábio M.

2017-12-01

In [Dhandapani and Ramachandran, "Area and power efficient DCT architecture for image compression", EURASIP Journal on Advances in Signal Processing 2014, 2014:180] the authors claim to have introduced an approximation for the discrete cosine transform capable of outperforming several well-known approximations in literature in terms of additive complexity. We could not verify the above results and we offer corrections for their work.

Enterprise-wide PACS: beyond radiology, an architecture to manage all medical images.

PubMed

Bandon, David; Lovis, Christian; Geissbühler, Antoine; Vallée, Jean-Paul

2005-08-01

Picture archiving and communication systems (PACS) have the vocation to manage all medical images acquired within the hospital. To address the various situations encountered in the imaging specialties, the traditional architecture used for the radiology department has to evolve. We present our preliminarily results toward an enterprise-wide PACS intended to support all kind of image production in medicine, from biomolecular images to whole-body pictures. Our solution is based on an existing radiologic PACS system from which images are distributed through an electronic patient record to all care facilities. This platform is enriched with a flexible integration framework supporting digital image communication in medicine (DICOM) and DICOM-XML formats. In addition, a generic workflow engine highly customizable is used to drive work processes. Echocardiology; hematology; ear, nose, and throat; and dermatology, including wounds, follow-up is the first implemented extensions outside of radiology. We also propose a global strategy for further developments based on three possible architectures for an enterprise-wide PACS.

An Image Retrieval and Processing Expert System for the World Wide Web

NASA Technical Reports Server (NTRS)

Rodriguez, Ricardo; Rondon, Angelica; Bruno, Maria I.; Vasquez, Ramon

1998-01-01

This paper presents a system that is being developed in the Laboratory of Applied Remote Sensing and Image Processing at the University of P.R. at Mayaguez. It describes the components that constitute its architecture. The main elements are: a Data Warehouse, an Image Processing Engine, and an Expert System. Together, they provide a complete solution to researchers from different fields that make use of images in their investigations. Also, since it is available to the World Wide Web, it provides remote access and processing of images.

An improved architecture for video rate image transformations

NASA Technical Reports Server (NTRS)

Fisher, Timothy E.; Juday, Richard D.

1989-01-01

Geometric image transformations are of interest to pattern recognition algorithms for their use in simplifying some aspects of the pattern recognition process. Examples include reducing sensitivity to rotation, scale, and perspective of the object being recognized. The NASA Programmable Remapper can perform a wide variety of geometric transforms at full video rate. An architecture is proposed that extends its abilities and alleviates many of the first version's shortcomings. The need for the improvements are discussed in the context of the initial Programmable Remapper and the benefits and limitations it has delivered. The implementation and capabilities of the proposed architecture are discussed.

The AIS-5000 parallel processor

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

Schmitt, L.A.; Wilson, S.S.

1988-05-01

The AIS-5000 is a commercially available massively parallel processor which has been designed to operate in an industrial environment. It has fine-grained parallelism with up to 1024 processing elements arranged in a single-instruction multiple-data (SIMD) architecture. The processing elements are arranged in a one-dimensional chain that, for computer vision applications, can be as wide as the image itself. This architecture has superior cost/performance characteristics than two-dimensional mesh-connected systems. The design of the processing elements and their interconnections as well as the software used to program the system allow a wide variety of algorithms and applications to be implemented. In thismore » paper, the overall architecture of the system is described. Various components of the system are discussed, including details of the processing elements, data I/O pathways and parallel memory organization. A virtual two-dimensional model for programming image-based algorithms for the system is presented. This model is supported by the AIS-5000 hardware and software and allows the system to be treated as a full-image-size, two-dimensional, mesh-connected parallel processor. Performance bench marks are given for certain simple and complex functions.« less

Rhizoslides: paper-based growth system for non-destructive, high throughput phenotyping of root development by means of image analysis.

PubMed

Le Marié, Chantal; Kirchgessner, Norbert; Marschall, Daniela; Walter, Achim; Hund, Andreas

2014-01-01

A quantitative characterization of root system architecture is currently being attempted for various reasons. Non-destructive, rapid analyses of root system architecture are difficult to perform due to the hidden nature of the root. Hence, improved methods to measure root architecture are necessary to support knowledge-based plant breeding and to analyse root growth responses to environmental changes. Here, we report on the development of a novel method to reveal growth and architecture of maize root systems. The method is based on the cultivation of different root types within several layers of two-dimensional, large (50 × 60 cm) plates (rhizoslides). A central plexiglass screen stabilizes the system and is covered on both sides with germination paper providing water and nutrients for the developing root, followed by a transparent cover foil to prevent the roots from falling dry and to stabilize the system. The embryonic roots grow hidden between a Plexiglas surface and paper, whereas crown roots grow visible between paper and the transparent cover. Long cultivation with good image quality up to 20 days (four fully developed leaves) was enhanced by suppressing fungi with a fungicide. Based on hyperspectral microscopy imaging, the quality of different germination papers was tested and three provided sufficient contrast to distinguish between roots and background (segmentation). Illumination, image acquisition and segmentation were optimised to facilitate efficient root image analysis. Several software packages were evaluated with regard to their precision and the time investment needed to measure root system architecture. The software 'Smart Root' allowed precise evaluation of root development but needed substantial user interference. 'GiaRoots' provided the best segmentation method for batch processing in combination with a good analysis of global root characteristics but overestimated root length due to thinning artefacts. 'WhinRhizo' offered the most rapid and precise evaluation of root lengths in diameter classes, but had weaknesses with respect to image segmentation and analysis of root system architecture. A new technique has been established for non-destructive root growth studies and quantification of architectural traits beyond seedlings stages. However, automation of the scanning process and appropriate software remains the bottleneck for high throughput analysis.

Design and Fabrication of High-Efficiency CMOS/CCD Imagers

NASA Technical Reports Server (NTRS)

Pain, Bedabrata

2007-01-01

An architecture for back-illuminated complementary metal oxide/semiconductor (CMOS) and charge-coupled-device (CCD) ultraviolet/visible/near infrared- light image sensors, and a method of fabrication to implement the architecture, are undergoing development. The architecture and method are expected to enable realization of the full potential of back-illuminated CMOS/CCD imagers to perform with high efficiency, high sensitivity, excellent angular response, and in-pixel signal processing. The architecture and method are compatible with next-generation CMOS dielectric-forming and metallization techniques, and the process flow of the method is compatible with process flows typical of the manufacture of very-large-scale integrated (VLSI) circuits. The architecture and method overcome all obstacles that have hitherto prevented high-yield, low-cost fabrication of back-illuminated CMOS/CCD imagers by use of standard VLSI fabrication tools and techniques. It is not possible to discuss the obstacles in detail within the space available for this article. Briefly, the obstacles are posed by the problems of generating light-absorbing layers having desired uniform and accurate thicknesses, passivation of surfaces, forming structures for efficient collection of charge carriers, and wafer-scale thinning (in contradistinction to diescale thinning). A basic element of the present architecture and method - the element that, more than any other, makes it possible to overcome the obstacles - is the use of an alternative starting material: Instead of starting with a conventional bulk-CMOS wafer that consists of a p-doped epitaxial silicon layer grown on a heavily-p-doped silicon substrate, one starts with a special silicon-on-insulator (SOI) wafer that consists of a thermal oxide buried between a lightly p- or n-doped, thick silicon layer and a device silicon layer of appropriate thickness and doping. The thick silicon layer is used as a handle: that is, as a mechanical support for the device silicon layer during micro-fabrication.

In-flight control and communication architecture of the GLORIA imaging limb sounder on atmospheric research aircraft

NASA Astrophysics Data System (ADS)

Kretschmer, E.; Bachner, M.; Blank, J.; Dapp, R.; Ebersoldt, A.; Friedl-Vallon, F.; Guggenmoser, T.; Gulde, T.; Hartmann, V.; Lutz, R.; Maucher, G.; Neubert, T.; Oelhaf, H.; Preusse, P.; Schardt, G.; Schmitt, C.; Schönfeld, A.; Tan, V.

2015-06-01

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA), a Fourier-transform-spectrometer-based limb spectral imager, operates on high-altitude research aircraft to study the transit region between the troposphere and the stratosphere. It is one of the most sophisticated systems to be flown on research aircraft in Europe, requiring constant monitoring and human intervention in addition to an automation system. To ensure proper functionality and interoperability on multiple platforms, a flexible control and communication system was laid out. The architectures of the communication system as well as the protocols used are reviewed. The integration of this architecture in the automation process as well as the scientific campaign flight application context are discussed.

In-flight control and communication architecture of the GLORIA imaging limb-sounder on atmospheric research aircraft

NASA Astrophysics Data System (ADS)

Kretschmer, E.; Bachner, M.; Blank, J.; Dapp, R.; Ebersoldt, A.; Friedl-Vallon, F.; Guggenmoser, T.; Gulde, T.; Hartmann, V.; Lutz, R.; Maucher, G.; Neubert, T.; Oelhaf, H.; Preusse, P.; Schardt, G.; Schmitt, C.; Schönfeld, A.; Tan, V.

2015-02-01

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA), a Fourier transform spectrometer based limb spectral imager, operates on high-altitude research aircraft to study the transit region between the troposphere and the stratosphere. It is one of the most sophisticated systems to be flown on research aircraft in Europe, requiring constant monitoring and human intervention in addition to an automation system. To ensure proper functionality and interoperability on multiple platforms, a flexible control and communication system was laid out. The architectures of the communication system as well as the protocols used are reviewed. The integration of this architecture in the automation process as well as the scientific campaign flight application context are discussed.

Iplt--image processing library and toolkit for the electron microscopy community.

PubMed

Philippsen, Ansgar; Schenk, Andreas D; Stahlberg, Henning; Engel, Andreas

2003-01-01

We present the foundation for establishing a modular, collaborative, integrated, open-source architecture for image processing of electron microscopy images, named iplt. It is designed around object oriented paradigms and implemented using the programming languages C++ and Python. In many aspects it deviates from classical image processing approaches. This paper intends to motivate developers within the community to participate in this on-going project. The iplt homepage can be found at http://www.iplt.org.

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.

Synthetic Aperture Radar (SAR) data processing

NASA Technical Reports Server (NTRS)

Beckner, F. L.; Ahr, H. A.; Ausherman, D. A.; Cutrona, L. J.; Francisco, S.; Harrison, R. E.; Heuser, J. S.; Jordan, R. L.; Justus, J.; Manning, B.

1978-01-01

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed.

TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization.

PubMed

Ollion, Jean; Cochennec, Julien; Loll, François; Escudé, Christophe; Boudier, Thomas

2013-07-15

The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images. Here, we describe Tools for Analysis of Nuclear Genome Organization (TANGO), an image analysis tool dedicated to the study of nuclear architecture. TANGO is a coherent framework allowing biologists to perform the complete analysis process of 3D fluorescence images by combining two environments: ImageJ (http://imagej.nih.gov/ij/) for image processing and quantitative analysis and R (http://cran.r-project.org) for statistical processing of measurement results. It includes an intuitive user interface providing the means to precisely build a segmentation procedure and set-up analyses, without possessing programming skills. TANGO is a versatile tool able to process large sets of images, allowing quantitative study of nuclear organization. TANGO is composed of two programs: (i) an ImageJ plug-in and (ii) a package (rtango) for R. They are both free and open source, available (http://biophysique.mnhn.fr/tango) for Linux, Microsoft Windows and Macintosh OSX. Distribution is under the GPL v.2 licence. thomas.boudier@snv.jussieu.fr Supplementary data are available at Bioinformatics online.

Onboard data-processing architecture of the soft X-ray imager (SXI) on NeXT satellite

NASA Astrophysics Data System (ADS)

Ozaki, Masanobu; Dotani, Tadayasu; Tsunemi, Hiroshi; Hayashida, Kiyoshi; Tsuru, Takeshi G.

2004-09-01

NeXT is the X-ray satellite proposed for the next Japanese space science mission. While the satellite total mass and the launching vehicle are similar to the prior satellite Astro-E2, the sensitivity is much improved; it requires all the components to be lighter and faster than previous architecture. This paper shows the data processing architecture of the X-ray CCD camera system SXI (Soft X-ray Imager), which is the top half of the WXI (Wide-band X-ray Imager) of the sensitivity in 0.2-80keV. The system is basically a variation of Astro-E2 XIS, but event extraction speed is much faster than it to fulfill the requirements coming from the large effective area and fast exposure period. At the same time, data transfer lines between components are redesigned in order to reduce the number and mass of the wire harnesses that limit the flexibility of the component distribution.

Architecture of distributed picture archiving and communication systems for storing and processing high resolution medical images

NASA Astrophysics Data System (ADS)

Tokareva, Victoria

2018-04-01

New generation medicine demands a better quality of analysis increasing the amount of data collected during checkups, and simultaneously decreasing the invasiveness of a procedure. Thus it becomes urgent not only to develop advanced modern hardware, but also to implement special software infrastructure for using it in everyday clinical practice, so-called Picture Archiving and Communication Systems (PACS). Developing distributed PACS is a challenging task for nowadays medical informatics. The paper discusses the architecture of distributed PACS server for processing large high-quality medical images, with respect to technical specifications of modern medical imaging hardware, as well as international standards in medical imaging software. The MapReduce paradigm is proposed for image reconstruction by server, and the details of utilizing the Hadoop framework for this task are being discussed in order to provide the design of distributed PACS as ergonomic and adapted to the needs of end users as possible.

JAtlasView: a Java atlas-viewer for browsing biomedical 3D images and atlases.

PubMed

Feng, Guangjie; Burton, Nick; Hill, Bill; Davidson, Duncan; Kerwin, Janet; Scott, Mark; Lindsay, Susan; Baldock, Richard

2005-03-09

Many three-dimensional (3D) images are routinely collected in biomedical research and a number of digital atlases with associated anatomical and other information have been published. A number of tools are available for viewing this data ranging from commercial visualization packages to freely available, typically system architecture dependent, solutions. Here we discuss an atlas viewer implemented to run on any workstation using the architecture neutral Java programming language. We report the development of a freely available Java based viewer for 3D image data, descibe the structure and functionality of the viewer and how automated tools can be developed to manage the Java Native Interface code. The viewer allows arbitrary re-sectioning of the data and interactive browsing through the volume. With appropriately formatted data, for example as provided for the Electronic Atlas of the Developing Human Brain, a 3D surface view and anatomical browsing is available. The interface is developed in Java with Java3D providing the 3D rendering. For efficiency the image data is manipulated using the Woolz image-processing library provided as a dynamically linked module for each machine architecture. We conclude that Java provides an appropriate environment for efficient development of these tools and techniques exist to allow computationally efficient image-processing libraries to be integrated relatively easily.

Software architecture for time-constrained machine vision applications

NASA Astrophysics Data System (ADS)

Usamentiaga, Rubén; Molleda, Julio; García, Daniel F.; Bulnes, Francisco G.

2013-01-01

Real-time image and video processing applications require skilled architects, and recent trends in the hardware platform make the design and implementation of these applications increasingly complex. Many frameworks and libraries have been proposed or commercialized to simplify the design and tuning of real-time image processing applications. However, they tend to lack flexibility, because they are normally oriented toward particular types of applications, or they impose specific data processing models such as the pipeline. Other issues include large memory footprints, difficulty for reuse, and inefficient execution on multicore processors. We present a novel software architecture for time-constrained machine vision applications that addresses these issues. The architecture is divided into three layers. The platform abstraction layer provides a high-level application programming interface for the rest of the architecture. The messaging layer provides a message-passing interface based on a dynamic publish/subscribe pattern. A topic-based filtering in which messages are published to topics is used to route the messages from the publishers to the subscribers interested in a particular type of message. The application layer provides a repository for reusable application modules designed for machine vision applications. These modules, which include acquisition, visualization, communication, user interface, and data processing, take advantage of the power of well-known libraries such as OpenCV, Intel IPP, or CUDA. Finally, the proposed architecture is applied to a real machine vision application: a jam detector for steel pickling lines.

Fast semivariogram computation using FPGA architectures

NASA Astrophysics Data System (ADS)

Lagadapati, Yamuna; Shirvaikar, Mukul; Dong, Xuanliang

2015-02-01

The semivariogram is a statistical measure of the spatial distribution of data and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. The semivariogram is a plot of semivariances for different lag distances between pixels. A semi-variance, γ(h), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h. Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O(n2). Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz, but they can perform tens of thousands of calculations per clock cycle while operating in the low range of power. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. The design consists of several modules dedicated to the constituent computational tasks. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current implementation is focused on isotropic semivariogram computations only. Anisotropic semivariogram implementation is anticipated to be an extension of the current architecture, ostensibly based on refinements to the current modules. The algorithm is benchmarked using VHDL on a Xilinx XUPV5-LX110T development Kit, which utilizes the Virtex5 FPGA. Medical image data from MRI scans are utilized for the experiments. Computational speedup is measured with respect to Matlab implementation on a personal computer with an Intel i7 multi-core processor. Preliminary simulation results indicate that a significant advantage in speed can be attained by the architectures, making the algorithm viable for implementation in medical devices

Manyscale Computing for Sensor Processing in Support of Space Situational Awareness

NASA Astrophysics Data System (ADS)

Schmalz, M.; Chapman, W.; Hayden, E.; Sahni, S.; Ranka, S.

2014-09-01

Increasing image and signal data burden associated with sensor data processing in support of space situational awareness implies continuing computational throughput growth beyond the petascale regime. In addition to growing applications data burden and diversity, the breadth, diversity and scalability of high performance computing architectures and their various organizations challenge the development of a single, unifying, practicable model of parallel computation. Therefore, models for scalable parallel processing have exploited architectural and structural idiosyncrasies, yielding potential misapplications when legacy programs are ported among such architectures. In response to this challenge, we have developed a concise, efficient computational paradigm and software called Manyscale Computing to facilitate efficient mapping of annotated application codes to heterogeneous parallel architectures. Our theory, algorithms, software, and experimental results support partitioning and scheduling of application codes for envisioned parallel architectures, in terms of work atoms that are mapped (for example) to threads or thread blocks on computational hardware. Because of the rigor, completeness, conciseness, and layered design of our manyscale approach, application-to-architecture mapping is feasible and scalable for architectures at petascales, exascales, and above. Further, our methodology is simple, relying primarily on a small set of primitive mapping operations and support routines that are readily implemented on modern parallel processors such as graphics processing units (GPUs) and hybrid multi-processors (HMPs). In this paper, we overview the opportunities and challenges of manyscale computing for image and signal processing in support of space situational awareness applications. We discuss applications in terms of a layered hardware architecture (laboratory > supercomputer > rack > processor > component hierarchy). Demonstration applications include performance analysis and results in terms of execution time as well as storage, power, and energy consumption for bus-connected and/or networked architectures. The feasibility of the manyscale paradigm is demonstrated by addressing four principal challenges: (1) architectural/structural diversity, parallelism, and locality, (2) masking of I/O and memory latencies, (3) scalability of design as well as implementation, and (4) efficient representation/expression of parallel applications. Examples will demonstrate how manyscale computing helps solve these challenges efficiently on real-world computing systems.

Flexible distributed architecture for semiconductor process control and experimentation

NASA Astrophysics Data System (ADS)

Gower, Aaron E.; Boning, Duane S.; McIlrath, Michael B.

1997-01-01

Semiconductor fabrication requires an increasingly expensive and integrated set of tightly controlled processes, driving the need for a fabrication facility with fully computerized, networked processing equipment. We describe an integrated, open system architecture enabling distributed experimentation and process control for plasma etching. The system was developed at MIT's Microsystems Technology Laboratories and employs in-situ CCD interferometry based analysis in the sensor-feedback control of an Applied Materials Precision 5000 Plasma Etcher (AME5000). Our system supports accelerated, advanced research involving feedback control algorithms, and includes a distributed interface that utilizes the internet to make these fabrication capabilities available to remote users. The system architecture is both distributed and modular: specific implementation of any one task does not restrict the implementation of another. The low level architectural components include a host controller that communicates with the AME5000 equipment via SECS-II, and a host controller for the acquisition and analysis of the CCD sensor images. A cell controller (CC) manages communications between these equipment and sensor controllers. The CC is also responsible for process control decisions; algorithmic controllers may be integrated locally or via remote communications. Finally, a system server images connections from internet/intranet (web) based clients and uses a direct link with the CC to access the system. Each component communicates via a predefined set of TCP/IP socket based messages. This flexible architecture makes integration easier and more robust, and enables separate software components to run on the same or different computers independent of hardware or software platform.

A FPGA-based architecture for real-time image matching

NASA Astrophysics Data System (ADS)

Wang, Jianhui; Zhong, Sheng; Xu, Wenhui; Zhang, Weijun; Cao, Zhiguo

2013-10-01

Image matching is a fundamental task in computer vision. It is used to establish correspondence between two images taken at different viewpoint or different time from the same scene. However, its large computational complexity has been a challenge to most embedded systems. This paper proposes a single FPGA-based image matching system, which consists of SIFT feature detection, BRIEF descriptor extraction and BRIEF matching. It optimizes the FPGA architecture for the SIFT feature detection to reduce the FPGA resources utilization. Moreover, we implement BRIEF description and matching on FPGA also. The proposed system can implement image matching at 30fps (frame per second) for 1280x720 images. Its processing speed can meet the demand of most real-life computer vision applications.

Radiology Architecture Project Primer.

PubMed

Sze, Raymond W; Hogan, Laurie; Teshima, Satoshi; Davidson, Scott

2017-12-19

The rapid pace of technologic advancement and increasing expectations for patient- and family-friendly environments make it common for radiology leaders to be involved in imaging remodel and construction projects. Most radiologists and business directors lack formal training in architectural and construction processes but are expected to play significant and often leading roles in all phases of an imaging construction project. Avoidable mistakes can result in significant increased costs and scheduling delays; knowledgeable participation and communication can result in a final product that enhances staff workflow and morale and improves patient care and experience. This article presents practical guidelines for preparing for and leading a new imaging architectural and construction project. We share principles derived from the radiology and nonradiology literature and our own experience over the past decade completely remodeling a large pediatric radiology department and building a full-service outpatient imaging center. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

A Comparative Study : Microprogrammed Vs Risc Architectures For Symbolic Processing

NASA Astrophysics Data System (ADS)

Heudin, J. C.; Metivier, C.; Demigny, D.; Maurin, T.; Zavidovique, B.; Devos, F.

1987-05-01

It is oftenclaimed that conventional computers are not well suited for human-like tasks : Vision (Image Processing), Intelligence (Symbolic Processing) ... In the particular case of Artificial Intelligence, dynamic type-checking is one example of basic task that must be improved. The solution implemented in most Lisp work-stations consists in a microprogrammed architecture with a tagged memory. Another way to gain efficiency is to design a well suited instruction set for symbolic processing, which reduces the semantic gap between the high level language and the machine code. In this framework, the RISC concept provides a convenient approach to study new architectures for symbolic processing. This paper compares both approaches and describes our projectof designing a compact symbolic processor for Artificial Intelligence applications.

From Landsat through SLI: Ball Aerospace Instrument Architecture for Earth Surface Monitoring

NASA Astrophysics Data System (ADS)

Wamsley, P. R.; Gilmore, A. S.; Malone, K. J.; Kampe, T. U.; Good, W. S.

2017-12-01

The Landsat legacy spans more than forty years of moderate resolution, multi-spectral imaging of the Earth's surface. Applications for Landsat data include global environmental change, disaster planning and recovery, crop and natural resource management, and glaciology. In recent years, coastal water science has been greatly enhanced by the outstanding on-orbit performance of Landsat 8. Ball Aerospace designed and built the Operational Land Imager (OLI) instrument on Landsat 8, and is in the process of building OLI 2 for Landsat 9. Both of these instruments have the same design however improved performance is expected from OLI 2 due to greater image bit depth (14 bit on OLI 2 vs 12 bit on OLI). Ball Aerospace is currently working on two novel instrument architectures applicable to Sustainable Land Imaging for Landsat 10 and beyond. With increased budget constraints probable for future missions, technological improvements must be included in future instrument architectures to enable increased capabilities at lower cost. Ball presents the instrument architectures and associated capabilities enabling new science in past, current, and future Landsat missions.

Low-power coprocessor for Haar-like feature extraction with pixel-based pipelined architecture

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Fujita, Yuki; Zhang, Xiangyu; Chen, Lei; Jürgen Mattausch, Hans

2017-04-01

Intelligent analysis of image and video data requires image-feature extraction as an important processing capability for machine-vision realization. A coprocessor with pixel-based pipeline (CFEPP) architecture is developed for real-time Haar-like cell-based feature extraction. Synchronization with the image sensor’s pixel frequency and immediate usage of each input pixel for the feature-construction process avoids the dependence on memory-intensive conventional strategies like integral-image construction or frame buffers. One 180 nm CMOS prototype can extract the 1680-dimensional Haar-like feature vectors, applied in the speeded up robust features (SURF) scheme, using an on-chip memory of only 96 kb (kilobit). Additionally, a low power dissipation of only 43.45 mW at 1.8 V supply voltage is achieved during VGA video procession at 120 MHz frequency with more than 325 fps. The Haar-like feature-extraction coprocessor is further evaluated by the practical application of vehicle recognition, achieving the expected high accuracy which is comparable to previous work.

Parallel processing approach to transform-based image coding

NASA Astrophysics Data System (ADS)

Normile, James O.; Wright, Dan; Chu, Ken; Yeh, Chia L.

1991-06-01

This paper describes a flexible parallel processing architecture designed for use in real time video processing. The system consists of floating point DSP processors connected to each other via fast serial links, each processor has access to a globally shared memory. A multiple bus architecture in combination with a dual ported memory allows communication with a host control processor. The system has been applied to prototyping of video compression and decompression algorithms. The decomposition of transform based algorithms for decompression into a form suitable for parallel processing is described. A technique for automatic load balancing among the processors is developed and discussed, results ar presented with image statistics and data rates. Finally techniques for accelerating the system throughput are analyzed and results from the application of one such modification described.

Semivariogram Analysis of Bone Images Implemented on FPGA Architectures.

PubMed

Shirvaikar, Mukul; Lagadapati, Yamuna; Dong, Xuanliang

2017-03-01

Osteoporotic fractures are a major concern for the healthcare of elderly and female populations. Early diagnosis of patients with a high risk of osteoporotic fractures can be enhanced by introducing second-order statistical analysis of bone image data using techniques such as variogram analysis. Such analysis is computationally intensive thereby creating an impediment for introduction into imaging machines found in common clinical settings. This paper investigates the fast implementation of the semivariogram algorithm, which has been proven to be effective in modeling bone strength, and should be of interest to readers in the areas of computer-aided diagnosis and quantitative image analysis. The semivariogram is a statistical measure of the spatial distribution of data, and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. A semi-variance, γ ( h ), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h . Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O ( n 2 ) Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current implementation is focused on isotropic semivariogram computations only. The algorithm is benchmarked using VHDL on a Xilinx XUPV5-LX110T development Kit, which utilizes the Virtex5 FPGA. Medical image data from DXA scans are utilized for the experiments. Implementation results show that a significant advantage in computational speed is attained by the architectures with respect to implementation on a personal computer with an Intel i7 multi-core processor.

Semivariogram Analysis of Bone Images Implemented on FPGA Architectures

PubMed Central

Shirvaikar, Mukul; Lagadapati, Yamuna; Dong, Xuanliang

2016-01-01

Osteoporotic fractures are a major concern for the healthcare of elderly and female populations. Early diagnosis of patients with a high risk of osteoporotic fractures can be enhanced by introducing second-order statistical analysis of bone image data using techniques such as variogram analysis. Such analysis is computationally intensive thereby creating an impediment for introduction into imaging machines found in common clinical settings. This paper investigates the fast implementation of the semivariogram algorithm, which has been proven to be effective in modeling bone strength, and should be of interest to readers in the areas of computer-aided diagnosis and quantitative image analysis. The semivariogram is a statistical measure of the spatial distribution of data, and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. A semi-variance, γ(h), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h. Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O (n2) Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current implementation is focused on isotropic semivariogram computations only. The algorithm is benchmarked using VHDL on a Xilinx XUPV5-LX110T development Kit, which utilizes the Virtex5 FPGA. Medical image data from DXA scans are utilized for the experiments. Implementation results show that a significant advantage in computational speed is attained by the architectures with respect to implementation on a personal computer with an Intel i7 multi-core processor. PMID:28428829

Performance evaluation of canny edge detection on a tiled multicore architecture

NASA Astrophysics Data System (ADS)

Brethorst, Andrew Z.; Desai, Nehal; Enright, Douglas P.; Scrofano, Ronald

2011-01-01

In the last few years, a variety of multicore architectures have been used to parallelize image processing applications. In this paper, we focus on assessing the parallel speed-ups of different Canny edge detection parallelization strategies on the Tile64, a tiled multicore architecture developed by the Tilera Corporation. Included in these strategies are different ways Canny edge detection can be parallelized, as well as differences in data management. The two parallelization strategies examined were loop-level parallelism and domain decomposition. Loop-level parallelism is achieved through the use of OpenMP,1 and it is capable of parallelization across the range of values over which a loop iterates. Domain decomposition is the process of breaking down an image into subimages, where each subimage is processed independently, in parallel. The results of the two strategies show that for the same number of threads, programmer implemented, domain decomposition exhibits higher speed-ups than the compiler managed, loop-level parallelism implemented with OpenMP.

Cache write generate for parallel image processing on shared memory architectures.

PubMed

Wittenbrink, C M; Somani, A K; Chen, C H

1996-01-01

We investigate cache write generate, our cache mode invention. We demonstrate that for parallel image processing applications, the new mode improves main memory bandwidth, CPU efficiency, cache hits, and cache latency. We use register level simulations validated by the UW-Proteus system. Many memory, cache, and processor configurations are evaluated.

Synthetic Foveal Imaging Technology

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Monacos, Steve P. (Inventor); Hoenk, Michael E. (Inventor)

2013-01-01

Apparatuses and methods are disclosed that create a synthetic fovea in order to identify and highlight interesting portions of an image for further processing and rapid response. Synthetic foveal imaging implements a parallel processing architecture that uses reprogrammable logic to implement embedded, distributed, real-time foveal image processing from different sensor types while simultaneously allowing for lossless storage and retrieval of raw image data. Real-time, distributed, adaptive processing of multi-tap image sensors with coordinated processing hardware used for each output tap is enabled. In mosaic focal planes, a parallel-processing network can be implemented that treats the mosaic focal plane as a single ensemble rather than a set of isolated sensors. Various applications are enabled for imaging and robotic vision where processing and responding to enormous amounts of data quickly and efficiently is important.

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.

DDGIPS: a general image processing system in robot vision

NASA Astrophysics Data System (ADS)

Tian, Yuan; Ying, Jun; Ye, Xiuqing; Gu, Weikang

2000-10-01

Real-Time Image Processing is the key work in robot vision. With the limitation of the hardware technique, many algorithm-oriented firmware systems were designed in the past. But their architectures were not flexible enough to achieve a multi-algorithm development system. Because of the rapid development of microelectronics technique, many high performance DSP chips and high density FPGA chips have come to life, and this makes it possible to construct a more flexible architecture in real-time image processing system. In this paper, a Double DSP General Image Processing System (DDGIPS) is concerned. We try to construct a two-DSP-based FPGA-computational system with two TMS320C6201s. The TMS320C6x devices are fixed-point processors based on the advanced VLIW CPU, which has eight functional units, including two multipliers and six arithmetic logic units. These features make C6x a good candidate for a general purpose system. In our system, the two TMS320C6201s each has a local memory space, and they also have a shared system memory space which enables them to intercommunicate and exchange data efficiently. At the same time, they can be directly inter-connected in star-shaped architecture. All of these are under the control of a FPGA group. As the core of the system, FPGA plays a very important role: it takes charge of DPS control, DSP communication, memory space access arbitration and the communication between the system and the host machine. And taking advantage of reconfiguring FPGA, all of the interconnection between the two DSP or between DSP and FPGA can be changed. In this way, users can easily rebuild the real-time image processing system according to the data stream and the task of the application and gain great flexibility.

DDGIPS: a general image processing system in robot vision

NASA Astrophysics Data System (ADS)

Tian, Yuan; Ying, Jun; Ye, Xiuqing; Gu, Weikang

2000-10-01

Real-Time Image Processing is the key work in robot vision. With the limitation of the hardware technique, many algorithm-oriented firmware systems were designed in the past. But their architectures were not flexible enough to achieve a multi- algorithm development system. Because of the rapid development of microelectronics technique, many high performance DSP chips and high density FPGA chips have come to life, and this makes it possible to construct a more flexible architecture in real-time image processing system. In this paper, a Double DSP General Image Processing System (DDGIPS) is concerned. We try to construct a two-DSP-based FPGA-computational system with two TMS320C6201s. The TMS320C6x devices are fixed-point processors based on the advanced VLIW CPU, which has eight functional units, including two multipliers and six arithmetic logic units. These features make C6x a good candidate for a general purpose system. In our system, the two TMS320C6210s each has a local memory space, and they also have a shared system memory space which enable them to intercommunicate and exchange data efficiently. At the same time, they can be directly interconnected in star- shaped architecture. All of these are under the control of FPGA group. As the core of the system, FPGA plays a very important role: it takes charge of DPS control, DSP communication, memory space access arbitration and the communication between the system and the host machine. And taking advantage of reconfiguring FPGA, all of the interconnection between the two DSP or between DSP and FPGA can be changed. In this way, users can easily rebuild the real-time image processing system according to the data stream and the task of the application and gain great flexibility.

Ground Penetrating Radar Imaging of Ancient Clastic Deposits: A Tool for Three-Dimensional Outcrop Studies

NASA Astrophysics Data System (ADS)

Akinpelu, Oluwatosin Caleb

The growing need for better definition of flow units and depositional heterogeneities in petroleum reservoirs and aquifers has stimulated a renewed interest in outcrop studies as reservoir analogues in the last two decades. Despite this surge in interest, outcrop studies remain largely two-dimensional; a major limitation to direct application of outcrop knowledge to the three dimensional heterogeneous world of subsurface reservoirs. Behind-outcrop Ground Penetrating Radar (GPR) imaging provides high-resolution geophysical data, which when combined with two dimensional architectural outcrop observation, becomes a powerful interpretation tool. Due to the high resolution, non-destructive and non-invasive nature of the GPR signal, as well as its reflection-amplitude sensitivity to shaly lithologies, three-dimensional outcrop studies combining two dimensional architectural element data and behind-outcrop GPR imaging hold significant promise with the potential to revolutionize outcrop studies the way seismic imaging changed basin analysis. Earlier attempts at GPR imaging on ancient clastic deposits were fraught with difficulties resulting from inappropriate field techniques and subsequent poorly-informed data processing steps. This project documents advances in GPR field methodology, recommends appropriate data collection and processing procedures and validates the value of integrating outcrop-based architectural-element mapping with GPR imaging to obtain three dimensional architectural data from outcrops. Case studies from a variety of clastic deposits: Whirlpool Formation (Niagara Escarpment), Navajo Sandstone (Moab, Utah), Dunvegan Formation (Pink Mountain, British Columbia), Chinle Formation (Southern Utah) and St. Mary River Formation (Alberta) demonstrate the usefulness of this approach for better interpretation of outcrop scale ancient depositional processes and ultimately as a tool for refining existing facies models, as well as a predictive tool for subsurface reservoir modelling. While this approach is quite promising for detailed three-dimensional outcrop studies, it is not an all-purpose panacea; thick overburden, poor antenna-ground coupling in rough terrains typical of outcrops, low penetration and rapid signal attenuation in mudstone and diagenetic clay- rich deposits often limit the prospects of this novel technique.

Parallel asynchronous systems and image processing algorithms

NASA Technical Reports Server (NTRS)

Coon, D. D.; Perera, A. G. U.

1989-01-01

A new hardware approach to implementation of image processing algorithms is described. The approach is based on silicon devices which would permit an independent analog processing channel to be dedicated to evey pixel. A laminar architecture consisting of a stack of planar arrays of the device would form a two-dimensional array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuronlike asynchronous pulse coded form through the laminar processor. Such systems would integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The research is aimed at implementation of algorithms, such as the intensity dependent summation algorithm and pyramid processing structures, which are motivated by the operation of natural vision systems. Implementation of natural vision algorithms would benefit from the use of neuronlike information coding and the laminar, 2-D parallel, vision system type architecture. Besides providing a neural network framework for implementation of natural vision algorithms, a 2-D parallel approach could eliminate the serial bottleneck of conventional processing systems. Conversion to serial format would occur only after raw intensity data has been substantially processed. An interesting challenge arises from the fact that the mathematical formulation of natural vision algorithms does not specify the means of implementation, so that hardware implementation poses intriguing questions involving vision science.

Computer Sciences and Data Systems, volume 1

NASA Technical Reports Server (NTRS)

1987-01-01

Topics addressed include: software engineering; university grants; institutes; concurrent processing; sparse distributed memory; distributed operating systems; intelligent data management processes; expert system for image analysis; fault tolerant software; and architecture research.

Uranus: a rapid prototyping tool for FPGA embedded computer vision

NASA Astrophysics Data System (ADS)

Rosales-Hernández, Victor; Castillo-Jimenez, Liz; Viveros-Velez, Gilberto; Zuñiga-Grajeda, Virgilio; Treviño Torres, Abel; Arias-Estrada, M.

2007-01-01

The starting point for all successful system development is the simulation. Performing high level simulation of a system can help to identify, insolate and fix design problems. This work presents Uranus, a software tool for simulation and evaluation of image processing algorithms with support to migrate them to an FPGA environment for algorithm acceleration and embedded processes purposes. The tool includes an integrated library of previous coded operators in software and provides the necessary support to read and display image sequences as well as video files. The user can use the previous compiled soft-operators in a high level process chain, and code his own operators. Additional to the prototyping tool, Uranus offers FPGA-based hardware architecture with the same organization as the software prototyping part. The hardware architecture contains a library of FPGA IP cores for image processing that are connected with a PowerPC based system. The Uranus environment is intended for rapid prototyping of machine vision and the migration to FPGA accelerator platform, and it is distributed for academic purposes.

Artificial Neural Networks for Processing Graphs with Application to Image Understanding: A Survey

NASA Astrophysics Data System (ADS)

Bianchini, Monica; Scarselli, Franco

In graphical pattern recognition, each data is represented as an arrangement of elements, that encodes both the properties of each element and the relations among them. Hence, patterns are modelled as labelled graphs where, in general, labels can be attached to both nodes and edges. Artificial neural networks able to process graphs are a powerful tool for addressing a great variety of real-world problems, where the information is naturally organized in entities and relationships among entities and, in fact, they have been widely used in computer vision, f.i. in logo recognition, in similarity retrieval, and for object detection. In this chapter, we propose a survey of neural network models able to process structured information, with a particular focus on those architectures tailored to address image understanding applications. Starting from the original recursive model (RNNs), we subsequently present different ways to represent images - by trees, forests of trees, multiresolution trees, directed acyclic graphs with labelled edges, general graphs - and, correspondingly, neural network architectures appropriate to process such structures.

Basic research planning in mathematical pattern recognition and image analysis

NASA Technical Reports Server (NTRS)

Bryant, J.; Guseman, L. F., Jr.

1981-01-01

Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

Low level image processing techniques using the pipeline image processing engine in the flight telerobotic servicer

NASA Technical Reports Server (NTRS)

Nashman, Marilyn; Chaconas, Karen J.

1988-01-01

The sensory processing system for the NASA/NBS Standard Reference Model (NASREM) for telerobotic control is described. This control system architecture was adopted by NASA of the Flight Telerobotic Servicer. The control system is hierarchically designed and consists of three parallel systems: task decomposition, world modeling, and sensory processing. The Sensory Processing System is examined, and in particular the image processing hardware and software used to extract features at low levels of sensory processing for tasks representative of those envisioned for the Space Station such as assembly and maintenance are described.

Digital image processing: a primer for JVIR authors and readers: Part 3: Digital image editing.

PubMed

LaBerge, Jeanne M; Andriole, Katherine P

2003-12-01

This is the final installment of a three-part series on digital image processing intended to prepare authors for online submission of manuscripts. In the first two articles of the series, the fundamentals of digital image architecture were reviewed and methods of importing images to the computer desktop were described. In this article, techniques are presented for editing images in preparation for online submission. A step-by-step guide to basic editing with use of Adobe Photoshop is provided and the ethical implications of this activity are explored.

Parallel computer vision

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

Uhr, L.

1987-01-01

This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.

Feeding People's Curiosity: Leveraging the Cloud for Automatic Dissemination of Mars Images

NASA Technical Reports Server (NTRS)

Knight, David; Powell, Mark

2013-01-01

Smartphones and tablets have made wireless computing ubiquitous, and users expect instant, on-demand access to information. The Mars Science Laboratory (MSL) operations software suite, MSL InterfaCE (MSLICE), employs a different back-end image processing architecture compared to that of the Mars Exploration Rovers (MER) in order to better satisfy modern consumer-driven usage patterns and to offer greater server-side flexibility. Cloud services are a centerpiece of the server-side architecture that allows new image data to be delivered automatically to both scientists using MSLICE and the general public through the MSL website (http://mars.jpl.nasa.gov/msl/).

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.

Design and Decorative Art in Shaping of Architectural Environment Image

NASA Astrophysics Data System (ADS)

Shabalina, N. M.

2017-11-01

The relevance of the topic is determined by the dynamic development of the promising branch, i.e. the architectural environment design, which requires, on the one hand, consideration of the morphology and typology of this art form, on the other hand, the specificity of the architectural environment artistic image. The intensive development of innovative computer technologies and materials in modern engineering, improvement of the information communications forms in their totality has led to the application of new methods in design and construction which, in their turn, have required the development of additional methods for content and context analysis in the integrated assessment of socially significant architectural environments. In the modern culture, correlative processes are steadily developing leading us to a new understanding of the interaction of architecture, decorative art and design. Their rapprochement at the morphological level has been noted which makes it possible to reveal a specific method of synthesis and similarity. The architecture of postmodern styles differs in its bionic form becoming an interactive part of the society and approaching its structural qualities with painting, sculpture, and design. In the modern world, these processes acquire multi-valued semantic nuances, expand the importance of associativity and dynamic processuality in the perception of environmental objects and demand the development of new approaches to the assessment of the architectural design environment. Within the framework of the universal paradigm of modern times the concept of the world develops as a set of systems that live according to the self-organization laws.

Using virtual data for training deep model for hand gesture recognition

NASA Astrophysics Data System (ADS)

Nikolaev, E. I.; Dvoryaninov, P. V.; Lensky, Y. Y.; Drozdovsky, N. S.

2018-05-01

Deep learning has shown real promise for the classification efficiency for hand gesture recognition problems. In this paper, the authors present experimental results for a deeply-trained model for hand gesture recognition through the use of hand images. The authors have trained two deep convolutional neural networks. The first architecture produces the hand position as a 2D-vector by input hand image. The second one predicts the hand gesture class for the input image. The first proposed architecture produces state of the art results with an accuracy rate of 89% and the second architecture with split input produces accuracy rate of 85.2%. In this paper, the authors also propose using virtual data for training a supervised deep model. Such technique is aimed to avoid using original labelled images in the training process. The interest of this method in data preparation is motivated by the need to overcome one of the main challenges of deep supervised learning: using a copious amount of labelled data during training.

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.

A high-throughput two channel discrete wavelet transform architecture for the JPEG2000 standard

NASA Astrophysics Data System (ADS)

Badakhshannoory, Hossein; Hashemi, Mahmoud R.; Aminlou, Alireza; Fatemi, Omid

2005-07-01

The Discrete Wavelet Transform (DWT) is increasingly recognized in image and video compression standards, as indicated by its use in JPEG2000. The lifting scheme algorithm is an alternative DWT implementation that has a lower computational complexity and reduced resource requirement. In the JPEG2000 standard two lifting scheme based filter banks are introduced: the 5/3 and 9/7. In this paper a high throughput, two channel DWT architecture for both of the JPEG2000 DWT filters is presented. The proposed pipelined architecture has two separate input channels that process the incoming samples simultaneously with minimum memory requirement for each channel. The architecture had been implemented in VHDL and synthesized on a Xilinx Virtex2 XCV1000. The proposed architecture applies DWT on a 2K by 1K image at 33 fps with a 75 MHZ clock frequency. This performance is achieved with 70% less resources than two independent single channel modules. The high throughput and reduced resource requirement has made this architecture the proper choice for real time applications such as Digital Cinema.

A VLSI implementation for synthetic aperture radar image processing

NASA Technical Reports Server (NTRS)

Premkumar, A.; Purviance, J.

1990-01-01

A simple physical model for the Synthetic Aperture Radar (SAR) is presented. This model explains the one dimensional and two dimensional nature of the received SAR signal in the range and azimuth directions. A time domain correlator, its algorithm, and features are explained. The correlator is ideally suited for VLSI implementation. A real time SAR architecture using these correlators is proposed. In the proposed architecture, the received SAR data is processed using one dimensional correlators for determining the range while two dimensional correlators are used to determine the azimuth of a target. The architecture uses only three different types of custom VLSI chips and a small amount of memory.

Diamond Eye: a distributed architecture for image data mining

NASA Astrophysics Data System (ADS)

Burl, Michael C.; Fowlkes, Charless; Roden, Joe; Stechert, Andre; Mukhtar, Saleem

1999-02-01

Diamond Eye is a distributed software architecture, which enables users (scientists) to analyze large image collections by interacting with one or more custom data mining servers via a Java applet interface. Each server is coupled with an object-oriented database and a computational engine, such as a network of high-performance workstations. The database provides persistent storage and supports querying of the 'mined' information. The computational engine provides parallel execution of expensive image processing, object recognition, and query-by-content operations. Key benefits of the Diamond Eye architecture are: (1) the design promotes trial evaluation of advanced data mining and machine learning techniques by potential new users (all that is required is to point a web browser to the appropriate URL), (2) software infrastructure that is common across a range of science mining applications is factored out and reused, and (3) the system facilitates closer collaborations between algorithm developers and domain experts.

Content-addressable read/write memories for image analysis

NASA Technical Reports Server (NTRS)

Snyder, W. E.; Savage, C. D.

1982-01-01

The commonly encountered image analysis problems of region labeling and clustering are found to be cases of search-and-rename problem which can be solved in parallel by a system architecture that is inherently suitable for VLSI implementation. This architecture is a novel form of content-addressable memory (CAM) which provides parallel search and update functions, allowing speed reductions down to constant time per operation. It has been proposed in related investigations by Hall (1981) that, with VLSI, CAM-based structures with enhanced instruction sets for general purpose processing will be feasible.

Finite Element Analysis of Film Stack Architecture for Complementary Metal-Oxide-Semiconductor Image Sensors.

PubMed

Wu, Kuo-Tsai; Hwang, Sheng-Jye; Lee, Huei-Huang

2017-05-02

Image sensors are the core components of computer, communication, and consumer electronic products. Complementary metal oxide semiconductor (CMOS) image sensors have become the mainstay of image-sensing developments, but are prone to leakage current. In this study, we simulate the CMOS image sensor (CIS) film stacking process by finite element analysis. To elucidate the relationship between the leakage current and stack architecture, we compare the simulated and measured leakage currents in the elements. Based on the analysis results, we further improve the performance by optimizing the architecture of the film stacks or changing the thin-film material. The material parameters are then corrected to improve the accuracy of the simulation results. The simulated and experimental results confirm a positive correlation between measured leakage current and stress. This trend is attributed to the structural defects induced by high stress, which generate leakage. Using this relationship, we can change the structure of the thin-film stack to reduce the leakage current and thereby improve the component life and reliability of the CIS components.

Finite Element Analysis of Film Stack Architecture for Complementary Metal-Oxide–Semiconductor Image Sensors

PubMed Central

Wu, Kuo-Tsai; Hwang, Sheng-Jye; Lee, Huei-Huang

2017-01-01

Image sensors are the core components of computer, communication, and consumer electronic products. Complementary metal oxide semiconductor (CMOS) image sensors have become the mainstay of image-sensing developments, but are prone to leakage current. In this study, we simulate the CMOS image sensor (CIS) film stacking process by finite element analysis. To elucidate the relationship between the leakage current and stack architecture, we compare the simulated and measured leakage currents in the elements. Based on the analysis results, we further improve the performance by optimizing the architecture of the film stacks or changing the thin-film material. The material parameters are then corrected to improve the accuracy of the simulation results. The simulated and experimental results confirm a positive correlation between measured leakage current and stress. This trend is attributed to the structural defects induced by high stress, which generate leakage. Using this relationship, we can change the structure of the thin-film stack to reduce the leakage current and thereby improve the component life and reliability of the CIS components. PMID:28468324

Hardware-Abbildung eines videobasierten Verfahrens zur echtzeitfähigen Auswertung von Winkelhistogrammen auf eine modulare Coprozessor-Architektur

NASA Astrophysics Data System (ADS)

Flatt, H.; Tarnowsky, A.; Blume, H.; Pirsch, P.

2010-10-01

Dieser Beitrag behandelt die Abbildung eines videobasierten Verfahrens zur echtzeitfähigen Auswertung von Winkelhistogrammen auf eine modulare Coprozessor-Architektur. Die Architektur besteht aus mehreren dedizierten Recheneinheiten zur parallelen Verarbeitung rechenintensiver Bildverarbeitungsverfahren und ist mit einem RISC-Prozessor verbunden. Eine konfigurierbare Architekturerweiterung um eine Recheneinheit zur Auswertung von Winkelhistogrammen von Objekten ermöglicht in Verbindung mit dem RISC eine echtzeitfähige Klassifikation. Je nach Konfiguration sind für die Architekturerweiterung auf einem Xilinx Virtex-5-FPGA zwischen 3300 und 12 000 Lookup-Tables erforderlich. Bei einer Taktfrequenz von 100 MHz können unabhängig von der Bildauflösung pro Einzelbild in einem 25-Hz-Videodatenstrom bis zu 100 Objekte der Größe 256×256 Pixel analysiert werden. This paper presents the mapping of a video-based approach for real-time evaluation of angular histograms on a modular coprocessor architecture. The architecture comprises several dedicated processing elements for parallel processing of computation-intensive image processing tasks and is coupled with a RISC processor. A configurable architecture extension, especially a processing element for evaluating angular histograms of objects in conjunction with a RISC processor, provides a real-time classification. Depending on the configuration of the architecture extension, 3 300 to 12 000 look-up tables are required for a Xilinx Virtex-5 FPGA implementation. Running at a clock frequency of 100 MHz and independently of the image resolution per frame, 100 objects of size 256×256 pixels are analyzed in a 25 Hz video stream by the architecture.

Programmable Remapper with Single Flow Architecture

NASA Technical Reports Server (NTRS)

Fisher, Timothy E. (Inventor)

1993-01-01

An apparatus for image processing comprising a camera for receiving an original visual image and transforming the original visual image into an analog image, a first converter for transforming the analog image of the camera to a digital image, a processor having a single flow architecture for receiving the digital image and producing, with a single algorithm, an output image, a second converter for transforming the digital image of the processor to an analog image, and a viewer for receiving the analog image, transforming the analog image into a transformed visual image for observing the transformations applied to the original visual image. The processor comprises one or more subprocessors for the parallel reception of a digital image for producing an output matrix of the transformed visual image. More particularly, the processor comprises a plurality of subprocessors for receiving in parallel and transforming the digital image for producing a matrix of the transformed visual image, and an output interface means for receiving the respective portions of the transformed visual image from the respective subprocessor for producing an output matrix of the transformed visual image.

Sparsity based target detection for compressive spectral imagery

NASA Astrophysics Data System (ADS)

Boada, David Alberto; Arguello Fuentes, Henry

2016-09-01

Hyperspectral imagery provides significant information about the spectral characteristics of objects and materials present in a scene. It enables object and feature detection, classification, or identification based on the acquired spectral characteristics. However, it relies on sophisticated acquisition and data processing systems able to acquire, process, store, and transmit hundreds or thousands of image bands from a given area of interest which demands enormous computational resources in terms of storage, computationm, and I/O throughputs. Specialized optical architectures have been developed for the compressed acquisition of spectral images using a reduced set of coded measurements contrary to traditional architectures that need a complete set of measurements of the data cube for image acquisition, dealing with the storage and acquisition limitations. Despite this improvement, if any processing is desired, the image has to be reconstructed by an inverse algorithm in order to be processed, which is also an expensive task. In this paper, a sparsity-based algorithm for target detection in compressed spectral images is presented. Specifically, the target detection model adapts a sparsity-based target detector to work in a compressive domain, modifying the sparse representation basis in the compressive sensing problem by means of over-complete training dictionaries and a wavelet basis representation. Simulations show that the presented method can achieve even better detection results than the state of the art methods.

An intersubject variable regional anesthesia simulator with a virtual patient architecture.

PubMed

Ullrich, Sebastian; Grottke, Oliver; Fried, Eduard; Frommen, Thorsten; Liao, Wei; Rossaint, Rolf; Kuhlen, Torsten; Deserno, Thomas M

2009-11-01

The main purpose is to provide an intuitive VR-based training environment for regional anesthesia (RA). The research question is how to process subject-specific datasets, organize them in a meaningful way and how to perform the simulation for peripheral regions. We propose a flexible virtual patient architecture and methods to process datasets. Image acquisition, image processing (especially segmentation), interactive nerve modeling and permutations (nerve instantiation) are described in detail. The simulation of electric impulse stimulation and according responses are essential for the training of peripheral RA and solved by an approach based on the electric distance. We have created an XML-based virtual patient database with several subjects. Prototypes of the simulation are implemented and run on multimodal VR hardware (e.g., stereoscopic display and haptic device). A first user pilot study has confirmed our approach. The virtual patient architecture enables support for arbitrary scenarios on different subjects. This concept can also be used for other simulators. In future work, we plan to extend the simulation and conduct further evaluations in order to provide a tool for routine training for RA.

BreakingNews: Article Annotation by Image and Text Processing.

PubMed

Ramisa, Arnau; Yan, Fei; Moreno-Noguer, Francesc; Mikolajczyk, Krystian

2018-05-01

Building upon recent Deep Neural Network architectures, current approaches lying in the intersection of Computer Vision and Natural Language Processing have achieved unprecedented breakthroughs in tasks like automatic captioning or image retrieval. Most of these learning methods, though, rely on large training sets of images associated with human annotations that specifically describe the visual content. In this paper we propose to go a step further and explore the more complex cases where textual descriptions are loosely related to the images. We focus on the particular domain of news articles in which the textual content often expresses connotative and ambiguous relations that are only suggested but not directly inferred from images. We introduce an adaptive CNN architecture that shares most of the structure for multiple tasks including source detection, article illustration and geolocation of articles. Deep Canonical Correlation Analysis is deployed for article illustration, and a new loss function based on Great Circle Distance is proposed for geolocation. Furthermore, we present BreakingNews, a novel dataset with approximately 100K news articles including images, text and captions, and enriched with heterogeneous meta-data (such as GPS coordinates and user comments). We show this dataset to be appropriate to explore all aforementioned problems, for which we provide a baseline performance using various Deep Learning architectures, and different representations of the textual and visual features. We report very promising results and bring to light several limitations of current state-of-the-art in this kind of domain, which we hope will help spur progress in the field.

Processing Cones: A Computational Structure for Image Analysis.

DTIC Science & Technology

1981-12-01

image analysis applications, referred to as a processing cone, is described and sample algorithms are presented. A fundamental characteristic of the structure is its hierarchical organization into two-dimensional arrays of decreasing resolution. In this architecture, a protypical function is defined on a local window of data and applied uniformly to all windows in a parallel manner. Three basic modes of processing are supported in the cone: reduction operations (upward processing), horizontal operations (processing at a single level) and projection operations (downward

Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2017-08-01

Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. We show that the implementation of SLECNS based on known equivalentors or traditional correlators is possible if they are based on proposed equivalental two-dimensional functions of image similarity. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalental weighing of input patterns. Real model experiments in Mathcad are demonstrated, which confirm that non-linear processing on equivalent functions allows you to determine the neuron winners and adjust the weight matrix. Experimental results have shown that such models can be successfully used for auto- and hetero-associative recognition. They can also be used to explain some mechanisms known as "focus" and "competing gain-inhibition concept". The SLECNS architecture and hardware implementations of its basic nodes based on multi-channel convolvers and correlators with time integration are proposed. The parameters and performance of such architectures are estimated.

Image2000: A Free, Innovative, Java Based Imaging Package

NASA Technical Reports Server (NTRS)

Pell, Nicholas; Wheeler, Phil; Cornwell, Carl; Matusow, David; Obenschain, Arthur F. (Technical Monitor)

2001-01-01

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's (GSFC) Scientific and Educational Endeavors (SEE) and the Center for Image Processing in Education (CIPE) use satellite image processing as part of their science lessons developed for students and educators. The image processing products that they use, as part of these lessons, no longer fulfill the needs of SEE and CIPE because these products are either dependent on a particular computing platform, hard to customize and extend, or do not have enough functionality. SEE and CIPE began looking for what they considered the "perfect" image processing tool that was platform independent, rich in functionality and could easily be extended and customized for their purposes. At the request of SEE, NASA's GSFC, code 588 the Advanced Architectures and Automation Branch developed a powerful new Java based image processing endeavors.

A Wireless Capsule Endoscope System With Low-Power Controlling and Processing ASIC.

PubMed

Xinkai Chen; Xiaoyu Zhang; Linwei Zhang; Xiaowen Li; Nan Qi; Hanjun Jiang; Zhihua Wang

2009-02-01

This paper presents the design of a wireless capsule endoscope system. The proposed system is mainly composed of a CMOS image sensor, a RF transceiver and a low-power controlling and processing application specific integrated circuit (ASIC). Several design challenges involving system power reduction, system miniaturization and wireless wake-up method are resolved by employing optimized system architecture, integration of an area and power efficient image compression module, a power management unit (PMU) and a novel wireless wake-up subsystem with zero standby current in the ASIC design. The ASIC has been fabricated in 0.18-mum CMOS technology with a die area of 3.4 mm * 3.3 mm. The digital baseband can work under a power supply down to 0.95 V with a power dissipation of 1.3 mW. The prototype capsule based on the ASIC and a data recorder has been developed. Test result shows that proposed system architecture with local image compression lead to an average of 45% energy reduction for transmitting an image frame.

Parametric dense stereovision implementation on a system-on chip (SoC).

PubMed

Gardel, Alfredo; Montejo, Pablo; García, Jorge; Bravo, Ignacio; Lázaro, José L

2012-01-01

This paper proposes a novel hardware implementation of a dense recovery of stereovision 3D measurements. Traditionally 3D stereo systems have imposed the maximum number of stereo correspondences, introducing a large restriction on artificial vision algorithms. The proposed system-on-chip (SoC) provides great performance and efficiency, with a scalable architecture available for many different situations, addressing real time processing of stereo image flow. Using double buffering techniques properly combined with pipelined processing, the use of reconfigurable hardware achieves a parametrisable SoC which gives the designer the opportunity to decide its right dimension and features. The proposed architecture does not need any external memory because the processing is done as image flow arrives. Our SoC provides 3D data directly without the storage of whole stereo images. Our goal is to obtain high processing speed while maintaining the accuracy of 3D data using minimum resources. Configurable parameters may be controlled by later/parallel stages of the vision algorithm executed on an embedded processor. Considering hardware FPGA clock of 100 MHz, image flows up to 50 frames per second (fps) of dense stereo maps of more than 30,000 depth points could be obtained considering 2 Mpix images, with a minimum initial latency. The implementation of computer vision algorithms on reconfigurable hardware, explicitly low level processing, opens up the prospect of its use in autonomous systems, and they can act as a coprocessor to reconstruct 3D images with high density information in real time.

Research and implementation of the algorithm for unwrapped and distortion correction basing on CORDIC for panoramic image

NASA Astrophysics Data System (ADS)

Zhang, Zhenhai; Li, Kejie; Wu, Xiaobing; Zhang, Shujiang

2008-03-01

The unwrapped and correcting algorithm based on Coordinate Rotation Digital Computer (CORDIC) and bilinear interpolation algorithm was presented in this paper, with the purpose of processing dynamic panoramic annular image. An original annular panoramic image captured by panoramic annular lens (PAL) can be unwrapped and corrected to conventional rectangular image without distortion, which is much more coincident with people's vision. The algorithm for panoramic image processing is modeled by VHDL and implemented in FPGA. The experimental results show that the proposed panoramic image algorithm for unwrapped and distortion correction has the lower computation complexity and the architecture for dynamic panoramic image processing has lower hardware cost and power consumption. And the proposed algorithm is valid.

Exemplar-Based Image and Video Stylization Using Fully Convolutional Semantic Features.

PubMed

Zhu, Feida; Yan, Zhicheng; Bu, Jiajun; Yu, Yizhou

2017-05-10

Color and tone stylization in images and videos strives to enhance unique themes with artistic color and tone adjustments. It has a broad range of applications from professional image postprocessing to photo sharing over social networks. Mainstream photo enhancement softwares, such as Adobe Lightroom and Instagram, provide users with predefined styles, which are often hand-crafted through a trial-and-error process. Such photo adjustment tools lack a semantic understanding of image contents and the resulting global color transform limits the range of artistic styles it can represent. On the other hand, stylistic enhancement needs to apply distinct adjustments to various semantic regions. Such an ability enables a broader range of visual styles. In this paper, we first propose a novel deep learning architecture for exemplar-based image stylization, which learns local enhancement styles from image pairs. Our deep learning architecture consists of fully convolutional networks (FCNs) for automatic semantics-aware feature extraction and fully connected neural layers for adjustment prediction. Image stylization can be efficiently accomplished with a single forward pass through our deep network. To extend our deep network from image stylization to video stylization, we exploit temporal superpixels (TSPs) to facilitate the transfer of artistic styles from image exemplars to videos. Experiments on a number of datasets for image stylization as well as a diverse set of video clips demonstrate the effectiveness of our deep learning architecture.

A System-on-Chip Solution for Point-of-Care Ultrasound Imaging Systems: Architecture and ASIC Implementation.

PubMed

Kang, Jeeun; Yoon, Changhan; Lee, Jaejin; Kye, Sang-Bum; Lee, Yongbae; Chang, Jin Ho; Kim, Gi-Duck; Yoo, Yangmo; Song, Tai-kyong

2016-04-01

In this paper, we present a novel system-on-chip (SOC) solution for a portable ultrasound imaging system (PUS) for point-of-care applications. The PUS-SOC includes all of the signal processing modules (i.e., the transmit and dynamic receive beamformer modules, mid- and back-end processors, and color Doppler processors) as well as an efficient architecture for hardware-based imaging methods (e.g., dynamic delay calculation, multi-beamforming, and coded excitation and compression). The PUS-SOC was fabricated using a UMC 130-nm NAND process and has 16.8 GFLOPS of computing power with a total equivalent gate count of 12.1 million, which is comparable to a Pentium-4 CPU. The size and power consumption of the PUS-SOC are 27×27 mm(2) and 1.2 W, respectively. Based on the PUS-SOC, a prototype hand-held US imaging system was implemented. Phantom experiments demonstrated that the PUS-SOC can provide appropriate image quality for point-of-care applications with a compact PDA size ( 200×120×45 mm(3)) and 3 hours of battery life.

Client/server approach to image capturing

NASA Astrophysics Data System (ADS)

Tuijn, Chris; Stokes, Earle

1998-01-01

The diversity of the digital image capturing devices on the market today is quite astonishing and ranges from low-cost CCD scanners to digital cameras (for both action and stand-still scenes), mid-end CCD scanners for desktop publishing and pre- press applications and high-end CCD flatbed scanners and drum- scanners with photo multiplier technology. Each device and market segment has its own specific needs which explains the diversity of the associated scanner applications. What all those applications have in common is the need to communicate with a particular device to import the digital images; after the import, additional image processing might be needed as well as color management operations. Although the specific requirements for all of these applications might differ considerably, a number of image capturing and color management facilities as well as other services are needed which can be shared. In this paper, we propose a client/server architecture for scanning and image editing applications which can be used as a common component for all these applications. One of the principal components of the scan server is the input capturing module. The specification of the input jobs is based on a generic input device model. Through this model we make abstraction of the specific scanner parameters and define the scan job definitions by a number of absolute parameters. As a result, scan job definitions will be less dependent on a particular scanner and have a more universal meaning. In this context, we also elaborate on the interaction of the generic parameters and the color characterization (i.e., the ICC profile). Other topics that are covered are the scheduling and parallel processing capabilities of the server, the image processing facilities, the interaction with the ICC engine, the communication facilities (both in-memory and over the network) and the different client architectures (stand-alone applications, TWAIN servers, plug-ins, OLE or Apple-event driven applications). This paper is structured as follows. In the introduction, we further motive the need for a scan server-based architecture. In the second section, we give a brief architectural overview of the scan server and the other components it is connected to. The third chapter exposes the generic model for input devices as well as the image processing model; the fourth chapter reveals the different shapes the scanning applications (or modules) can have. In the last section, we briefly summarize the presented material and point out trends for future development.

The data storage grid: the next generation of fault-tolerant storage for backup and disaster recovery of clinical images

NASA Astrophysics Data System (ADS)

King, Nelson E.; Liu, Brent; Zhou, Zheng; Documet, Jorge; Huang, H. K.

2005-04-01

Grid Computing represents the latest and most exciting technology to evolve from the familiar realm of parallel, peer-to-peer and client-server models that can address the problem of fault-tolerant storage for backup and recovery of clinical images. We have researched and developed a novel Data Grid testbed involving several federated PAC systems based on grid architecture. By integrating a grid computing architecture to the DICOM environment, a failed PACS archive can recover its image data from others in the federation in a timely and seamless fashion. The design reflects the five-layer architecture of grid computing: Fabric, Resource, Connectivity, Collective, and Application Layers. The testbed Data Grid architecture representing three federated PAC systems, the Fault-Tolerant PACS archive server at the Image Processing and Informatics Laboratory, Marina del Rey, the clinical PACS at Saint John's Health Center, Santa Monica, and the clinical PACS at the Healthcare Consultation Center II, USC Health Science Campus, will be presented. The successful demonstration of the Data Grid in the testbed will provide an understanding of the Data Grid concept in clinical image data backup as well as establishment of benchmarks for performance from future grid technology improvements and serve as a road map for expanded research into large enterprise and federation level data grids to guarantee 99.999 % up time.

Flexible medical image management using service-oriented architecture.

PubMed

Shaham, Oded; Melament, Alex; Barak-Corren, Yuval; Kostirev, Igor; Shmueli, Noam; Peres, Yardena

2012-01-01

Management of medical images increasingly involves the need for integration with a variety of information systems. To address this need, we developed Content Management Offering (CMO), a platform for medical image management supporting interoperability through compliance with standards. CMO is based on the principles of service-oriented architecture, implemented with emphasis on three areas: clarity of business process definition, consolidation of service configuration management, and system scalability. Owing to the flexibility of this platform, a small team is able to accommodate requirements of customers varying in scale and in business needs. We describe two deployments of CMO, highlighting the platform's value to customers. CMO represents a flexible approach to medical image management, which can be applied to a variety of information technology challenges in healthcare and life sciences organizations.

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

PubMed

Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

2015-04-01

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods.

Wide-angle camera with multichannel architecture using microlenses on a curved surface.

PubMed

Liang, Wei-Lun; Shen, Hui-Kai; Su, Guo-Dung J

2014-06-10

We propose a multichannel imaging system that combines the principles of an insect's compound eye and the human eye. The optical system enables a reduction in track length of the imaging device to achieve miniaturization. The multichannel structure is achieved by a curved microlens array, and a Hypergon lens is used as the main lens to simulate the human eye, achieving large field of view (FOV). With this architecture, each microlens of the array transmits a segment of the overall FOV. The partial images are recorded in separate channels and stitched together to form the final image of the whole FOV by image processing. The design is 2.7 mm thick, with 59 channels; the 100°×80° full FOV is optimized using ZEMAX ray-tracing software on an image plane. The image plane size is 4.53  mm×3.29  mm. Given the recent progress in the fabrication of microlenses, this image system has the potential to be commercialized in the near future.

New generation of meteorology cameras

NASA Astrophysics Data System (ADS)

Janout, Petr; Blažek, Martin; Páta, Petr

2017-12-01

A new generation of the WILLIAM (WIde-field aLL-sky Image Analyzing Monitoring system) camera includes new features such as monitoring of rain and storm clouds during the day observation. Development of the new generation of weather monitoring cameras responds to the demand for monitoring of sudden weather changes. However, new WILLIAM cameras are ready to process acquired image data immediately, release warning against sudden torrential rains, and send it to user's cell phone and email. Actual weather conditions are determined from image data, and results of image processing are complemented by data from sensors of temperature, humidity, and atmospheric pressure. In this paper, we present the architecture, image data processing algorithms of mentioned monitoring camera and spatially-variant model of imaging system aberrations based on Zernike polynomials.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

NASA Astrophysics Data System (ADS)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

A Study of Alternative Computer Architectures for System Reliability and Software Simplification.

DTIC Science & Technology

1981-04-22

compression. Several known applications of neighborhood processing, such as noise removal, and boundary smoothing, are shown to be special cases of...Processing [21] A small effort was undertaken to implement image array processing at a very low cost. To this end, a standard Qwip Facsimile

The automated data processing architecture for the GPI Exoplanet Survey

NASA Astrophysics Data System (ADS)

Wang, Jason J.; Perrin, Marshall D.; Savransky, Dmitry; Arriaga, Pauline; Chilcote, Jeffrey K.; De Rosa, Robert J.; Millar-Blanchaer, Maxwell A.; Marois, Christian; Rameau, Julien; Wolff, Schuyler G.; Shapiro, Jacob; Ruffio, Jean-Baptiste; Graham, James R.; Macintosh, Bruce

2017-09-01

The Gemini Planet Imager Exoplanet Survey (GPIES) is a multi-year direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the GPIES Data Cruncher, combines multiple data reduction pipelines together to intelligently process all spectroscopic, polarimetric, and calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow-up on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our data reduction pipelines. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real-time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.

Large-Scale Image Analytics Using Deep Learning

NASA Astrophysics Data System (ADS)

Ganguly, S.; Nemani, R. R.; Basu, S.; Mukhopadhyay, S.; Michaelis, A.; Votava, P.

2014-12-01

High resolution land cover classification maps are needed to increase the accuracy of current Land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) land cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agricultural Imaging Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~100 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. In order to perform image analytics in such a granular system, it is mandatory to devise an intelligent archiving and query system for image retrieval, file structuring, metadata processing and filtering of all available image scenes. Using the Open NASA Earth Exchange (NEX) initiative, which is a partnership with Amazon Web Services (AWS), we have developed an end-to-end architecture for designing the database and the deep belief network (following the distbelief computing model) to solve a grand challenge of scaling this process across quarter million NAIP tiles that cover the entire Continental United States. The AWS core components that we use to solve this problem are DynamoDB along with S3 for database query and storage, ElastiCache shared memory architecture for image segmentation, Elastic Map Reduce (EMR) for image feature extraction, and the memory optimized Elastic Cloud Compute (EC2) for the learning algorithm.

Concurrent Image Processing Executive (CIPE). Volume 1: Design overview

NASA Technical Reports Server (NTRS)

Lee, Meemong; Groom, Steven L.; Mazer, Alan S.; Williams, Winifred I.

1990-01-01

The design and implementation of a Concurrent Image Processing Executive (CIPE), which is intended to become the support system software for a prototype high performance science analysis workstation are described. The target machine for this software is a JPL/Caltech Mark 3fp Hypercube hosted by either a MASSCOMP 5600 or a Sun-3, Sun-4 workstation; however, the design will accommodate other concurrent machines of similar architecture, i.e., local memory, multiple-instruction-multiple-data (MIMD) machines. The CIPE system provides both a multimode user interface and an applications programmer interface, and has been designed around four loosely coupled modules: user interface, host-resident executive, hypercube-resident executive, and application functions. The loose coupling between modules allows modification of a particular module without significantly affecting the other modules in the system. In order to enhance hypercube memory utilization and to allow expansion of image processing capabilities, a specialized program management method, incremental loading, was devised. To minimize data transfer between host and hypercube, a data management method which distributes, redistributes, and tracks data set information was implemented. The data management also allows data sharing among application programs. The CIPE software architecture provides a flexible environment for scientific analysis of complex remote sensing image data, such as planetary data and imaging spectrometry, utilizing state-of-the-art concurrent computation capabilities.

A Generic Ground Framework for Image Expertise Centres and Small-Sized Production Centres

NASA Astrophysics Data System (ADS)

Sellé, A.

2009-05-01

Initiated by the Pleiadas Earth Observation Program, the CNES (French Space Agency) has developed a generic collaborative framework for its image quality centre, highly customisable for any upcoming expertise centre. This collaborative framework has been design to be used by a group of experts or scientists that want to share data and processings and manage interfaces with external entities. Its flexible and scalable architecture complies with the core requirements: defining a user data model with no impact on the software (generic access data), integrating user processings with a GUI builder and built-in APIs, and offering a scalable architecture to fit any preformance requirement and accompany growing projects. The CNES jas given licensing grants for two software companies that will be able to redistribute this framework to any customer.

Building Shadow Detection from Ghost Imagery

NASA Astrophysics Data System (ADS)

Zhou, G.; Sha, J.; Yue, T.; Wang, Q.; Liu, X.; Huang, S.; Pan, Q.; Wei, J.

2018-05-01

Shadow is one of the basic features of remote sensing image, it expresses a lot of information of the object which is loss or interference, and the removal of shadow is always a difficult problem to remote sensing image processing. In this paper, it is mainly analyzes the characteristics and properties of shadows from the ghost image (traditional orthorectification). The DBM and the interior and exterior orientation elements of the image are used to calculate the zenith angle of sun. Then this paper combines the scope of the architectural shadows which has be determined by the zenith angle of sun with the region growing method to make the detection of architectural shadow areas. This method lays a solid foundation for the shadow of the repair from the ghost image later. It will greatly improve the accuracy of shadow detection from buildings and make it more conducive to solve the problem of urban large-scale aerial imagines.

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.

Contextual analysis of immunological response through whole-organ fluorescent imaging.

PubMed

Woodruff, Matthew C; Herndon, Caroline N; Heesters, B A; Carroll, Michael C

2013-09-01

As fluorescent microscopy has developed, significant insights have been gained into the establishment of immune response within secondary lymphoid organs, particularly in draining lymph nodes. While established techniques such as confocal imaging and intravital multi-photon microscopy have proven invaluable, they provide limited insight into the architectural and structural context in which these responses occur. To interrogate the role of the lymph node environment in immune response effectively, a new set of imaging tools taking into account broader architectural context must be implemented into emerging immunological questions. Using two different methods of whole-organ imaging, optical clearing and three-dimensional reconstruction of serially sectioned lymph nodes, fluorescent representations of whole lymph nodes can be acquired at cellular resolution. Using freely available post-processing tools, images of unlimited size and depth can be assembled into cohesive, contextual snapshots of immunological response. Through the implementation of robust iterative analysis techniques, these highly complex three-dimensional images can be objectified into sortable object data sets. These data can then be used to interrogate complex questions at the cellular level within the broader context of lymph node biology. By combining existing imaging technology with complex methods of sample preparation and capture, we have developed efficient systems for contextualizing immunological phenomena within lymphatic architecture. In combination with robust approaches to image analysis, these advances provide a path to integrating scientific understanding of basic lymphatic biology into the complex nature of immunological response.

On-chip skin color detection using a triple-well CMOS process

NASA Astrophysics Data System (ADS)

Boussaid, Farid; Chai, Douglas; Bouzerdoum, Abdesselam

2004-03-01

In this paper, a current-mode VLSI architecture enabling on read-out skin detection without the need for any on-chip memory elements is proposed. An important feature of the proposed architecture is that it removes the need for demosaicing. Color separation is achieved using the strong wavelength dependence of the absorption coefficient in silicon. This wavelength dependence causes a very shallow absorption of blue light and enables red light to penetrate deeply in silicon. A triple-well process, allowing a P-well to be placed inside an N-well, is chosen to fabricate three vertically integrated photodiodes acting as the RGB color detector for each pixel. Pixels of an input RGB image are classified as skin or non-skin pixels using a statistical skin color model, chosen to offer an acceptable trade-off between skin detection performance and implementation complexity. A single processing unit is used to classify all pixels of the input RGB image. This results in reduced mismatch and also in an increased pixel fill-factor. Furthermore, the proposed current-mode architecture is programmable, allowing external control of all classifier parameters to compensate for mismatch and changing lighting conditions.

Parallel architecture for rapid image generation and analysis

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

Nerheim, R.J.

1987-01-01

A multiprocessor architecture inspired by the Disney multiplane camera is proposed. For many applications, this approach produces a natural mapping of processors to objects in a scene. Such a mapping promotes parallelism and reduces the hidden-surface work with minimal interprocessor communication and low-overhead cost. Existing graphics architectures store the final picture as a monolithic entity. The architecture here stores each object's image separately. It assembles the final composite picture from component images only when the video display needs to be refreshed. This organization simplifies the work required to animate moving objects that occlude other objects. In addition, the architecture hasmore » multiple processors that generate the component images in parallel. This further shortens the time needed to create a composite picture. In addition to generating images for animation, the architecture has the ability to decompose images.« less

High-frame rate multiport CCD imager and camera

NASA Astrophysics Data System (ADS)

Levine, Peter A.; Patterson, David R.; Esposito, Benjamin J.; Tower, John R.; Lawler, William B.

1993-01-01

A high frame rate visible CCD camera capable of operation up to 200 frames per second is described. The camera produces a 256 X 256 pixel image by using one quadrant of a 512 X 512 16-port, back illuminated CCD imager. Four contiguous outputs are digitally reformatted into a correct, 256 X 256 image. This paper details the architecture and timing used for the CCD drive circuits, analog processing, and the digital reformatter.

A data-management system using sensor technology and wireless devices for port security

NASA Astrophysics Data System (ADS)

Saldaña, Manuel; Rivera, Javier; Oyola, Jose; Manian, Vidya

2014-05-01

Sensor technologies such as infrared sensors and hyperspectral imaging, video camera surveillance are proven to be viable in port security. Drawing from sources such as infrared sensor data, digital camera images and processed hyperspectral images, this article explores the implementation of a real-time data delivery system. In an effort to improve the manner in which anomaly detection data is delivered to interested parties in port security, this system explores how a client-server architecture can provide protected access to data, reports, and device status. Sensor data and hyperspectral image data will be kept in a monitored directory, where the system will link it to existing users in the database. Since this system will render processed hyperspectral images that are dynamically added to the server - which often occupy a large amount of space - the resolution of these images is trimmed down to around 1024×768 pixels. Changes that occur in any image or data modification that originates from any sensor will trigger a message to all users that have a relation with the aforementioned. These messages will be sent to the corresponding users through automatic email generation and through a push notification using Google Cloud Messaging for Android. Moreover, this paper presents the complete architecture for data reception from the sensors, processing, storage and discusses how users of this system such as port security personnel can use benefit from the use of this service to receive secure real-time notifications if their designated sensors have detected anomalies and/or have remote access to results from processed hyperspectral imagery relevant to their assigned posts.

Development of Targeting UAVs Using Electric Helicopters and Yamaha RMAX

DTIC Science & Technology

2007-05-17

including the QNX real - time operating system . The video overlay board is useful to display the onboard camera’s image with important information such as... real - time operating system . Fully utilizing the built-in multi-processing architecture with inter-process synchronization and communication

Video sensor architecture for surveillance applications.

PubMed

Sánchez, Jordi; Benet, Ginés; Simó, José E

2012-01-01

This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%.

Video Sensor Architecture for Surveillance Applications

PubMed Central

Sánchez, Jordi; Benet, Ginés; Simó, José E.

2012-01-01

This paper introduces a flexible hardware and software architecture for a smart video sensor. This sensor has been applied in a video surveillance application where some of these video sensors are deployed, constituting the sensory nodes of a distributed surveillance system. In this system, a video sensor node processes images locally in order to extract objects of interest, and classify them. The sensor node reports the processing results to other nodes in the cloud (a user or higher level software) in the form of an XML description. The hardware architecture of each sensor node has been developed using two DSP processors and an FPGA that controls, in a flexible way, the interconnection among processors and the image data flow. The developed node software is based on pluggable components and runs on a provided execution run-time. Some basic and application-specific software components have been developed, in particular: acquisition, segmentation, labeling, tracking, classification and feature extraction. Preliminary results demonstrate that the system can achieve up to 7.5 frames per second in the worst case, and the true positive rates in the classification of objects are better than 80%. PMID:22438723

Optically Sectioned Imaging of Microvasculature of In-Vivo and Ex-Vivo Thick Tissue Models with Speckle-illumination HiLo Microscopy and HiLo Image Processing Implementation in MATLAB Architecture

NASA Astrophysics Data System (ADS)

Suen, Ricky Wai

The work described in this thesis covers the conversion of HiLo image processing into MATLAB architecture and the use of speckle-illumination HiLo microscopy for use of ex-vivo and in-vivo imaging of thick tissue models. HiLo microscopy is a wide-field fluorescence imaging technique and has been demonstrated to produce optically sectioned images comparable to confocal in thin samples. The imaging technique was developed by Jerome Mertz and the Boston University Biomicroscopy Lab and has been implemented in our lab as a stand-alone optical setup and a modification to a conventional fluorescence microscope. Speckle-illumination HiLo microscopy combines two images taken under speckle-illumination and standard uniform-illumination to generate an optically sectioned image that reject out-of-focus fluorescence. The evaluated speckle contrast in the images is used as a weighting function where elements that move out-of-focus have a speckle contrast that decays to zero. The experiments shown here demonstrate the capability of our HiLo microscopes to produce optically-sectioned images of the microvasculature of ex-vivo and in-vivo thick tissue models. The HiLo microscope were used to image the microvasculature of ex-vivo mouse heart sections prepared for optical histology and the microvasculature of in-vivo rodent dorsal window chamber models. Studies in label-free surface profiling with HiLo microscopy is also presented.

Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Editor); Schenker, Paul (Editor)

1987-01-01

The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

PCI bus content-addressable-memory (CAM) implementation on FPGA for pattern recognition/image retrieval in a distributed environment

NASA Astrophysics Data System (ADS)

Megherbi, Dalila B.; Yan, Yin; Tanmay, Parikh; Khoury, Jed; Woods, C. L.

2004-11-01

Recently surveillance and Automatic Target Recognition (ATR) applications are increasing as the cost of computing power needed to process the massive amount of information continues to fall. This computing power has been made possible partly by the latest advances in FPGAs and SOPCs. In particular, to design and implement state-of-the-Art electro-optical imaging systems to provide advanced surveillance capabilities, there is a need to integrate several technologies (e.g. telescope, precise optics, cameras, image/compute vision algorithms, which can be geographically distributed or sharing distributed resources) into a programmable system and DSP systems. Additionally, pattern recognition techniques and fast information retrieval, are often important components of intelligent systems. The aim of this work is using embedded FPGA as a fast, configurable and synthesizable search engine in fast image pattern recognition/retrieval in a distributed hardware/software co-design environment. In particular, we propose and show a low cost Content Addressable Memory (CAM)-based distributed embedded FPGA hardware architecture solution with real time recognition capabilities and computing for pattern look-up, pattern recognition, and image retrieval. We show how the distributed CAM-based architecture offers a performance advantage of an order-of-magnitude over RAM-based architecture (Random Access Memory) search for implementing high speed pattern recognition for image retrieval. The methods of designing, implementing, and analyzing the proposed CAM based embedded architecture are described here. Other SOPC solutions/design issues are covered. Finally, experimental results, hardware verification, and performance evaluations using both the Xilinx Virtex-II and the Altera Apex20k are provided to show the potential and power of the proposed method for low cost reconfigurable fast image pattern recognition/retrieval at the hardware/software co-design level.

Miniaturized optical wavelength sensors

NASA Astrophysics Data System (ADS)

Kung, Helen Ling-Ning

Recently semiconductor processing technology has been applied to the miniaturization of optical wavelength sensors. Compact sensors enable new applications such as integrated diode-laser wavelength monitors and frequency lockers, portable chemical and biological detection, and portable and adaptive hyperspectral imaging arrays. Small sensing systems have trade-offs between resolution, operating range, throughput, multiplexing and complexity. We have developed a new wavelength sensing architecture that balances these parameters for applications involving hyperspectral imaging spectrometer arrays. In this thesis we discuss and demonstrate two new wavelength-sensing architectures whose single-pixel designs can easily be extended into spectrometer arrays. The first class of devices is based on sampling a standing wave. These devices are based on measuring the wavelength-dependent period of optical standing waves formed by the interference of forward and reflected waves at a mirror. We fabricated two different devices based on this principle. The first device is a wavelength monitor, which measures the wavelength and power of a monochromatic source. The second device is a spectrometer that can also act as a selective spectral coherence sensor. The spectrometer contains a large displacement piston-motion MEMS mirror and a thin GaAs photodiode flip-chip bonded to a quartz substrate. The performance of this spectrometer is similar to that of a Michelson in resolution, operating range, throughput and multiplexing but with the added advantages of fewer components and one-dimensional architecture. The second class of devices is based on the Talbot self-imaging effect. The Talbot effect occurs when a periodic object is illuminated with a spatially coherent wave. Periodically spaced self-images are formed behind the object. The spacing of the self-images is proportional to wavelength of the incident light. We discuss and demonstrate how this effect can be used for spectroscopy. In the conclusion we compare these two new miniaturized spectrometer architectures to existing miniaturized spectrometers. We believe that the combination of miniaturized wavelength sensors and smart processing should facilitate the development real-time, adaptive and portable sensing systems.

Space Debris Detection on the HPDP, a Coarse-Grained Reconfigurable Array Architecture for Space

NASA Astrophysics Data System (ADS)

Suarez, Diego Andres; Bretz, Daniel; Helfers, Tim; Weidendorfer, Josef; Utzmann, Jens

2016-08-01

Stream processing, widely used in communications and digital signal processing applications, requires high- throughput data processing that is achieved in most cases using Application-Specific Integrated Circuit (ASIC) designs. Lack of programmability is an issue especially in space applications, which use on-board components with long life-cycles requiring applications updates. To this end, the High Performance Data Processor (HPDP) architecture integrates an array of coarse-grained reconfigurable elements to provide both flexible and efficient computational power suitable for stream-based data processing applications in space. In this work the capabilities of the HPDP architecture are demonstrated with the implementation of a real-time image processing algorithm for space debris detection in a space-based space surveillance system. The implementation challenges and alternatives are described making trade-offs to improve performance at the expense of negligible degradation of detection accuracy. The proposed implementation uses over 99% of the available computational resources. Performance estimations based on simulations show that the HPDP can amply match the application requirements.

Acousto-Optic Processing of 2-D Signals Using Temporal and Spatial Integration.

DTIC Science & Technology

1983-05-31

Documents includes data on: Architectures; Coherence Properties of Pulsed Laser Diodes; Acousto - optic device data; Dynamic Range Issues; Image correlation; Synthetic aperture radar; 2-D Fourier transform; and Moments.

Bioinspired architecture approach for a one-billion transistor smart CMOS camera chip

NASA Astrophysics Data System (ADS)

Fey, Dietmar; Komann, Marcus

2007-05-01

In the paper we present a massively parallel VLSI architecture for future smart CMOS camera chips with up to one billion transistors. To exploit efficiently the potential offered by future micro- or nanoelectronic devices traditional on central structures oriented parallel architectures based on MIMD or SIMD approaches will fail. They require too long and too many global interconnects for the distribution of code or the access to common memory. On the other hand nature developed self-organising and emergent principles to manage successfully complex structures based on lots of interacting simple elements. Therefore we developed a new as Marching Pixels denoted emergent computing paradigm based on a mixture of bio-inspired computing models like cellular automaton and artificial ants. In the paper we present different Marching Pixels algorithms and the corresponding VLSI array architecture. A detailed synthesis result for a 0.18 μm CMOS process shows that a 256×256 pixel image is processed in less than 10 ms assuming a moderate 100 MHz clock rate for the processor array. Future higher integration densities and a 3D chip stacking technology will allow the integration and processing of Mega pixels within the same time since our architecture is fully scalable.

Architecture of next-generation information management systems for digital radiology enterprises

NASA Astrophysics Data System (ADS)

Wong, Stephen T. C.; Wang, Huili; Shen, Weimin; Schmidt, Joachim; Chen, George; Dolan, Tom

2000-05-01

Few information systems today offer a clear and flexible means to define and manage the automated part of radiology processes. None of them provide a coherent and scalable architecture that can easily cope with heterogeneity and inevitable local adaptation of applications. Most importantly, they often lack a model that can integrate clinical and administrative information to aid better decisions in managing resources, optimizing operations, and improving productivity. Digital radiology enterprises require cost-effective solutions to deliver information to the right person in the right place and at the right time. We propose a new architecture of image information management systems for digital radiology enterprises. Such a system is based on the emerging technologies in workflow management, distributed object computing, and Java and Web techniques, as well as Philips' domain knowledge in radiology operations. Our design adapts the approach of '4+1' architectural view. In this new architecture, PACS and RIS will become one while the user interaction can be automated by customized workflow process. Clinical service applications are implemented as active components. They can be reasonably substituted by applications of local adaptations and can be multiplied for fault tolerance and load balancing. Furthermore, it will provide powerful query and statistical functions for managing resources and improving productivity in real time. This work will lead to a new direction of image information management in the next millennium. We will illustrate the innovative design with implemented examples of a working prototype.

Parallel Processing Systems for Passive Ranging During Helicopter Flight

NASA Technical Reports Server (NTRS)

Sridhar, Bavavar; Suorsa, Raymond E.; Showman, Robert D. (Technical Monitor)

1994-01-01

The complexity of rotorcraft missions involving operations close to the ground result in high pilot workload. In order to allow a pilot time to perform mission-oriented tasks, sensor-aiding and automation of some of the guidance and control functions are highly desirable. Images from an electro-optical sensor provide a covert way of detecting objects in the flight path of a low-flying helicopter. Passive ranging consists of processing a sequence of images using techniques based on optical low computation and recursive estimation. The passive ranging algorithm has to extract obstacle information from imagery at rates varying from five to thirty or more frames per second depending on the helicopter speed. We have implemented and tested the passive ranging algorithm off-line using helicopter-collected images. However, the real-time data and computation requirements of the algorithm are beyond the capability of any off-the-shelf microprocessor or digital signal processor. This paper describes the computational requirements of the algorithm and uses parallel processing technology to meet these requirements. Various issues in the selection of a parallel processing architecture are discussed and four different computer architectures are evaluated regarding their suitability to process the algorithm in real-time. Based on this evaluation, we conclude that real-time passive ranging is a realistic goal and can be achieved with a short time.

Automated Root Tracking with "Root System Analyzer"

NASA Astrophysics Data System (ADS)

Schnepf, Andrea; Jin, Meina; Ockert, Charlotte; Bol, Roland; Leitner, Daniel

2015-04-01

Crucial factors for plant development are water and nutrient availability in soils. Thus, root architecture is a main aspect of plant productivity and needs to be accurately considered when describing root processes. Images of root architecture contain a huge amount of information, and image analysis helps to recover parameters describing certain root architectural and morphological traits. The majority of imaging systems for root systems are designed for two-dimensional images, such as RootReader2, GiA Roots, SmartRoot, EZ-Rhizo, and Growscreen, but most of them are semi-automated and involve mouse-clicks in each root by the user. "Root System Analyzer" is a new, fully automated approach for recovering root architectural parameters from two-dimensional images of root systems. Individual roots can still be corrected manually in a user interface if required. The algorithm starts with a sequence of segmented two-dimensional images showing the dynamic development of a root system. For each image, morphological operators are used for skeletonization. Based on this, a graph representation of the root system is created. A dynamic root architecture model helps to determine which edges of the graph belong to an individual root. The algorithm elongates each root at the root tip and simulates growth confined within the already existing graph representation. The increment of root elongation is calculated assuming constant growth. For each root, the algorithm finds all possible paths and elongates the root in the direction of the optimal path. In this way, each edge of the graph is assigned to one or more coherent roots. Image sequences of root systems are handled in such a way that the previous image is used as a starting point for the current image. The algorithm is implemented in a set of Matlab m-files. Output of Root System Analyzer is a data structure that includes for each root an identification number, the branching order, the time of emergence, the parent identification number, the distance between branching point to the parent root base, the root length, the root radius and the nodes that belong to each individual root path. This information is relevant for the analysis of dynamic root system development as well as the parameterisation of root architecture models. Here, we show results of Root System Analyzer applied to analyse the root systems of wheat plants grown in rhizotrons. Different treatments with respect to soil moisture and apatite concentrations were used to test the effects of those conditions on root system development. Photographs of the root systems were taken at high spatial and temporal resolution and root systems are automatically tracked.

A fast image registration approach of neural activities in light-sheet fluorescence microscopy images

NASA Astrophysics Data System (ADS)

Meng, Hui; Hui, Hui; Hu, Chaoen; Yang, Xin; Tian, Jie

2017-03-01

The ability of fast and single-neuron resolution imaging of neural activities enables light-sheet fluorescence microscopy (LSFM) as a powerful imaging technique in functional neural connection applications. The state-of-art LSFM imaging system can record the neuronal activities of entire brain for small animal, such as zebrafish or C. elegans at single-neuron resolution. However, the stimulated and spontaneous movements in animal brain result in inconsistent neuron positions during recording process. It is time consuming to register the acquired large-scale images with conventional method. In this work, we address the problem of fast registration of neural positions in stacks of LSFM images. This is necessary to register brain structures and activities. To achieve fast registration of neural activities, we present a rigid registration architecture by implementation of Graphics Processing Unit (GPU). In this approach, the image stacks were preprocessed on GPU by mean stretching to reduce the computation effort. The present image was registered to the previous image stack that considered as reference. A fast Fourier transform (FFT) algorithm was used for calculating the shift of the image stack. The calculations for image registration were performed in different threads while the preparation functionality was refactored and called only once by the master thread. We implemented our registration algorithm on NVIDIA Quadro K4200 GPU under Compute Unified Device Architecture (CUDA) programming environment. The experimental results showed that the registration computation can speed-up to 550ms for a full high-resolution brain image. Our approach also has potential to be used for other dynamic image registrations in biomedical applications.

The internal architecture of dendritic spines revealed by super-resolution imaging: What did we learn so far?

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

MacGillavry, Harold D., E-mail: h.d.macgillavry@uu.nl; Hoogenraad, Casper C., E-mail: c.hoogenraad@uu.nl

2015-07-15

The molecular architecture of dendritic spines defines the efficiency of signal transmission across excitatory synapses. It is therefore critical to understand the mechanisms that control the dynamic localization of the molecular constituents within spines. However, because of the small scale at which most processes within spines take place, conventional light microscopy techniques are not adequate to provide the necessary level of resolution. Recently, super-resolution imaging techniques have overcome the classical barrier imposed by the diffraction of light, and can now resolve the localization and dynamic behavior of proteins within small compartments with nanometer precision, revolutionizing the study of dendritic spinemore » architecture. Here, we highlight exciting new findings from recent super-resolution studies on neuronal spines, and discuss how these studies revealed important new insights into how protein complexes are assembled and how their dynamic behavior shapes the efficiency of synaptic transmission.« less

Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

NASA Astrophysics Data System (ADS)

Lhamon, Michael Earl

A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase-only implementation with lower detection performance than full complex electronic systems. Our study includes pseudo-random pixel encoding techniques for approximating full complex filtering. Optical filter bank implementation is possible and they have the advantage of time averaging the entire filter bank at real time rates. Time-averaged optical filtering is computational comparable to billions of digital operations-per-second. For this reason, we believe future trends in high speed pattern recognition will involve hybrid architectures of both optical and DSP elements.

In vivo cellular imaging with microscopes enabled by MEMS scanners

NASA Astrophysics Data System (ADS)

Ra, Hyejun

High-resolution optical imaging plays an important role in medical diagnosis and biomedical research. Confocal microscopy is a widely used imaging method for obtaining cellular and sub-cellular images of biological tissue in reflectance and fluorescence modes. Its characteristic optical sectioning capability also enables three-dimensional (3-D) image reconstruction. However, its use has mostly been limited to excised tissues due to the requirement of high numerical aperture (NA) lenses for cellular resolution. Microscope miniaturization can enable in vivo imaging to make possible early cancer diagnosis and biological studies in the innate environment. In this dissertation, microscope miniaturization for in vivo cellular imaging is presented. The dual-axes confocal (DAC) architecture overcomes limitations of the conventional single-axis confocal (SAC) architecture to allow for miniaturization with high resolution. A microelectromechanical systems (MEMS) scanner is the central imaging component that is key in miniaturization of the DAC architecture. The design, fabrication, and characterization of the two-dimensional (2-D) MEMS scanner are presented. The gimbaled MEMS scanner is fabricated on a double silicon-on-insulator (SOI) wafer and is actuated by self-aligned vertical electrostatic combdrives. The imaging performance of the MEMS scanner in a DAC configuration is shown in a breadboard microscope setup, where reflectance and fluorescence imaging is demonstrated. Then, the MEMS scanner is integrated into a miniature DAC microscope. The whole imaging system is integrated into a portable unit for research in small animal models of human biology and disease. In vivo 3-D imaging is demonstrated on mouse skin models showing gene transfer and siRNA silencing. The siRNA silencing process is sequentially imaged in one mouse over time.

System design and implementation of digital-image processing using computational grids

NASA Astrophysics Data System (ADS)

Shen, Zhanfeng; Luo, Jiancheng; Zhou, Chenghu; Huang, Guangyu; Ma, Weifeng; Ming, Dongping

2005-06-01

As a special type of digital image, remotely sensed images are playing increasingly important roles in our daily lives. Because of the enormous amounts of data involved, and the difficulties of data processing and transfer, an important issue for current computer and geo-science experts is developing internet technology to implement rapid remotely sensed image processing. Computational grids are able to solve this problem effectively. These networks of computer workstations enable the sharing of data and resources, and are used by computer experts to solve imbalances of network resources and lopsided usage. In China, computational grids combined with spatial-information-processing technology have formed a new technology: namely, spatial-information grids. In the field of remotely sensed images, spatial-information grids work more effectively for network computing, data processing, resource sharing, task cooperation and so on. This paper focuses mainly on the application of computational grids to digital-image processing. Firstly, we describe the architecture of digital-image processing on the basis of computational grids, its implementation is then discussed in detail with respect to the technology of middleware. The whole network-based intelligent image-processing system is evaluated on the basis of the experimental analysis of remotely sensed image-processing tasks; the results confirm the feasibility of the application of computational grids to digital-image processing.

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification

PubMed Central

Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references. PMID:29581722

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification.

PubMed

Yu, Yunlong; Liu, Fuxian

2018-01-01

One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new two-stream deep architecture for aerial scene classification. First, we use two pretrained convolutional neural networks (CNNs) as feature extractor to learn deep features from the original aerial image and the processed aerial image through saliency detection, respectively. Second, two feature fusion strategies are adopted to fuse the two different types of deep convolutional features extracted by the original RGB stream and the saliency stream. Finally, we use the extreme learning machine (ELM) classifier for final classification with the fused features. The effectiveness of the proposed architecture is tested on four challenging datasets: UC-Merced dataset with 21 scene categories, WHU-RS dataset with 19 scene categories, AID dataset with 30 scene categories, and NWPU-RESISC45 dataset with 45 challenging scene categories. The experimental results demonstrate that our architecture gets a significant classification accuracy improvement over all state-of-the-art references.

Use of a multimission system for cost effective support of planetary science data processing

NASA Technical Reports Server (NTRS)

Green, William B.

1994-01-01

JPL's Multimission Operations Systems Office (MOSO) provides a multimission facility at JPL for processing science instrument data from NASA's planetary missions. This facility, the Multimission Image Processing System (MIPS), is developed and maintained by MOSO to meet requirements that span the NASA family of planetary missions. Although the word 'image' appears in the title, MIPS is used to process instrument data from a variety of science instruments. This paper describes the design of a new system architecture now being implemented within the MIPS to support future planetary mission activities at significantly reduced operations and maintenance cost.

Encryption of QR code and grayscale image in interference-based scheme with high quality retrieval and silhouette problem removal

NASA Astrophysics Data System (ADS)

Qin, Yi; Wang, Hongjuan; Wang, Zhipeng; Gong, Qiong; Wang, Danchen

2016-09-01

In optical interference-based encryption (IBE) scheme, the currently available methods have to employ the iterative algorithms in order to encrypt two images and retrieve cross-talk free decrypted images. In this paper, we shall show that this goal can be achieved via an analytical process if one of the two images is QR code. For decryption, the QR code is decrypted in the conventional architecture and the decryption has a noisy appearance. Nevertheless, the robustness of QR code against noise enables the accurate acquisition of its content from the noisy retrieval, as a result of which the primary QR code can be exactly regenerated. Thereafter, a novel optical architecture is proposed to recover the grayscale image by aid of the QR code. In addition, the proposal has totally eliminated the silhouette problem existing in the previous IBE schemes, and its effectiveness and feasibility have been demonstrated by numerical simulations.

Dynamic Optically Multiplexed Imaging

DTIC Science & Technology

2015-07-29

Direction LENS.ZMX Configuration 1 of 1 3D Layout 10/21/2014 Scale: 1.000020.00 Millimeters X Y Z Parent Lens (a) (b) 0 20 40 60 80 100 0 20 40 60 80 100...V. Shah, and T. Shih “Design Architectures for Optically Multiplexed Imaging,” in submission 9 R. Gupta, P . Indyk, E. Price, and Y . Rachlin...the number of multiplexed images. As a result, measurements from a sufficiently fast sampling sensor can be processed to yield a low distortion image

Vacuum-bag-only processing of composites

NASA Astrophysics Data System (ADS)

Thomas, Shad

Ultrasonic imaging in the C-scan mode in conjunction with the amplitude of the reflected signal was used to measure flow rates of an epoxy resin film penetrating through the thickness of single layers of woven carbon fabric. Assemblies, comprised of a single layer of fabric and film, were vacuum-bagged and ultrasonically scanned in a water tank during impregnation at 50°C, 60°C, 70°C, and 80°C. Measured flow rates were plotted versus inverse viscosity to determine the permeability in the thin film, non-saturated system. The results demonstrated that ultrasonic imaging in the C-scan mode is an effective method of measuring z-direction resin flow through a single layer of fabric. The permeability values determined in this work were consistent with permeability values reported in the literature. Capillary flow was not observed at the temperatures and times required for pressurized flow to occur. The flow rate at 65°C was predicted from the linear plot of flow rate versus inverse viscosity. The effects of fabric architecture on through-thickness flow rates during impregnation of an epoxy resin film were measured by ultrasonic imaging. Multilayered laminates comprised of woven carbon fabrics and epoxy films (prepregs) were fabricated by vacuum-bagging. Ultrasonic imaging was performed in a heated water tank (65°C) during impregnation. Impregnation rates showed a strong dependence on fabric architecture, despite similar areal densities. Impregnation rates are directly affected by inter-tow spacing and tow nesting, which depend on fabric architecture, and are indirectly affected by areal densities. A new method of predicting resin infusion rates in prepreg and resin film infusion processes was proposed. The Stokes equation was used to derive an equation to predict the impregnation rate of laminates as a function of fabric architecture. Flow rate data previously measured by ultrasound was analyzed with the new equation and the Kozeny-Carman equation. A fiber interaction parameter was determined as a function of fabric architecture. The derived equation is straight-forward to use, unlike the Kozeny-Carman equation. The results demonstrated that the newly derived equation can be used to predict the resin infusion rate of multilayer laminates.

GREENPLEX -- A SUSTAINABLE URBAN FORM FOR THE 21ST CENTURY

EPA Science Inventory

Outputs include images of architecture, space usage, social design, elevators, skybridges, ETFE envelope, structures, construction process, HVAC system, and water system.  Outputs include performance metrics for the University Community Greenplex and traditional univer...

Integrated system for automated financial document processing

NASA Astrophysics Data System (ADS)

Hassanein, Khaled S.; Wesolkowski, Slawo; Higgins, Ray; Crabtree, Ralph; Peng, Antai

1997-02-01

A system was developed that integrates intelligent document analysis with multiple character/numeral recognition engines in order to achieve high accuracy automated financial document processing. In this system, images are accepted in both their grayscale and binary formats. A document analysis module starts by extracting essential features from the document to help identify its type (e.g. personal check, business check, etc.). These features are also utilized to conduct a full analysis of the image to determine the location of interesting zones such as the courtesy amount and the legal amount. These fields are then made available to several recognition knowledge sources such as courtesy amount recognition engines and legal amount recognition engines through a blackboard architecture. This architecture allows all the available knowledge sources to contribute incrementally and opportunistically to the solution of the given recognition query. Performance results on a test set of machine printed business checks using the integrated system are also reported.

Concurrent Image Processing Executive (CIPE). Volume 2: Programmer's guide

NASA Technical Reports Server (NTRS)

Williams, Winifred I.

1990-01-01

This manual is intended as a guide for application programmers using the Concurrent Image Processing Executive (CIPE). CIPE is intended to become the support system software for a prototype high performance science analysis workstation. In its current configuration CIPE utilizes a JPL/Caltech Mark 3fp Hypercube with a Sun-4 host. CIPE's design is capable of incorporating other concurrent architectures as well. CIPE provides a programming environment to applications' programmers to shield them from various user interfaces, file transactions, and architectural complexities. A programmer may choose to write applications to use only the Sun-4 or to use the Sun-4 with the hypercube. A hypercube program will use the hypercube's data processors and optionally the Weitek floating point accelerators. The CIPE programming environment provides a simple set of subroutines to activate user interface functions, specify data distributions, activate hypercube resident applications, and to communicate parameters to and from the hypercube.

Architecture and data processing alternatives for the tse computer. Volume 4: Image rotation using tse operations

NASA Technical Reports Server (NTRS)

Kao, M. H.; Bodenheimer, R. E.

1976-01-01

The tse computer's capability of achieving image congruence between temporal and multiple images with misregistration due to rotational differences is reported. The coordinate transformations are obtained and a general algorithms is devised to perform image rotation using tse operations very efficiently. The details of this algorithm as well as its theoretical implications are presented. Step by step procedures of image registration are described in detail. Numerous examples are also employed to demonstrate the correctness and the effectiveness of the algorithms and conclusions and recommendations are made.

Establishing Base Elements of Perspective in Order to Reconstruct Architectural Buildings from Photographs

NASA Astrophysics Data System (ADS)

Dzwierzynska, Jolanta

2017-12-01

The use of perspective images, especially historical photographs for retrieving information about presented architectural environment is a fast developing field recently. The photography image is a perspective image with secure geometrical connection with reality, therefore it is possible to reverse this process. The aim of the herby study is establishing requirements which a photographic perspective representation should meet for a reconstruction purpose, as well as determination of base elements of perspective such as a horizon line and a circle of depth, which is a key issue in any reconstruction. The starting point in the reconstruction process is geometrical analysis of the photograph, especially determination of the kind of perspective projection applied, which is defined by the building location towards a projection plane. Next, proper constructions can be used. The paper addresses the problem of establishing base elements of perspective on the basis of the photograph image in the case when camera calibration is impossible to establish. It presents different geometric construction methods selected dependently on the starting assumptions. Therefore, the methods described in the paper seem to be universal. Moreover, they can be used even in the case of poor quality photographs with poor perspective geometry. Such constructions can be realized with computer aid when the photographs are in digital form as it is presented in the paper. The accuracy of the applied methods depends on the photography image accuracy, as well as drawing accuracy, however, it is sufficient for further reconstruction. Establishing base elements of perspective presented in the paper is especially useful in difficult cases of reconstruction, when one lacks information about reconstructed architectural form and it is necessary to lean on solid geometry.

Data path design and image quality aspects of the next generation multifunctional printer

NASA Astrophysics Data System (ADS)

Brassé, M. H. H.; de Smet, S. P. R. C.

2008-01-01

Multifunctional devices (MFDs) are increasingly used as a document hub. The MFD is used as a copier, scanner, printer, and it facilitates digital document distribution and sharing. This imposes new requirements on the design of the data path and its image processing. Various design aspects need to be taken into account, including system performance, features, image quality, and cost price. A good balance is required in order to develop a competitive MFD. A modular datapath architecture is presented that supports all the envisaged use cases. Besides copying, colour scanning is becoming an important use case of a modern MFD. The copy-path use case is described and it is shown how colour scanning can also be supported with a minimal adaptation to the architecture. The key idea is to convert the scanner data to an opponent colour space representation at the beginning of the image processing pipeline. The sub-sampling of chromatic information allows for the saving of scarce hardware resources without significant perceptual loss of quality. In particular, we have shown that functional FPGA modules from the copy application can also be used for the scan-to-file application. This makes the presented approach very cost-effective while complying with market conform image quality standards.

Application of parallelized software architecture to an autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Shakya, Rahul; Wright, Adam; Shin, Young Ho; Momin, Orko; Petkovsek, Steven; Wortman, Paul; Gautam, Prasanna; Norton, Adam

2011-01-01

This paper presents improvements made to Q, an autonomous ground vehicle designed to participate in the Intelligent Ground Vehicle Competition (IGVC). For the 2010 IGVC, Q was upgraded with a new parallelized software architecture and a new vision processor. Improvements were made to the power system reducing the number of batteries required for operation from six to one. In previous years, a single state machine was used to execute the bulk of processing activities including sensor interfacing, data processing, path planning, navigation algorithms and motor control. This inefficient approach led to poor software performance and made it difficult to maintain or modify. For IGVC 2010, the team implemented a modular parallel architecture using the National Instruments (NI) LabVIEW programming language. The new architecture divides all the necessary tasks - motor control, navigation, sensor data collection, etc. into well-organized components that execute in parallel, providing considerable flexibility and facilitating efficient use of processing power. Computer vision is used to detect white lines on the ground and determine their location relative to the robot. With the new vision processor and some optimization of the image processing algorithm used last year, two frames can be acquired and processed in 70ms. With all these improvements, Q placed 2nd in the autonomous challenge.

Thread concept for automatic task parallelization in image analysis

NASA Astrophysics Data System (ADS)

Lueckenhaus, Maximilian; Eckstein, Wolfgang

1998-09-01

Parallel processing of image analysis tasks is an essential method to speed up image processing and helps to exploit the full capacity of distributed systems. However, writing parallel code is a difficult and time-consuming process and often leads to an architecture-dependent program that has to be re-implemented when changing the hardware. Therefore it is highly desirable to do the parallelization automatically. For this we have developed a special kind of thread concept for image analysis tasks. Threads derivated from one subtask may share objects and run in the same context but may process different threads of execution and work on different data in parallel. In this paper we describe the basics of our thread concept and show how it can be used as basis of an automatic task parallelization to speed up image processing. We further illustrate the design and implementation of an agent-based system that uses image analysis threads for generating and processing parallel programs by taking into account the available hardware. The tests made with our system prototype show that the thread concept combined with the agent paradigm is suitable to speed up image processing by an automatic parallelization of image analysis tasks.

A semantically-aided architecture for a web-based monitoring system for carotid atherosclerosis.

PubMed

Kolias, Vassileios D; Stamou, Giorgos; Golemati, Spyretta; Stoitsis, Giannis; Gkekas, Christos D; Liapis, Christos D; Nikita, Konstantina S

2015-08-01

Carotid atherosclerosis is a multifactorial disease and its clinical diagnosis depends on the evaluation of heterogeneous clinical data, such as imaging exams, biochemical tests and the patient's clinical history. The lack of interoperability between Health Information Systems (HIS) does not allow the physicians to acquire all the necessary data for the diagnostic process. In this paper, a semantically-aided architecture is proposed for a web-based monitoring system for carotid atherosclerosis that is able to gather and unify heterogeneous data with the use of an ontology and to create a common interface for data access enhancing the interoperability of HIS. The architecture is based on an application ontology of carotid atherosclerosis that is used to (a) integrate heterogeneous data sources on the basis of semantic representation and ontological reasoning and (b) access the critical information using SPARQL query rewriting and ontology-based data access services. The architecture was tested over a carotid atherosclerosis dataset consisting of the imaging exams and the clinical profile of 233 patients, using a set of complex queries, constructed by the physicians. The proposed architecture was evaluated with respect to the complexity of the queries that the physicians could make and the retrieval speed. The proposed architecture gave promising results in terms of interoperability, data integration of heterogeneous sources with an ontological way and expanded capabilities of query and retrieval in HIS.

Optical imaging of architecture and function in the living brain sheds new light on cortical mechanisms underlying visual perception.

PubMed

Grinvald, A

1992-01-01

Long standing questions related to brain mechanisms underlying perception can finally be resolved by direct visualization of the architecture and function of mammalian cortex. This advance has been accomplished with the aid of two optical imaging techniques with which one can literally see how the brain functions. The upbringing of this technology required a multi-disciplinary approach integrating brain research with organic chemistry, spectroscopy, biophysics, computer sciences, optics and image processing. Beyond the technological ramifications, recent research shed new light on cortical mechanisms underlying sensory perception. Clinical applications of this technology for precise mapping of the cortical surface of patients during neurosurgery have begun. Below is a brief summary of our own research and a description of the technical specifications of the two optical imaging techniques. Like every technique, optical imaging also suffers from severe limitations. Here we mostly emphasize some of its advantages relative to all alternative imaging techniques currently in use. The limitations are critically discussed in our recent reviews. For a series of other reviews, see Cohen (1989).

The 2nd Symposium on the Frontiers of Massively Parallel Computations

NASA Technical Reports Server (NTRS)

Mills, Ronnie (Editor)

1988-01-01

Programming languages, computer graphics, neural networks, massively parallel computers, SIMD architecture, algorithms, digital terrain models, sort computation, simulation of charged particle transport on the massively parallel processor and image processing are among the topics discussed.

GPU Accelerated Vector Median Filter

NASA Technical Reports Server (NTRS)

Aras, Rifat; Shen, Yuzhong

2011-01-01

Noise reduction is an important step for most image processing tasks. For three channel color images, a widely used technique is vector median filter in which color values of pixels are treated as 3-component vectors. Vector median filters are computationally expensive; for a window size of n x n, each of the n(sup 2) vectors has to be compared with other n(sup 2) - 1 vectors in distances. General purpose computation on graphics processing units (GPUs) is the paradigm of utilizing high-performance many-core GPU architectures for computation tasks that are normally handled by CPUs. In this work. NVIDIA's Compute Unified Device Architecture (CUDA) paradigm is used to accelerate vector median filtering. which has to the best of our knowledge never been done before. The performance of GPU accelerated vector median filter is compared to that of the CPU and MPI-based versions for different image and window sizes, Initial findings of the study showed 100x improvement of performance of vector median filter implementation on GPUs over CPU implementations and further speed-up is expected after more extensive optimizations of the GPU algorithm .

Real-time orthorectification by FPGA-based hardware acceleration

NASA Astrophysics Data System (ADS)

Kuo, David; Gordon, Don

2010-10-01

Orthorectification that corrects the perspective distortion of remote sensing imagery, providing accurate geolocation and ease of correlation to other images is a valuable first-step in image processing for information extraction. However, the large amount of metadata and the floating-point matrix transformations required to operate on each pixel make this a computation and I/O (Input/Output) intensive process. As result much imagery is either left unprocessed or loses timesensitive value in the long processing cycle. However, the computation on each pixel can be reduced substantially by using computational results of the neighboring pixels and accelerated by special pipelined hardware architecture in one to two orders of magnitude. A specialized coprocessor that is implemented inside an FPGA (Field Programmable Gate Array) chip and surrounded by vendorsupported hardware IP (Intellectual Property) shares the computation workload with CPU through PCI-Express interface. The ultimate speed of one pixel per clock (125 MHz) is achieved by the pipelined systolic array architecture. The optimal partition between software and hardware, the timing profile among image I/O and computation, and the highly automated GUI (Graphical User Interface) that fully exploits this speed increase to maximize overall image production throughput will also be discussed. The software that runs on a workstation with the acceleration hardware orthorectifies 16 Megapixels per second, which is 16 times faster than without the hardware. It turns the production time from months to days. A real-life successful story of an imaging satellite company that adopted such workstations for their orthorectified imagery production will be presented. The potential candidacy of the image processing computation that can be accelerated more efficiently by the same approach will also be analyzed.

An Efficient Implementation of Deep Convolutional Neural Networks for MRI Segmentation.

PubMed

Hoseini, Farnaz; Shahbahrami, Asadollah; Bayat, Peyman

2018-02-27

Image segmentation is one of the most common steps in digital image processing, classifying a digital image into different segments. The main goal of this paper is to segment brain tumors in magnetic resonance images (MRI) using deep learning. Tumors having different shapes, sizes, brightness and textures can appear anywhere in the brain. These complexities are the reasons to choose a high-capacity Deep Convolutional Neural Network (DCNN) containing more than one layer. The proposed DCNN contains two parts: architecture and learning algorithms. The architecture and the learning algorithms are used to design a network model and to optimize parameters for the network training phase, respectively. The architecture contains five convolutional layers, all using 3 × 3 kernels, and one fully connected layer. Due to the advantage of using small kernels with fold, it allows making the effect of larger kernels with smaller number of parameters and fewer computations. Using the Dice Similarity Coefficient metric, we report accuracy results on the BRATS 2016, brain tumor segmentation challenge dataset, for the complete, core, and enhancing regions as 0.90, 0.85, and 0.84 respectively. The learning algorithm includes the task-level parallelism. All the pixels of an MR image are classified using a patch-based approach for segmentation. We attain a good performance and the experimental results show that the proposed DCNN increases the segmentation accuracy compared to previous techniques.

Surveillance and reconnaissance ground system architecture

NASA Astrophysics Data System (ADS)

Devambez, Francois

2001-12-01

Modern conflicts induces various modes of deployment, due to the type of conflict, the type of mission, and phase of conflict. It is then impossible to define fixed architecture systems for surveillance ground segments. Thales has developed a structure for a ground segment based on the operational functions required, and on the definition of modules and networks. Theses modules are software and hardware modules, including communications and networks. This ground segment is called MGS (Modular Ground Segment), and is intended for use in airborne reconnaissance systems, surveillance systems, and U.A.V. systems. Main parameters for the definition of a modular ground image exploitation system are : Compliance with various operational configurations, Easy adaptation to the evolution of theses configurations, Interoperability with NATO and multinational forces, Security, Multi-sensors, multi-platforms capabilities, Technical modularity, Evolutivity Reduction of life cycle cost The general performances of the MGS are presented : type of sensors, acquisition process, exploitation of images, report generation, data base management, dissemination, interface with C4I. The MGS is then described as a set of hardware and software modules, and their organization to build numerous operational configurations. Architectures are from minimal configuration intended for a mono-sensor image exploitation system, to a full image intelligence center, for a multilevel exploitation of multi-sensor.

A Real-Time Image Acquisition And Processing System For A RISC-Based Microcomputer

NASA Astrophysics Data System (ADS)

Luckman, Adrian J.; Allinson, Nigel M.

1989-03-01

A low cost image acquisition and processing system has been developed for the Acorn Archimedes microcomputer. Using a Reduced Instruction Set Computer (RISC) architecture, the ARM (Acorn Risc Machine) processor provides instruction speeds suitable for image processing applications. The associated improvement in data transfer rate has allowed real-time video image acquisition without the need for frame-store memory external to the microcomputer. The system is comprised of real-time video digitising hardware which interfaces directly to the Archimedes memory, and software to provide an integrated image acquisition and processing environment. The hardware can digitise a video signal at up to 640 samples per video line with programmable parameters such as sampling rate and gain. Software support includes a work environment for image capture and processing with pixel, neighbourhood and global operators. A friendly user interface is provided with the help of the Archimedes Operating System WIMP (Windows, Icons, Mouse and Pointer) Manager. Windows provide a convenient way of handling images on the screen and program control is directed mostly by pop-up menus.

Optical information-processing systems and architectures II; Proceedings of the Meeting, San Diego, CA, July 9-13, 1990

NASA Astrophysics Data System (ADS)

Javidi, Bahram

The present conference discusses topics in the fields of neural networks, acoustooptic signal processing, pattern recognition, phase-only processing, nonlinear signal processing, image processing, optical computing, and optical information processing. Attention is given to the optical implementation of an inner-product neural associative memory, optoelectronic associative recall via motionless-head/parallel-readout optical disk, a compact real-time acoustooptic image correlator, a multidimensional synthetic estimation filter, and a light-efficient joint transform optical correlator. Also discussed are a high-resolution spatial light modulator, compact real-time interferometric Fourier-transform processors, a fast decorrelation algorithm for permutation arrays, the optical interconnection of optical modules, and carry-free optical binary adders.

Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery.

PubMed

Zhao, Yi; Ma, Jiale; Li, Xiaohui; Zhang, Jie

2018-02-27

An unmanned aerial vehicle (UAV) equipped with global positioning systems (GPS) can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both) and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network) is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset 'UAV_Fire'. A 15-layered self-learning DCNN architecture named 'Fire_Net' is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc.) of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, 'Fire_Net' guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified.

Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery

PubMed Central

Zhao, Yi; Ma, Jiale; Li, Xiaohui

2018-01-01

An unmanned aerial vehicle (UAV) equipped with global positioning systems (GPS) can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both) and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network) is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset ‘UAV_Fire’. A 15-layered self-learning DCNN architecture named ‘Fire_Net’ is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc.) of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, ‘Fire_Net’ guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified. PMID:29495504

Design of a multi-spectral imager built using the compressive sensing single-pixel camera architecture

NASA Astrophysics Data System (ADS)

McMackin, Lenore; Herman, Matthew A.; Weston, Tyler

2016-02-01

We present the design of a multi-spectral imager built using the architecture of the single-pixel camera. The architecture is enabled by the novel sampling theory of compressive sensing implemented optically using the Texas Instruments DLP™ micro-mirror array. The array not only implements spatial modulation necessary for compressive imaging but also provides unique diffractive spectral features that result in a multi-spectral, high-spatial resolution imager design. The new camera design provides multi-spectral imagery in a wavelength range that extends from the visible to the shortwave infrared without reduction in spatial resolution. In addition to the compressive imaging spectrometer design, we present a diffractive model of the architecture that allows us to predict a variety of detailed functional spatial and spectral design features. We present modeling results, architectural design and experimental results that prove the concept.

Transforming medical imaging applications into collaborative PACS-based telemedical systems

NASA Astrophysics Data System (ADS)

Maani, Rouzbeh; Camorlinga, Sergio; Arnason, Neil

2011-03-01

Telemedical systems are not practical for use in a clinical workflow unless they are able to communicate with the Picture Archiving and Communications System (PACS). On the other hand, there are many medical imaging applications that are not developed as telemedical systems. Some medical imaging applications do not support collaboration and some do not communicate with the PACS and therefore limit their usability in clinical workflows. This paper presents a general architecture based on a three-tier architecture model. The architecture and the components developed within it, transform medical imaging applications into collaborative PACS-based telemedical systems. As a result, current medical imaging applications that are not telemedical, not supporting collaboration, and not communicating with PACS, can be enhanced to support collaboration among a group of physicians, be accessed remotely, and be clinically useful. The main advantage of the proposed architecture is that it does not impose any modification to the current medical imaging applications and does not make any assumptions about the underlying architecture or operating system.

Tracking Training-Related Plasticity by Combining fMRI and DTI: The Right Hemisphere Ventral Stream Mediates Musical Syntax Processing.

PubMed

Oechslin, Mathias S; Gschwind, Markus; James, Clara E

2018-04-01

As a functional homolog for left-hemispheric syntax processing in language, neuroimaging studies evidenced involvement of right prefrontal regions in musical syntax processing, of which underlying white matter connectivity remains unexplored so far. In the current experiment, we investigated the underlying pathway architecture in subjects with 3 levels of musical expertise. Employing diffusion tensor imaging tractography, departing from seeds from our previous functional magnetic resonance imaging study on music syntax processing in the same participants, we identified a pathway in the right ventral stream that connects the middle temporal lobe with the inferior frontal cortex via the extreme capsule, and corresponds to the left hemisphere ventral stream, classically attributed to syntax processing in language comprehension. Additional morphometric consistency analyses allowed dissociating tract core from more dispersed fiber portions. Musical expertise related to higher tract consistency of the right ventral stream pathway. Specifically, tract consistency in this pathway predicted the sensitivity for musical syntax violations. We conclude that enduring musical practice sculpts ventral stream architecture. Our results suggest that training-related pathway plasticity facilitates the right hemisphere ventral stream information transfer, supporting an improved sound-to-meaning mapping in music.

Iris unwrapping using the Bresenham circle algorithm for real-time iris recognition

NASA Astrophysics Data System (ADS)

Carothers, Matthew T.; Ngo, Hau T.; Rakvic, Ryan N.; Broussard, Randy P.

2015-02-01

An efficient parallel architecture design for the iris unwrapping process in a real-time iris recognition system using the Bresenham Circle Algorithm is presented in this paper. Based on the characteristics of the model parameters this algorithm was chosen over the widely used polar conversion technique as the iris unwrapping model. The architecture design is parallelized to increase the throughput of the system and is suitable for processing an inputted image size of 320 × 240 pixels in real-time using Field Programmable Gate Array (FPGA) technology. Quartus software is used to implement, verify, and analyze the design's performance using the VHSIC Hardware Description Language. The system's predicted processing time is faster than the modern iris unwrapping technique used today∗.

Document Image Parsing and Understanding using Neuromorphic Architecture

DTIC Science & Technology

2015-03-01

processing speed at different layers. In the pattern matching layer, the computing power of multicore processors is explored to reduce the processing...developed to reduce the processing speed at different layers. In the pattern matching layer, the computing power of multicore processors is explored... cortex where the complex data is reduced to abstract representations. The abstract representation is compared to stored patterns in massively parallel

Onboard FPGA-based SAR processing for future spaceborne systems

NASA Technical Reports Server (NTRS)

Le, Charles; Chan, Samuel; Cheng, Frank; Fang, Winston; Fischman, Mark; Hensley, Scott; Johnson, Robert; Jourdan, Michael; Marina, Miguel; Parham, Bruce;

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

PubMed Central

Rellán-Álvarez, Rubén; Lobet, Guillaume; Lindner, Heike; Pradier, Pierre-Luc; Sebastian, Jose; Yee, Muh-Ching; Geng, Yu; Trontin, Charlotte; LaRue, Therese; Schrager-Lavelle, Amanda; Haney, Cara H; Nieu, Rita; Maloof, Julin; Vogel, John P; Dinneny, José R

2015-01-01

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes. DOI: http://dx.doi.org/10.7554/eLife.07597.001 PMID:26287479

GLO-Roots: An imaging platform enabling multidimensional characterization of soil-grown root systems

DOE PAGES

Rellan-Alvarez, Ruben; Lobet, Guillaume; Lindner, Heike; ...

2015-08-19

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow themore » spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.« less

Visualizing Cell Architecture and Molecular Location Using Soft X-Ray Tomography and Correlated Cryo-Light Microscopy

PubMed Central

McDermott, Gerry; Le Gros, Mark A.; Larabell, Carolyn A.

2012-01-01

Living cells are structured to create a range of microenvironments that support specific chemical reactions and processes. Understanding how cells function therefore requires detailed knowledge of both the subcellular architecture and the location of specific molecules within this framework. Here we review the development of two correlated cellular imaging techniques that fulfill this need. Cells are first imaged using cryogenic fluorescence microscopy to determine the location of molecules of interest that have been labeled with fluorescent tags. The same specimen is then imaged using soft X-ray tomography to generate a high-contrast, 3D reconstruction of the cells. Data from the two modalities are then combined to produce a composite, information-rich view of the cell. This correlated imaging approach can be applied across the spectrum of problems encountered in cell biology, from basic research to biotechnological and biomedical applications such as the optimization of biofuels and the development of new pharmaceuticals. PMID:22242730

Fusion of Local Statistical Parameters for Buried Underwater Mine Detection in Sonar Imaging

NASA Astrophysics Data System (ADS)

Maussang, F.; Rombaut, M.; Chanussot, J.; Hétet, A.; Amate, M.

2008-12-01

Detection of buried underwater objects, and especially mines, is a current crucial strategic task. Images provided by sonar systems allowing to penetrate in the sea floor, such as the synthetic aperture sonars (SASs), are of great interest for the detection and classification of such objects. However, the signal-to-noise ratio is fairly low and advanced information processing is required for a correct and reliable detection of the echoes generated by the objects. The detection method proposed in this paper is based on a data-fusion architecture using the belief theory. The input data of this architecture are local statistical characteristics extracted from SAS data corresponding to the first-, second-, third-, and fourth-order statistical properties of the sonar images, respectively. The interest of these parameters is derived from a statistical model of the sonar data. Numerical criteria are also proposed to estimate the detection performances and to validate the method.

Architecture and applications of a high resolution gated SPAD image sensor

PubMed Central

Burri, Samuel; Maruyama, Yuki; Michalet, Xavier; Regazzoni, Francesco; Bruschini, Claudio; Charbon, Edoardo

2014-01-01

We present the architecture and three applications of the largest resolution image sensor based on single-photon avalanche diodes (SPADs) published to date. The sensor, fabricated in a high-voltage CMOS process, has a resolution of 512 × 128 pixels and a pitch of 24 μm. The fill-factor of 5% can be increased to 30% with the use of microlenses. For precise control of the exposure and for time-resolved imaging, we use fast global gating signals to define exposure windows as small as 4 ns. The uniformity of the gate edges location is ∼140 ps (FWHM) over the whole array, while in-pixel digital counting enables frame rates as high as 156 kfps. Currently, our camera is used as a highly sensitive sensor with high temporal resolution, for applications ranging from fluorescence lifetime measurements to fluorescence correlation spectroscopy and generation of true random numbers. PMID:25090572

Anisotropic analysis of trabecular architecture in human femur bone radiographs using quaternion wavelet transforms.

PubMed

Sangeetha, S; Sujatha, C M; Manamalli, D

2014-01-01

In this work, anisotropy of compressive and tensile strength regions of femur trabecular bone are analysed using quaternion wavelet transforms. The normal and abnormal femur trabecular bone radiographic images are considered for this study. The sub-anatomic regions, which include compressive and tensile regions, are delineated using pre-processing procedures. These delineated regions are subjected to quaternion wavelet transforms and statistical parameters are derived from the transformed images. These parameters are correlated with apparent porosity, which is derived from the strength regions. Further, anisotropy is also calculated from the transformed images and is analyzed. Results show that the anisotropy values derived from second and third phase components of quaternion wavelet transform are found to be distinct for normal and abnormal samples with high statistical significance for both compressive and tensile regions. These investigations demonstrate that architectural anisotropy derived from QWT analysis is able to differentiate normal and abnormal samples.

Multifractal geometry in analysis and processing of digital retinal photographs for early diagnosis of human diabetic macular edema.

PubMed

Tălu, Stefan

2013-07-01

The purpose of this paper is to determine a quantitative assessment of the human retinal vascular network architecture for patients with diabetic macular edema (DME). Multifractal geometry and lacunarity parameters are used in this study. A set of 10 segmented and skeletonized human retinal images, corresponding to both normal (five images) and DME states of the retina (five images), from the DRIVE database was analyzed using the Image J software. Statistical analyses were performed using Microsoft Office Excel 2003 and GraphPad InStat software. The human retinal vascular network architecture has a multifractal geometry. The average of generalized dimensions (Dq) for q = 0, 1, 2 of the normal images (segmented versions), is similar to the DME cases (segmented versions). The average of generalized dimensions (Dq) for q = 0, 1 of the normal images (skeletonized versions), is slightly greater than the DME cases (skeletonized versions). However, the average of D2 for the normal images (skeletonized versions) is similar to the DME images. The average of lacunarity parameter, Λ, for the normal images (segmented and skeletonized versions) is slightly lower than the corresponding values for DME images (segmented and skeletonized versions). The multifractal and lacunarity analysis provides a non-invasive predictive complementary tool for an early diagnosis of patients with DME.

Fluorescent Nano-Probes to Image Plant Cell Walls by Super-Resolution STED Microscopy

PubMed Central

Paës, Gabriel; Habrant, Anouck; Terryn, Christine

2018-01-01

Lignocellulosic biomass is a complex network of polymers making up the cell walls of plants. It represents a feedstock of sustainable resources to be converted into fuels, chemicals, and materials. Because of its complex architecture, lignocellulose is a recalcitrant material that requires some pretreatments and several types of catalysts to be transformed efficiently. Gaining more knowledge in the architecture of plant cell walls is therefore important to understand and optimize transformation processes. For the first time, super-resolution imaging of poplar wood samples has been performed using the Stimulated Emission Depletion (STED) technique. In comparison to standard confocal images, STED reveals new details in cell wall structure, allowing the identification of secondary walls and middle lamella with fine details, while keeping open the possibility to perform topochemistry by the use of relevant fluorescent nano-probes. In particular, the deconvolution of STED images increases the signal-to-noise ratio so that images become very well defined. The obtained results show that the STED super-resolution technique can be easily implemented by using cheap commercial fluorescent rhodamine-PEG nano-probes which outline the architecture of plant cell walls due to their interaction with lignin. Moreover, the sample preparation only requires easily-prepared plant sections of a few tens of micrometers, in addition to an easily-implemented post-treatment of images. Overall, the STED super-resolution technique in combination with a variety of nano-probes can provide a new vision of plant cell wall imaging by filling in the gap between classical photon microscopy and electron microscopy. PMID:29415498

Fluorescent Nano-Probes to Image Plant Cell Walls by Super-Resolution STED Microscopy.

PubMed

Paës, Gabriel; Habrant, Anouck; Terryn, Christine

2018-02-06

Lignocellulosic biomass is a complex network of polymers making up the cell walls of plants. It represents a feedstock of sustainable resources to be converted into fuels, chemicals, and materials. Because of its complex architecture, lignocellulose is a recalcitrant material that requires some pretreatments and several types of catalysts to be transformed efficiently. Gaining more knowledge in the architecture of plant cell walls is therefore important to understand and optimize transformation processes. For the first time, super-resolution imaging of poplar wood samples has been performed using the Stimulated Emission Depletion (STED) technique. In comparison to standard confocal images, STED reveals new details in cell wall structure, allowing the identification of secondary walls and middle lamella with fine details, while keeping open the possibility to perform topochemistry by the use of relevant fluorescent nano-probes. In particular, the deconvolution of STED images increases the signal-to-noise ratio so that images become very well defined. The obtained results show that the STED super-resolution technique can be easily implemented by using cheap commercial fluorescent rhodamine-PEG nano-probes which outline the architecture of plant cell walls due to their interaction with lignin. Moreover, the sample preparation only requires easily-prepared plant sections of a few tens of micrometers, in addition to an easily-implemented post-treatment of images. Overall, the STED super-resolution technique in combination with a variety of nano-probes can provide a new vision of plant cell wall imaging by filling in the gap between classical photon microscopy and electron microscopy.

Identification of hand motion using background subtraction method and extraction of image binary with backpropagation neural network on skeleton model

NASA Astrophysics Data System (ADS)

Fauziah; Wibowo, E. P.; Madenda, S.; Hustinawati

2018-03-01

Capturing and recording motion in human is mostly done with the aim for sports, health, animation films, criminality, and robotic applications. In this study combined background subtraction and back propagation neural network. This purpose to produce, find similarity movement. The acquisition process using 8 MP resolution camera MP4 format, duration 48 seconds, 30frame/rate. video extracted produced 1444 pieces and results hand motion identification process. Phase of image processing performed is segmentation process, feature extraction, identification. Segmentation using bakground subtraction, extracted feature basically used to distinguish between one object to another object. Feature extraction performed by using motion based morfology analysis based on 7 invariant moment producing four different classes motion: no object, hand down, hand-to-side and hands-up. Identification process used to recognize of hand movement using seven inputs. Testing and training with a variety of parameters tested, it appears that architecture provides the highest accuracy in one hundred hidden neural network. The architecture is used propagate the input value of the system implementation process into the user interface. The result of the identification of the type of the human movement has been clone to produce the highest acuracy of 98.5447%. The training process is done to get the best results.

Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

NASA Astrophysics Data System (ADS)

Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

2016-01-01

The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

SPEKTROP DPU: optoelectronic platform for fast multispectral imaging

NASA Astrophysics Data System (ADS)

Graczyk, Rafal; Sitek, Piotr; Stolarski, Marcin

2010-09-01

In recent years it easy to spot and increasing need of high-quality Earth imaging in airborne and space applications. This is due fact that government and local authorities urge for up to date topological data for administrative purposes. On the other hand, interest in environmental sciences, push for ecological approach, efficient agriculture and forests management are also heavily supported by Earth images in various resolutions and spectral ranges. "SPEKTROP DPU: Opto-electronic platform for fast multi-spectral imaging" paper describes architectural datails of data processing unit, part of universal and modular platform that provides high quality imaging functionality in aerospace applications.

NetVLAD: CNN Architecture for Weakly Supervised Place Recognition.

PubMed

Arandjelovic, Relja; Gronat, Petr; Torii, Akihiko; Pajdla, Tomas; Sivic, Josef

2018-06-01

We tackle the problem of large scale visual place recognition, where the task is to quickly and accurately recognize the location of a given query photograph. We present the following four principal contributions. First, we develop a convolutional neural network (CNN) architecture that is trainable in an end-to-end manner directly for the place recognition task. The main component of this architecture, NetVLAD, is a new generalized VLAD layer, inspired by the "Vector of Locally Aggregated Descriptors" image representation commonly used in image retrieval. The layer is readily pluggable into any CNN architecture and amenable to training via backpropagation. Second, we create a new weakly supervised ranking loss, which enables end-to-end learning of the architecture's parameters from images depicting the same places over time downloaded from Google Street View Time Machine. Third, we develop an efficient training procedure which can be applied on very large-scale weakly labelled tasks. Finally, we show that the proposed architecture and training procedure significantly outperform non-learnt image representations and off-the-shelf CNN descriptors on challenging place recognition and image retrieval benchmarks.

Motion camera based on a custom vision sensor and an FPGA architecture

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel

1998-09-01

A digital camera for custom focal plane arrays was developed. The camera allows the test and development of analog or mixed-mode arrays for focal plane processing. The camera is used with a custom sensor for motion detection to implement a motion computation system. The custom focal plane sensor detects moving edges at the pixel level using analog VLSI techniques. The sensor communicates motion events using the event-address protocol associated to a temporal reference. In a second stage, a coprocessing architecture based on a field programmable gate array (FPGA) computes the time-of-travel between adjacent pixels. The FPGA allows rapid prototyping and flexible architecture development. Furthermore, the FPGA interfaces the sensor to a compact PC computer which is used for high level control and data communication to the local network. The camera could be used in applications such as self-guided vehicles, mobile robotics and smart surveillance systems. The programmability of the FPGA allows the exploration of further signal processing like spatial edge detection or image segmentation tasks. The article details the motion algorithm, the sensor architecture, the use of the event- address protocol for velocity vector computation and the FPGA architecture used in the motion camera system.

3D measurement by digital photogrammetry

NASA Astrophysics Data System (ADS)

Schneider, Carl T.

1993-12-01

Photogrammetry is well known in geodetic surveys as aerial photogrammetry or close range applications as architectural photogrammetry. The photogrammetric methods and algorithms combined with digital cameras and digital image processing methods are now introduced for industrial applications as automation and quality control. The presented paper will describe the photogrammetric and digital image processing algorithms and the calibration methods. These algorithms and methods were demonstrated with application examples. These applications are a digital photogrammetric workstation as a mobil multi purpose 3D measuring tool and a tube measuring system as an example for a single purpose tool.

An Intelligent Architecture Based on Field Programmable Gate Arrays Designed to Detect Moving Objects by Using Principal Component Analysis

PubMed Central

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L.; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices. PMID:22163406

An intelligent architecture based on Field Programmable Gate Arrays designed to detect moving objects by using Principal Component Analysis.

PubMed

Bravo, Ignacio; Mazo, Manuel; Lázaro, José L; Gardel, Alfredo; Jiménez, Pedro; Pizarro, Daniel

2010-01-01

This paper presents a complete implementation of the Principal Component Analysis (PCA) algorithm in Field Programmable Gate Array (FPGA) devices applied to high rate background segmentation of images. The classical sequential execution of different parts of the PCA algorithm has been parallelized. This parallelization has led to the specific development and implementation in hardware of the different stages of PCA, such as computation of the correlation matrix, matrix diagonalization using the Jacobi method and subspace projections of images. On the application side, the paper presents a motion detection algorithm, also entirely implemented on the FPGA, and based on the developed PCA core. This consists of dynamically thresholding the differences between the input image and the one obtained by expressing the input image using the PCA linear subspace previously obtained as a background model. The proposal achieves a high ratio of processed images (up to 120 frames per second) and high quality segmentation results, with a completely embedded and reliable hardware architecture based on commercial CMOS sensors and FPGA devices.

Next-generation digital camera integration and software development issues

NASA Astrophysics Data System (ADS)

Venkataraman, Shyam; Peters, Ken; Hecht, Richard

1998-04-01

This paper investigates the complexities associated with the development of next generation digital cameras due to requirements in connectivity and interoperability. Each successive generation of digital camera improves drastically in cost, performance, resolution, image quality and interoperability features. This is being accomplished by advancements in a number of areas: research, silicon, standards, etc. As the capabilities of these cameras increase, so do the requirements for both hardware and software. Today, there are two single chip camera solutions in the market including the Motorola MPC 823 and LSI DCAM- 101. Real time constraints for a digital camera may be defined by the maximum time allowable between capture of images. Constraints in the design of an embedded digital camera include processor architecture, memory, processing speed and the real-time operating systems. This paper will present the LSI DCAM-101, a single-chip digital camera solution. It will present an overview of the architecture and the challenges in hardware and software for supporting streaming video in such a complex device. Issues presented include the development of the data flow software architecture, testing and integration on this complex silicon device. The strategy for optimizing performance on the architecture will also be presented.

Onboard spectral imager data processor

NASA Astrophysics Data System (ADS)

Otten, Leonard J.; Meigs, Andrew D.; Franklin, Abraham J.; Sears, Robert D.; Robison, Mark W.; Rafert, J. Bruce; Fronterhouse, Donald C.; Grotbeck, Ronald L.

1999-10-01

Previous papers have described the concept behind the MightySat II.1 program, the satellite's Fourier Transform imaging spectrometer's optical design, the design for the spectral imaging payload, and its initial qualification testing. This paper discusses the on board data processing designed to reduce the amount of downloaded data by an order of magnitude and provide a demonstration of a smart spaceborne spectral imaging sensor. Two custom components, a spectral imager interface 6U VME card that moves data at over 30 MByte/sec, and four TI C-40 processors mounted to a second 6U VME and daughter card, are used to adapt the sensor to the spacecraft and provide the necessary high speed processing. A system architecture that offers both on board real time image processing and high-speed post data collection analysis of the spectral data has been developed. In addition to the on board processing of the raw data into a usable spectral data volume, one feature extraction technique has been incorporated. This algorithm operates on the basic interferometric data. The algorithm is integrated within the data compression process to search for uploadable feature descriptions.

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

An ATR architecture for algorithm development and testing

NASA Astrophysics Data System (ADS)

Breivik, Gøril M.; Løkken, Kristin H.; Brattli, Alvin; Palm, Hans C.; Haavardsholm, Trym

2013-05-01

A research platform with four cameras in the infrared and visible spectral domains is under development at the Norwegian Defence Research Establishment (FFI). The platform will be mounted on a high-speed jet aircraft and will primarily be used for image acquisition and for development and test of automatic target recognition (ATR) algorithms. The sensors on board produce large amounts of data, the algorithms can be computationally intensive and the data processing is complex. This puts great demands on the system architecture; it has to run in real-time and at the same time be suitable for algorithm development. In this paper we present an architecture for ATR systems that is designed to be exible, generic and efficient. The architecture is module based so that certain parts, e.g. specific ATR algorithms, can be exchanged without affecting the rest of the system. The modules are generic and can be used in various ATR system configurations. A software framework in C++ that handles large data ows in non-linear pipelines is used for implementation. The framework exploits several levels of parallelism and lets the hardware processing capacity be fully utilised. The ATR system is under development and has reached a first level that can be used for segmentation algorithm development and testing. The implemented system consists of several modules, and although their content is still limited, the segmentation module includes two different segmentation algorithms that can be easily exchanged. We demonstrate the system by applying the two segmentation algorithms to infrared images from sea trial recordings.

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.

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

Novel wavelength diversity technique for high-speed atmospheric turbulence compensation

NASA Astrophysics Data System (ADS)

Arrasmith, William W.; Sullivan, Sean F.

2010-04-01

The defense, intelligence, and homeland security communities are driving a need for software dominant, real-time or near-real time atmospheric turbulence compensated imagery. The development of parallel processing capabilities are finding application in diverse areas including image processing, target tracking, pattern recognition, and image fusion to name a few. A novel approach to the computationally intensive case of software dominant optical and near infrared imaging through atmospheric turbulence is addressed in this paper. Previously, the somewhat conventional wavelength diversity method has been used to compensate for atmospheric turbulence with great success. We apply a new correlation based approach to the wavelength diversity methodology using a parallel processing architecture enabling high speed atmospheric turbulence compensation. Methods for optical imaging through distributed turbulence are discussed, simulation results are presented, and computational and performance assessments are provided.

Ultrahigh-frame CCD imagers

NASA Astrophysics Data System (ADS)

Lowrance, John L.; Mastrocola, V. J.; Renda, George F.; Swain, Pradyumna K.; Kabra, R.; Bhaskaran, Mahalingham; Tower, John R.; Levine, Peter A.

2004-02-01

This paper describes the architecture, process technology, and performance of a family of high burst rate CCDs. These imagers employ high speed, low lag photo-detectors with local storage at each photo-detector to achieve image capture at rates greater than 106 frames per second. One imager has a 64 x 64 pixel array with 12 frames of storage. A second imager has a 80 x 160 array with 28 frames of storage, and the third imager has a 64 x 64 pixel array with 300 frames of storage. Application areas include capture of rapid mechanical motion, optical wavefront sensing, fluid cavitation research, combustion studies, plasma research and wind-tunnel-based gas dynamics research.

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.

Matrix decomposition graphics processing unit solver for Poisson image editing

NASA Astrophysics Data System (ADS)

Lei, Zhao; Wei, Li

2012-10-01

In recent years, gradient-domain methods have been widely discussed in the image processing field, including seamless cloning and image stitching. These algorithms are commonly carried out by solving a large sparse linear system: the Poisson equation. However, solving the Poisson equation is a computational and memory intensive task which makes it not suitable for real-time image editing. A new matrix decomposition graphics processing unit (GPU) solver (MDGS) is proposed to settle the problem. A matrix decomposition method is used to distribute the work among GPU threads, so that MDGS will take full advantage of the computing power of current GPUs. Additionally, MDGS is a hybrid solver (combines both the direct and iterative techniques) and has two-level architecture. These enable MDGS to generate identical solutions with those of the common Poisson methods and achieve high convergence rate in most cases. This approach is advantageous in terms of parallelizability, enabling real-time image processing, low memory-taken and extensive applications.

Specialized Computer Systems for Environment Visualization

NASA Astrophysics Data System (ADS)

Al-Oraiqat, Anas M.; Bashkov, Evgeniy A.; Zori, Sergii A.

2018-06-01

The need for real time image generation of landscapes arises in various fields as part of tasks solved by virtual and augmented reality systems, as well as geographic information systems. Such systems provide opportunities for collecting, storing, analyzing and graphically visualizing geographic data. Algorithmic and hardware software tools for increasing the realism and efficiency of the environment visualization in 3D visualization systems are proposed. This paper discusses a modified path tracing algorithm with a two-level hierarchy of bounding volumes and finding intersections with Axis-Aligned Bounding Box. The proposed algorithm eliminates the branching and hence makes the algorithm more suitable to be implemented on the multi-threaded CPU and GPU. A modified ROAM algorithm is used to solve the qualitative visualization of reliefs' problems and landscapes. The algorithm is implemented on parallel systems—cluster and Compute Unified Device Architecture-networks. Results show that the implementation on MPI clusters is more efficient than Graphics Processing Unit/Graphics Processing Clusters and allows real-time synthesis. The organization and algorithms of the parallel GPU system for the 3D pseudo stereo image/video synthesis are proposed. With realizing possibility analysis on a parallel GPU-architecture of each stage, 3D pseudo stereo synthesis is performed. An experimental prototype of a specialized hardware-software system 3D pseudo stereo imaging and video was developed on the CPU/GPU. The experimental results show that the proposed adaptation of 3D pseudo stereo imaging to the architecture of GPU-systems is efficient. Also it accelerates the computational procedures of 3D pseudo-stereo synthesis for the anaglyph and anamorphic formats of the 3D stereo frame without performing optimization procedures. The acceleration is on average 11 and 54 times for test GPUs.

Fast Image Subtraction Using Multi-cores and GPUs

NASA Astrophysics Data System (ADS)

Hartung, Steven; Shukla, H.

2013-01-01

Many important image processing techniques in astronomy require a massive number of computations per pixel. Among them is an image differencing technique known as Optimal Image Subtraction (OIS), which is very useful for detecting and characterizing transient phenomena. Like many image processing routines, OIS computations increase proportionally with the number of pixels being processed, and the number of pixels in need of processing is increasing rapidly. Utilizing many-core graphical processing unit (GPU) technology in a hybrid conjunction with multi-core CPU and computer clustering technologies, this work presents a new astronomy image processing pipeline architecture. The chosen OIS implementation focuses on the 2nd order spatially-varying kernel with the Dirac delta function basis, a powerful image differencing method that has seen limited deployment in part because of the heavy computational burden. This tool can process standard image calibration and OIS differencing in a fashion that is scalable with the increasing data volume. It employs several parallel processing technologies in a hierarchical fashion in order to best utilize each of their strengths. The Linux/Unix based application can operate on a single computer, or on an MPI configured cluster, with or without GPU hardware. With GPU hardware available, even low-cost commercial video cards, the OIS convolution and subtraction times for large images can be accelerated by up to three orders of magnitude.

A Biological-Plausable Architecture for Shape Recognition

DTIC Science & Technology

2006-06-30

between curves. Information Processing Letters, 64, 1997. [4] Irving Biederman . Recognition-by-components: A theory of human image understanding...Psychological Review, 94(2):115–147, 1987 . 43 [5] C. Cadieu, M. Kouh, M. Riesenhuber, and T. Poggio. Shape representation in v4: Investi- gating position

Optimization of image processing algorithms on mobile platforms

NASA Astrophysics Data System (ADS)

Poudel, Pramod; Shirvaikar, Mukul

2011-03-01

This work presents a technique to optimize popular image processing algorithms on mobile platforms such as cell phones, net-books and personal digital assistants (PDAs). The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has a mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM and a DSP core supported by shared memory, is presented with implementation details. The target platform chosen is the popular OMAP 3530 processor for embedded media systems. It has an asymmetric dual-core architecture with an ARM Cortex-A8 and a TMS320C64x Digital Signal Processor (DSP). The development platform was the BeagleBoard with 256 MB of NAND RAM and 256 MB SDRAM memory. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template matching tasks such as face-recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core which runs a popular operating system such as Linux or Windows CE. However, the DSP is architecturally more efficient at handling DFT algorithms. The algorithms are tested on a variety of images and performance results are presented measuring the speedup obtained due to dual-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks, while the DSP addresses performance-hungry algorithms.

Toward a Low-Cost System for High-Throughput Image-Based Phenotyping of Root System Architecture

NASA Astrophysics Data System (ADS)

Davis, T. W.; Schneider, D. J.; Cheng, H.; Shaw, N.; Kochian, L. V.; Shaff, J. E.

2015-12-01

Root system architecture is being studied more closely for improved nutrient acquisition, stress tolerance and carbon sequestration by relating the genetic material that corresponds to preferential physical features. This information can help direct plant breeders in addressing the growing concerns regarding the global demand on crops and fossil fuels. To help support this incentive comes a need to make high-throughput image-based phenotyping of plant roots, at the individual plant scale, simpler and more affordable. Our goal is to create an affordable and portable product for simple image collection, processing and management that will extend root phenotyping to institutions with limited funding (e.g., in developing countries). Thus, a new integrated system has been developed using the Raspberry Pi single-board computer. Similar to other 3D-based imaging platforms, the system utilizes a stationary camera to photograph a rotating crop root system (e.g., rice, maize or sorghum) that is suspended either in a gel or on a mesh (for hydroponics). In contrast, the new design takes advantage of powerful open-source hardware and software to reduce the system costs, simplify the imaging process, and manage the large datasets produced by the high-resolution photographs. A newly designed graphical user interface (GUI) unifies the system controls (e.g., adjusting camera and motor settings and orchestrating the motor motion with image capture), making it easier to accommodate a variety of experiments. During each imaging session, integral metadata necessary for reproducing experiment results are collected (e.g., plant type and age, growing conditions and treatments, camera settings) using hierarchical data format files. These metadata are searchable within the GUI and can be selected and extracted for further analysis. The GUI also supports an image previewer that performs limited image processing (e.g., thresholding and cropping). Root skeletonization, 3D reconstruction and trait calculation (e.g., rooting depth, rooting angle, total volume of roots) is being developed in conjunction with this project.

Interactive Volume Exploration of Petascale Microscopy Data Streams Using a Visualization-Driven Virtual Memory Approach.

PubMed

Hadwiger, M; Beyer, J; Jeong, Won-Ki; Pfister, H

2012-12-01

This paper presents the first volume visualization system that scales to petascale volumes imaged as a continuous stream of high-resolution electron microscopy images. Our architecture scales to dense, anisotropic petascale volumes because it: (1) decouples construction of the 3D multi-resolution representation required for visualization from data acquisition, and (2) decouples sample access time during ray-casting from the size of the multi-resolution hierarchy. Our system is designed around a scalable multi-resolution virtual memory architecture that handles missing data naturally, does not pre-compute any 3D multi-resolution representation such as an octree, and can accept a constant stream of 2D image tiles from the microscopes. A novelty of our system design is that it is visualization-driven: we restrict most computations to the visible volume data. Leveraging the virtual memory architecture, missing data are detected during volume ray-casting as cache misses, which are propagated backwards for on-demand out-of-core processing. 3D blocks of volume data are only constructed from 2D microscope image tiles when they have actually been accessed during ray-casting. We extensively evaluate our system design choices with respect to scalability and performance, compare to previous best-of-breed systems, and illustrate the effectiveness of our system for real microscopy data from neuroscience.

The use of algorithmic behavioural transfer functions in parametric EO system performance models

NASA Astrophysics Data System (ADS)

Hickman, Duncan L.; Smith, Moira I.

2015-10-01

The use of mathematical models to predict the overall performance of an electro-optic (EO) system is well-established as a methodology and is used widely to support requirements definition, system design, and produce performance predictions. Traditionally these models have been based upon cascades of transfer functions based on established physical theory, such as the calculation of signal levels from radiometry equations, as well as the use of statistical models. However, the performance of an EO system is increasing being dominated by the on-board processing of the image data and this automated interpretation of image content is complex in nature and presents significant modelling challenges. Models and simulations of EO systems tend to either involve processing of image data as part of a performance simulation (image-flow) or else a series of mathematical functions that attempt to define the overall system characteristics (parametric). The former approach is generally more accurate but statistically and theoretically weak in terms of specific operational scenarios, and is also time consuming. The latter approach is generally faster but is unable to provide accurate predictions of a system's performance under operational conditions. An alternative and novel architecture is presented in this paper which combines the processing speed attributes of parametric models with the accuracy of image-flow representations in a statistically valid framework. An additional dimension needed to create an effective simulation is a robust software design whose architecture reflects the structure of the EO System and its interfaces. As such, the design of the simulator can be viewed as a software prototype of a new EO System or an abstraction of an existing design. This new approach has been used successfully to model a number of complex military systems and has been shown to combine improved performance estimation with speed of computation. Within the paper details of the approach and architecture are described in detail, and example results based on a practical application are then given which illustrate the performance benefits. Finally, conclusions are drawn and comments given regarding the benefits and uses of the new approach.

Dedicated hardware processor and corresponding system-on-chip design for real-time laser speckle imaging.

PubMed

Jiang, Chao; Zhang, Hongyan; Wang, Jia; Wang, Yaru; He, Heng; Liu, Rui; Zhou, Fangyuan; Deng, Jialiang; Li, Pengcheng; Luo, Qingming

2011-11-01

Laser speckle imaging (LSI) is a noninvasive and full-field optical imaging technique which produces two-dimensional blood flow maps of tissues from the raw laser speckle images captured by a CCD camera without scanning. We present a hardware-friendly algorithm for the real-time processing of laser speckle imaging. The algorithm is developed and optimized specifically for LSI processing in the field programmable gate array (FPGA). Based on this algorithm, we designed a dedicated hardware processor for real-time LSI in FPGA. The pipeline processing scheme and parallel computing architecture are introduced into the design of this LSI hardware processor. When the LSI hardware processor is implemented in the FPGA running at the maximum frequency of 130 MHz, up to 85 raw images with the resolution of 640×480 pixels can be processed per second. Meanwhile, we also present a system on chip (SOC) solution for LSI processing by integrating the CCD controller, memory controller, LSI hardware processor, and LCD display controller into a single FPGA chip. This SOC solution also can be used to produce an application specific integrated circuit for LSI processing.

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.

Automated detection scheme of architectural distortion in mammograms using adaptive Gabor filter

NASA Astrophysics Data System (ADS)

Yoshikawa, Ruriha; Teramoto, Atsushi; Matsubara, Tomoko; Fujita, Hiroshi

2013-03-01

Breast cancer is a serious health concern for all women. Computer-aided detection for mammography has been used for detecting mass and micro-calcification. However, there are challenges regarding the automated detection of the architectural distortion about the sensitivity. In this study, we propose a novel automated method for detecting architectural distortion. Our method consists of the analysis of the mammary gland structure, detection of the distorted region, and reduction of false positive results. We developed the adaptive Gabor filter for analyzing the mammary gland structure that decides filter parameters depending on the thickness of the gland structure. As for post-processing, healthy mammary glands that run from the nipple to the chest wall are eliminated by angle analysis. Moreover, background mammary glands are removed based on the intensity output image obtained from adaptive Gabor filter. The distorted region of the mammary gland is then detected as an initial candidate using a concentration index followed by binarization and labeling. False positives in the initial candidate are eliminated using 23 types of characteristic features and a support vector machine. In the experiments, we compared the automated detection results with interpretations by a radiologist using 50 cases (200 images) from the Digital Database of Screening Mammography (DDSM). As a result, true positive rate was 82.72%, and the number of false positive per image was 1.39. There results indicate that the proposed method may be useful for detecting architectural distortion in mammograms.

Connecting a cognitive architecture to robotic perception

NASA Astrophysics Data System (ADS)

Kurup, Unmesh; Lebiere, Christian; Stentz, Anthony; Hebert, Martial

2012-06-01

We present an integrated architecture in which perception and cognition interact and provide information to each other leading to improved performance in real-world situations. Our system integrates the Felzenswalb et. al. object-detection algorithm with the ACT-R cognitive architecture. The targeted task is to predict and classify pedestrian behavior in a checkpoint scenario, most specifically to discriminate between normal versus checkpoint-avoiding behavior. The Felzenswalb algorithm is a learning-based algorithm for detecting and localizing objects in images. ACT-R is a cognitive architecture that has been successfully used to model human cognition with a high degree of fidelity on tasks ranging from basic decision-making to the control of complex systems such as driving or air traffic control. The Felzenswalb algorithm detects pedestrians in the image and provides ACT-R a set of features based primarily on their locations. ACT-R uses its pattern-matching capabilities, specifically its partial-matching and blending mechanisms, to track objects across multiple images and classify their behavior based on the sequence of observed features. ACT-R also provides feedback to the Felzenswalb algorithm in the form of expected object locations that allow the algorithm to eliminate false-positives and improve its overall performance. This capability is an instance of the benefits pursued in developing a richer interaction between bottom-up perceptual processes and top-down goal-directed cognition. We trained the system on individual behaviors (only one person in the scene) and evaluated its performance across single and multiple behavior sets.

An image based information system - Architecture for correlating satellite and topological data bases

NASA Technical Reports Server (NTRS)

Bryant, N. A.; Zobrist, A. L.

1978-01-01

The paper describes the development of an image based information system and its use to process a Landsat thematic map showing land use or land cover in conjunction with a census tract polygon file to produce a tabulation of land use acreages per census tract. The system permits the efficient cross-tabulation of two or more geo-coded data sets, thereby setting the stage for the practical implementation of models of diffusion processes or cellular transformation. Characteristics of geographic information systems are considered, and functional requirements, such as data management, geocoding, image data management, and data analysis are discussed. The system is described, and the potentialities of its use are examined.

Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

PubMed

Mori, Shinichiro

2017-08-01

To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising. Setup images of prostate cancer patients were acquired with two oblique X-ray fluoroscopic units. Two types of residual network were designed: a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN). We changed the convolutional kernel size and number of convolutional layers for both networks, and the number of pooling and upsampling layers for rCAE. The ground-truth image was applied to the contrast-limited adaptive histogram equalization (CLAHE) method of image processing. Network models were trained to keep the quality of the output image close to that of the ground-truth image from the input image without image processing. For image denoising evaluation, noisy input images were used for the training. More than 6 convolutional layers with convolutional kernels >5×5 improved image quality. However, this did not allow real-time imaging. After applying a pair of pooling and upsampling layers to both networks, rCAEs with >3 convolutions each and rCNNs with >12 convolutions with a pair of pooling and upsampling layers achieved real-time processing at 30 frames per second (fps) with acceptable image quality. Use of our suggested network achieved real-time image processing for contrast enhancement and image denoising by the use of a conventional modern personal computer. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Architecture of the parallel hierarchical network for fast image recognition

NASA Astrophysics Data System (ADS)

Timchenko, Leonid; Wójcik, Waldemar; Kokriatskaia, Natalia; Kutaev, Yuriy; Ivasyuk, Igor; Kotyra, Andrzej; Smailova, Saule

2016-09-01

Multistage integration of visual information in the brain allows humans to respond quickly to most significant stimuli while maintaining their ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing includes main types of cortical multistage convergence. The input images are mapped into a flexible hierarchy that reflects complexity of image data. Procedures of the temporal image decomposition and hierarchy formation are described in mathematical expressions. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image that encapsulates a structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a quick response of the system. The result is presented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match. With regard to the forecasting method, its idea lies in the following. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the parallel-hierarchical network.

Low-level processing for real-time image analysis

NASA Technical Reports Server (NTRS)

Eskenazi, R.; Wilf, J. M.

1979-01-01

A system that detects object outlines in television images in real time is described. A high-speed pipeline processor transforms the raw image into an edge map and a microprocessor, which is integrated into the system, clusters the edges, and represents them as chain codes. Image statistics, useful for higher level tasks such as pattern recognition, are computed by the microprocessor. Peak intensity and peak gradient values are extracted within a programmable window and are used for iris and focus control. The algorithms implemented in hardware and the pipeline processor architecture are described. The strategy for partitioning functions in the pipeline was chosen to make the implementation modular. The microprocessor interface allows flexible and adaptive control of the feature extraction process. The software algorithms for clustering edge segments, creating chain codes, and computing image statistics are also discussed. A strategy for real time image analysis that uses this system is given.

Pre-Hardware Optimization and Implementation Of Fast Optics Closed Control Loop Algorithms

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Lyon, Richard G.; Herman, Jay R.; Abuhassan, Nader

2004-01-01

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent - the Fast Fourier Transform (FFT). The FFT is particularly useful in two-dimensional (2-D) image processing (FFT2) within optical systems control. However, timing constraints of a fast optics closed control loop would require a supercomputer to run the software implementation of the FFT2 and its inverse, as well as other image processing representative algorithm, such as numerical image folding and fringe feature extraction. A laboratory supercomputer is not always available even for ground operations and is not feasible for a night project. However, the computationally intensive algorithms still warrant alternative implementation using reconfigurable computing technologies (RC) such as Digital Signal Processors (DSP) and Field Programmable Gate Arrays (FPGA), which provide low cost compact super-computing capabilities. We present a new RC hardware implementation and utilization architecture that significantly reduces the computational complexity of a few basic image-processing algorithm, such as FFT2, image folding and phase diversity for the NASA Solar Viewing Interferometer Prototype (SVIP) using a cluster of DSPs and FPGAs. The DSP cluster utilization architecture also assures avoidance of a single point of failure, while using commercially available hardware. This, combined with the control algorithms pre-hardware optimization, or the first time allows construction of image-based 800 Hertz (Hz) optics closed control loops on-board a spacecraft, based on the SVIP ground instrument. That spacecraft is the proposed Earth Atmosphere Solar Occultation Imager (EASI) to study greenhouse gases CO2, C2H, H2O, O3, O2, N2O from Lagrange-2 point in space. This paper provides an advanced insight into a new type of science capabilities for future space exploration missions based on on-board image processing for control and for robotics missions using vision sensors. It presents a top-level description of technologies required for the design and construction of SVIP and EASI and to advance the spatial-spectral imaging and large-scale space interferometry science and engineering.

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.

Image-based 3D reconstruction and virtual environmental walk-through

NASA Astrophysics Data System (ADS)

Sun, Jifeng; Fang, Lixiong; Luo, Ying

2001-09-01

We present a 3D reconstruction method, which combines geometry-based modeling, image-based modeling and rendering techniques. The first component is an interactive geometry modeling method which recovery of the basic geometry of the photographed scene. The second component is model-based stereo algorithm. We discus the image processing problems and algorithms of walking through in virtual space, then designs and implement a high performance multi-thread wandering algorithm. The applications range from architectural planning and archaeological reconstruction to virtual environments and cinematic special effects.

Architectural design for a low cost FPGA-based traffic signal detection system in vehicles

NASA Astrophysics Data System (ADS)

López, Ignacio; Salvador, Rubén; Alarcón, Jaime; Moreno, Félix

2007-05-01

In this paper we propose an architecture for an embedded traffic signal detection system. Development of Advanced Driver Assistance Systems (ADAS) is one of the major trends of research in automotion nowadays. Examples of past and ongoing projects in the field are CHAMELEON ("Pre-Crash Application all around the vehicle" IST 1999-10108), PREVENT (Preventive and Active Safety Applications, FP6-507075, http://www.prevent-ip.org/) and AVRT in the US (Advanced Vision-Radar Threat Detection (AVRT): A Pre-Crash Detection and Active Safety System). It can be observed a major interest in systems for real-time analysis of complex driving scenarios, evaluating risk and anticipating collisions. The system will use a low cost CCD camera on the dashboard facing the road. The images will be processed by an Altera Cyclone family FPGA. The board does median and Sobel filtering of the incoming frames at PAL rate, and analyzes them for several categories of signals. The result is conveyed to the driver. The scarce resources provided by the hardware require an architecture developed for optimal use. The system will use a combination of neural networks and an adapted blackboard architecture. Several neural networks will be used in sequence for image analysis, by reconfiguring a single, generic hardware neural network in the FPGA. This generic network is optimized for speed, in order to admit several executions within the frame rate. The sequence will follow the execution cycle of the blackboard architecture. The global, blackboard architecture being developed and the hardware architecture for the generic, reconfigurable FPGA perceptron will be explained in this paper. The project is still at an early stage. However, some hardware implementation results are already available and will be offered in the paper.

Designing flexible engineering systems utilizing embedded architecture options

NASA Astrophysics Data System (ADS)

Pierce, Jeff G.

This dissertation develops and applies an integrated framework for embedding flexibility in an engineered system architecture. Systems are constantly faced with unpredictability in the operational environment, threats from competing systems, obsolescence of technology, and general uncertainty in future system demands. Current systems engineering and risk management practices have focused almost exclusively on mitigating or preventing the negative consequences of uncertainty. This research recognizes that high uncertainty also presents an opportunity to design systems that can flexibly respond to changing requirements and capture additional value throughout the design life. There does not exist however a formalized approach to designing appropriately flexible systems. This research develops a three stage integrated flexibility framework based on the concept of architecture options embedded in the system design. Stage One defines an eight step systems engineering process to identify candidate architecture options. This process encapsulates the operational uncertainty though scenario development, traces new functional requirements to the affected design variables, and clusters the variables most sensitive to change. The resulting clusters can generate insight into the most promising regions in the architecture to embed flexibility in the form of architecture options. Stage Two develops a quantitative option valuation technique, grounded in real options theory, which is able to value embedded architecture options that exhibit variable expiration behavior. Stage Three proposes a portfolio optimization algorithm, for both discrete and continuous options, to select the optimal subset of architecture options, subject to budget and risk constraints. Finally, the feasibility, extensibility and limitations of the framework are assessed by its application to a reconnaissance satellite system development problem. Detailed technical data, performance models, and cost estimates were compiled for the Tactical Imaging Constellation Architecture Study and leveraged to complete a realistic proof-of-concept.

The architecture of a video image processor for the space station

NASA Technical Reports Server (NTRS)

Yalamanchili, S.; Lee, D.; Fritze, K.; Carpenter, T.; Hoyme, K.; Murray, N.

1987-01-01

The architecture of a video image processor for space station applications is described. The architecture was derived from a study of the requirements of algorithms that are necessary to produce the desired functionality of many of these applications. Architectural options were selected based on a simulation of the execution of these algorithms on various architectural organizations. A great deal of emphasis was placed on the ability of the system to evolve and grow over the lifetime of the space station. The result is a hierarchical parallel architecture that is characterized by high level language programmability, modularity, extensibility and can meet the required performance goals.

Application of Astronomical Compositions in Small Architectural Forms

NASA Astrophysics Data System (ADS)

Haykazun, Ani

2016-12-01

The small architectural forms are an important part of the Armenian architecture. Their compositions are diverse including quadrihedral structures, cross-stones, monuments, gravestones, memorial stones, etc. From ancient times to the late middle ages, and up to themodern small architectural forms, there are many decorative elements of astronomical character. Among them, one can more often see stars, the sun, the moon, the sky, the planets, the sign of eternity and other symbolic decorative images, which play a major role in the formation of the artistic image of the architectural compositions. The analysis of application of astronomical compositions will help more comprehensively introduce the compositional peculiarities of the small architectural forms.

New readout integrated circuit using continuous time fixed pattern noise correction

NASA Astrophysics Data System (ADS)

Dupont, Bertrand; Chammings, G.; Rapellin, G.; Mandier, C.; Tchagaspanian, M.; Dupont, Benoit; Peizerat, A.; Yon, J. J.

2008-04-01

LETI has been involved in IRFPA development since 1978; the design department (LETI/DCIS) has focused its work on new ROIC architecture since many years. The trend is to integrate advanced functions into the CMOS design to achieve cost efficient sensors production. Thermal imaging market is today more and more demanding of systems with instant ON capability and low power consumption. The purpose of this paper is to present the latest developments of fixed pattern noise continuous time correction. Several architectures are proposed, some are based on hardwired digital processing and some are purely analog. Both are using scene based algorithms. Moreover a new method is proposed for simultaneous correction of pixel offsets and sensitivities. In this scope, a new architecture of readout integrated circuit has been implemented; this architecture is developed with 0.18μm CMOS technology. The specification and the application of the ROIC are discussed in details.

An open architecture for hybrid force-visual servo control of robotic manipulators in unstructured environments

NASA Astrophysics Data System (ADS)

Hassanzadeh, Iraj; Janabi-Sharifi, Farrokh

2005-12-01

In this paper, a new open architecture for visual servo control tasks is illustrated. A Puma-560 robotic manipulator is used to prove the concept. This design enables doing hybrid forcehisual servo control in an unstructured environment in different modes. Also, it can be controlled through Internet in teleoperation mode using a haptic device. Our proposed structure includes two major parts, hardware and software. In terms of hardware, it consists of a master (host) computer, a slave (target) computer, a Puma 560 manipulator, a CCD camera, a force sensor and a haptic device. There are five DAQ cards, interfacing Puma 560 and a slave computer. An open architecture package is developed using Matlab (R), Simulink (R) and XPC target toolbox. This package has the Hardware-In-the-Loop (HIL) property, i.e., enables one to readily implement different configurations of force, visual or hybrid control in real time. The implementation includes the following stages. First of all, retrofitting of puma was carried out. Then a modular joint controller for Puma 560 was realized using Simulink (R). Force sensor driver and force control implementation were written, using sjknction blocks of Simulink (R). Visual images were captured through Image Acquisition Toolbox of Matlab (R), and processed using Image Processing Toolbox. A haptic device interface was also written in Simulink (R). Thus, this setup could be readily reconfigured and accommodate any other robotic manipulator and/or other sensors without the trouble of the external issues relevant to the control, interface and software, while providing flexibility in components modification.

Using deep learning for content-based medical image retrieval

NASA Astrophysics Data System (ADS)

Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

2017-03-01

Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

Single-photon imaging in complementary metal oxide semiconductor processes

PubMed Central

Charbon, E.

2014-01-01

This paper describes the basics of single-photon counting in complementary metal oxide semiconductors, through single-photon avalanche diodes (SPADs), and the making of miniaturized pixels with photon-counting capability based on SPADs. Some applications, which may take advantage of SPAD image sensors, are outlined, such as fluorescence-based microscopy, three-dimensional time-of-flight imaging and biomedical imaging, to name just a few. The paper focuses on architectures that are best suited to those applications and the trade-offs they generate. In this context, architectures are described that efficiently collect the output of single pixels when designed in large arrays. Off-chip readout circuit requirements are described for a variety of applications in physics, medicine and the life sciences. Owing to the dynamic nature of SPADs, designs featuring a large number of SPADs require careful analysis of the target application for an optimal use of silicon real estate and of limited readout bandwidth. The paper also describes the main trade-offs involved in architecting such chips and the solutions adopted with focus on scalability and miniaturization. PMID:24567470

Augmenting cognitive architectures to support diagrammatic imagination.

PubMed

Chandrasekaran, Balakrishnan; Banerjee, Bonny; Kurup, Unmesh; Lele, Omkar

2011-10-01

Diagrams are a form of spatial representation that supports reasoning and problem solving. Even when diagrams are external, not to mention when there are no external representations, problem solving often calls for internal representations, that is, representations in cognition, of diagrammatic elements and internal perceptions on them. General cognitive architectures--Soar and ACT-R, to name the most prominent--do not have representations and operations to support diagrammatic reasoning. In this article, we examine some requirements for such internal representations and processes in cognitive architectures. We discuss the degree to which DRS, our earlier proposal for such an internal representation for diagrams, meets these requirements. In DRS, the diagrams are not raw images, but a composition of objects that can be individuated and thus symbolized, while, unlike traditional symbols, the referent of the symbol is an object that retains its perceptual essence, namely, its spatiality. This duality provides a way to resolve what anti-imagists thought was a contradiction in mental imagery: the compositionality of mental images that seemed to be unique to symbol systems, and their support of a perceptual experience of images and some types of perception on them. We briefly review the use of DRS to augment Soar and ACT-R with a diagrammatic representation component. We identify issues for further research. Copyright © 2011 Cognitive Science Society, Inc.

Assessment of the radiofrequency ablation dynamics of esophageal tissue with optical coherence tomography

NASA Astrophysics Data System (ADS)

Lee, Hsiang-Chieh; Ahsen, Osman O.; Liu, Jonathan J.; Tsai, Tsung-Han; Huang, Qin; Mashimo, Hiroshi; Fujimoto, James G.

2017-07-01

Radiofrequency ablation (RFA) is widely used for the eradication of dysplasia and the treatment of early stage esophageal carcinoma in patients with Barrett's esophagus (BE). However, there are several factors, such as variation of BE epithelium (EP) thickness among individual patients and varying RFA catheter-tissue contact, which may compromise RFA efficacy. We used a high-speed optical coherence tomography (OCT) system to identify and monitor changes in the esophageal tissue architecture from RFA. Two different OCT imaging/RFA application protocols were performed using an ex vivo swine esophagus model: (1) post-RFA volumetric OCT imaging for quantitative analysis of the coagulum formation using RFA applications with different energy settings, and (2) M-mode OCT imaging for monitoring the dynamics of tissue architectural changes in real time during RFA application. Post-RFA volumetric OCT measurements showed an increase in the coagulum thickness with respect to the increasing RFA energies. Using a subset of the specimens, OCT measurements of coagulum and coagulum + residual EP thickness were shown to agree with histology, which accounted for specimen shrinkage during histological processing. In addition, we demonstrated the feasibility of OCT for real-time visualization of the architectural changes during RFA application with different energy settings. Results suggest feasibility of using OCT for RFA treatment planning and guidance.

Systems autonomy

NASA Technical Reports Server (NTRS)

Lum, Henry, Jr.

1988-01-01

Information on systems autonomy is given in viewgraph form. Information is given on space systems integration, intelligent autonomous systems, automated systems for in-flight mission operations, the Systems Autonomy Demonstration Project on the Space Station Thermal Control System, the architecture of an autonomous intelligent system, artificial intelligence research issues, machine learning, and real-time image processing.

A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation

NASA Astrophysics Data System (ADS)

Cruz-Roa, Angel; Arevalo, John; Basavanhally, Ajay; Madabhushi, Anant; González, Fabio

2015-01-01

Learning data representations directly from the data itself is an approach that has shown great success in different pattern recognition problems, outperforming state-of-the-art feature extraction schemes for different tasks in computer vision, speech recognition and natural language processing. Representation learning applies unsupervised and supervised machine learning methods to large amounts of data to find building-blocks that better represent the information in it. Digitized histopathology images represents a very good testbed for representation learning since it involves large amounts of high complex, visual data. This paper presents a comparative evaluation of different supervised and unsupervised representation learning architectures to specifically address open questions on what type of learning architectures (deep or shallow), type of learning (unsupervised or supervised) is optimal. In this paper we limit ourselves to addressing these questions in the context of distinguishing between anaplastic and non-anaplastic medulloblastomas from routine haematoxylin and eosin stained images. The unsupervised approaches evaluated were sparse autoencoders and topographic reconstruct independent component analysis, and the supervised approach was convolutional neural networks. Experimental results show that shallow architectures with more neurons are better than deeper architectures without taking into account local space invariances and that topographic constraints provide useful invariant features in scale and rotations for efficient tumor differentiation.

Sensor-based architecture for medical imaging workflow analysis.

PubMed

Silva, Luís A Bastião; Campos, Samuel; Costa, Carlos; Oliveira, José Luis

2014-08-01

The growing use of computer systems in medical institutions has been generating a tremendous quantity of data. While these data have a critical role in assisting physicians in the clinical practice, the information that can be extracted goes far beyond this utilization. This article proposes a platform capable of assembling multiple data sources within a medical imaging laboratory, through a network of intelligent sensors. The proposed integration framework follows a SOA hybrid architecture based on an information sensor network, capable of collecting information from several sources in medical imaging laboratories. Currently, the system supports three types of sensors: DICOM repository meta-data, network workflows and examination reports. Each sensor is responsible for converting unstructured information from data sources into a common format that will then be semantically indexed in the framework engine. The platform was deployed in the Cardiology department of a central hospital, allowing identification of processes' characteristics and users' behaviours that were unknown before the utilization of this solution.

Investigating the Potential of Deep Neural Networks for Large-Scale Classification of Very High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Postadjian, T.; Le Bris, A.; Sahbi, H.; Mallet, C.

2017-05-01

Semantic classification is a core remote sensing task as it provides the fundamental input for land-cover map generation. The very recent literature has shown the superior performance of deep convolutional neural networks (DCNN) for many classification tasks including the automatic analysis of Very High Spatial Resolution (VHR) geospatial images. Most of the recent initiatives have focused on very high discrimination capacity combined with accurate object boundary retrieval. Therefore, current architectures are perfectly tailored for urban areas over restricted areas but not designed for large-scale purposes. This paper presents an end-to-end automatic processing chain, based on DCNNs, that aims at performing large-scale classification of VHR satellite images (here SPOT 6/7). Since this work assesses, through various experiments, the potential of DCNNs for country-scale VHR land-cover map generation, a simple yet effective architecture is proposed, efficiently discriminating the main classes of interest (namely buildings, roads, water, crops, vegetated areas) by exploiting existing VHR land-cover maps for training.

Modeling of biologically motivated self-learning equivalent-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for image fragments clustering and recognition

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2018-03-01

The biologically-motivated self-learning equivalence-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will be discussed. We shall consider these neural structures and their spatial-invariant equivalental models (SIEMs) based on proposed equivalent two-dimensional functions of image similarity and the corresponding matrix-matrix (or tensor) procedures using as basic operations of continuous logic and nonlinear processing. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalent weighing of input patterns. We show that these SL_EC_RMNSs have several advantages, such as the self-study and self-identification of features and signs of the similarity of fragments, ability to clustering and recognize of image fragments with best efficiency and strong mutual correlation. The proposed combined with learning-recognition clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively continuous logic and nonlinear processing algorithms and to k-average method or method the winner takes all (WTA). The experimental results confirmed that fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an images of different dimensions (a reference array) and fragments with diferent dimensions for clustering is carried out. The experiments, using the software environment Mathcad showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. The experimental results show that such models can be successfully used for auto- and hetero-associative recognition. Also they can be used to explain some mechanisms, known as "the reinforcementinhibition concept". Also we demonstrate a real model experiments, which confirm that the nonlinear processing by equivalent function allow to determine the neuron-winners and customize the weight matrix. At the end of the report, we will show how to use the obtained results and to propose new more efficient hardware architecture of SL_EC_RMNS based on matrix-tensor multipliers. Also we estimate the parameters and performance of such architectures.

Deformable Image Registration based on Similarity-Steered CNN Regression.

PubMed

Cao, Xiaohuan; Yang, Jianhua; Zhang, Jun; Nie, Dong; Kim, Min-Jeong; Wang, Qian; Shen, Dinggang

2017-09-01

Existing deformable registration methods require exhaustively iterative optimization, along with careful parameter tuning, to estimate the deformation field between images. Although some learning-based methods have been proposed for initiating deformation estimation, they are often template-specific and not flexible in practical use. In this paper, we propose a convolutional neural network (CNN) based regression model to directly learn the complex mapping from the input image pair (i.e., a pair of template and subject) to their corresponding deformation field. Specifically, our CNN architecture is designed in a patch-based manner to learn the complex mapping from the input patch pairs to their respective deformation field. First, the equalized active-points guided sampling strategy is introduced to facilitate accurate CNN model learning upon a limited image dataset. Then, the similarity-steered CNN architecture is designed, where we propose to add the auxiliary contextual cue, i.e., the similarity between input patches, to more directly guide the learning process. Experiments on different brain image datasets demonstrate promising registration performance based on our CNN model. Furthermore, it is found that the trained CNN model from one dataset can be successfully transferred to another dataset, although brain appearances across datasets are quite variable.

A Web-based telemedicine system for diabetic retinopathy screening using digital fundus photography.

PubMed

Wei, Jack C; Valentino, Daniel J; Bell, Douglas S; Baker, Richard S

2006-02-01

The purpose was to design and implement a Web-based telemedicine system for diabetic retinopathy screening using digital fundus cameras and to make the software publicly available through Open Source release. The process of retinal imaging and case reviewing was modeled to optimize workflow and implement use of computer system. The Web-based system was built on Java Servlet and Java Server Pages (JSP) technologies. Apache Tomcat was chosen as the JSP engine, while MySQL was used as the main database and Laboratory of Neuro Imaging (LONI) Image Storage Architecture, from the LONI-UCLA, as the platform for image storage. For security, all data transmissions were carried over encrypted Internet connections such as Secure Socket Layer (SSL) and HyperText Transfer Protocol over SSL (HTTPS). User logins were required and access to patient data was logged for auditing. The system was deployed at Hubert H. Humphrey Comprehensive Health Center and Martin Luther King/Drew Medical Center of Los Angeles County Department of Health Services. Within 4 months, 1500 images of more than 650 patients were taken at Humphrey's Eye Clinic and successfully transferred to King/Drew's Department of Ophthalmology. This study demonstrates an effective architecture for remote diabetic retinopathy screening.

USC orthogonal multiprocessor for image processing with neural networks

NASA Astrophysics Data System (ADS)

Hwang, Kai; Panda, Dhabaleswar K.; Haddadi, Navid

1990-07-01

This paper presents the architectural features and imaging applications of the Orthogonal MultiProcessor (OMP) system, which is under construction at the University of Southern California with research funding from NSF and assistance from several industrial partners. The prototype OMP is being built with 16 Intel i860 RISC microprocessors and 256 parallel memory modules using custom-designed spanning buses, which are 2-D interleaved and orthogonally accessed without conflicts. The 16-processor OMP prototype is targeted to achieve 430 MIPS and 600 Mflops, which have been verified by simulation experiments based on the design parameters used. The prototype OMP machine will be initially applied for image processing, computer vision, and neural network simulation applications. We summarize important vision and imaging algorithms that can be restructured with neural network models. These algorithms can efficiently run on the OMP hardware with linear speedup. The ultimate goal is to develop a high-performance Visual Computer (Viscom) for integrated low- and high-level image processing and vision tasks.

Advances of Molecular Imaging for Monitoring the Anatomical and Functional Architecture of the Olfactory System.

PubMed

Zhang, Xintong; Bi, Anyao; Gao, Quansheng; Zhang, Shuai; Huang, Kunzhu; Liu, Zhiguo; Gao, Tang; Zeng, Wenbin

2016-01-20

The olfactory system of organisms serves as a genetically and anatomically model for studying how sensory input can be translated into behavior output. Some neurologic diseases are considered to be related to olfactory disturbance, especially Alzheimer's disease, Parkinson's disease, multiple sclerosis, and so forth. However, it is still unclear how the olfactory system affects disease generation processes and olfaction delivery processes. Molecular imaging, a modern multidisciplinary technology, can provide valid tools for the early detection and characterization of diseases, evaluation of treatment, and study of biological processes in living subjects, since molecular imaging applies specific molecular probes as a novel approach to produce special data to study biological processes in cellular and subcellular levels. Recently, molecular imaging plays a key role in studying the activation of olfactory system, thus it could help to prevent or delay some diseases. Herein, we present a comprehensive review on the research progress of the imaging probes for visualizing olfactory system, which is classified on different imaging modalities, including PET, MRI, and optical imaging. Additionally, the probes' design, sensing mechanism, and biological application are discussed. Finally, we provide an outlook for future studies in this field.

Algorithm architecture co-design for ultra low-power image sensor

NASA Astrophysics Data System (ADS)

Laforest, T.; Dupret, A.; Verdant, A.; Lattard, D.; Villard, P.

2012-03-01

In a context of embedded video surveillance, stand alone leftbehind image sensors are used to detect events with high level of confidence, but also with a very low power consumption. Using a steady camera, motion detection algorithms based on background estimation to find regions in movement are simple to implement and computationally efficient. To reduce power consumption, the background is estimated using a down sampled image formed of macropixels. In order to extend the class of moving objects to be detected, we propose an original mixed mode architecture developed thanks to an algorithm architecture co-design methodology. This programmable architecture is composed of a vector of SIMD processors. A basic RISC architecture was optimized in order to implement motion detection algorithms with a dedicated set of 42 instructions. Definition of delta modulation as a calculation primitive has allowed to implement algorithms in a very compact way. Thereby, a 1920x1080@25fps CMOS image sensor performing integrated motion detection is proposed with a power estimation of 1.8 mW.

Distributed Computing Architecture for Image-Based Wavefront Sensing and 2 D FFTs

NASA Technical Reports Server (NTRS)

Smith, Jeffrey S.; Dean, Bruce H.; Haghani, Shadan

2006-01-01

Image-based wavefront sensing (WFS) provides significant advantages over interferometric-based wavefi-ont sensors such as optical design simplicity and stability. However, the image-based approach is computational intensive, and therefore, specialized high-performance computing architectures are required in applications utilizing the image-based approach. The development and testing of these high-performance computing architectures are essential to such missions as James Webb Space Telescope (JWST), Terrestial Planet Finder-Coronagraph (TPF-C and CorSpec), and Spherical Primary Optical Telescope (SPOT). The development of these specialized computing architectures require numerous two-dimensional Fourier Transforms, which necessitate an all-to-all communication when applied on a distributed computational architecture. Several solutions for distributed computing are presented with an emphasis on a 64 Node cluster of DSPs, multiple DSP FPGAs, and an application of low-diameter graph theory. Timing results and performance analysis will be presented. The solutions offered could be applied to other all-to-all communication and scientifically computationally complex problems.

Functional Magnetic Resonance Imaging and Pediatric Anxiety

ERIC Educational Resources Information Center

Pine, Daniel S.; Guyer, Amanda E.; Leibenluft, Ellen; Peterson, Bradley S.; Gerber, Andrew

2008-01-01

The use of functional magnetic resonance imaging in investigating pediatric anxiety disorders is studied. Functional magnetic resonance imaging can be utilized in demonstrating parallels between the neural architecture of difference in anxiety of humans and the neural architecture of attention-orienting behavior in nonhuman primates or rodents.…

Overview of the DART project

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

Berry, K.R.; Hansen, F.R.; Napolitano, L.M.

1992-01-01

DART (DSP Arrary for Reconfigurable Tasks) is a parallel architecture of two high-performance SDP (digital signal processing) chips with the flexibility to handle a wide range of real-time applications. Each of the 32-bit floating-point DSP processes in DART is programmable in a high-level languate ( C'' or Ada). We have added extensions to the real-time operating system used by DART in order to support parallel processor. The combination of high-level language programmability, a real-time operating system, and parallel processing support significantly reduces the development cost of application software for signal processing and control applications. We have demonstrated this capability bymore » using DART to reconstruct images in the prototype VIP (Video Imaging Projectile) groundstation.« less

Overview of the DART project

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

Berry, K.R.; Hansen, F.R.; Napolitano, L.M.

1992-01-01

DART (DSP Arrary for Reconfigurable Tasks) is a parallel architecture of two high-performance SDP (digital signal processing) chips with the flexibility to handle a wide range of real-time applications. Each of the 32-bit floating-point DSP processes in DART is programmable in a high-level languate (``C`` or Ada). We have added extensions to the real-time operating system used by DART in order to support parallel processor. The combination of high-level language programmability, a real-time operating system, and parallel processing support significantly reduces the development cost of application software for signal processing and control applications. We have demonstrated this capability by usingmore » DART to reconstruct images in the prototype VIP (Video Imaging Projectile) groundstation.« less

How to Build a Hybrid Neurofeedback Platform Combining EEG and fMRI

PubMed Central

Mano, Marsel; Lécuyer, Anatole; Bannier, Elise; Perronnet, Lorraine; Noorzadeh, Saman; Barillot, Christian

2017-01-01

Multimodal neurofeedback estimates brain activity using information acquired with more than one neurosignal measurement technology. In this paper we describe how to set up and use a hybrid platform based on simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), then we illustrate how to use it for conducting bimodal neurofeedback experiments. The paper is intended for those willing to build a multimodal neurofeedback system, to guide them through the different steps of the design, setup, and experimental applications, and help them choose a suitable hardware and software configuration. Furthermore, it reports practical information from bimodal neurofeedback experiments conducted in our lab. The platform presented here has a modular parallel processing architecture that promotes real-time signal processing performance and simple future addition and/or replacement of processing modules. Various unimodal and bimodal neurofeedback experiments conducted in our lab showed high performance and accuracy. Currently, the platform is able to provide neurofeedback based on electroencephalography and functional magnetic resonance imaging, but the architecture and the working principles described here are valid for any other combination of two or more real-time brain activity measurement technologies. PMID:28377691

SOI-CMOS Process for Monolithic, Radiation-Tolerant, Science-Grade Imagers

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

Williams, George; Lee, Adam

In Phase I, Voxtel worked with Jazz and Sandia to document and simulate the processes necessary to implement a DH-BSI SOI CMOS imaging process. The development is based upon mature SOI CMOS process at both fabs, with the addition of only a few custom processing steps for integration and electrical interconnection of the fully-depleted photodetectors. In Phase I, Voxtel also characterized the Sandia process, including the CMOS7 design rules, and we developed the outline of a process option that included a “BOX etch”, that will permit a “detector in handle” SOI CMOS process to be developed The process flows weremore » developed in cooperation with both Jazz and Sandia process engineers, along with detailed TCAD modeling and testing of the photodiode array architectures. In addition, Voxtel tested the radiation performance of the Jazz’s CA18HJ process, using standard and circular-enclosed transistors.« less

NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment.

PubMed

Mezgec, Simon; Koroušić Seljak, Barbara

2017-06-27

Automatic food image recognition systems are alleviating the process of food-intake estimation and dietary assessment. However, due to the nature of food images, their recognition is a particularly challenging task, which is why traditional approaches in the field have achieved a low classification accuracy. Deep neural networks have outperformed such solutions, and we present a novel approach to the problem of food and drink image detection and recognition that uses a newly-defined deep convolutional neural network architecture, called NutriNet. This architecture was tuned on a recognition dataset containing 225,953 512 × 512 pixel images of 520 different food and drink items from a broad spectrum of food groups, on which we achieved a classification accuracy of 86 . 72 % , along with an accuracy of 94 . 47 % on a detection dataset containing 130 , 517 images. We also performed a real-world test on a dataset of self-acquired images, combined with images from Parkinson's disease patients, all taken using a smartphone camera, achieving a top-five accuracy of 55 % , which is an encouraging result for real-world images. Additionally, we tested NutriNet on the University of Milano-Bicocca 2016 (UNIMIB2016) food image dataset, on which we improved upon the provided baseline recognition result. An online training component was implemented to continually fine-tune the food and drink recognition model on new images. The model is being used in practice as part of a mobile app for the dietary assessment of Parkinson's disease patients.

Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.

Web Image Retrieval Using Self-Organizing Feature Map.

ERIC Educational Resources Information Center

Wu, Qishi; Iyengar, S. Sitharama; Zhu, Mengxia

2001-01-01

Provides an overview of current image retrieval systems. Describes the architecture of the SOFM (Self Organizing Feature Maps) based image retrieval system, discussing the system architecture and features. Introduces the Kohonen model, and describes the implementation details of SOFM computation and its learning algorithm. Presents a test example…

Feasibility study on sensor data fusion for the CP-140 aircraft: fusion architecture analyses

NASA Astrophysics Data System (ADS)

Shahbazian, Elisa

1995-09-01

Loral Canada completed (May 1995) a Department of National Defense (DND) Chief of Research and Development (CRAD) contract, to study the feasibility of implementing a multi- sensor data fusion (MSDF) system onboard the CP-140 Aurora aircraft. This system is expected to fuse data from: (a) attributed measurement oriented sensors (ESM, IFF, etc.); (b) imaging sensors (FLIR, SAR, etc.); (c) tracking sensors (radar, acoustics, etc.); (d) data from remote platforms (data links); and (e) non-sensor data (intelligence reports, environmental data, visual sightings, encyclopedic data, etc.). Based on purely theoretical considerations a central-level fusion architecture will lead to a higher performance fusion system. However, there are a number of systems and fusion architecture issues involving fusion of such dissimilar data: (1) the currently existing sensors are not designed to provide the type of data required by a fusion system; (2) the different types (attribute, imaging, tracking, etc.) of data may require different degree of processing, before they can be used within a fusion system efficiently; (3) the data quality from different sensors, and more importantly from remote platforms via the data links must be taken into account before fusing; and (4) the non-sensor data may impose specific requirements on the fusion architecture (e.g. variable weight/priority for the data from different sensors). This paper presents the analyses performed for the selection of the fusion architecture for the enhanced sensor suite planned for the CP-140 aircraft in the context of the mission requirements and environmental conditions.

Flow measurements in sewers based on image analysis: automatic flow velocity algorithm.

PubMed

Jeanbourquin, D; Sage, D; Nguyen, L; Schaeli, B; Kayal, S; Barry, D A; Rossi, L

2011-01-01

Discharges of combined sewer overflows (CSOs) and stormwater are recognized as an important source of environmental contamination. However, the harsh sewer environment and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. An in situ system for sewer water flow monitoring based on video images was evaluated. Algorithms to determine water velocities were developed based on image-processing techniques. The image-based water velocity algorithm identifies surface features and measures their positions with respect to real world coordinates. A web-based user interface and a three-tier system architecture enable remote configuration of the cameras and the image-processing algorithms in order to calculate automatically flow velocity on-line. Results of investigations conducted in a CSO are presented. The system was found to measure reliably water velocities, thereby providing the means to understand particular hydraulic behaviors.

MWIR imaging spectrometer with digital time delay integration for remote sensing and characterization of solar system objects

NASA Astrophysics Data System (ADS)

Kendrick, Stephen E.; Harwit, Alex; Kaplan, Michael; Smythe, William D.

2007-09-01

An MWIR TDI (Time Delay and Integration) Imager and Spectrometer (MTIS) instrument for characterizing from orbit the moons of Jupiter and Saturn is proposed. Novel to this instrument is the planned implementation of a digital TDI detector array and an innovative imaging/spectroscopic architecture. Digital TDI enables a higher SNR for high spatial resolution surface mapping of Titan and Enceladus and for improved spectral discrimination and resolution at Europa. The MTIS imaging/spectroscopic architecture combines a high spatial resolution coarse wavelength resolution imaging spectrometer with a hyperspectral sensor to spectrally decompose a portion of the data adjacent to the data sampled in the imaging spectrometer. The MTIS instrument thus maps with high spatial resolution a planetary object while spectrally decomposing enough of the data that identification of the constituent materials is highly likely. Additionally, digital TDI systems have the ability to enable the rejection of radiation induced spikes in high radiation environments (Europa) and the ability to image in low light levels (Titan and Enceladus). The ability to image moving objects that might be missed utilizing a conventional TDI system is an added advantage and is particularly important for characterizing atmospheric effects and separating atmospheric and surface components. This can be accomplished with on-orbit processing or collecting and returning individual non co-added frames.

Network simulations of optical illusions

NASA Astrophysics Data System (ADS)

Shinbrot, Troy; Lazo, Miguel Vivar; Siu, Theo

We examine a dynamical network model of visual processing that reproduces several aspects of a well-known optical illusion, including subtle dependencies on curvature and scale. The model uses a genetic algorithm to construct the percept of an image, and we show that this percept evolves dynamically so as to produce the illusions reported. We find that the perceived illusions are hardwired into the model architecture and we propose that this approach may serve as an archetype to distinguish behaviors that are due to nature (i.e. a fixed network architecture) from those subject to nurture (that can be plastically altered through learning).

Alaska Synthetic Aperture Radar (SAR) Facility science data processing architecture

NASA Technical Reports Server (NTRS)

Hilland, Jeffrey E.; Bicknell, Thomas; Miller, Carol L.

1991-01-01

The paper describes the architecture of the Alaska SAR Facility (ASF) at Fairbanks, being developed to generate science data products for supporting research in sea ice motion, ice classification, sea-ice-ocean interaction, glacier behavior, ocean waves, and hydrological and geological study areas. Special attention is given to the individual substructures of the ASF: the Receiving Ground Station (RGS), the SAR Processor System, and the Interactive Image Analysis System. The SAR data will be linked to the RGS by the ESA ERS-1 and ERS-2, the Japanese ERS-1, and the Canadian Radarsat.

Real-time control system for adaptive resonator

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

Flath, L; An, J; Brase, J

2000-07-24

Sustained operation of high average power solid-state lasers currently requires an adaptive resonator to produce the optimal beam quality. We describe the architecture of a real-time adaptive control system for correcting intra-cavity aberrations in a heat capacity laser. Image data collected from a wavefront sensor are processed and used to control phase with a high-spatial-resolution deformable mirror. Our controller takes advantage of recent developments in low-cost, high-performance processor technology. A desktop-based computational engine and object-oriented software architecture replaces the high-cost rack-mount embedded computers of previous systems.

Fiber-optic hydrophone array for acoustic surveillance in the littoral

NASA Astrophysics Data System (ADS)

Hill, David; Nash, Phillip

2005-05-01

We describe a fibre-optic hydrophone array system architecture that can be tailored to meet the underwater acoustic surveillance requirements of the military, counter terrorist and customs authorities in protecting ports and harbours, offshore production facilities or coastal approaches. Physically the fibre-optic hydrophone array is in the form of a lightweight cable, enabling rapid deployment from a small vessel. Based upon an optical architecture of time and wavelength multiplexed interferometric hydrophones, the array is comprised of a series of hydrophone sub-arrays. Using multiple sub-arrays, extended perimeters many tens of kilometres in length can be monitored. Interrogated via a long (~50km) optical fibre data link, the acoustic date is processed using the latest open architecture sonar processing platform, ensuring that acoustic targets below, on and above the surface are detected, tracked and classified. Results obtained from an at sea trial of a 96-channel hydrophone array are given, showing the passive detection and tracking of a diver, small surface craft and big ocean going ships beyond the horizon. Furthermore, we describe how the OptaMarine fibre-optic hydrophone array fits into an integrated multi-layered approach to port and harbour security consisting of active sonar for diver detection and hull imaging, as well as thermal imaging and CCTV for surface monitoring. Finally, we briefly describe a complimentary land perimeter intruder detection system consisting of an array of fibre optic accelerometers.

High-Level Vision: Top-Down Processing in Neurally Inspired Architectures

DTIC Science & Technology

2008-02-01

shunting subsystem). Visual input from the lateral geniculate enters the visual buffer via the black arrow at the bottom. Processing subsystems used... lateral geniculate nucleus of the thalamus (LGNd), the superior colliculus of the midbrain, and cortical regions V1 through V4. Beyond early vision...resonance imaging FOA: focus of attention IMPER: IMagery and PERception model IS: information shunting system LGNd: dorsal lateral geniculate nucleus

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.

Details of the Collagen and Elastin Architecture in the Human Limbal Conjunctiva, Tenon's Capsule and Sclera Revealed by Two-Photon Excited Fluorescence Microscopy.

PubMed

Park, Choul Yong; Marando, Catherine M; Liao, Jason A; Lee, Jimmy K; Kwon, Jiwon; Chuck, Roy S

2016-10-01

To investigate the architecture and distribution of collagen and elastin in human limbal conjunctiva, Tenon's capsule, and sclera. The limbal conjunctiva, Tenon's capsule, and sclera of human donor corneal buttons were imaged with an inverted two-photon excited fluorescence microscope. No fixation process was necessary. The laser (Ti:sapphire) was tuned at 850 nm for two-photon excitation. Backscatter signals of second harmonic generation (SHG) and autofluorescence (AF) were collected through a 425/30-nm and a 525/45-nm emission filter, respectively. Multiple, consecutive, and overlapping (z-stack) images were acquired. Collagen signals were collected with SHG, whereas elastin signals were collected with AF. The size and density of collagen bundles varied widely depending on depth: increasing from conjunctiva to sclera. In superficial image planes, collagen bundles were <10 μm in width, in a loose, disorganized arrangement. In deeper image planes (episclera and superficial sclera), collagen bundles were thicker (near 100 μm in width) and densely packed. Comparatively, elastin fibers were thinner and sparse. The orientation of elastin fibers was independent of collagen fibers in superficial layers; but in deep sclera, elastin fibers wove through collagen interbundle gaps. At the limbus, both collagen and elastin fibers were relatively compact and were distributed perpendicular to the limbal annulus. Two-photon excited fluorescence microscopy has enabled us to understand in greater detail the collagen and elastin architecture of the human limbal conjunctiva, Tenon's capsule, and sclera.

Architecture for a 1-GHz Digital RADAR

NASA Technical Reports Server (NTRS)

Mallik, Udayan

2011-01-01

An architecture for a Direct RF-digitization Type Digital Mode RADAR was developed at GSFC in 2008. Two variations of a basic architecture were developed for use on RADAR imaging missions using aircraft and spacecraft. Both systems can operate with a pulse repetition rate up to 10 MHz with 8 received RF samples per pulse repetition interval, or at up to 19 kHz with 4K received RF samples per pulse repetition interval. The first design describes a computer architecture for a Continuous Mode RADAR transceiver with a real-time signal processing and display architecture. The architecture can operate at a high pulse repetition rate without interruption for an infinite amount of time. The second design describes a smaller and less costly burst mode RADAR that can transceive high pulse repetition rate RF signals without interruption for up to 37 seconds. The burst-mode RADAR was designed to operate on an off-line signal processing paradigm. The temporal distribution of RF samples acquired and reported to the RADAR processor remains uniform and free of distortion in both proposed architectures. The majority of the RADAR's electronics is implemented in digital CMOS (complementary metal oxide semiconductor), and analog circuits are restricted to signal amplification operations and analog to digital conversion. An implementation of the proposed systems will create a 1-GHz, Direct RF-digitization Type, L-Band Digital RADAR--the highest band achievable for Nyquist Rate, Direct RF-digitization Systems that do not implement an electronic IF downsample stage (after the receiver signal amplification stage), using commercially available off-the-shelf integrated circuits.

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.

Combining multi-layered bitmap files using network specific hardware

DOEpatents

DuBois, David H [Los Alamos, NM; DuBois, Andrew J [Santa Fe, NM; Davenport, Carolyn Connor [Los Alamos, NM

2012-02-28

Images and video can be produced by compositing or alpha blending a group of image layers or video layers. Increasing resolution or the number of layers results in increased computational demands. As such, the available computational resources limit the images and videos that can be produced. A computational architecture in which the image layers are packetized and streamed through processors can be easily scaled so to handle many image layers and high resolutions. The image layers are packetized to produce packet streams. The packets in the streams are received, placed in queues, and processed. For alpha blending, ingress queues receive the packetized image layers which are then z sorted and sent to egress queues. The egress queue packets are alpha blended to produce an output image or video.

Vision-based system for the control and measurement of wastewater flow rate in sewer systems.

PubMed

Nguyen, L S; Schaeli, B; Sage, D; Kayal, S; Jeanbourquin, D; Barry, D A; Rossi, L

2009-01-01

Combined sewer overflows and stormwater discharges represent an important source of contamination to the environment. However, the harsh environment inside sewers and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. In the following, we present and evaluate an in situ system for the monitoring of water flow in sewers based on video images. This paper focuses on the measurement of the water level based on image-processing techniques. The developed image-based water level algorithms identify the wall/water interface from sewer images and measure its position with respect to real world coordinates. A web-based user interface and a 3-tier system architecture enable the remote configuration of the cameras and the image-processing algorithms. Images acquired and processed by our system were found to reliably measure water levels and thereby to provide crucial information leading to better understand particular hydraulic behaviors. In terms of robustness and accuracy, the water level algorithm provided equal or better results compared to traditional water level probes in three different in situ configurations.

Image-Based Modeling Techniques for Architectural Heritage 3d Digitalization: Limits and Potentialities

NASA Astrophysics Data System (ADS)

Santagati, C.; Inzerillo, L.; Di Paola, F.

2013-07-01

3D reconstruction from images has undergone a revolution in the last few years. Computer vision techniques use photographs from data set collection to rapidly build detailed 3D models. The simultaneous applications of different algorithms (MVS), the different techniques of image matching, feature extracting and mesh optimization are inside an active field of research in computer vision. The results are promising: the obtained models are beginning to challenge the precision of laser-based reconstructions. Among all the possibilities we can mainly distinguish desktop and web-based packages. Those last ones offer the opportunity to exploit the power of cloud computing in order to carry out a semi-automatic data processing, thus allowing the user to fulfill other tasks on its computer; whereas desktop systems employ too much processing time and hard heavy approaches. Computer vision researchers have explored many applications to verify the visual accuracy of 3D model but the approaches to verify metric accuracy are few and no one is on Autodesk 123D Catch applied on Architectural Heritage Documentation. Our approach to this challenging problem is to compare the 3Dmodels by Autodesk 123D Catch and 3D models by terrestrial LIDAR considering different object size, from the detail (capitals, moldings, bases) to large scale buildings for practitioner purpose.

On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences

PubMed Central

Thiyagalingam, Jeyarajan; Goodman, Daniel; Schnabel, Julia A.; Trefethen, Anne; Grau, Vicente

2011-01-01

Images are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures. Towards this, GPU-specific implementations of image analysis algorithms are particularly promising. In this paper, we investigate the mapping of an enhanced motion estimation algorithm to novel GPU-specific architectures, the resulting challenges and benefits therein. Using a database of three-dimensional image sequences, we show that the mapping leads to substantial performance gains, up to a factor of 60, and can provide near-real-time experience. We also show how architectural peculiarities of these devices can be best exploited in the benefit of algorithms, most specifically for addressing the challenges related to their access patterns and different memory configurations. Finally, we evaluate the performance of the algorithm on three different GPU architectures and perform a comprehensive analysis of the results. PMID:21869880

Architecture of a high-performance surgical guidance system based on C-arm cone-beam CT: software platform for technical integration and clinical translation

NASA Astrophysics Data System (ADS)

Uneri, Ali; Schafer, Sebastian; Mirota, Daniel; Nithiananthan, Sajendra; Otake, Yoshito; Reaungamornrat, Sureerat; Yoo, Jongheun; Stayman, J. Webster; Reh, Douglas; Gallia, Gary L.; Khanna, A. Jay; Hager, Gregory; Taylor, Russell H.; Kleinszig, Gerhard; Siewerdsen, Jeffrey H.

2011-03-01

Intraoperative imaging modalities are becoming more prevalent in recent years, and the need for integration of these modalities with surgical guidance is rising, creating new possibilities as well as challenges. In the context of such emerging technologies and new clinical applications, a software architecture for cone-beam CT (CBCT) guided surgery has been developed with emphasis on binding open-source surgical navigation libraries and integrating intraoperative CBCT with novel, application-specific registration and guidance technologies. The architecture design is focused on accelerating translation of task-specific technical development in a wide range of applications, including orthopaedic, head-and-neck, and thoracic surgeries. The surgical guidance system is interfaced with a prototype mobile C-arm for high-quality CBCT and through a modular software architecture, integration of different tools and devices consistent with surgical workflow in each of these applications is realized. Specific modules are developed according to the surgical task, such as: 3D-3D rigid or deformable registration of preoperative images, surgical planning data, and up-to-date CBCT images; 3D-2D registration of planning and image data in real-time fluoroscopy and/or digitally reconstructed radiographs (DRRs); compatibility with infrared, electromagnetic, and video-based trackers used individually or in hybrid arrangements; augmented overlay of image and planning data in endoscopic or in-room video; real-time "virtual fluoroscopy" computed from GPU-accelerated DRRs; and multi-modality image display. The platform aims to minimize offline data processing by exposing quantitative tools that analyze and communicate factors of geometric precision. The system was translated to preclinical phantom and cadaver studies for assessment of fiducial (FRE) and target registration error (TRE) showing sub-mm accuracy in targeting and video overlay within intraoperative CBCT. The work culminates in the development of a CBCT guidance system (reported here for the first time) that leverages the technical developments in Carm CBCT and associated technologies for realizing a high-performance system for translation to clinical studies.

VIEW-Station software and its graphical user interface

NASA Astrophysics Data System (ADS)

Kawai, Tomoaki; Okazaki, Hiroshi; Tanaka, Koichiro; Tamura, Hideyuki

1992-04-01

VIEW-Station is a workstation-based image processing system which merges the state-of-the- art software environment of Unix with the computing power of a fast image processor. VIEW- Station has a hierarchical software architecture, which facilitates device independence when porting across various hardware configurations, and provides extensibility in the development of application systems. The core image computing language is V-Sugar. V-Sugar provides a set of image-processing datatypes and allows image processing algorithms to be simply expressed, using a functional notation. VIEW-Station provides a hardware independent window system extension called VIEW-Windows. In terms of GUI (Graphical User Interface) VIEW-Station has two notable aspects. One is to provide various types of GUI as visual environments for image processing execution. Three types of interpreters called (mu) V- Sugar, VS-Shell and VPL are provided. Users may choose whichever they prefer based on their experience and tasks. The other notable aspect is to provide facilities to create GUI for new applications on the VIEW-Station system. A set of widgets are available for construction of task-oriented GUI. A GUI builder called VIEW-Kid is developed for WYSIWYG interactive interface design.

Coherent X-ray diffraction imaging of nanoengineered polymeric capsules

NASA Astrophysics Data System (ADS)

Erokhina, S.; Pastorino, L.; Di Lisa, D.; Kiiamov, A. G.; Faizullina, A. R.; Tayurskii, D. A.; Iannotta, S.; Erokhin, V.

2017-10-01

For the first time, nanoengineered polymeric capsules and their architecture have been studied with coherent X-ray diffraction imaging technique. The use of coherent X-ray diffraction imaging technique allowed us to analyze the samples immersed in a liquid. We report about the significant difference between polymeric capsule architectures under dry and liquid conditions.

Server-based Approach to Web Visualization of Integrated Three-dimensional Brain Imaging Data

PubMed Central

Poliakov, Andrew V.; Albright, Evan; Hinshaw, Kevin P.; Corina, David P.; Ojemann, George; Martin, Richard F.; Brinkley, James F.

2005-01-01

The authors describe a client-server approach to three-dimensional (3-D) visualization of neuroimaging data, which enables researchers to visualize, manipulate, and analyze large brain imaging datasets over the Internet. All computationally intensive tasks are done by a graphics server that loads and processes image volumes and 3-D models, renders 3-D scenes, and sends the renderings back to the client. The authors discuss the system architecture and implementation and give several examples of client applications that allow visualization and analysis of integrated language map data from single and multiple patients. PMID:15561787

Three-dimensional Biomimetic Technology: Novel Biorubber Creates Defined Micro- and Macro-scale Architectures in Collagen Hydrogels

PubMed Central

Rodriguez-Rivera, Veronica; Weidner, John W.; Yost, Michael J.

2016-01-01

Tissue scaffolds play a crucial role in the tissue regeneration process. The ideal scaffold must fulfill several requirements such as having proper composition, targeted modulus, and well-defined architectural features. Biomaterials that recapitulate the intrinsic architecture of in vivo tissue are vital for studying diseases as well as to facilitate the regeneration of lost and malformed soft tissue. A novel biofabrication technique was developed which combines state of the art imaging, three-dimensional (3D) printing, and selective enzymatic activity to create a new generation of biomaterials for research and clinical application. The developed material, Bovine Serum Albumin rubber, is reaction injected into a mold that upholds specific geometrical features. This sacrificial material allows the adequate transfer of architectural features to a natural scaffold material. The prototype consists of a 3D collagen scaffold with 4 and 3 mm channels that represent a branched architecture. This paper emphasizes the use of this biofabrication technique for the generation of natural constructs. This protocol utilizes a computer-aided software (CAD) to manufacture a solid mold which will be reaction injected with BSA rubber followed by the enzymatic digestion of the rubber, leaving its architectural features within the scaffold material. PMID:26967145

Three-dimensional Biomimetic Technology: Novel Biorubber Creates Defined Micro- and Macro-scale Architectures in Collagen Hydrogels.

PubMed

Rodriguez-Rivera, Veronica; Weidner, John W; Yost, Michael J

2016-02-12

Tissue scaffolds play a crucial role in the tissue regeneration process. The ideal scaffold must fulfill several requirements such as having proper composition, targeted modulus, and well-defined architectural features. Biomaterials that recapitulate the intrinsic architecture of in vivo tissue are vital for studying diseases as well as to facilitate the regeneration of lost and malformed soft tissue. A novel biofabrication technique was developed which combines state of the art imaging, three-dimensional (3D) printing, and selective enzymatic activity to create a new generation of biomaterials for research and clinical application. The developed material, Bovine Serum Albumin rubber, is reaction injected into a mold that upholds specific geometrical features. This sacrificial material allows the adequate transfer of architectural features to a natural scaffold material. The prototype consists of a 3D collagen scaffold with 4 and 3 mm channels that represent a branched architecture. This paper emphasizes the use of this biofabrication technique for the generation of natural constructs. This protocol utilizes a computer-aided software (CAD) to manufacture a solid mold which will be reaction injected with BSA rubber followed by the enzymatic digestion of the rubber, leaving its architectural features within the scaffold material.

Recognition of degraded handwritten digits using dynamic Bayesian networks

NASA Astrophysics Data System (ADS)

Likforman-Sulem, Laurence; Sigelle, Marc

2007-01-01

We investigate in this paper the application of dynamic Bayesian networks (DBNs) to the recognition of handwritten digits. The main idea is to couple two separate HMMs into various architectures. First, a vertical HMM and a horizontal HMM are built observing the evolving streams of image columns and image rows respectively. Then, two coupled architectures are proposed to model interactions between these two streams and to capture the 2D nature of character images. Experiments performed on the MNIST handwritten digit database show that coupled architectures yield better recognition performances than non-coupled ones. Additional experiments conducted on artificially degraded (broken) characters demonstrate that coupled architectures better cope with such degradation than non coupled ones and than discriminative methods such as SVMs.

MTI science, data products, and ground-data processing overview

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Atkins, William H.; Balick, Lee K.; Borel, Christoph C.; Clodius, William B.; Christensen, R. Wynn; Davis, Anthony B.; Echohawk, J. C.; Galbraith, Amy E.; Hirsch, Karen L.; Krone, James B.; Little, Cynthia K.; McLachlan, Peter M.; Morrison, Aaron; Pollock, Kimberly A.; Pope, Paul A.; Novak, Curtis; Ramsey, Keri A.; Riddle, Emily E.; Rohde, Charles A.; Roussel-Dupre, Diane C.; Smith, Barham W.; Smith, Kathy; Starkovich, Kim; Theiler, James P.; Weber, Paul G.

2001-08-01

The mission of the Multispectral Thermal Imager (MTI) satellite is to demonstrate the efficacy of highly accurate multispectral imaging for passive characterization of urban and industrial areas, as well as sites of environmental interest. The satellite makes top-of-atmosphere radiance measurements that are subsequently processed into estimates of surface properties such as vegetation health, temperatures, material composition and others. The MTI satellite also provides simultaneous data for atmospheric characterization at high spatial resolution. To utilize these data the MTI science program has several coordinated components, including modeling, comprehensive ground-truth measurements, image acquisition planning, data processing and data interpretation and analysis. Algorithms have been developed to retrieve a multitude of physical quantities and these algorithms are integrated in a processing pipeline architecture that emphasizes automation, flexibility and programmability. In addition, the MTI science team has produced detailed site, system and atmospheric models to aid in system design and data analysis. This paper provides an overview of the MTI research objectives, data products and ground data processing.

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.

Ground Optical Signal Processing Architecture for Contributing SSA Space Based Sensor Data

NASA Astrophysics Data System (ADS)

Koblick, D.; Klug, M.; Goldsmith, A.; Flewelling, B.; Jah, M.; Shanks, J.; Piña, R.

2014-09-01

The main objective of the DARPA program Orbit Outlook (O^2) is to improve the metric tracking and detection performance of the Space Situational Network (SSN) by adding a diverse low-cost network of contributing sensors to the Space Situational Awareness (SSA) mission. In order to accomplish this objective, not only must a sensor be in constant communication with a planning and scheduling system to process tasking requests, there must be an underlying framework to provide useful data products, such as angles only measurements. Existing optical signal processing implementations such as the Optical Processing Architecture at Lincoln (OPAL) are capable of converting mission data collections to angles only observations, but may be difficult for many users to obtain, support, and customize for low-cost missions and demonstration programs. The Ground Optical Signal Processing Architecture (GOSPA) will ingest raw imagery and telemetry data from a space based electro optical sensor and perform a background removal process to remove anomalous pixels, interpolate over bad pixels, and dominant temporal noise. After background removal, the streak end points and target centroids are located using a corner detection algorithm developed by Air Force Research Laboratory. These identified streak locations are then fused with the corresponding spacecraft telemetry data to determine the Right Ascension and Declination measurements with respect to time. To demonstrate the performance of GOSPA, non-rate tracking collections against a satellite in Geosynchronous Orbit are simulated from a visible optical imaging sensor in a polar Low Earth Orbit. Stars, noise and bad pixels are added to the simulated images based on look angles and sensor parameters. These collections are run through the GOSPA framework to provide angles- only measurements to the Air Force Research Laboratory Constrained Admissible Region Multiple Hypothesis Filter (CAR-MHF) in which an Initial Orbit Determination is performed and compared to truth data.

Hardware implementation of hierarchical volume subdivision-based elastic registration.

PubMed

Dandekar, Omkar; Walimbe, Vivek; Shekhar, Raj

2006-01-01

Real-time, elastic and fully automated 3D image registration is critical to the efficiency and effectiveness of many image-guided diagnostic and treatment procedures relying on multimodality image fusion or serial image comparison. True, real-time performance will make many 3D image registration-based techniques clinically viable. Hierarchical volume subdivision-based image registration techniques are inherently faster than most elastic registration techniques, e.g. free-form deformation (FFD)-based techniques, and are more amenable for achieving real-time performance through hardware acceleration. Our group has previously reported an FPGA-based architecture for accelerating FFD-based image registration. In this article we show how our existing architecture can be adapted to support hierarchical volume subdivision-based image registration. A proof-of-concept implementation of the architecture achieved speedups of 100 for elastic registration against an optimized software implementation on a 3.2 GHz Pentium III Xeon workstation. Due to inherent parallel nature of the hierarchical volume subdivision-based image registration techniques further speedup can be achieved by using several computing modules in parallel.

Intelligent robotic tracker

NASA Technical Reports Server (NTRS)

Otaguro, W. S.; Kesler, L. O.; Land, K. C.; Rhoades, D. E.

1987-01-01

An intelligent tracker capable of robotic applications requiring guidance and control of platforms, robotic arms, and end effectors has been developed. This packaged system capable of supervised autonomous robotic functions is partitioned into a multiple processor/parallel processing configuration. The system currently interfaces to cameras but has the capability to also use three-dimensional inputs from scanning laser rangers. The inputs are fed into an image processing and tracking section where the camera inputs are conditioned for the multiple tracker algorithms. An executive section monitors the image processing and tracker outputs and performs all the control and decision processes. The present architecture of the system is presented with discussion of its evolutionary growth for space applications. An autonomous rendezvous demonstration of this system was performed last year. More realistic demonstrations in planning are discussed.

Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks

NASA Astrophysics Data System (ADS)

Roth, Holger; Oda, Masahiro; Shimizu, Natsuki; Oda, Hirohisa; Hayashi, Yuichiro; Kitasaka, Takayuki; Fujiwara, Michitaka; Misawa, Kazunari; Mori, Kensaku

2018-03-01

Pancreas segmentation in computed tomography imaging has been historically difficult for automated methods because of the large shape and size variations between patients. In this work, we describe a custom-build 3D fully convolutional network (FCN) that can process a 3D image including the whole pancreas and produce an automatic segmentation. We investigate two variations of the 3D FCN architecture; one with concatenation and one with summation skip connections to the decoder part of the network. We evaluate our methods on a dataset from a clinical trial with gastric cancer patients, including 147 contrast enhanced abdominal CT scans acquired in the portal venous phase. Using the summation architecture, we achieve an average Dice score of 89.7 +/- 3.8 (range [79.8, 94.8])% in testing, achieving the new state-of-the-art performance in pancreas segmentation on this dataset.

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

Mendonsa, D; Nekoogar, F; Martz, H

This document describes the functionality of every component in the DHS/IDD archival and storage hardware system shown in Fig. 1. The document describes steps by step process of image data being received at LLNL then being processed and made available to authorized personnel and collaborators. Throughout this document references will be made to one of two figures, Fig. 1 describing the elements of the architecture and the Fig. 2 describing the workflow and how the project utilizes the available hardware.

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.

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms

PubMed Central

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts’ Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2–100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms. PMID:28487831

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

PubMed

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

A customizable system for real-time image processing using the Blackfin DSProcessor and the MicroC/OS-II real-time kernel

NASA Astrophysics Data System (ADS)

Coffey, Stephen; Connell, Joseph

2005-06-01

This paper presents a development platform for real-time image processing based on the ADSP-BF533 Blackfin processor and the MicroC/OS-II real-time operating system (RTOS). MicroC/OS-II is a completely portable, ROMable, pre-emptive, real-time kernel. The Blackfin Digital Signal Processors (DSPs), incorporating the Analog Devices/Intel Micro Signal Architecture (MSA), are a broad family of 16-bit fixed-point products with a dual Multiply Accumulate (MAC) core. In addition, they have a rich instruction set with variable instruction length and both DSP and MCU functionality thus making them ideal for media based applications. Using the MicroC/OS-II for task scheduling and management, the proposed system can capture and process raw RGB data from any standard 8-bit greyscale image sensor in soft real-time and then display the processed result using a simple PC graphical user interface (GUI). Additionally, the GUI allows configuration of the image capture rate and the system and core DSP clock rates thereby allowing connectivity to a selection of image sensors and memory devices. The GUI also allows selection from a set of image processing algorithms based in the embedded operating system.

A hardware architecture for real-time shadow removal in high-contrast video

NASA Astrophysics Data System (ADS)

Verdugo, Pablo; Pezoa, Jorge E.; Figueroa, Miguel

2017-09-01

Broadcasting an outdoor sports event at daytime is a challenging task due to the high contrast that exists between areas in the shadow and light conditions within the same scene. Commercial cameras typically do not handle the high dynamic range of such scenes in a proper manner, resulting in broadcast streams with very little shadow detail. We propose a hardware architecture for real-time shadow removal in high-resolution video, which reduces the shadow effect and simultaneously improves shadow details. The algorithm operates only on the shadow portions of each video frame, thus improving the results and producing more realistic images than algorithms that operate on the entire frame, such as simplified Retinex and histogram shifting. The architecture receives an input in the RGB color space, transforms it into the YIQ space, and uses color information from both spaces to produce a mask of the shadow areas present in the image. The mask is then filtered using a connected components algorithm to eliminate false positives and negatives. The hardware uses pixel information at the edges of the mask to estimate the illumination ratio between light and shadow in the image, which is then used to correct the shadow area. Our prototype implementation simultaneously processes up to 7 video streams of 1920×1080 pixels at 60 frames per second on a Xilinx Kintex-7 XC7K325T FPGA.

Fast maximum intensity projections of large medical data sets by exploiting hierarchical memory architectures.

PubMed

Kiefer, Gundolf; Lehmann, Helko; Weese, Jürgen

2006-04-01

Maximum intensity projections (MIPs) are an important visualization technique for angiographic data sets. Efficient data inspection requires frame rates of at least five frames per second at preserved image quality. Despite the advances in computer technology, this task remains a challenge. On the one hand, the sizes of computed tomography and magnetic resonance images are increasing rapidly. On the other hand, rendering algorithms do not automatically benefit from the advances in processor technology, especially for large data sets. This is due to the faster evolving processing power and the slower evolving memory access speed, which is bridged by hierarchical cache memory architectures. In this paper, we investigate memory access optimization methods and use them for generating MIPs on general-purpose central processing units (CPUs) and graphics processing units (GPUs), respectively. These methods can work on any level of the memory hierarchy, and we show that properly combined methods can optimize memory access on multiple levels of the hierarchy at the same time. We present performance measurements to compare different algorithm variants and illustrate the influence of the respective techniques. On current hardware, the efficient handling of the memory hierarchy for CPUs improves the rendering performance by a factor of 3 to 4. On GPUs, we observed that the effect is even larger, especially for large data sets. The methods can easily be adjusted to different hardware specifics, although their impact can vary considerably. They can also be used for other rendering techniques than MIPs, and their use for more general image processing task could be investigated in the future.

DSPACE hardware architecture for on-board real-time image/video processing in European space missions

NASA Astrophysics Data System (ADS)

Saponara, Sergio; Donati, Massimiliano; Fanucci, Luca; Odendahl, Maximilian; Leupers, Reiner; Errico, Walter

2013-02-01

The on-board data processing is a vital task for any satellite and spacecraft due to the importance of elaborate the sensing data before sending them to the Earth, in order to exploit effectively the bandwidth to the ground station. In the last years the amount of sensing data collected by scientific and commercial space missions has increased significantly, while the available downlink bandwidth is comparatively stable. The increasing demand of on-board real-time processing capabilities represents one of the critical issues in forthcoming European missions. Faster and faster signal and image processing algorithms are required to accomplish planetary observation, surveillance, Synthetic Aperture Radar imaging and telecommunications. The only available space-qualified Digital Signal Processor (DSP) free of International Traffic in Arms Regulations (ITAR) restrictions faces inadequate performance, thus the development of a next generation European DSP is well known to the space community. The DSPACE space-qualified DSP architecture fills the gap between the computational requirements and the available devices. It leverages a pipelined and massively parallel core based on the Very Long Instruction Word (VLIW) paradigm, with 64 registers and 8 operational units, along with cache memories, memory controllers and SpaceWire interfaces. Both the synthesizable VHDL and the software development tools are generated from the LISA high-level model. A Xilinx-XC7K325T FPGA is chosen to realize a compact PCI demonstrator board. Finally first synthesis results on CMOS standard cell technology (ASIC 180 nm) show an area of around 380 kgates and a peak performance of 1000 MIPS and 750 MFLOPS at 125MHz.

VENI, video, VICI: The merging of computer and video technologies

NASA Technical Reports Server (NTRS)

Horowitz, Jay G.

1993-01-01

The topics covered include the following: High Definition Television (HDTV) milestones; visual information bandwidth; television frequency allocation and bandwidth; horizontal scanning; workstation RGB color domain; NTSC color domain; American HDTV time-table; HDTV image size; digital HDTV hierarchy; task force on digital image architecture; open architecture model; future displays; and the ULTIMATE imaging system.

Architectural Heritage Documentation by Using Low Cost Uav with Fisheye Lens: Otag-I Humayun in Istanbul as a Case Study

NASA Astrophysics Data System (ADS)

Yastikli, N.; Özerdem, Ö. Z.

2017-11-01

The digital documentation of architectural heritage is important for monitoring, preserving, managing as well as 3B BIM modelling, time-space VR (virtual reality) applications. The unmanned aerial vehicles (UAVs) have been widely used in these application thanks to rapid developments in technology which enable the high resolution images with resolutions in millimeters. Moreover, it has become possible to produce highly accurate 3D point clouds with structure from motion (SfM) and multi-view stereo (MVS), to obtain a surface reconstruction of a realistic 3D architectural heritage model by using high-overlap images and 3D modeling software such as Context capture, Pix4Dmapper, Photoscan. In this study, digital documentation of Otag-i Humayun (The Ottoman Empire Sultan's Summer Palace) located in Davutpaşa, Istanbul/Turkey is aimed using low cost UAV. The data collections have been made with low cost UAS 3DR Solo UAV with GoPro Hero 4 with fisheye lens. The data processing was accomplished by using commercial Pix4D software. The dense point clouds, a true orthophoto and 3D solid model of the Otag-i Humayun were produced results. The quality check of the produced point clouds has been performed. The obtained result from Otag-i Humayun in Istanbul proved that, the low cost UAV with fisheye lens can be successfully used for architectural heritage documentation.

Clinical results of HIS, RIS, PACS integration using data integration CASE tools

NASA Astrophysics Data System (ADS)

Taira, Ricky K.; Chan, Hing-Ming; Breant, Claudine M.; Huang, Lu J.; Valentino, Daniel J.

1995-05-01

Current infrastructure research in PACS is dominated by the development of communication networks (local area networks, teleradiology, ATM networks, etc.), multimedia display workstations, and hierarchical image storage architectures. However, limited work has been performed on developing flexible, expansible, and intelligent information processing architectures for the vast decentralized image and text data repositories prevalent in healthcare environments. Patient information is often distributed among multiple data management systems. Current large-scale efforts to integrate medical information and knowledge sources have been costly with limited retrieval functionality. Software integration strategies to unify distributed data and knowledge sources is still lacking commercially. Systems heterogeneity (i.e., differences in hardware platforms, communication protocols, database management software, nomenclature, etc.) is at the heart of the problem and is unlikely to be standardized in the near future. In this paper, we demonstrate the use of newly available CASE (computer- aided software engineering) tools to rapidly integrate HIS, RIS, and PACS information systems. The advantages of these tools include fast development time (low-level code is generated from graphical specifications), and easy system maintenance (excellent documentation, easy to perform changes, and centralized code repository in an object-oriented database). The CASE tools are used to develop and manage the `middle-ware' in our client- mediator-serve architecture for systems integration. Our architecture is scalable and can accommodate heterogeneous database and communication protocols.

ESARR: enhanced situational awareness via road sign recognition

NASA Astrophysics Data System (ADS)

Perlin, V. E.; Johnson, D. B.; Rohde, M. M.; Lupa, R. M.; Fiorani, G.; Mohammad, S.

2010-04-01

The enhanced situational awareness via road sign recognition (ESARR) system provides vehicle position estimates in the absence of GPS signal via automated processing of roadway fiducials (primarily directional road signs). Sign images are detected and extracted from vehicle-mounted camera system, and preprocessed and read via a custom optical character recognition (OCR) system specifically designed to cope with low quality input imagery. Vehicle motion and 3D scene geometry estimation enables efficient and robust sign detection with low false alarm rates. Multi-level text processing coupled with GIS database validation enables effective interpretation even of extremely low resolution low contrast sign images. In this paper, ESARR development progress will be reported on, including the design and architecture, image processing framework, localization methodologies, and results to date. Highlights of the real-time vehicle-based directional road-sign detection and interpretation system will be described along with the challenges and progress in overcoming them.

Fuzzy logic and image processing techniques for the interpretation of seismic data

NASA Astrophysics Data System (ADS)

Orozco-del-Castillo, M. G.; Ortiz-Alemán, C.; Urrutia-Fucugauchi, J.; Rodríguez-Castellanos, A.

2011-06-01

Since interpretation of seismic data is usually a tedious and repetitive task, the ability to do so automatically or semi-automatically has become an important objective of recent research. We believe that the vagueness and uncertainty in the interpretation process makes fuzzy logic an appropriate tool to deal with seismic data. In this work we developed a semi-automated fuzzy inference system to detect the internal architecture of a mass transport complex (MTC) in seismic images. We propose that the observed characteristics of a MTC can be expressed as fuzzy if-then rules consisting of linguistic values associated with fuzzy membership functions. The constructions of the fuzzy inference system and various image processing techniques are presented. We conclude that this is a well-suited problem for fuzzy logic since the application of the proposed methodology yields a semi-automatically interpreted MTC which closely resembles the MTC from expert manual interpretation.

Optimized Laplacian image sharpening algorithm based on graphic processing unit

NASA Astrophysics Data System (ADS)

Ma, Tinghuai; Li, Lu; Ji, Sai; Wang, Xin; Tian, Yuan; Al-Dhelaan, Abdullah; Al-Rodhaan, Mznah

2014-12-01

In classical Laplacian image sharpening, all pixels are processed one by one, which leads to large amount of computation. Traditional Laplacian sharpening processed on CPU is considerably time-consuming especially for those large pictures. In this paper, we propose a parallel implementation of Laplacian sharpening based on Compute Unified Device Architecture (CUDA), which is a computing platform of Graphic Processing Units (GPU), and analyze the impact of picture size on performance and the relationship between the processing time of between data transfer time and parallel computing time. Further, according to different features of different memory, an improved scheme of our method is developed, which exploits shared memory in GPU instead of global memory and further increases the efficiency. Experimental results prove that two novel algorithms outperform traditional consequentially method based on OpenCV in the aspect of computing speed.

Face recognition: database acquisition, hybrid algorithms, and human studies

NASA Astrophysics Data System (ADS)

Gutta, Srinivas; Huang, Jeffrey R.; Singh, Dig; Wechsler, Harry

1997-02-01

One of the most important technologies absent in traditional and emerging frontiers of computing is the management of visual information. Faces are accessible `windows' into the mechanisms that govern our emotional and social lives. The corresponding face recognition tasks considered herein include: (1) Surveillance, (2) CBIR, and (3) CBIR subject to correct ID (`match') displaying specific facial landmarks such as wearing glasses. We developed robust matching (`classification') and retrieval schemes based on hybrid classifiers and showed their feasibility using the FERET database. The hybrid classifier architecture consist of an ensemble of connectionist networks--radial basis functions-- and decision trees. The specific characteristics of our hybrid architecture include (a) query by consensus as provided by ensembles of networks for coping with the inherent variability of the image formation and data acquisition process, and (b) flexible and adaptive thresholds as opposed to ad hoc and hard thresholds. Experimental results, proving the feasibility of our approach, yield (i) 96% accuracy, using cross validation (CV), for surveillance on a data base consisting of 904 images (ii) 97% accuracy for CBIR tasks, on a database of 1084 images, and (iii) 93% accuracy, using CV, for CBIR subject to correct ID match tasks on a data base of 200 images.

Enhanced tactical radar correlator (ETRAC): true interoperability of the 1990s

NASA Astrophysics Data System (ADS)

Guillen, Frank J.

1994-10-01

The enhanced tactical radar correlator (ETRAC) system is under development at Westinghouse Electric Corporation for the Army Space Program Office (ASPO). ETRAC is a real-time synthetic aperture radar (SAR) processing system that provides tactical IMINT to the corps commander. It features an open architecture comprised of ruggedized commercial-off-the-shelf (COTS), UNIX based workstations and processors. The architecture features the DoD common SAR processor (CSP), a multisensor computing platform to accommodate a variety of current and future imaging needs. ETRAC's principal functions include: (1) Mission planning and control -- ETRAC provides mission planning and control for the U-2R and ASARS-2 sensor, including capability for auto replanning, retasking, and immediate spot. (2) Image formation -- the image formation processor (IFP) provides the CPU intensive processing capability to produce real-time imagery for all ASARS imaging modes of operation. (3) Image exploitation -- two exploitation workstations are provided for first-phase image exploitation, manipulation, and annotation. Products include INTEL reports, annotated NITF SID imagery, high resolution hard copy prints and targeting data. ETRAC is transportable via two C-130 aircraft, with autonomous drive on/off capability for high mobility. Other autonomous capabilities include rapid setup/tear down, extended stand-alone support, internal environmental control units (ECUs) and power generation. ETRAC's mission is to provide the Army field commander with accurate, reliable, and timely imagery intelligence derived from collections made by the ASARS-2 sensor, located on-board the U-2R aircraft. To accomplish this mission, ETRAC receives video phase history (VPH) directly from the U-2R aircraft and converts it in real time into soft copy imagery for immediate exploitation and dissemination to the tactical users.

Design of an Airborne L-Band Cross-Track Scanning Scatterometer

NASA Technical Reports Server (NTRS)

Hilliard, Lawrence M. (Technical Monitor)

2002-01-01

In this report, we describe the design of an airborne L-band cross-track scanning scatterometer suitable for airborne operation aboard the NASA P-3 aircraft. The scatterometer is being designed for joint operation with existing L-band radiometers developed by NASA for soil moisture and ocean salinity remote sensing. In addition, design tradeoffs for a space-based radar system have been considered, with particular attention given to antenna architectures suitable for sharing the antenna between the radar and radiometer. During this study, we investigated a number of imaging techniques, including the use of real and synthetic aperture processing in both the along track and cross-track dimensions. The architecture selected will permit a variety of beamforming algorithms to be implemented, although real aperture processing, with hardware beamforming, provides better sidelobe suppression than synthetic array processing and superior signal-to-noise performance. In our discussions with the staff of NASA GSFC, we arrived at an architecture that employs complete transmit/receive modules for each subarray. Amplitude and phase control at each of the transmit modules will allow a low-sidelobe transmit pattern to be generated over scan angles of +/- 50 degrees. Each receiver module will include all electronics necessary to downconvert the received signal to an IF offset of 30 MHz where it will be digitized for further processing.

ASIC Readout Circuit Architecture for Large Geiger Photodiode Arrays

NASA Technical Reports Server (NTRS)

Vasile, Stefan; Lipson, Jerold

2012-01-01

The objective of this work was to develop a new class of readout integrated circuit (ROIC) arrays to be operated with Geiger avalanche photodiode (GPD) arrays, by integrating multiple functions at the pixel level (smart-pixel or active pixel technology) in 250-nm CMOS (complementary metal oxide semiconductor) processes. In order to pack a maximum of functions within a minimum pixel size, the ROIC array is a full, custom application-specific integrated circuit (ASIC) design using a mixed-signal CMOS process with compact primitive layout cells. The ROIC array was processed to allow assembly in bump-bonding technology with photon-counting infrared detector arrays into 3-D imaging cameras (LADAR). The ROIC architecture was designed to work with either common- anode Si GPD arrays or common-cathode InGaAs GPD arrays. The current ROIC pixel design is hardwired prior to processing one of the two GPD array configurations, and it has the provision to allow soft reconfiguration to either array (to be implemented into the next ROIC array generation). The ROIC pixel architecture implements the Geiger avalanche quenching, bias, reset, and time to digital conversion (TDC) functions in full-digital design, and uses time domain over-sampling (vernier) to allow high temporal resolution at low clock rates, increased data yield, and improved utilization of the laser beam.

A synchrotron radiation microtomography system for the analysis of trabecular bone samples.

PubMed

Salomé, M; Peyrin, F; Cloetens, P; Odet, C; Laval-Jeantet, A M; Baruchel, J; Spanne, P

1999-10-01

X-ray computed microtomography is particularly well suited for studying trabecular bone architecture, which requires three-dimensional (3-D) images with high spatial resolution. For this purpose, we describe a three-dimensional computed microtomography (microCT) system using synchrotron radiation, developed at ESRF. Since synchrotron radiation provides a monochromatic and high photon flux x-ray beam, it allows high resolution and a high signal-to-noise ratio imaging. The principle of the system is based on truly three-dimensional parallel tomographic acquisition. It uses a two-dimensional (2-D) CCD-based detector to record 2-D radiographs of the transmitted beam through the sample under different angles of view. The 3-D tomographic reconstruction, performed by an exact 3-D filtered backprojection algorithm, yields 3-D images with cubic voxels. The spatial resolution of the detector was experimentally measured. For the application to bone investigation, the voxel size was set to 6.65 microm, and the experimental spatial resolution was found to be 11 microm. The reconstructed linear attenuation coefficient was calibrated from hydroxyapatite phantoms. Image processing tools are being developed to extract structural parameters quantifying trabecular bone architecture from the 3-D microCT images. First results on human trabecular bone samples are presented.

Volumetric three-dimensional display system with rasterization hardware

NASA Astrophysics Data System (ADS)

Favalora, Gregg E.; Dorval, Rick K.; Hall, Deirdre M.; Giovinco, Michael; Napoli, Joshua

2001-06-01

An 8-color multiplanar volumetric display is being developed by Actuality Systems, Inc. It will be capable of utilizing an image volume greater than 90 million voxels, which we believe is the greatest utilizable voxel set of any volumetric display constructed to date. The display is designed to be used for molecular visualization, mechanical CAD, e-commerce, entertainment, and medical imaging. As such, it contains a new graphics processing architecture, novel high-performance line- drawing algorithms, and an API similar to a current standard. Three-dimensional imagery is created by projecting a series of 2-D bitmaps ('image slices') onto a diffuse screen that rotates at 600 rpm. Persistence of vision fuses the slices into a volume-filling 3-D image. A modified three-panel Texas Instruments projector provides slices at approximately 4 kHz, resulting in 8-color 3-D imagery comprised of roughly 200 radially-disposed slices which are updated at 20 Hz. Each slice has a resolution of 768 by 768 pixels, subtending 10 inches. An unusual off-axis projection scheme incorporating tilted rotating optics is used to maintain good focus across the projection screen. The display electronics includes a custom rasterization architecture which converts the user's 3- D geometry data into image slices, as well as 6 Gbits of DDR SDRAM graphics memory.

NutriNet: A Deep Learning Food and Drink Image Recognition System for Dietary Assessment

PubMed Central

Koroušić Seljak, Barbara

2017-01-01

Automatic food image recognition systems are alleviating the process of food-intake estimation and dietary assessment. However, due to the nature of food images, their recognition is a particularly challenging task, which is why traditional approaches in the field have achieved a low classification accuracy. Deep neural networks have outperformed such solutions, and we present a novel approach to the problem of food and drink image detection and recognition that uses a newly-defined deep convolutional neural network architecture, called NutriNet. This architecture was tuned on a recognition dataset containing 225,953 512 × 512 pixel images of 520 different food and drink items from a broad spectrum of food groups, on which we achieved a classification accuracy of 86.72%, along with an accuracy of 94.47% on a detection dataset containing 130,517 images. We also performed a real-world test on a dataset of self-acquired images, combined with images from Parkinson’s disease patients, all taken using a smartphone camera, achieving a top-five accuracy of 55%, which is an encouraging result for real-world images. Additionally, we tested NutriNet on the University of Milano-Bicocca 2016 (UNIMIB2016) food image dataset, on which we improved upon the provided baseline recognition result. An online training component was implemented to continually fine-tune the food and drink recognition model on new images. The model is being used in practice as part of a mobile app for the dietary assessment of Parkinson’s disease patients. PMID:28653995

Evolution in High Spatial Resolution Imaging of Faint, Complex Objects

NASA Astrophysics Data System (ADS)

van Belle, G.

The astrophysical community has been working at the task of obtaining image information of the smallest structures in the sky via the use of optical interferometry for well over a century. A richly diverse family of technology architectures has been explored over the years, and yet the current family of facilities are all striking similar. Although there may be other, heretofore undeployed, architectures that support the goal of collecting image information at the highest resolutions, we expect dramatic advances at the component level of long-baseline interferometry to be the best avenue for advancing the technique, rather than entirely new architectures.

Optical multiple-image hiding based on interference and grating modulation

NASA Astrophysics Data System (ADS)

He, Wenqi; Peng, Xiang; Meng, Xiangfeng

2012-07-01

We present a method for multiple-image hiding on the basis of interference-based encryption architecture and grating modulation. By using a modified phase retrieval algorithm, we can separately hide a number of secret images into one arbitrarily preselected host image associated with a set of phase-only masks (POMs), which are regarded as secret keys. Thereafter, a grating modulation operation is introduced to multiplex and store the different POMs into a single key mask, which is then assigned to the authorized users in privacy. For recovery, after an appropriate demultiplexing process, one can reconstruct the distributions of all the secret keys and then recover the corresponding hidden images with suppressed crosstalk. Computer simulation results are presented to validate the feasibility of our approach.

Vertically integrated photonic multichip module architecture for vision applications

NASA Astrophysics Data System (ADS)

Tanguay, Armand R., Jr.; Jenkins, B. Keith; von der Malsburg, Christoph; Mel, Bartlett; Holt, Gary; O'Brien, John D.; Biederman, Irving; Madhukar, Anupam; Nasiatka, Patrick; Huang, Yunsong

2000-05-01

The development of a truly smart camera, with inherent capability for low latency semi-autonomous object recognition, tracking, and optimal image capture, has remained an elusive goal notwithstanding tremendous advances in the processing power afforded by VLSI technologies. These features are essential for a number of emerging multimedia- based applications, including enhanced augmented reality systems. Recent advances in understanding of the mechanisms of biological vision systems, together with similar advances in hybrid electronic/photonic packaging technology, offer the possibility of artificial biologically-inspired vision systems with significantly different, yet complementary, strengths and weaknesses. We describe herein several system implementation architectures based on spatial and temporal integration techniques within a multilayered structure, as well as the corresponding hardware implementation of these architectures based on the hybrid vertical integration of multiple silicon VLSI vision chips by means of dense 3D photonic interconnections.

Nanometer-scale oxide thin film transistor with potential for high-density image sensor applications.

PubMed

Jeon, Sanghun; Park, Sungho; Song, Ihun; Hur, Ji-Hyun; Park, Jaechul; Kim, Hojung; Kim, Sunil; Kim, Sangwook; Yin, Huaxiang; Chung, U-In; Lee, Eunha; Kim, Changjung

2011-01-01

The integration of electronically active oxide components onto silicon circuits represents an innovative approach to improving the functionality of novel devices. Like most semiconductor devices, complementary-metal-oxide-semiconductor image sensors (CISs) have physical limitations when progressively scaled down to extremely small dimensions. In this paper, we propose a novel hybrid CIS architecture that is based on the combination of nanometer-scale amorphous In-Ga-Zn-O (a-IGZO) thin-film transistors (TFTs) and a conventional Si photo diode (PD). With this approach, we aim to overcome the loss of quantum efficiency and image quality due to the continuous miniaturization of PDs. Specifically, the a-IGZO TFT with 180 nm gate length is probed to exhibit remarkable performance including low 1/f noise and high output gain, despite fabrication temperatures as low as 200 °C. In particular, excellent device performance is achieved using a double-layer gate dielectric (Al₂O₃/SiO₂) combined with a trapezoidal active region formed by a tailored etching process. A self-aligned top gate structure is adopted to ensure low parasitic capacitance. Lastly, three-dimensional (3D) process simulation tools are employed to optimize the four-pixel CIS structure. The results demonstrate how our stacked hybrid device could be the starting point for new device strategies in image sensor architectures. Furthermore, we expect the proposed approach to be applicable to a wide range of micro- and nanoelectronic devices and systems.

The image-guided surgery toolkit IGSTK: an open source C++ software toolkit.

PubMed

Enquobahrie, Andinet; Cheng, Patrick; Gary, Kevin; Ibanez, Luis; Gobbi, David; Lindseth, Frank; Yaniv, Ziv; Aylward, Stephen; Jomier, Julien; Cleary, Kevin

2007-11-01

This paper presents an overview of the image-guided surgery toolkit (IGSTK). IGSTK is an open source C++ software library that provides the basic components needed to develop image-guided surgery applications. It is intended for fast prototyping and development of image-guided surgery applications. The toolkit was developed through a collaboration between academic and industry partners. Because IGSTK was designed for safety-critical applications, the development team has adopted lightweight software processes that emphasizes safety and robustness while, at the same time, supporting geographically separated developers. A software process that is philosophically similar to agile software methods was adopted emphasizing iterative, incremental, and test-driven development principles. The guiding principle in the architecture design of IGSTK is patient safety. The IGSTK team implemented a component-based architecture and used state machine software design methodologies to improve the reliability and safety of the components. Every IGSTK component has a well-defined set of features that are governed by state machines. The state machine ensures that the component is always in a valid state and that all state transitions are valid and meaningful. Realizing that the continued success and viability of an open source toolkit depends on a strong user community, the IGSTK team is following several key strategies to build an active user community. These include maintaining a users and developers' mailing list, providing documentation (application programming interface reference document and book), presenting demonstration applications, and delivering tutorial sessions at relevant scientific conferences.

Analysis of straw row in the image to control the trajectory of the agricultural combine harvester

NASA Astrophysics Data System (ADS)

Shkanaev, Aleksandr Yurievich; Polevoy, Dmitry Valerevich; Panchenko, Aleksei Vladimirovich; Krokhina, Darya Alekseevna; Nailevish, Sadekov Rinat

2018-04-01

The paper proposes a solution to the automatic operation of the combine harvester along the straw rows by means of the images from the camera, installed in the cab of the harvester. The U-Net is used to recognize straw rows in the image. The edges of the row are approximated in the segmented image by the curved lines and further converted into the harvester coordinate system for the automatic operating system. The "new" network architecture and approaches to the row approximation has improved the quality of the recognition task and the processing speed of the frames up to 96% and 7.5 fps, respectively. Keywords: Grain harvester,

Design Criteria For Networked Image Analysis System

NASA Astrophysics Data System (ADS)

Reader, Cliff; Nitteberg, Alan

1982-01-01

Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

Austro-Hungarian Public Building Refurbishment and Energy Efficiency Measures - A Case Study on a Public Building in Sarajevo

NASA Astrophysics Data System (ADS)

Salihbegović, Amira; Čaušević, Amir; Rustempašić, Nerman; Avdić, Dženis; Smajlović, Esad

2017-10-01

Among other pieces of architectural historical heritage in Sarajevo, and Bosnia-Herzegovina in general, the Austro-Hungarian architecture has preserved its original architectural, artistic and engineering characteristics. Both residential and public representative urban blocks, streets and squares are of distinguishable ambience in the architectural and urban image of the city and are testifying about our architectural past. A number of buildings is valorised and protected by law in terms of their architectural, artistic and historical value. In addition, these buildings have a distinct functional, ambiental, historical, and even aesthetical value. To make them last longer, refurbishment of these buildings is challenging and presents potential and multiple benefits for the city, and beyond. Refurbishing built environment through functional reorganizing, redesign and energy efficiency measures applications could result in prolonged longevity, architectural identity preservation and interior comfort improvement. Besides, implemented measures for energy efficiency, through the refurbishment process, should optimize the needs for energy consumption in treated buildings. This paper defines options in comfort improvements and redesign, without implying risks to the building longevity, analyses interventions and energy efficiency measures which would enable potential energy saving assessment in the refurbishment process of masonry buildings. This paper also discusses the different techniques that can be adopted for conservation and preservation of historical masonry buildings from the Austro-Hungarian period dealing with energy efficiency. The works were preceded by historical research and on-site investigations. This paper describes a methodology to quantify their vulnerability. A scheme of structural retrofitting is suggested following the research conducted. Revitalization of the building consisted in the reconstruction of the old building structure, creating the inner courtyard and covering it with a glass roof.

Architecture of the software for LAMOST fiber positioning subsystem

NASA Astrophysics Data System (ADS)

Peng, Xiaobo; Xing, Xiaozheng; Hu, Hongzhuan; Zhai, Chao; Li, Weimin

2004-09-01

The architecture of the software which controls the LAMOST fiber positioning sub-system is described. The software is composed of two parts as follows: a main control program in a computer and a unit controller program in a MCS51 single chip microcomputer ROM. And the function of the software includes: Client/Server model establishment, observation planning, collision handling, data transmission, pulse generation, CCD control, image capture and processing, and data analysis etc. Particular attention is paid to the ways in which different parts of the software can communicate. Also software techniques for multi threads, SOCKET programming, Microsoft Windows message response, and serial communications are discussed.

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.

Label-free tissue scanner for colorectal cancer screening

NASA Astrophysics Data System (ADS)

Kandel, Mikhail E.; Sridharan, Shamira; Liang, Jon; Luo, Zelun; Han, Kevin; Macias, Virgilia; Shah, Anish; Patel, Roshan; Tangella, Krishnarao; Kajdacsy-Balla, Andre; Guzman, Grace; Popescu, Gabriel

2017-06-01

The current practice of surgical pathology relies on external contrast agents to reveal tissue architecture, which is then qualitatively examined by a trained pathologist. The diagnosis is based on the comparison with standardized empirical, qualitative assessments of limited objectivity. We propose an approach to pathology based on interferometric imaging of "unstained" biopsies, which provides unique capabilities for quantitative diagnosis and automation. We developed a label-free tissue scanner based on "quantitative phase imaging," which maps out optical path length at each point in the field of view and, thus, yields images that are sensitive to the "nanoscale" tissue architecture. Unlike analysis of stained tissue, which is qualitative in nature and affected by color balance, staining strength and imaging conditions, optical path length measurements are intrinsically quantitative, i.e., images can be compared across different instruments and clinical sites. These critical features allow us to automate the diagnosis process. We paired our interferometric optical system with highly parallelized, dedicated software algorithms for data acquisition, allowing us to image at a throughput comparable to that of commercial tissue scanners while maintaining the nanoscale sensitivity to morphology. Based on the measured phase information, we implemented software tools for autofocusing during imaging, as well as image archiving and data access. To illustrate the potential of our technology for large volume pathology screening, we established an "intrinsic marker" for colorectal disease that detects tissue with dysplasia or colorectal cancer and flags specific areas for further examination, potentially improving the efficiency of existing pathology workflows.

GPU accelerated fuzzy connected image segmentation by using CUDA.

PubMed

Zhuge, Ying; Cao, Yong; Miller, Robert W

2009-01-01

Image segmentation techniques using fuzzy connectedness principles have shown their effectiveness in segmenting a variety of objects in several large applications in recent years. However, one problem of these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays commodity graphics hardware provides high parallel computing power. In this paper, we present a parallel fuzzy connected image segmentation algorithm on Nvidia's Compute Unified Device Architecture (CUDA) platform for segmenting large medical image data sets. Our experiments based on three data sets with small, medium, and large data size demonstrate the efficiency of the parallel algorithm, which achieves a speed-up factor of 7.2x, 7.3x, and 14.4x, correspondingly, for the three data sets over the sequential implementation of fuzzy connected image segmentation algorithm on CPU.

Three-dimensional cardiac architecture determined by two-photon microtomy

NASA Astrophysics Data System (ADS)

Huang, Hayden; MacGillivray, Catherine; Kwon, Hyuk-Sang; Lammerding, Jan; Robbins, Jeffrey; Lee, Richard T.; So, Peter

2009-07-01

Cardiac architecture is inherently three-dimensional, yet most characterizations rely on two-dimensional histological slices or dissociated cells, which remove the native geometry of the heart. We previously developed a method for labeling intact heart sections without dissociation and imaging large volumes while preserving their three-dimensional structure. We further refine this method to permit quantitative analysis of imaged sections. After data acquisition, these sections are assembled using image-processing tools, and qualitative and quantitative information is extracted. By examining the reconstructed cardiac blocks, one can observe end-to-end adjacent cardiac myocytes (cardiac strands) changing cross-sectional geometries, merging and separating from other strands. Quantitatively, representative cross-sectional areas typically used for determining hypertrophy omit the three-dimensional component; we show that taking orientation into account can significantly alter the analysis. Using fast-Fourier transform analysis, we analyze the gross organization of cardiac strands in three dimensions. By characterizing cardiac structure in three dimensions, we are able to determine that the α crystallin mutation leads to hypertrophy with cross-sectional area increases, but not necessarily via changes in fiber orientation distribution.

Compact FPGA-based beamformer using oversampled 1-bit A/D converters.

PubMed

Tomov, Borislav Gueorguiev; Jensen, Jørgen Arendt

2005-05-01

A compact medical ultrasound beamformer architecture that uses oversampled 1-bit analog-to-digital (A/D) converters is presented. Sparse sample processing is used, as the echo signal for the image lines is reconstructed in 512 equidistant focal points along the line through its in-phase and quadrature components. That information is sufficient for presenting a B-mode image and creating a color flow map. The high sampling rate provides the necessary delay resolution for the focusing. The low channel data width (1-bit) makes it possible to construct a compact beamformer logic. The signal reconstruction is done using finite impulse reponse (FIR) filters, applied on selected bit sequences of the delta-sigma modulator output stream. The approach allows for a multichannel beamformer to fit in a single field programmable gate array (FPGA) device. A 32-channel beamformer is estimated to occupy 50% of the available logic resources in a commercially available mid-range FPGA, and to be able to operate at 129 MHz. Simulation of the architecture at 140 MHz provides images with a dynamic range approaching 60 dB for an excitation frequency of 3 MHz.

Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities.

PubMed

Ghafoorian, Mohsen; Karssemeijer, Nico; Heskes, Tom; van Uden, Inge W M; Sanchez, Clara I; Litjens, Geert; de Leeuw, Frank-Erik; van Ginneken, Bram; Marchiori, Elena; Platel, Bram

2017-07-11

The anatomical location of imaging features is of crucial importance for accurate diagnosis in many medical tasks. Convolutional neural networks (CNN) have had huge successes in computer vision, but they lack the natural ability to incorporate the anatomical location in their decision making process, hindering success in some medical image analysis tasks. In this paper, to integrate the anatomical location information into the network, we propose several deep CNN architectures that consider multi-scale patches or take explicit location features while training. We apply and compare the proposed architectures for segmentation of white matter hyperintensities in brain MR images on a large dataset. As a result, we observe that the CNNs that incorporate location information substantially outperform a conventional segmentation method with handcrafted features as well as CNNs that do not integrate location information. On a test set of 50 scans, the best configuration of our networks obtained a Dice score of 0.792, compared to 0.805 for an independent human observer. Performance levels of the machine and the independent human observer were not statistically significantly different (p-value = 0.06).

Stellar imager (SI): enhancements to the mission enabled by the constellation architecture (Ares I/Ares V)

NASA Astrophysics Data System (ADS)

Carpenter, Kenneth G.; Karovska, Margarita; Lyon, Richard G.; Mozurkewich, D.; Schrijver, Carolus

2009-08-01

Stellar Imager (SI) is a space-based, UV/Optical Interferometer (UVOI) with over 200x the resolution of HST. It will enable 0.1 milli-arcsec spectral imaging of stellar surfaces and the Universe in general and open an enormous new "discovery space" for astrophysics with its combination of high angular resolution, dynamic imaging, and spectral energy resolution. SI's goal is to study the role of magnetism in the Universe and revolutionize our understanding of: 1) Solar/Stellar Magnetic Activity and their impact on Space Weather, Planetary Climates, and Life, 2) Magnetic and Accretion Processes and their roles in the Origin & Evolution of Structure and in the Transport of Matter throughout the Universe, 3) the close-in structure of Active Galactic Nuclei and their winds, and 4) Exo-Solar Planet Transits and Disks. SI is a "Landmark/Discovery Mission" in 2005 Heliophysics Roadmap and a candidate UVOI in the 2006 Astrophysics Strategic Plan and is targeted for launch in the mid-2020's. It is a NASA Vision Mission and has been recommended for further study in a 2008 NRC report on missions potentially enabled/enhanced by an Ares V launch. In this paper, we discuss the science goals and required capabilities of SI, the baseline architecture of the mission assuming launch on one or more Delta rockets, and then the potential significant enhancements to the SI science and mission architecture that would be made possible by a launch in the larger volume Ares V payload fairing, and by servicing options under consideration in the Constellation program.

From Panoramic Photos to a Low-Cost Photogrammetric Workflow for Cultural Heritage 3d Documentation

NASA Astrophysics Data System (ADS)

D'Annibale, E.; Tassetti, A. N.; Malinverni, E. S.

2013-07-01

The research aims to optimize a workflow of architecture documentation: starting from panoramic photos, tackling available instruments and technologies to propose an integrated, quick and low-cost solution of Virtual Architecture. The broader research background shows how to use spherical panoramic images for the architectural metric survey. The input data (oriented panoramic photos), the level of reliability and Image-based Modeling methods constitute an integrated and flexible 3D reconstruction approach: from the professional survey of cultural heritage to its communication in virtual museum. The proposed work results from the integration and implementation of different techniques (Multi-Image Spherical Photogrammetry, Structure from Motion, Imagebased Modeling) with the aim to achieve high metric accuracy and photorealistic performance. Different documentation chances are possible within the proposed workflow: from the virtual navigation of spherical panoramas to complex solutions of simulation and virtual reconstruction. VR tools make for the integration of different technologies and the development of new solutions for virtual navigation. Image-based Modeling techniques allow 3D model reconstruction with photo realistic and high-resolution texture. High resolution of panoramic photo and algorithms of panorama orientation and photogrammetric restitution vouch high accuracy and high-resolution texture. Automated techniques and their following integration are subject of this research. Data, advisably processed and integrated, provide different levels of analysis and virtual reconstruction joining the photogrammetric accuracy to the photorealistic performance of the shaped surfaces. Lastly, a new solution of virtual navigation is tested. Inside the same environment, it proposes the chance to interact with high resolution oriented spherical panorama and 3D reconstructed model at once.

Stellar Imager (SI): Enhancements to the Mission Enabled by the Constellation Architecture (Ares I/Ares V)

NASA Technical Reports Server (NTRS)

Carpenter, Kenneth G.; Lyon, Richard G.; Karovska, Margarita; Mozurkwich, D.; Schrijver, Carolus

2009-01-01

Stellar Imager (SI) is a space-based, UV/Optical Interferometer (UVOI) with over 200x the resolution of HST. It will enable 0.1 milli-aresec spectral imaging of stellar surfaces and the Universe in general and open an enormous new "discovery space" for astrophysics with its combination of high angular resolution, dynamic imaging , and spectral energy resolution. SI's goal is to study the role of magnetism in the Universe and revolutionize our understanding of 1) Solar/Stellar Magnetic Activity and their impact on Space Weather, Planetary Climates, and Life, 2) Magnetic and Accretion Processes and their roles in the Origin & Evolution of Structure and in the Transport of Matter throughout the Universe, 3) the close-in structure of Active Galactic Nuclei and their winds, and 4) Exo-Solar Planet Transits and Disks. SI is a "Landmark-Discovery Mission" in 2005 Heliophysics Roadmap and a candidate UVOI in the 2006 Astrophysics Strategic Plan and is targeted for launch in the mid-2020's. It is a NASA Vision Mission and has been recommended for further study in a 2008 NRC report on missions potentially enabled/enhanced by an Ares V launch. In this paper, we discuss the science goals and required capabilities of SI, the baseline architecture of the mission assuming launch on one or more Delta rockets, and then the potential significant enhancements to the SI science and mission architecture that would be made possible by a launch in the larger volume Ares V payload fairing, and by servicing options under consideration in the Constellation program.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies.

PubMed

Atkinson, Jonathan A; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E; Griffiths, Marcus; Wells, Darren M

2017-10-01

Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. © The Authors 2017. Published by Oxford University Press.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies

PubMed Central

Atkinson, Jonathan A.; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E.; Griffiths, Marcus

2017-01-01

Abstract Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. PMID:29020748

A technique system for the measurement, reconstruction and character extraction of rice plant architecture

PubMed Central

Li, Xumeng; Wang, Xiaohui; Wei, Hailin; Zhu, Xinguang; Peng, Yulin; Li, Ming; Li, Tao; Huang, Huang

2017-01-01

This study developed a technique system for the measurement, reconstruction, and trait extraction of rice canopy architectures, which have challenged functional–structural plant modeling for decades and have become the foundation of the design of ideo-plant architectures. The system uses the location-separation-measurement method (LSMM) for the collection of data on the canopy architecture and the analytic geometry method for the reconstruction and visualization of the three-dimensional (3D) digital architecture of the rice plant. It also uses the virtual clipping method for extracting the key traits of the canopy architecture such as the leaf area, inclination, and azimuth distribution in spatial coordinates. To establish the technique system, we developed (i) simple tools to measure the spatial position of the stem axis and azimuth of the leaf midrib and to capture images of tillers and leaves; (ii) computer software programs for extracting data on stem diameter, leaf nodes, and leaf midrib curves from the tiller images and data on leaf length, width, and shape from the leaf images; (iii) a database of digital architectures that stores the measured data and facilitates the reconstruction of the 3D visual architecture and the extraction of architectural traits; and (iv) computation algorithms for virtual clipping to stratify the rice canopy, to extend the stratified surface from the horizontal plane to a general curved surface (including a cylindrical surface), and to implement in silico. Each component of the technique system was quantitatively validated and visually compared to images, and the sensitivity of the virtual clipping algorithms was analyzed. This technique is inexpensive and accurate and provides high throughput for the measurement, reconstruction, and trait extraction of rice canopy architectures. The technique provides a more practical method of data collection to serve functional–structural plant models of rice and for the optimization of rice canopy types. Moreover, the technique can be easily adapted for other cereal crops such as wheat, which has numerous stems and leaves sheltering each other. PMID:28558045

Real time 3D structural and Doppler OCT imaging on graphics processing units

NASA Astrophysics Data System (ADS)

Sylwestrzak, Marcin; Szlag, Daniel; Szkulmowski, Maciej; Gorczyńska, Iwona; Bukowska, Danuta; Wojtkowski, Maciej; Targowski, Piotr

2013-03-01

In this report the application of graphics processing unit (GPU) programming for real-time 3D Fourier domain Optical Coherence Tomography (FdOCT) imaging with implementation of Doppler algorithms for visualization of the flows in capillary vessels is presented. Generally, the time of the data processing of the FdOCT data on the main processor of the computer (CPU) constitute a main limitation for real-time imaging. Employing additional algorithms, such as Doppler OCT analysis, makes this processing even more time consuming. Lately developed GPUs, which offers a very high computational power, give a solution to this problem. Taking advantages of them for massively parallel data processing, allow for real-time imaging in FdOCT. The presented software for structural and Doppler OCT allow for the whole processing with visualization of 2D data consisting of 2000 A-scans generated from 2048 pixels spectra with frame rate about 120 fps. The 3D imaging in the same mode of the volume data build of 220 × 100 A-scans is performed at a rate of about 8 frames per second. In this paper a software architecture, organization of the threads and optimization applied is shown. For illustration the screen shots recorded during real time imaging of the phantom (homogeneous water solution of Intralipid in glass capillary) and the human eye in-vivo is presented.

Automated Segmentation of Light-Sheet Fluorescent Imaging to Characterize Experimental Doxorubicin-Induced Cardiac Injury and Repair.

PubMed

Packard, René R Sevag; Baek, Kyung In; Beebe, Tyler; Jen, Nelson; Ding, Yichen; Shi, Feng; Fei, Peng; Kang, Bong Jin; Chen, Po-Heng; Gau, Jonathan; Chen, Michael; Tang, Jonathan Y; Shih, Yu-Huan; Ding, Yonghe; Li, Debiao; Xu, Xiaolei; Hsiai, Tzung K

2017-08-17

This study sought to develop an automated segmentation approach based on histogram analysis of raw axial images acquired by light-sheet fluorescent imaging (LSFI) to establish rapid reconstruction of the 3-D zebrafish cardiac architecture in response to doxorubicin-induced injury and repair. Input images underwent a 4-step automated image segmentation process consisting of stationary noise removal, histogram equalization, adaptive thresholding, and image fusion followed by 3-D reconstruction. We applied this method to 3-month old zebrafish injected intraperitoneally with doxorubicin followed by LSFI at 3, 30, and 60 days post-injection. We observed an initial decrease in myocardial and endocardial cavity volumes at day 3, followed by ventricular remodeling at day 30, and recovery at day 60 (P < 0.05, n = 7-19). Doxorubicin-injected fish developed ventricular diastolic dysfunction and worsening global cardiac function evidenced by elevated E/A ratios and myocardial performance indexes quantified by pulsed-wave Doppler ultrasound at day 30, followed by normalization at day 60 (P < 0.05, n = 9-20). Treatment with the γ-secretase inhibitor, DAPT, to inhibit cleavage and release of Notch Intracellular Domain (NICD) blocked cardiac architectural regeneration and restoration of ventricular function at day 60 (P < 0.05, n = 6-14). Our approach provides a high-throughput model with translational implications for drug discovery and genetic modifiers of chemotherapy-induced cardiomyopathy.

Microlens array processor with programmable weight mask and direct optical input

NASA Astrophysics Data System (ADS)

Schmid, Volker R.; Lueder, Ernst H.; Bader, Gerhard; Maier, Gert; Siegordner, Jochen

1999-03-01

We present an optical feature extraction system with a microlens array processor. The system is suitable for online implementation of a variety of transforms such as the Walsh transform and DCT. Operating with incoherent light, our processor accepts direct optical input. Employing a sandwich- like architecture, we obtain a very compact design of the optical system. The key elements of the microlens array processor are a square array of 15 X 15 spherical microlenses on acrylic substrate and a spatial light modulator as transmissive mask. The light distribution behind the mask is imaged onto the pixels of a customized a-Si image sensor with adjustable gain. We obtain one output sample for each microlens image and its corresponding weight mask area as summation of the transmitted intensity within one sensor pixel. The resulting architecture is very compact and robust like a conventional camera lens while incorporating a high degree of parallelism. We successfully demonstrate a Walsh transform into the spatial frequency domain as well as the implementation of a discrete cosine transform with digitized gray values. We provide results showing the transformation performance for both synthetic image patterns and images of natural texture samples. The extracted frequency features are suitable for neural classification of the input image. Other transforms and correlations can be implemented in real-time allowing adaptive optical signal processing.

Influence of macromolecular architecture on necking in polymer extrusion film casting process

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

Pol, Harshawardhan; Banik, Sourya; Azad, Lal Busher

2015-05-22

Extrusion film casting (EFC) is an important polymer processing technique that is used to produce several thousand tons of polymer films/coatings on an industrial scale. In this research, we are interested in understanding quantitatively how macromolecular chain architecture (for example long chain branching (LCB) or molecular weight distribution (MWD or PDI)) influences the necking and thickness distribution of extrusion cast films. We have used different polymer resins of linear and branched molecular architecture to produce extrusion cast films under controlled experimental conditions. The necking profiles of the films were imaged and the velocity profiles during EFC were monitored using particlemore » tracking velocimetry (PTV) technique. Additionally, the temperature profiles were captured using an IR thermography and thickness profiles were calculated. The experimental results are compared with predictions of one-dimensional flow model of Silagy et al{sup 1} wherein the polymer resin rheology is modeled using molecular constitutive equations such as the Rolie-Poly (RP) and extended Pom Pom (XPP). We demonstrate that the 1-D flow model containing the molecular constitutive equations provides new insights into the role of macromolecular chain architecture on film necking.{sup 1}D. Silagy, Y. Demay, and J-F. Agassant, Polym. Eng. Sci., 36, 2614 (1996)« less

Analysis of area-time efficiency for an integrated focal plane architecture

NASA Astrophysics Data System (ADS)

Robinson, William H.; Wills, D. Scott

2003-05-01

Monolithic integration of photodetectors, analog-to-digital converters, digital processing, and data storage can improve the performance and efficiency of next-generation portable image products. Our approach combines these components into a single processing element, which is tiled to form a SIMD focal plane processor array with the capability to execute early image applications such as median filtering (noise removal), convolution (smoothing), and inside edge detection (segmentation). Digitizing and processing a pixel at the detection site presents new design challenges, including the allocation of silicon resources. This research investigates the area-time (A"T2) efficiency by adjusting the number of Pixels-per-Processing Element (PPE). Area calculations are based upon hardware implementations of components scaled for 250nm or 120nm technology. The total execution time is calculated from the sequential execution of each application on a generic focal plane architectural simulator. For a Quad-CIF system resolution (176×144), results show that 1 PPE provides the optimal area-time efficiency (5.7 μs2 x mm2 for 250nm, 1.7 μs2 x mm2 for 120nm) but requires a large silicon chip (2072mm2 for 250nm, 614mm2 for 120nm). Increasing the PPE to 4 or 16 can reduce silicon area by 48% and 60% respectively (120nm technology) while maintaining performance within real-time constraints.

An integrated autonomous rendezvous and docking system architecture using Centaur modern avionics

NASA Technical Reports Server (NTRS)

Nelson, Kurt

1991-01-01

The avionics system for the Centaur upper stage is in the process of being modernized with the current state-of-the-art in strapdown inertial guidance equipment. This equipment includes an integrated flight control processor with a ring laser gyro based inertial guidance system. This inertial navigation unit (INU) uses two MIL-STD-1750A processors and communicates over the MIL-STD-1553B data bus. Commands are translated into load activation through a Remote Control Unit (RCU) which incorporates the use of solid state relays. Also, a programmable data acquisition system replaces separate multiplexer and signal conditioning units. This modern avionics suite is currently being enhanced through independent research and development programs to provide autonomous rendezvous and docking capability using advanced cruise missile image processing technology and integrated GPS navigational aids. A system concept was developed to combine these technologies in order to achieve a fully autonomous rendezvous, docking, and autoland capability. The current system architecture and the evolution of this architecture using advanced modular avionics concepts being pursued for the National Launch System are discussed.

Parallel algorithms for mapping pipelined and parallel computations

NASA Technical Reports Server (NTRS)

Nicol, David M.

1988-01-01

Many computational problems in image processing, signal processing, and scientific computing are naturally structured for either pipelined or parallel computation. When mapping such problems onto a parallel architecture it is often necessary to aggregate an obvious problem decomposition. Even in this context the general mapping problem is known to be computationally intractable, but recent advances have been made in identifying classes of problems and architectures for which optimal solutions can be found in polynomial time. Among these, the mapping of pipelined or parallel computations onto linear array, shared memory, and host-satellite systems figures prominently. This paper extends that work first by showing how to improve existing serial mapping algorithms. These improvements have significantly lower time and space complexities: in one case a published O(nm sup 3) time algorithm for mapping m modules onto n processors is reduced to an O(nm log m) time complexity, and its space requirements reduced from O(nm sup 2) to O(m). Run time complexity is further reduced with parallel mapping algorithms based on these improvements, which run on the architecture for which they create the mappings.

Advanced Magnetic Resonance Imaging techniques to probe muscle structure and function

NASA Astrophysics Data System (ADS)

Malis, Vadim

Structural and functional Magnetic Resonance Imaging (MRI) studies of skeletal muscle allow the elucidation of muscle physiology under normal and pathological conditions. Continuing on the efforts of the Muscle Imaging and Modeling laboratory, the focus of the thesis is to (i) extend and refine two challenging imaging modalities: structural imaging using Diffusion Tensor Imaging (DTI) and functional imaging based on Velocity Encoded Phase Contrast Imaging (VE-PC) and (ii) apply these methods to explore age related structure and functional differences of the gastrocnemius muscle. Diffusion Tensor Imaging allows the study of tissue microstructure as well as muscle fiber architecture. The images, based on an ultrafast single shot Echo Planar Imaging (EPI) sequence, suffer from geometric distortions and low signal to noise ratio. A processing pipeline was developed to correct for distortions and to improve image Signal to Noise Ratio (SNR). DTI acquired on a senior and young cohort of subjects were processed through the pipeline and differences in DTI derived indices and fiber architecture between the two cohorts were explored. The DTI indices indicated that at the microstructural level, fiber atrophy was accompanied with a reduction in fiber volume fraction. At the fiber architecture level, fiber length and pennation angles decreased with age that potentially contribute to the loss of muscle force with age. Velocity Encoded Phase Contrast imaging provides tissue (e.g. muscle) velocity at each voxel which allows the study of strain and Strain Rate (SR) under dynamic conditions. The focus of the thesis was to extract 2D strain rate tensor maps from the velocity images and apply the method to study age related differences. The tensor mapping can potentially provide unique information on the extracellular matrix and lateral transmission the role of these two elements has recently emerged as important determinants of force loss with age. In the cross sectional study on aging, strain rate during isometric contraction was significantly reduced in the seniors; presumably from decrease in muscle slack and increase in stiffness with age. Other parameters of interest from this study that allow inferences on the ECM and lateral transmission are the asymmetry of deformation in the fiber cross section as well as the angle between the SR and muscle fiber. The last part of thesis, which is a 'work-in-progress', is the extension to 3D SR tensor mapping using a 3D spatial, 3D velocity encoded imaging sequence. This is combined with Diffusion Tensor Imaging to obtain the lead eigenvector (muscle fiber direction) at each voxel. The 3D SR is then rotated to the basis of the DTI to obtain a 'Fiber Aligned Strain rate: FASR'. The off diagonal elements of FASR are shear strain terms. Detailed analysis of the shear strain will provide a unique non-invasive method to probe lateral transmission.

Image and Morphology in Modern Theory of Architecture

NASA Astrophysics Data System (ADS)

Yankovskaya, Y. S.; Merenkov, A. V.

2017-11-01

This paper is devoted to some important and fundamental problems of the modern Russian architectural theory. These problems are: methodological and technological retardation; substitution of the modern professional architectural theoretical knowledge by the humanitarian concepts; preference of the traditional historical or historical-theoretical research. One of the most probable ways is the formation of useful modern subject (and multi-subject)-oriented concepts in architecture. To get over the criticism and distrust of the architectural theory is possible through the recognition of an important role of the subject (architect, consumer, contractor, ruler, etc.) and direction of the practical tasks of the forming human environment in the today’s rapidly changing world and post-industrial society. In this article we consider the evolution of two basic concepts for the theory of architecture such as the image and morphology.

Modeling Stratigraphic Architecture of Deep-water Deposits Using a Small Unmanned Aircraft: Neogene Thin-bedded Turbidites, East Coast Basin, New Zealand

NASA Astrophysics Data System (ADS)

Nieminski, N.; Graham, S. A.

2014-12-01

One of the outstanding challenges of field geology is inaccessibility of exposure. The ability to view and characterize outcrops that are difficult to study from the ground is greatly improved by aerial investigation. Detailed stratigraphic architecture of such exposures is best addressed by using advances and availability of small unmanned aircraft systems (sUAS) that can safely navigate from high-altitude overviews of study areas to within a meter of the exposure of interest. High-resolution photographs acquired at various elevations and azimuths by sUAS are then used to convert field measurements to digital representations in three-dimensions at a fine scale. Photogrammetric software is used to capture complex, detailed topography by creating digital surface models with a range imaging technique that estimates three-dimensional structures from two-dimensional image sequences. The digital surface model is overlain by detailed, high-resolution photography. Pairing sUAS technology with readily available photogrammetry software that requires little processing time and resources offers a revolutionary and cost-effective methodology for geoscientists to investigate and quantify stratigraphic and structural complexity of field studies from the convenience of the office. These methods of imaging and modeling remote outcrops are demonstrated in the East Coast Basin, New Zealand, where wave-cut platform exposures of Miocene deep-water deposits offer a unique opportunity to investigate the flow processes and resulting characteristics of thin-bedded turbidite deposits. Stratigraphic architecture of wavecut platform and vertically-dipping exposures of these thin-bedded turbidites is investigated with sUAS coupled with Structure from Motion (SfM) photogrammetry software. This approach allows the geometric and spatial variation of deep-water architecture to be characterized continuously along 2,000 meters of lateral exposure, as well as to measure and quantify cyclic variations in thin-bedded turbidites at centimeter scale. Results yield a spatial and temporal understanding of a deep-water depositional system at a scale that was previously unattainable using conventional field geology techniques, and a virtual outcrop that can be used for classroom education.

Performances of multiprocessor multidisk architectures for continuous media storage

NASA Astrophysics Data System (ADS)

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

1996-03-01

Multimedia interfaces increase the need for large image databases, capable of storing and reading streams of data with strict synchronicity and isochronicity requirements. In order to fulfill these requirements, we consider a parallel image server architecture which relies on arrays of intelligent disk nodes, each disk node being composed of one processor and one or more disks. This contribution analyzes through bottleneck performance evaluation and simulation the behavior of two multi-processor multi-disk architectures: a point-to-point architecture and a shared-bus architecture similar to current multiprocessor workstation architectures. We compare the two architectures on the basis of two multimedia algorithms: the compute-bound frame resizing by resampling and the data-bound disk-to-client stream transfer. The results suggest that the shared bus is a potential bottleneck despite its very high hardware throughput (400Mbytes/s) and that an architecture with addressable local memories located closely to their respective processors could partially remove this bottleneck. The point- to-point architecture is scalable and able to sustain high throughputs for simultaneous compute- bound and data-bound operations.

Cardiac Light-Sheet Fluorescent Microscopy for Multi-Scale and Rapid Imaging of Architecture and Function

NASA Astrophysics Data System (ADS)

Fei, Peng; Lee, Juhyun; Packard, René R. Sevag; Sereti, Konstantina-Ioanna; Xu, Hao; Ma, Jianguo; Ding, Yichen; Kang, Hanul; Chen, Harrison; Sung, Kevin; Kulkarni, Rajan; Ardehali, Reza; Kuo, C.-C. Jay; Xu, Xiaolei; Ho, Chih-Ming; Hsiai, Tzung K.

2016-03-01

Light Sheet Fluorescence Microscopy (LSFM) enables multi-dimensional and multi-scale imaging via illuminating specimens with a separate thin sheet of laser. It allows rapid plane illumination for reduced photo-damage and superior axial resolution and contrast. We hereby demonstrate cardiac LSFM (c-LSFM) imaging to assess the functional architecture of zebrafish embryos with a retrospective cardiac synchronization algorithm for four-dimensional reconstruction (3-D space + time). By combining our approach with tissue clearing techniques, we reveal the entire cardiac structures and hypertrabeculation of adult zebrafish hearts in response to doxorubicin treatment. By integrating the resolution enhancement technique with c-LSFM to increase the resolving power under a large field-of-view, we demonstrate the use of low power objective to resolve the entire architecture of large-scale neonatal mouse hearts, revealing the helical orientation of individual myocardial fibers. Therefore, our c-LSFM imaging approach provides multi-scale visualization of architecture and function to drive cardiovascular research with translational implication in congenital heart diseases.

SAVA 3: A testbed for integration and control of visual processes

NASA Technical Reports Server (NTRS)

Crowley, James L.; Christensen, Henrik

1994-01-01

The development of an experimental test-bed to investigate the integration and control of perception in a continuously operating vision system is described. The test-bed integrates a 12 axis robotic stereo camera head mounted on a mobile robot, dedicated computer boards for real-time image acquisition and processing, and a distributed system for image description. The architecture was designed to: (1) be continuously operating, (2) integrate software contributions from geographically dispersed laboratories, (3) integrate description of the environment with 2D measurements, 3D models, and recognition of objects, (4) capable of supporting diverse experiments in gaze control, visual servoing, navigation, and object surveillance, and (5) dynamically reconfiguarable.

The Montage architecture for grid-enabled science processing of large, distributed datasets

NASA Technical Reports Server (NTRS)

Jacob, Joseph C.; Katz, Daniel S .; Prince, Thomas; Berriman, Bruce G.; Good, John C.; Laity, Anastasia C.; Deelman, Ewa; Singh, Gurmeet; Su, Mei-Hui

2004-01-01

Montage is an Earth Science Technology Office (ESTO) Computational Technologies (CT) Round III Grand Challenge investigation to deploy a portable, compute-intensive, custom astronomical image mosaicking service for the National Virtual Observatory (NVO). Although Montage is developing a compute- and data-intensive service for the astronomy community, we are also helping to address a problem that spans both Earth and Space science, namely how to efficiently access and process multi-terabyte, distributed datasets. In both communities, the datasets are massive, and are stored in distributed archives that are, in most cases, remote from the available Computational resources. Therefore, state of the art computational grid technologies are a key element of the Montage portal architecture. This paper describes the aspects of the Montage design that are applicable to both the Earth and Space science communities.

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.

A network-based training environment: a medical image processing paradigm.

PubMed

Costaridou, L; Panayiotakis, G; Sakellaropoulos, P; Cavouras, D; Dimopoulos, J

1998-01-01

The capability of interactive multimedia and Internet technologies is investigated with respect to the implementation of a distance learning environment. The system is built according to a client-server architecture, based on the Internet infrastructure, composed of server nodes conceptually modelled as WWW sites. Sites are implemented by customization of available components. The environment integrates network-delivered interactive multimedia courses, network-based tutoring, SIG support, information databases of professional interest, as well as course and tutoring management. This capability has been demonstrated by means of an implemented system, validated with digital image processing content, specifically image enhancement. Image enhancement methods are theoretically described and applied to mammograms. Emphasis is given to the interactive presentation of the effects of algorithm parameters on images. The system end-user access depends on available bandwidth, so high-speed access can be achieved via LAN or local ISDN connections. Network based training offers new means of improved access and sharing of learning resources and expertise, as promising supplements in training.

Optical coherence microscopy as a novel, non-invasive method for the 4D live imaging of early mammalian embryos.

PubMed

Karnowski, Karol; Ajduk, Anna; Wieloch, Bartosz; Tamborski, Szymon; Krawiec, Krzysztof; Wojtkowski, Maciej; Szkulmowski, Maciej

2017-06-23

Imaging of living cells based on traditional fluorescence and confocal laser scanning microscopy has delivered an enormous amount of information critical for understanding biological processes in single cells. However, the requirement for a high numerical aperture and fluorescent markers still limits researchers' ability to visualize the cellular architecture without causing short- and long-term photodamage. Optical coherence microscopy (OCM) is a promising alternative that circumvents the technical limitations of fluorescence imaging techniques and provides unique access to fundamental aspects of early embryonic development, without the requirement for sample pre-processing or labeling. In the present paper, we utilized the internal motion of cytoplasm, as well as custom scanning and signal processing protocols, to effectively reduce the speckle noise typical for standard OCM and enable high-resolution intracellular time-lapse imaging. To test our imaging system we used mouse and pig oocytes and embryos and visualized them through fertilization and the first embryonic division, as well as at selected stages of oogenesis and preimplantation development. Because all morphological and morphokinetic properties recorded by OCM are believed to be biomarkers of oocyte/embryo quality, OCM may represent a new chapter in imaging-based preimplantation embryo diagnostics.

Determining skeletal muscle architecture with Laplacian simulations: a comparison with diffusion tensor imaging.

PubMed

Handsfield, Geoffrey G; Bolsterlee, Bart; Inouye, Joshua M; Herbert, Robert D; Besier, Thor F; Fernandez, Justin W

2017-12-01

Determination of skeletal muscle architecture is important for accurately modeling muscle behavior. Current methods for 3D muscle architecture determination can be costly and time-consuming, making them prohibitive for clinical or modeling applications. Computational approaches such as Laplacian flow simulations can estimate muscle fascicle orientation based on muscle shape and aponeurosis location. The accuracy of this approach is unknown, however, since it has not been validated against other standards for muscle architecture determination. In this study, muscle architectures from the Laplacian approach were compared to those determined from diffusion tensor imaging in eight adult medial gastrocnemius muscles. The datasets were subdivided into training and validation sets, and computational fluid dynamics software was used to conduct Laplacian simulations. In training sets, inputs of muscle geometry, aponeurosis location, and geometric flow guides resulted in good agreement between methods. Application of the method to validation sets showed no significant differences in pennation angle (mean difference [Formula: see text] or fascicle length (mean difference 0.9 mm). Laplacian simulation was thus effective at predicting gastrocnemius muscle architectures in healthy volunteers using imaging-derived muscle shape and aponeurosis locations. This method may serve as a tool for determining muscle architecture in silico and as a complement to other approaches.

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.

Measurement of hepatic steatosis based on magnetic resonance images

NASA Astrophysics Data System (ADS)

Tkaczyk, Adam; Jańczyk, Wojciech; Chełstowska, Sylwia; Socha, Piotr; Mulawka, Jan

2017-08-01

The subject of this work is the usage of digital image processing to measure hepatic steatosis. To calculate this value manually it requires a lot of time and precision from the radiologist. In order to resolve this issue, a C++ application has been created. This paper describes the algorithms that have been used to solve the problem. The next chapter presents the application architecture and introduces graphical user interface. The last section describes all the tests which have been carried out to check the correctness of the results.

CT imaging spectrum of infiltrative renal diseases.

PubMed

Ballard, David H; De Alba, Luis; Migliaro, Matias; Previgliano, Carlos H; Sangster, Guillermo P

2017-11-01

Most renal lesions replace the renal parenchyma as a focal space-occupying mass with borders distinguishing the mass from normal parenchyma. However, some renal lesions exhibit interstitial infiltration-a process that permeates the renal parenchyma by using the normal renal architecture for growth. These infiltrative lesions frequently show nonspecific patterns that lead to little or no contour deformity and have ill-defined borders on CT, making detection and diagnosis challenging. The purpose of this pictorial essay is to describe the CT imaging findings of various conditions that may manifest as infiltrative renal lesions.

Architecture and data processing alternatives for the TSE computer. Volume 2: Extraction of topological information from an image by the Tse computer

NASA Technical Reports Server (NTRS)

Jones, J. R.; Bodenheimer, R. E.

1976-01-01

A simple programmable Tse processor organization and arithmetic operations necessary for extraction of the desired topological information are described. Hardware additions to this organization are discussed along with trade-offs peculiar to the tse computing concept. An improved organization is presented along with the complementary software for the various arithmetic operations. The performance of the two organizations is compared in terms of speed, power, and cost. Software routines developed to extract the desired information from an image are included.

Medical image archive node simulation and architecture

NASA Astrophysics Data System (ADS)

Chiang, Ted T.; Tang, Yau-Kuo

1996-05-01

It is a well known fact that managed care and new treatment technologies are revolutionizing the health care provider world. Community Health Information Network and Computer-based Patient Record projects are underway throughout the United States. More and more hospitals are installing digital, `filmless' radiology (and other imagery) systems. They generate a staggering amount of information around the clock. For example, a typical 500-bed hospital might accumulate more than 5 terabytes of image data in a period of 30 years for conventional x-ray images and digital images such as Magnetic Resonance Imaging and Computer Tomography images. With several hospitals contributing to the archive, the storage required will be in the hundreds of terabytes. Systems for reliable, secure, and inexpensive storage and retrieval of digital medical information do not exist today. In this paper, we present a Medical Image Archive and Distribution Service (MIADS) concept. MIADS is a system shared by individual and community hospitals, laboratories, and doctors' offices that need to store and retrieve medical images. Due to the large volume and complexity of the data, as well as the diversified user access requirement, implementation of the MIADS will be a complex procedure. One of the key challenges to implementing a MIADS is to select a cost-effective, scalable system architecture to meet the ingest/retrieval performance requirements. We have performed an in-depth system engineering study, and developed a sophisticated simulation model to address this key challenge. This paper describes the overall system architecture based on our system engineering study and simulation results. In particular, we will emphasize system scalability and upgradability issues. Furthermore, we will discuss our simulation results in detail. The simulations study the ingest/retrieval performance requirements based on different system configurations and architectures for variables such as workload, tape access time, number of drives, number of exams per patient, number of Central Processing Units, patient grouping, and priority impacts. The MIADS, which could be a key component of a broader data repository system, will be able to communicate with and obtain data from existing hospital information systems. We will discuss the external interfaces enabling MIADS to communicate with and obtain data from existing Radiology Information Systems such as the Picture Archiving and Communication System (PACS). Our system design encompasses the broader aspects of the archive node, which could include multimedia data such as image, audio, video, and free text data. This system is designed to be integrated with current hospital PACS through a Digital Imaging and Communications in Medicine interface. However, the system can also be accessed through the Internet using Hypertext Transport Protocol or Simple File Transport Protocol. Our design and simulation work will be key to implementing a successful, scalable medical image archive and distribution system.

Design Method For Ultra-High Resolution Linear CCD Imagers

NASA Astrophysics Data System (ADS)

Sheu, Larry S.; Truong, Thanh; Yuzuki, Larry; Elhatem, Abdul; Kadekodi, Narayan

1984-11-01

This paper presents the design method to achieve ultra-high resolution linear imagers. This method utilizes advanced design rules and novel staggered bilinear photo sensor arrays with quadrilinear shift registers. Design constraint in the detector arrays and shift registers are analyzed. Imager architecture to achieve ultra-high resolution is presented. The characteristics of MTF, aliasing, speed, transfer efficiency and fine photolithography requirements associated with this architecture are also discussed. A CCD imager with advanced 1.5 um minimum feature size was fabricated. It is intended as a test vehicle for the next generation small sampling pitch ultra-high resolution CCD imager. Standard double-poly, two-phase shift registers were fabricated at an 8 um pitch using the advanced design rules. A special process step that blocked the source-drain implant from the shift register area was invented. This guaranteed excellent performance of the shift registers regardless of the small poly overlaps. A charge transfer efficiency of better than 0.99995 and maximum transfer speed of 8 MHz were achieved. The imager showed excellent performance. The dark current was less than 0.2 mV/ms, saturation 250 mV, adjacent photoresponse non-uniformity ± 4% and responsivity 0.7 V/ μJ/cm2 for the 8 μm x 6 μm photosensor size. The MTF was 0.6 at 62.5 cycles/mm. These results confirm the feasibility of the next generation ultra-high resolution CCD imagers.

Peer-to-peer architecture for multi-departmental distributed PACS

NASA Astrophysics Data System (ADS)

Rosset, Antoine; Heuberger, Joris; Pysher, Lance; Ratib, Osman

2006-03-01

We have elected to explore peer-to-peer technology as an alternative to centralized PACS architecture for the increasing requirements for wide access to images inside and outside a radiology department. The goal being to allow users across the enterprise to access any study anytime without the need for prefetching or routing of images from central archive. Images can be accessed between different workstations and local storage nodes. We implemented "bonjour" a new remote file access technology developed by Apple allowing applications to share data and files remotely with optimized data access and data transfer. Our Open-source image display platform called OsiriX was adapted to allow sharing of local DICOM images through direct access of each local SQL database to be accessible from any other OsiriX workstation over the network. A server version of Osirix Core Data database also allows to access distributed archives servers in the same way. The infrastructure implemented allows fast and efficient access to any image anywhere anytime independently from the actual physical location of the data. It also allows benefiting from the performance of distributed low-cost and high capacity storage servers that can provide efficient caching of PACS data that was found to be 10 to 20 x faster that accessing the same date from the central PACS archive. It is particularly suitable for large hospitals and academic environments where clinical conferences, interdisciplinary discussions and successive sessions of image processing are often part of complex workflow or patient management and decision making.

When Neuroscience 'Touches' Architecture: From Hapticity to a Supramodal Functioning of the Human Brain.

PubMed

Papale, Paolo; Chiesi, Leonardo; Rampinini, Alessandra C; Pietrini, Pietro; Ricciardi, Emiliano

2016-01-01

In the last decades, the rapid growth of functional brain imaging methodologies allowed cognitive neuroscience to address open questions in philosophy and social sciences. At the same time, novel insights from cognitive neuroscience research have begun to influence various disciplines, leading to a turn to cognition and emotion in the fields of planning and architectural design. Since 2003, the Academy of Neuroscience for Architecture has been supporting 'neuro-architecture' as a way to connect neuroscience and the study of behavioral responses to the built environment. Among the many topics related to multisensory perceptual integration and embodiment, the concept of hapticity was recently introduced, suggesting a pivotal role of tactile perception and haptic imagery in architectural appraisal. Arguments have thus risen in favor of the existence of shared cognitive foundations between hapticity and the supramodal functional architecture of the human brain. Precisely, supramodality refers to the functional feature of defined brain regions to process and represent specific information content in a more abstract way, independently of the sensory modality conveying such information to the brain. Here, we highlight some commonalities and differences between the concepts of hapticity and supramodality according to the distinctive perspectives of architecture and cognitive neuroscience. This comparison and connection between these two different approaches may lead to novel observations in regard to people-environment relationships, and even provide empirical foundations for a renewed evidence-based design theory.

Cryogenic Pupil Alignment Test Architecture for Aberrated Pupil Images

NASA Technical Reports Server (NTRS)

Bos, Brent; Kubalak, David A.; Antonille, Scott; Ohl, Raymond; Hagopian, John G.

2009-01-01

A document describes cryogenic test architecture for the James Webb Space Telescope (JWST) integrated science instrument module (ISIM). The ISIM element primarily consists of a mechanical metering structure, three science instruments, and a fine guidance sensor. One of the critical optomechanical alignments is the co-registration of the optical telescope element (OTE) exit pupil with the entrance pupils of the ISIM instruments. The test architecture has been developed to verify that the ISIM element will be properly aligned with the nominal OTE exit pupil when the two elements come together. The architecture measures three of the most critical pupil degrees-of-freedom during optical testing of the ISIM element. The pupil measurement scheme makes use of specularly reflective pupil alignment references located inside the JWST instruments, ground support equipment that contains a pupil imaging module, an OTE simulator, and pupil viewing channels in two of the JWST flight instruments. Pupil alignment references (PARs) are introduced into the instrument, and their reflections are checked using the instrument's mirrors. After the pupil imaging module (PIM) captures a reflected PAR image, the image will be analyzed to determine the relative alignment offset. The instrument pupil alignment preferences are specularly reflective mirrors with non-reflective fiducials, which makes the test architecture feasible. The instrument channels have fairly large fields of view, allowing PAR tip/tilt tolerances on the order of 0.5deg.

Development of IR imaging system simulator

NASA Astrophysics Data System (ADS)

Xiang, Xinglang; He, Guojing; Dong, Weike; Dong, Lu

2017-02-01

To overcome the disadvantages of the tradition semi-physical simulation and injection simulation equipment in the performance evaluation of the infrared imaging system (IRIS), a low-cost and reconfigurable IRIS simulator, which can simulate the realistic physical process of infrared imaging, is proposed to test and evaluate the performance of the IRIS. According to the theoretical simulation framework and the theoretical models of the IRIS, the architecture of the IRIS simulator is constructed. The 3D scenes are generated and the infrared atmospheric transmission effects are simulated using OGRE technology in real-time on the computer. The physical effects of the IRIS are classified as the signal response characteristic, modulation transfer characteristic and noise characteristic, and they are simulated on the single-board signal processing platform based on the core processor FPGA in real-time using high-speed parallel computation method.

General-purpose interface bus for multiuser, multitasking computer system

NASA Technical Reports Server (NTRS)

Generazio, Edward R.; Roth, Don J.; Stang, David B.

1990-01-01

The architecture of a multiuser, multitasking, virtual-memory computer system intended for the use by a medium-size research group is described. There are three central processing units (CPU) in the configuration, each with 16 MB memory, and two 474 MB hard disks attached. CPU 1 is designed for data analysis and contains an array processor for fast-Fourier transformations. In addition, CPU 1 shares display images viewed with the image processor. CPU 2 is designed for image analysis and display. CPU 3 is designed for data acquisition and contains 8 GPIB channels and an analog-to-digital conversion input/output interface with 16 channels. Up to 9 users can access the third CPU simultaneously for data acquisition. Focus is placed on the optimization of hardware interfaces and software, facilitating instrument control, data acquisition, and processing.

Time-to-impact sensors in robot vision applications based on the near-sensor image processing concept

NASA Astrophysics Data System (ADS)

Åström, Anders; Forchheimer, Robert

2012-03-01

Based on the Near-Sensor Image Processing (NSIP) concept and recent results concerning optical flow and Time-to- Impact (TTI) computation with this architecture, we show how these results can be used and extended for robot vision applications. The first case involves estimation of the tilt of an approaching planar surface. The second case concerns the use of two NSIP cameras to estimate absolute distance and speed similar to a stereo-matching system but without the need to do image correlations. Going back to a one-camera system, the third case deals with the problem to estimate the shape of the approaching surface. It is shown that the previously developed TTI method not only gives a very compact solution with respect to hardware complexity, but also surprisingly high performance.

Image acquisition context: procedure description attributes for clinically relevant indexing and selective retrieval of biomedical images.

PubMed

Bidgood, W D; Bray, B; Brown, N; Mori, A R; Spackman, K A; Golichowski, A; Jones, R H; Korman, L; Dove, B; Hildebrand, L; Berg, M

1999-01-01

To support clinically relevant indexing of biomedical images and image-related information based on the attributes of image acquisition procedures and the judgments (observations) expressed by observers in the process of image interpretation. The authors introduce the notion of "image acquisition context," the set of attributes that describe image acquisition procedures, and present a standards-based strategy for utilizing the attributes of image acquisition context as indexing and retrieval keys for digital image libraries. The authors' indexing strategy is based on an interdependent message/terminology architecture that combines the Digital Imaging and Communication in Medicine (DICOM) standard, the SNOMED (Systematized Nomenclature of Human and Veterinary Medicine) vocabulary, and the SNOMED DICOM microglossary. The SNOMED DICOM microglossary provides context-dependent mapping of terminology to DICOM data elements. The capability of embedding standard coded descriptors in DICOM image headers and image-interpretation reports improves the potential for selective retrieval of image-related information. This favorably affects information management in digital libraries.

A Biologically-Inspired Neural Network Architecture for Image Processing

DTIC Science & Technology

1990-12-01

was organized into twelve groups of 8-by-8 node arrays. Weights were con- strained for each group of nodes, with each node "viewing" a 5-by-5 pixel...single wIndow * smk 0; for(J-0; j< 6 4 ; J++)( sum -sum +t %borfi][J]*rfarray[j]; ) /* Finished calculating ore block, one j:,,sition (first layer

Feature-extracted joint transform correlation.

PubMed

Alam, M S

1995-12-10

A new technique for real-time optical character recognition that uses a joint transform correlator is proposed. This technique employs feature-extracted patterns for the reference image to detect a wide range of characters in one step. The proposed technique significantly enhances the processing speed when compared with the presently available joint transform correlator architectures and shows feasibility for multichannel joint transform correlation.

Processor architecture for airborne SAR systems

NASA Technical Reports Server (NTRS)

Glass, C. M.

1983-01-01

Digital processors for spaceborne imaging radars and application of the technology developed for airborne SAR systems are considered. Transferring algorithms and implementation techniques from airborne to spaceborne SAR processors offers obvious advantages. The following topics are discussed: (1) a quantification of the differences in processing algorithms for airborne and spaceborne SARs; and (2) an overview of three processors for airborne SAR systems.

Competing in the brave new (deregulated) world: Service innovation and brand strategy for utilities

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

Foster, D.; Lathrop, S.; Wolf, A.

This paper will address ways utilities can gain a competitive advantage despite industry turbulence. It details how to create successful brand and innovation strategies and how to link these in order to create successful new products and services for customers. After gaining a solid understanding of industry trends, the first step is to develop an ideal brand image and create a brand strategy around it. Next, companies must determine how to roll out and leverage brands to targeted customer segments over time through a brand architecture. Then, they must build an innovation strategy, defining where and how to apply newmore » technologies and develop new products and services. This strategy is linked to the brand architecture through a product architecture. Finally, companies must be able to successfully develop new products and services through a well-planned innovation process.« less

Digital visual communications using a Perceptual Components Architecture

NASA Technical Reports Server (NTRS)

Watson, Andrew B.

1991-01-01

The next era of space exploration will generate extraordinary volumes of image data, and management of this image data is beyond current technical capabilities. We propose a strategy for coding visual information that exploits the known properties of early human vision. This Perceptual Components Architecture codes images and image sequences in terms of discrete samples from limited bands of color, spatial frequency, orientation, and temporal frequency. This spatiotemporal pyramid offers efficiency (low bit rate), variable resolution, device independence, error-tolerance, and extensibility.

ScipionCloud: An integrative and interactive gateway for large scale cryo electron microscopy image processing on commercial and academic clouds.

PubMed

Cuenca-Alba, Jesús; Del Cano, Laura; Gómez Blanco, Josué; de la Rosa Trevín, José Miguel; Conesa Mingo, Pablo; Marabini, Roberto; S Sorzano, Carlos Oscar; Carazo, Jose María

2017-10-01

New instrumentation for cryo electron microscopy (cryoEM) has significantly increased data collection rate as well as data quality, creating bottlenecks at the image processing level. Current image processing model of moving the acquired images from the data source (electron microscope) to desktops or local clusters for processing is encountering many practical limitations. However, computing may also take place in distributed and decentralized environments. In this way, cloud is a new form of accessing computing and storage resources on demand. Here, we evaluate on how this new computational paradigm can be effectively used by extending our current integrative framework for image processing, creating ScipionCloud. This new development has resulted in a full installation of Scipion both in public and private clouds, accessible as public "images", with all the required preinstalled cryoEM software, just requiring a Web browser to access all Graphical User Interfaces. We have profiled the performance of different configurations on Amazon Web Services and the European Federated Cloud, always on architectures incorporating GPU's, and compared them with a local facility. We have also analyzed the economical convenience of different scenarios, so cryoEM scientists have a clearer picture of the setup that is best suited for their needs and budgets. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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.

Confocal fluorescence microscope with dual-axis architecture and biaxial postobjective scanning

PubMed Central

Wang, Thomas D.; Contag, Christopher H.; Mandella, Michael J.; Chan, Ning Y.; Kino, Gordon S.

2007-01-01

We present a novel confocal microscope that has dual-axis architecture and biaxial postobjective scanning for the collection of fluorescence images from biological specimens. This design uses two low-numerical-aperture lenses to achieve high axial resolution and long working distance, and the scanning mirror located distal to the lenses rotates along the orthogonal axes to produce arc-surface images over a large field of view (FOV). With fiber optic coupling, this microscope can potentially be scaled down to millimeter dimensions via microelectromechanical systems (MEMS) technology. We demonstrate a benchtop prototype with a spatial resolution ≤4.4 μm that collects fluorescence images with a high SNR and a good contrast ratio from specimens expressing GFP. Furthermore, the scanning mechanism produces only small differences in aberrations over the image FOV. These results demonstrate proof of concept of the dual-axis confocal architecture for in vivo molecular and cellular imaging. PMID:15250760

Image Acquisition Context

PubMed Central

Bidgood, W. Dean; Bray, Bruce; Brown, Nicolas; Mori, Angelo Rossi; Spackman, Kent A.; Golichowski, Alan; Jones, Robert H.; Korman, Louis; Dove, Brent; Hildebrand, Lloyd; Berg, Michael

1999-01-01

Objective: To support clinically relevant indexing of biomedical images and image-related information based on the attributes of image acquisition procedures and the judgments (observations) expressed by observers in the process of image interpretation. Design: The authors introduce the notion of “image acquisition context,” the set of attributes that describe image acquisition procedures, and present a standards-based strategy for utilizing the attributes of image acquisition context as indexing and retrieval keys for digital image libraries. Methods: The authors' indexing strategy is based on an interdependent message/terminology architecture that combines the Digital Imaging and Communication in Medicine (DICOM) standard, the SNOMED (Systematized Nomenclature of Human and Veterinary Medicine) vocabulary, and the SNOMED DICOM microglossary. The SNOMED DICOM microglossary provides context-dependent mapping of terminology to DICOM data elements. Results: The capability of embedding standard coded descriptors in DICOM image headers and image-interpretation reports improves the potential for selective retrieval of image-related information. This favorably affects information management in digital libraries. PMID:9925229

Tracking the mammary architectural features and detecting breast cancer with magnetic resonance diffusion tensor imaging.

PubMed

Nissan, Noam; Furman-Haran, Edna; Feinberg-Shapiro, Myra; Grobgeld, Dov; Eyal, Erez; Zehavi, Tania; Degani, Hadassa

2014-12-15

Breast cancer is the most common cause of cancer among women worldwide. Early detection of breast cancer has a critical role in improving the quality of life and survival of breast cancer patients. In this paper a new approach for the detection of breast cancer is described, based on tracking the mammary architectural elements using diffusion tensor imaging (DTI). The paper focuses on the scanning protocols and image processing algorithms and software that were designed to fit the diffusion properties of the mammary fibroglandular tissue and its changes during malignant transformation. The final output yields pixel by pixel vector maps that track the architecture of the entire mammary ductal glandular trees and parametric maps of the diffusion tensor coefficients and anisotropy indices. The efficiency of the method to detect breast cancer was tested by scanning women volunteers including 68 patients with breast cancer confirmed by histopathology findings. Regions with cancer cells exhibited a marked reduction in the diffusion coefficients and in the maximal anisotropy index as compared to the normal breast tissue, providing an intrinsic contrast for delineating the boundaries of malignant growth. Overall, the sensitivity of the DTI parameters to detect breast cancer was found to be high, particularly in dense breasts, and comparable to the current standard breast MRI method that requires injection of a contrast agent. Thus, this method offers a completely non-invasive, safe and sensitive tool for breast cancer detection.

NASA Tech Briefs, June 2013

NASA Technical Reports Server (NTRS)

2013-01-01

Topics include: Cloud Absorption Radiometer Autonomous Navigation System - CANS, Software Method for Computed Tomography Cylinder Data Unwrapping, Re-slicing, and Analysis, Discrete Data Qualification System and Method Comprising Noise Series Fault Detection, Simple Laser Communications Terminal for Downlink from Earth Orbit at Rates Exceeding 10 Gb/s, Application Program Interface for the Orion Aerodynamics Database, Hyperspectral Imager-Tracker, Web Application Software for Ground Operations Planning Database (GOPDb) Management, Software Defined Radio with Parallelized Software Architecture, Compact Radar Transceiver with Included Calibration, Software Defined Radio with Parallelized Software Architecture, Phase Change Material Thermal Power Generator, The Thermal Hogan - A Means of Surviving the Lunar Night, Micromachined Active Magnetic Regenerator for Low-Temperature Magnetic Coolers, Nano-Ceramic Coated Plastics, Preparation of a Bimetal Using Mechanical Alloying for Environmental or Industrial Use, Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO, Dual-Compartment Inflatable Suitlock, Modular Connector Keying Concept, Genesis Ultrapure Water Megasonic Wafer Spin Cleaner, Piezoelectrically Initiated Pyrotechnic Igniter, Folding Elastic Thermal Surface - FETS, Multi-Pass Quadrupole Mass Analyzer, Lunar Sulfur Capture System, Environmental Qualification of a Single-Crystal Silicon Mirror for Spaceflight Use, Planar Superconducting Millimeter-Wave/Terahertz Channelizing Filter, Qualification of UHF Antenna for Extreme Martian Thermal Environments, Ensemble Eclipse: A Process for Prefab Development Environment for the Ensemble Project, ISS Live!, Space Operations Learning Center (SOLC) iPhone/iPad Application, Software to Compare NPP HDF5 Data Files, Planetary Data Systems (PDS) Imaging Node Atlas II, Automatic Calibration of an Airborne Imaging System to an Inertial Navigation Unit, Translating MAPGEN to ASPEN for MER, Support Routines for In Situ Image Processing, and Semi-Supervised Eigenbasis Novelty Detection.

Computational Performance of Intel MIC, Sandy Bridge, and GPU Architectures: Implementation of a 1D c++/OpenMP Electrostatic Particle-In-Cell Code

DTIC Science & Technology

2014-05-01

fusion, space and astrophysical plasmas, but still the general picture can be presented quite well with the fluid approach [6, 7]. The microscopic...purpose computing CPU for algorithms where processing of large blocks of data is done in parallel. The reason for that is the GPU’s highly effective...parallel structure. Most of the image and video processing computations involve heavy matrix and vector op- erations over large amounts of data and

Experimental investigation of a page-oriented Lippmann holographic data storage system

NASA Astrophysics Data System (ADS)

Pauliat, Gilles; Contreras, Kevin

2010-06-01

Lippmann photography is a more than one century old interferometric process invented for recording colored images in thick black and white photographic emulsions. After a comparison between this photographic process and Denisyuk holography, we feature some hints to apply this technique to high density data storage by wavelength multiplexing in a page-oriented approach in thick media. For the first time we experimentally investigate this approach. We anticipated that this storage architecture should allow capacities as large as for conventional holography.

Image Processing

NASA Technical Reports Server (NTRS)

1987-01-01

A new spinoff product was derived from Geospectra Corporation's expertise in processing LANDSAT data in a software package. Called ATOM (for Automatic Topographic Mapping), it's capable of digitally extracting elevation information from stereo photos taken by spaceborne cameras. ATOM offers a new dimension of realism in applications involving terrain simulations, producing extremely precise maps of an area's elevations at a lower cost than traditional methods. ATOM has a number of applications involving defense training simulations and offers utility in architecture, urban planning, forestry, petroleum and mineral exploration.

Semi-automatic mapping of fault rocks on a Digital Outcrop Model, Gole Larghe Fault Zone (Southern Alps, Italy)

NASA Astrophysics Data System (ADS)

Vho, Alice; Bistacchi, Andrea

2015-04-01

A quantitative analysis of fault-rock distribution is of paramount importance for studies of fault zone architecture, fault and earthquake mechanics, and fluid circulation along faults at depth. Here we present a semi-automatic workflow for fault-rock mapping on a Digital Outcrop Model (DOM). This workflow has been developed on a real case of study: the strike-slip Gole Larghe Fault Zone (GLFZ). It consists of a fault zone exhumed from ca. 10 km depth, hosted in granitoid rocks of Adamello batholith (Italian Southern Alps). Individual seismogenic slip surfaces generally show green cataclasites (cemented by the precipitation of epidote and K-feldspar from hydrothermal fluids) and more or less well preserved pseudotachylytes (black when well preserved, greenish to white when altered). First of all, a digital model for the outcrop is reconstructed with photogrammetric techniques, using a large number of high resolution digital photographs, processed with VisualSFM software. By using high resolution photographs the DOM can have a much higher resolution than with LIDAR surveys, up to 0.2 mm/pixel. Then, image processing is performed to map the fault-rock distribution with the ImageJ-Fiji package. Green cataclasites and epidote/K-feldspar veins can be quite easily separated from the host rock (tonalite) using spectral analysis. Particularly, band ratio and principal component analysis have been tested successfully. The mapping of black pseudotachylyte veins is more tricky because the differences between the pseudotachylyte and biotite spectral signature are not appreciable. For this reason we have tested different morphological processing tools aimed at identifying (and subtracting) the tiny biotite grains. We propose a solution based on binary images involving a combination of size and circularity thresholds. Comparing the results with manually segmented images, we noticed that major problems occur only when pseudotachylyte veins are very thin and discontinuous. After having tested and refined the image analysis processing for some typical images, we have recorded a macro with ImageJ-Fiji allowing to process all the images for a given DOM. As a result, the three different types of rocks can be semi-automatically mapped on large DOMs using a simple and efficient procedure. This allows to develop quantitative analyses of fault rock distribution and thickness, fault trace roughness/curvature and length, fault zone architecture, and alteration halos due to hydrothermal fluid-rock interaction. To improve our workflow, additional or different morphological operators could be integrated in our procedure to yield a better resolution on small and thin pseudotachylyte veins (e.g. perimeter/area ratio).

Thin client (web browser)-based collaboration for medical imaging and web-enabled data.

PubMed

Le, Tuong Huu; Malhi, Nadeem

2002-01-01

Utilizing thin client software and open source server technology, a collaborative architecture was implemented allowing for sharing of Digital Imaging and Communications in Medicine (DICOM) and non-DICOM images with real-time markup. Using the Web browser as a thin client integrated with standards-based components, such as DHTML (dynamic hypertext markup language), JavaScript, and Java, collaboration was achieved through a Web server/proxy server combination utilizing Java Servlets and Java Server Pages. A typical collaborative session involved the driver, who directed the navigation of the other collaborators, the passengers, and provided collaborative markups of medical and nonmedical images. The majority of processing was performed on the server side, allowing for the client to remain thin and more accessible.

Fundamental performance differences between CMOS and CCD imagers: Part II

NASA Astrophysics Data System (ADS)

Janesick, James; Andrews, James; Tower, John; Grygon, Mark; Elliott, Tom; Cheng, John; Lesser, Michael; Pinter, Jeff

2007-09-01

A new class of CMOS imagers that compete with scientific CCDs is presented. The sensors are based on deep depletion backside illuminated technology to achieve high near infrared quantum efficiency and low pixel cross-talk. The imagers deliver very low read noise suitable for single photon counting - Fano-noise limited soft x-ray applications. Digital correlated double sampling signal processing necessary to achieve low read noise performance is analyzed and demonstrated for CMOS use. Detailed experimental data products generated by different pixel architectures (notably 3TPPD, 5TPPD and 6TPG designs) are presented including read noise, charge capacity, dynamic range, quantum efficiency, charge collection and transfer efficiency and dark current generation. Radiation damage data taken for the imagers is also reported.

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.

Evaluation of computational endomicroscopy architectures for minimally-invasive optical biopsy

NASA Astrophysics Data System (ADS)

Dumas, John P.; Lodhi, Muhammad A.; Bajwa, Waheed U.; Pierce, Mark C.

2017-02-01

We are investigating compressive sensing architectures for applications in endomicroscopy, where the narrow diameter probes required for tissue access can limit the achievable spatial resolution. We hypothesize that the compressive sensing framework can be used to overcome the fundamental pixel number limitation in fiber-bundle based endomicroscopy by reconstructing images with more resolvable points than fibers in the bundle. An experimental test platform was assembled to evaluate and compare two candidate architectures, based on introducing a coded amplitude mask at either a conjugate image or Fourier plane within the optical system. The benchtop platform consists of a common illumination and object path followed by separate imaging arms for each compressive architecture. The imaging arms contain a digital micromirror device (DMD) as a reprogrammable mask, with a CCD camera for image acquisition. One arm has the DMD positioned at a conjugate image plane ("IP arm"), while the other arm has the DMD positioned at a Fourier plane ("FP arm"). Lenses were selected and positioned within each arm to achieve an element-to-pixel ratio of 16 (230,400 mask elements mapped onto 14,400 camera pixels). We discuss our mathematical model for each system arm and outline the importance of accounting for system non-idealities. Reconstruction of a 1951 USAF resolution target using optimization-based compressive sensing algorithms produced images with higher spatial resolution than bicubic interpolation for both system arms when system non-idealities are included in the model. Furthermore, images generated with image plane coding appear to exhibit higher spatial resolution, but more noise, than images acquired through Fourier plane coding.

Parallel Wavefront Analysis for a 4D Interferometer

NASA Technical Reports Server (NTRS)

Rao, Shanti R.

2011-01-01

This software provides a programming interface for automating data collection with a PhaseCam interferometer from 4D Technology, and distributing the image-processing algorithm across a cluster of general-purpose computers. Multiple instances of 4Sight (4D Technology s proprietary software) run on a networked cluster of computers. Each connects to a single server (the controller) and waits for instructions. The controller directs the interferometer to several images, then assigns each image to a different computer for processing. When the image processing is finished, the server directs one of the computers to collate and combine the processed images, saving the resulting measurement in a file on a disk. The available software captures approximately 100 images and analyzes them immediately. This software separates the capture and analysis processes, so that analysis can be done at a different time and faster by running the algorithm in parallel across several processors. The PhaseCam family of interferometers can measure an optical system in milliseconds, but it takes many seconds to process the data so that it is usable. In characterizing an adaptive optics system, like the next generation of astronomical observatories, thousands of measurements are required, and the processing time quickly becomes excessive. A programming interface distributes data processing for a PhaseCam interferometer across a Windows computing cluster. A scriptable controller program coordinates data acquisition from the interferometer, storage on networked hard disks, and parallel processing. Idle time of the interferometer is minimized. This architecture is implemented in Python and JavaScript, and may be altered to fit a customer s needs.

Next Generation Image-Based Phenotyping of Root System Architecture

NASA Astrophysics Data System (ADS)

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

2016-12-01

The development of the Plant Root Imaging and Data Acquisition (PRIDA) hardware/software system enables researchers to collect digital images, along with all the relevant experimental details, of a range of hydroponically grown agricultural crop roots for 2D and 3D trait analysis. Previous efforts of image-based root phenotyping focused on young cereals, such as rice; however, there is a growing need to measure both older and larger root systems, such as those of maize and sorghum, to improve our understanding of the underlying genetics that control favorable rooting traits for plant breeding programs to combat the agricultural risks presented by climate change. Therefore, a larger imaging apparatus has been prototyped for capturing 3D root architecture with an adaptive control system and innovative plant root growth media that retains three-dimensional root architectural features. New publicly available multi-platform software has been released with considerations for both high throughput (e.g., 3D imaging of a single root system in under ten minutes) and high portability (e.g., support for the Raspberry Pi computer). The software features unified data collection, management, exploration and preservation for continued trait and genetics analysis of root system architecture. The new system makes data acquisition efficient and includes features that address the needs of researchers and technicians, such as reduced imaging time, semi-automated camera calibration with uncertainty characterization, and safe storage of the critical experimental data.

A Computationally Efficient Visual Saliency Algorithm Suitable for an Analog CMOS Implementation.

PubMed

D'Angelo, Robert; Wood, Richard; Lowry, Nathan; Freifeld, Geremy; Huang, Haiyao; Salthouse, Christopher D; Hollosi, Brent; Muresan, Matthew; Uy, Wes; Tran, Nhut; Chery, Armand; Poppe, Dorothy C; Sonkusale, Sameer

2018-06-27

Computer vision algorithms are often limited in their application by the large amount of data that must be processed. Mammalian vision systems mitigate this high bandwidth requirement by prioritizing certain regions of the visual field with neural circuits that select the most salient regions. This work introduces a novel and computationally efficient visual saliency algorithm for performing this neuromorphic attention-based data reduction. The proposed algorithm has the added advantage that it is compatible with an analog CMOS design while still achieving comparable performance to existing state-of-the-art saliency algorithms. This compatibility allows for direct integration with the analog-to-digital conversion circuitry present in CMOS image sensors. This integration leads to power savings in the converter by quantizing only the salient pixels. Further system-level power savings are gained by reducing the amount of data that must be transmitted and processed in the digital domain. The analog CMOS compatible formulation relies on a pulse width (i.e., time mode) encoding of the pixel data that is compatible with pulse-mode imagers and slope based converters often used in imager designs. This letter begins by discussing this time-mode encoding for implementing neuromorphic architectures. Next, the proposed algorithm is derived. Hardware-oriented optimizations and modifications to this algorithm are proposed and discussed. Next, a metric for quantifying saliency accuracy is proposed, and simulation results of this metric are presented. Finally, an analog synthesis approach for a time-mode architecture is outlined, and postsynthesis transistor-level simulations that demonstrate functionality of an implementation in a modern CMOS process are discussed.

Fiber micro-architecture in the longitudinal-radial and circumferential-radial planes of ascending thoracic aortic aneurysm media

PubMed Central

Tsamis, Alkiviadis; Phillippi, Julie A.; Koch, Ryan G.; Pasta, Salvatore; D'Amore, Antonio; Watkins, Simon C.; Wagner, William R.; Gleason, Thomas G.; Vorp, David A.

2013-01-01

It was recently demonstrated by our group that the delamination strength of ascending thoracic aortic aneurysms (ATAA) was lower than that of control (CTRL, non-aneurysmal) ascending thoracic aorta (ATA), and the reduced strength was more pronounced among bicuspid (BAV) vs. tricuspid aortic valve (TAV) patients, suggesting a different risk of aortic dissection for BAV patients. We hypothesized that aortic valve morphologic phenotype predicts fiber micro-architectural anomalies in ATA. To test the hypothesis, we characterized the micro-architecture in the longitudinal-radial (Z-RAD) and circumferential-radial (Θ-RAD) planes of human ATA tissue that was artificially dissected medially. The outer and inner-media of CTRL-ATA, BAV-ATAA and TAV-ATAA were imaged using multi-photon microscopy in the Z-RAD and Θ-RAD planes to observe collagen and elastin. Micrographs were processed using an image-based tool to quantify several micro-architectural characteristics. In the outer-media of BAV-ATAA, elastin was more undulated and less aligned about the Θ-axis when compared with CTRL-ATA, which is consistent with increased tensile stretch at inflection point of Θ-strips of adventitial-medial half of BAV-ATAA (1.28) when compared with CTRL-ATA (1.13). With increasing age, collagen became more undulated about the Z-axis within the outer-media of TAV-ATAA, and elastin became more oriented in the Z-axis and collagen less radially-oriented within the inner-media of TAV-ATAA. This discrepancy in the micro-architecture with fibers in the inner layers being more stretched and with disrupted radially-oriented components than fibers in the outer layers may be associated with the development, progression and vascular remodeling in aneurysms arising in TAV patients. PMID:24075403

Fiber micro-architecture in the longitudinal-radial and circumferential-radial planes of ascending thoracic aortic aneurysm media.

PubMed

Tsamis, Alkiviadis; Phillippi, Julie A; Koch, Ryan G; Pasta, Salvatore; D'Amore, Antonio; Watkins, Simon C; Wagner, William R; Gleason, Thomas G; Vorp, David A

2013-11-15

It was recently demonstrated by our group that the delamination strength of ascending thoracic aortic aneurysms (ATAA) was lower than that of control (CTRL, non-aneurysmal) ascending thoracic aorta (ATA), and the reduced strength was more pronounced among bicuspid (BAV) vs. tricuspid aortic valve (TAV) patients, suggesting a different risk of aortic dissection for BAV patients. We hypothesized that aortic valve morphologic phenotype predicts fiber micro-architectural anomalies in ATA. To test the hypothesis, we characterized the micro-architecture in the longitudinal-radial (Z-RAD) and circumferential-radial (Θ-RAD) planes of human ATA tissue that was artificially dissected medially. The outer and inner-media of CTRL-ATA, BAV-ATAA and TAV-ATAA were imaged using multi-photon microscopy in the Z-RAD and Θ-RAD planes to observe collagen and elastin. Micrographs were processed using an image-based tool to quantify several micro-architectural characteristics. In the outer-media of BAV-ATAA, elastin was more undulated and less aligned about the Θ-axis when compared with CTRL-ATA, which is consistent with increased tensile stretch at inflection point of Θ-strips of adventitial-medial half of BAV-ATAA (1.28) when compared with CTRL-ATA (1.13). With increasing age, collagen became more undulated about the Z-axis within the outer-media of TAV-ATAA, and elastin became more oriented in the Z-axis and collagen less radially-oriented within the inner-media of TAV-ATAA. This discrepancy in the micro-architecture with fibers in the inner layers being more stretched and with disrupted radially-oriented components than fibers in the outer layers may be associated with the development, progression and vascular remodeling in aneurysms arising in TAV patients. © 2013 Elsevier Ltd. All rights reserved.

Multiple-Sensor Discrimination of Closely-Spaced Objects on a Ballistic Trajectory

DTIC Science & Technology

2015-05-18

Nominal System Architecture ..................................................................................... 8 2 Simulation Environment... architecture ........................................................................................... 8 Figure 2. Simulation environment developed...uncertainty band for one or multiple sensors within the observation architecture . Resolving targets from one sensor image to another can prove difficult

Combining fluorescence imaging with Hi-C to study 3D genome architecture of the same single cell.

PubMed

Lando, David; Basu, Srinjan; Stevens, Tim J; Riddell, Andy; Wohlfahrt, Kai J; Cao, Yang; Boucher, Wayne; Leeb, Martin; Atkinson, Liam P; Lee, Steven F; Hendrich, Brian; Klenerman, Dave; Laue, Ernest D

2018-05-01

Fluorescence imaging and chromosome conformation capture assays such as Hi-C are key tools for studying genome organization. However, traditionally, they have been carried out independently, making integration of the two types of data difficult to perform. By trapping individual cell nuclei inside a well of a 384-well glass-bottom plate with an agarose pad, we have established a protocol that allows both fluorescence imaging and Hi-C processing to be carried out on the same single cell. The protocol identifies 30,000-100,000 chromosome contacts per single haploid genome in parallel with fluorescence images. Contacts can be used to calculate intact genome structures to better than 100-kb resolution, which can then be directly compared with the images. Preparation of 20 single-cell Hi-C libraries using this protocol takes 5 d of bench work by researchers experienced in molecular biology techniques. Image acquisition and analysis require basic understanding of fluorescence microscopy, and some bioinformatics knowledge is required to run the sequence-processing tools described here.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

NASA Astrophysics Data System (ADS)

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

PubMed

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-15

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

PubMed Central

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-01-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features. PMID:27079888

Integrating MRI-based geometry, composition and fiber architecture in a finite element model of the human intervertebral disc.

PubMed

Stadelmann, Marc A; Maquer, Ghislain; Voumard, Benjamin; Grant, Aaron; Hackney, David B; Vermathen, Peter; Alkalay, Ron N; Zysset, Philippe K

2018-05-17

Intervertebral disc degeneration is a common disease that is often related to impaired mechanical function, herniations and chronic back pain. The degenerative process induces alterations of the disc's shape, composition and structure that can be visualized in vivo using magnetic resonance imaging (MRI). Numerical tools such as finite element analysis (FEA) have the potential to relate MRI-based information to the altered mechanical behavior of the disc. However, in terms of geometry, composition and fiber architecture, current FE models rely on observations made on healthy discs and might therefore not be well suited to study the degeneration process. To address the issue, we propose a new, more realistic FE methodology based on diffusion tensor imaging (DTI). For this study, a human disc joint was imaged in a high-field MR scanner with proton-density weighted (PD) and DTI sequences. The PD image was segmented and an anatomy-specific mesh was generated. Assuming accordance between local principal diffusion direction and local mean collagen fiber alignment, corresponding fiber angles were assigned to each element. Those element-wise fiber directions and PD intensities allowed the homogenized model to smoothly account for composition and fibrous structure of the disc. The disc's in vitro mechanical behavior was quantified under tension, compression, flexion, extension, lateral bending and rotation. The six resulting load-displacement curves could be replicated by the FE model, which supports our approach as a first proof of concept towards patient-specific disc modeling. Copyright © 2018 Elsevier Ltd. All rights reserved.

Structural characterization of toxic oligomers that are kinetically trapped during α-synuclein fibril formation

PubMed Central

Chen, Serene W.; Drakulic, Srdja; Deas, Emma; Ouberai, Myriam; Aprile, Francesco A.; Arranz, Rocío; Ness, Samuel; Roodveldt, Cintia; Guilliams, Tim; De-Genst, Erwin J.; Klenerman, David; Wood, Nicholas W.; Knowles, Tuomas P.J.; Alfonso, Carlos; Rivas, Germán; Abramov, Andrey Y.; Valpuesta, José María; Dobson, Christopher M.; Cremades, Nunilo

2015-01-01

We describe the isolation and detailed structural characterization of stable toxic oligomers of α-synuclein that have accumulated during the process of amyloid formation. Our approach has allowed us to identify distinct subgroups of oligomers and to probe their molecular architectures by using cryo-electron microscopy (cryoEM) image reconstruction techniques. Although the oligomers exist in a range of sizes, with different extents and nature of β-sheet content and exposed hydrophobicity, they all possess a hollow cylindrical architecture with similarities to certain types of amyloid fibril, suggesting that the accumulation of at least some forms of amyloid oligomers is likely to be a consequence of very slow rates of rearrangement of their β-sheet structures. Our findings reveal the inherent multiplicity of the process of protein misfolding and the key role the β-sheet geometry acquired in the early stages of the self-assembly process plays in dictating the kinetic stability and the pathological nature of individual oligomeric species. PMID:25855634

Colt: an experiment in wormhole run-time reconfiguration

NASA Astrophysics Data System (ADS)

Bittner, Ray; Athanas, Peter M.; Musgrove, Mark

1996-10-01

Wormhole run-time reconfiguration (RTR) is an attempt to create a refined computing paradigm for high performance computational tasks. By combining concepts from field programmable gate array (FPGA) technologies with data flow computing, the Colt/Stallion architecture achieves high utilization of hardware resources, and facilitates rapid run-time reconfiguration. Targeted mainly at DSP-type operations, the Colt integrated circuit -- a prototype wormhole RTR device -- compares favorably to contemporary DSP alternatives in terms of silicon area consumed per unit computation and in computing performance. Although emphasis has been placed on signal processing applications, general purpose computation has not been overlooked. Colt is a prototype that defines an architecture not only at the chip level but also in terms of an overall system design. As this system is realized, the concept of wormhole RTR will be applied to numerical computation and DSP applications including those common to image processing, communications systems, digital filters, acoustic processing, real-time control systems and simulation acceleration.

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.

Raster Scan Computer Image Generation (CIG) System Based On Refresh Memory

NASA Astrophysics Data System (ADS)

Dichter, W.; Doris, K.; Conkling, C.

1982-06-01

A full color, Computer Image Generation (CIG) raster visual system has been developed which provides a high level of training sophistication by utilizing advanced semiconductor technology and innovative hardware and firmware techniques. Double buffered refresh memory and efficient algorithms eliminate the problem of conventional raster line ordering by allowing the generated image to be stored in a random fashion. Modular design techniques and simplified architecture provide significant advantages in reduced system cost, standardization of parts, and high reliability. The major system components are a general purpose computer to perform interfacing and data base functions; a geometric processor to define the instantaneous scene image; a display generator to convert the image to a video signal; an illumination control unit which provides final image processing; and a CRT monitor for display of the completed image. Additional optional enhancements include texture generators, increased edge and occultation capability, curved surface shading, and data base extensions.

A deep learning approach for pose estimation from volumetric OCT data.

PubMed

Gessert, Nils; Schlüter, Matthias; Schlaefer, Alexander

2018-05-01

Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging modality. OCT is suitable for accurate pose estimation due to its micrometer range resolution and volumetric field of view. However, OCT image processing is challenging due to speckle noise and reflection artifacts in addition to the images' 3D nature. We address pose estimation from OCT volume data with a new deep learning-based tracking framework. For this purpose, we design a new 3D convolutional neural network (CNN) architecture to directly predict the 6D pose of a small marker geometry from OCT volumes. We use a hexapod robot to automatically acquire labeled data points which we use to train 3D CNN architectures for multi-output regression. We use this setup to provide an in-depth analysis on deep learning-based pose estimation from volumes. Specifically, we demonstrate that exploiting volume information for pose estimation yields higher accuracy than relying on 2D representations with depth information. Supporting this observation, we provide quantitative and qualitative results that 3D CNNs effectively exploit the depth structure of marker objects. Regarding the deep learning aspect, we present efficient design principles for 3D CNNs, making use of insights from the 2D deep learning community. In particular, we present Inception3D as a new architecture which performs best for our application. We show that our deep learning approach reaches errors at our ground-truth label's resolution. We achieve a mean average error of 14.89 ± 9.3 µm and 0.096 ± 0.072° for position and orientation learning, respectively. Copyright © 2018 Elsevier B.V. All rights reserved.

A programmable display layer for virtual reality system architectures.

PubMed

Smit, Ferdi Alexander; van Liere, Robert; Froehlich, Bernd

2010-01-01

Display systems typically operate at a minimum rate of 60 Hz. However, existing VR-architectures generally produce application updates at a lower rate. Consequently, the display is not updated by the application every display frame. This causes a number of undesirable perceptual artifacts. We describe an architecture that provides a programmable display layer (PDL) in order to generate updated display frames. This replaces the default display behavior of repeating application frames until an update is available. We will show three benefits of the architecture typical to VR. First, smooth motion is provided by generating intermediate display frames by per-pixel depth-image warping using 3D motion fields. Smooth motion eliminates various perceptual artifacts due to judder. Second, we implement fine-grained latency reduction at the display frame level using a synchronized prediction of simulation objects and the viewpoint. This improves the average quality and consistency of latency reduction. Third, a crosstalk reduction algorithm for consecutive display frames is implemented, which improves the quality of stereoscopic images. To evaluate the architecture, we compare image quality and latency to that of a classic level-of-detail approach.

Statistical estimation of femur micro-architecture using optimal shape and density predictors.

PubMed

Lekadir, Karim; Hazrati-Marangalou, Javad; Hoogendoorn, Corné; Taylor, Zeike; van Rietbergen, Bert; Frangi, Alejandro F

2015-02-26

The personalization of trabecular micro-architecture has been recently shown to be important in patient-specific biomechanical models of the femur. However, high-resolution in vivo imaging of bone micro-architecture using existing modalities is still infeasible in practice due to the associated acquisition times, costs, and X-ray radiation exposure. In this study, we describe a statistical approach for the prediction of the femur micro-architecture based on the more easily extracted subject-specific bone shape and mineral density information. To this end, a training sample of ex vivo micro-CT images is used to learn the existing statistical relationships within the low and high resolution image data. More specifically, optimal bone shape and mineral density features are selected based on their predictive power and used within a partial least square regression model to estimate the unknown trabecular micro-architecture within the anatomical models of new subjects. The experimental results demonstrate the accuracy of the proposed approach, with average errors of 0.07 for both the degree of anisotropy and tensor norms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Vinobot and Vinoculer: Two Robotic Platforms for High-Throughput Field Phenotyping

PubMed Central

Shafiekhani, Ali; Kadam, Suhas; Fritschi, Felix B.; DeSouza, Guilherme N.

2017-01-01

In this paper, a new robotic architecture for plant phenotyping is being introduced. The architecture consists of two robotic platforms: an autonomous ground vehicle (Vinobot) and a mobile observation tower (Vinoculer). The ground vehicle collects data from individual plants, while the observation tower oversees an entire field, identifying specific plants for further inspection by the Vinobot. The advantage of this architecture is threefold: first, it allows the system to inspect large areas of a field at any time, during the day and night, while identifying specific regions affected by biotic and/or abiotic stresses; second, it provides high-throughput plant phenotyping in the field by either comprehensive or selective acquisition of accurate and detailed data from groups or individual plants; and third, it eliminates the need for expensive and cumbersome aerial vehicles or similarly expensive and confined field platforms. As the preliminary results from our algorithms for data collection and 3D image processing, as well as the data analysis and comparison with phenotype data collected by hand demonstrate, the proposed architecture is cost effective, reliable, versatile, and extendable. PMID:28124976

Fenomen (re)konstrukcji zespołów architektonicznych

NASA Astrophysics Data System (ADS)

Paczos, Joanna

2009-01-01

Complexes of architectural (re)contructions created not in situ, have existed in European culture since the ancient until present times. According to the time and place of their creation they used diferrent types of spatial compositions such as a villa suburbana (e.g. Villa Adriana in Tivoli near Rome), castle (e.g. Vajdahunyad Castle in Budapest), village (e.g. Poble Espanyol in Barcelona), town square (e.g. Nádvorie Európy in Komárno) etc. Firstly, they acted only as a cultural reminiscence, later they began to be also a kind of the scenographic setting of international and national exhibitions, and finally a specific kind of tourist attraction or architectural adaptation of urban space. The complex of architectural (re)constructions is characteristic of both eclectic culture and cultural eclecticism, it is an architectural pastiche of a structure of a cultural rebus, it is also an image of a permanently intensifying cultural phenomenon reflecting a process of condensation mixed simultaneously with fragmentation of the traditional culture, a phenomenon which is unfortunately current in a contemporary cultural tourism, too.

Efficient high-performance ultrasound beamforming using oversampling

NASA Astrophysics Data System (ADS)

Freeman, Steven R.; Quick, Marshall K.; Morin, Marc A.; Anderson, R. C.; Desilets, Charles S.; Linnenbrink, Thomas E.; O'Donnell, Matthew

1998-05-01

High-performance and efficient beamforming circuitry is very important in large channel count clinical ultrasound systems. Current state-of-the-art digital systems using multi-bit analog to digital converters (A/Ds) have matured to provide exquisite image quality with moderate levels of integration. A simplified oversampling beamforming architecture has been proposed that may a low integration of delta-sigma A/Ds onto the same chip as digital delay and processing circuitry to form a monolithic ultrasound beamformer. Such a beamformer may enable low-power handheld scanners for high-end systems with very large channel count arrays. This paper presents an oversampling beamformer architecture that generates high-quality images using very simple; digitization, delay, and summing circuits. Additional performance may be obtained with this oversampled system for narrow bandwidth excitations by mixing the RF signal down in frequency to a range where the electronic signal to nose ratio of the delta-sigma A/D is optimized. An oversampled transmit beamformer uses the same delay circuits as receive and eliminates the need for separate transmit function generators.

Stochastic associative memory

NASA Astrophysics Data System (ADS)

Baumann, Erwin W.; Williams, David L.

1993-08-01

Artificial neural networks capable of learning and recalling stochastic associations between non-deterministic quantities have received relatively little attention to date. One potential application of such stochastic associative networks is the generation of sensory 'expectations' based on arbitrary subsets of sensor inputs to support anticipatory and investigate behavior in sensor-based robots. Another application of this type of associative memory is the prediction of how a scene will look in one spectral band, including noise, based upon its appearance in several other wavebands. This paper describes a semi-supervised neural network architecture composed of self-organizing maps associated through stochastic inter-layer connections. This 'Stochastic Associative Memory' (SAM) can learn and recall non-deterministic associations between multi-dimensional probability density functions. The stochastic nature of the network also enables it to represent noise distributions that are inherent in any true sensing process. The SAM architecture, training process, and initial application to sensor image prediction are described. Relationships to Fuzzy Associative Memory (FAM) are discussed.

Evaluation of the Intel iWarp parallel processor for space flight applications

NASA Technical Reports Server (NTRS)

Hine, Butler P., III; Fong, Terrence W.

1993-01-01

The potential of a DARPA-sponsored advanced processor, the Intel iWarp, for use in future SSF Data Management Systems (DMS) upgrades is evaluated through integration into the Ames DMS testbed and applications testing. The iWarp is a distributed, parallel computing system well suited for high performance computing applications such as matrix operations and image processing. The system architecture is modular, supports systolic and message-based computation, and is capable of providing massive computational power in a low-cost, low-power package. As a consequence, the iWarp offers significant potential for advanced space-based computing. This research seeks to determine the iWarp's suitability as a processing device for space missions. In particular, the project focuses on evaluating the ease of integrating the iWarp into the SSF DMS baseline architecture and the iWarp's ability to support computationally stressing applications representative of SSF tasks.

Modular architecture of eukaryotic RNase P and RNase MRP revealed by electron microscopy.

PubMed

Hipp, Katharina; Galani, Kyriaki; Batisse, Claire; Prinz, Simone; Böttcher, Bettina

2012-04-01

Ribonuclease P (RNase P) and RNase MRP are closely related ribonucleoprotein enzymes, which process RNA substrates including tRNA precursors for RNase P and 5.8 S rRNA precursors, as well as some mRNAs, for RNase MRP. The structures of RNase P and RNase MRP have not yet been solved, so it is unclear how the proteins contribute to the structure of the complexes and how substrate specificity is determined. Using electron microscopy and image processing we show that eukaryotic RNase P and RNase MRP have a modular architecture, where proteins stabilize the RNA fold and contribute to cavities, channels and chambers between the modules. Such features are located at strategic positions for substrate recognition by shape and coordination of the cleaved-off sequence. These are also the sites of greatest difference between RNase P and RNase MRP, highlighting the importance of the adaptation of this region to the different substrates.

Cellular Tug-of-War: Forces at Work and DNA Stretching in Mitosis

NASA Astrophysics Data System (ADS)

Griffin, Brian; Kilfoil, Maria L.

2013-03-01

In the microscopic world of the cell dominated by thermal noise, a cell must be able to successfully segregate its DNA with high fidelity in order to pass its genetic information on to its progeny. In this process of mitosis in eukaryotes, driving forces act on the cytoskeleton-based architecture called the mitotic spindle to promote this division. Our preliminary data demonstrates that the dynamics of this process in yeast cells is universal. Moreover, the dynamics suggest an increasing load as the chromosomes are pulled apart. To investigate this, we use three-dimensional imaging to track the dynamics of the poles of this architecture and the points of attachment to chromosomes simultaneously and with high spatial resolution. We analyze the relative motions of chromosomes as they are organized before segregation and as they are pulled apart, using this data to investigate the force-response behavior of this cytoskeleton-chromosome polymer system.

Architecture of orogenic belts and convergent zones in Western Ishtar Terra, Venus

NASA Technical Reports Server (NTRS)

Head, James W.; Vorderbruegge, R. W.; Crumpler, L. S.

1989-01-01

Linear mountain belts in Ishtar Terra were recognized from Pioneer-Venus topography, and later Arecibo images showed banded terrain interpreted to represent folds. Subsequent analyses showed that the mountains represented orogenic belts, and that each had somewhat different features and characteristics. Orogenic belts are regions of focused shortening and compressional deformation and thus provide evidence for the nature of such deformation, processes of crustal thickening (brittle, ductile), and processes of crustal loss. Such information is important in understanding the nature of convergent zones on Venus (underthrusting, imbrication, subduction), the implications for rates of crustal recycling, and the nature of environments of melting and petrogenesis. The basic elements of four convergent zones and orogenic belts in western Ishtar Terra are identified and examined, and then assess the architecture of these zones (the manner in which the elements are arrayed), and their relationships. The basic nomenclature of the convergent zones is shown.

A web-based computer aided system for liver surgery planning: initial implementation on RayPlus

NASA Astrophysics Data System (ADS)

Luo, Ming; Yuan, Rong; Sun, Zhi; Li, Tianhong; Xie, Qingguo

2016-03-01

At present, computer aided systems for liver surgery design and risk evaluation are widely used in clinical all over the world. However, most systems are local applications that run on high-performance workstations, and the images have to processed offline. Compared with local applications, a web-based system is accessible anywhere and for a range of regardless of relative processing power or operating system. RayPlus (http://rayplus.life.hust.edu.cn), a B/S platform for medical image processing, was developed to give a jump start on web-based medical image processing. In this paper, we implement a computer aided system for liver surgery planning on the architecture of RayPlus. The system consists of a series of processing to CT images including filtering, segmentation, visualization and analyzing. Each processing is packaged into an executable program and runs on the server side. CT images in DICOM format are processed step by to interactive modeling on browser with zero-installation and server-side computing. The system supports users to semi-automatically segment the liver, intrahepatic vessel and tumor from the pre-processed images. Then, surface and volume models are built to analyze the vessel structure and the relative position between adjacent organs. The results show that the initial implementation meets satisfactorily its first-order objectives and provide an accurate 3D delineation of the liver anatomy. Vessel labeling and resection simulation are planned to add in the future. The system is available on Internet at the link mentioned above and an open username for testing is offered.

Performance of the Wavelet Decomposition on Massively Parallel Architectures

NASA Technical Reports Server (NTRS)

El-Ghazawi, Tarek A.; LeMoigne, Jacqueline; Zukor, Dorothy (Technical Monitor)

2001-01-01

Traditionally, Fourier Transforms have been utilized for performing signal analysis and representation. But although it is straightforward to reconstruct a signal from its Fourier transform, no local description of the signal is included in its Fourier representation. To alleviate this problem, Windowed Fourier transforms and then wavelet transforms have been introduced, and it has been proven that wavelets give a better localization than traditional Fourier transforms, as well as a better division of the time- or space-frequency plane than Windowed Fourier transforms. Because of these properties and after the development of several fast algorithms for computing the wavelet representation of any signal, in particular the Multi-Resolution Analysis (MRA) developed by Mallat, wavelet transforms have increasingly been applied to signal analysis problems, especially real-life problems, in which speed is critical. In this paper we present and compare efficient wavelet decomposition algorithms on different parallel architectures. We report and analyze experimental measurements, using NASA remotely sensed images. Results show that our algorithms achieve significant performance gains on current high performance parallel systems, and meet scientific applications and multimedia requirements. The extensive performance measurements collected over a number of high-performance computer systems have revealed important architectural characteristics of these systems, in relation to the processing demands of the wavelet decomposition of digital images.

CUDA Optimization Strategies for Compute- and Memory-Bound Neuroimaging Algorithms

PubMed Central

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W.

2011-01-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. PMID:21159404

CUDA optimization strategies for compute- and memory-bound neuroimaging algorithms.

PubMed

Lee, Daren; Dinov, Ivo; Dong, Bin; Gutman, Boris; Yanovsky, Igor; Toga, Arthur W

2012-06-01

As neuroimaging algorithms and technology continue to grow faster than CPU performance in complexity and image resolution, data-parallel computing methods will be increasingly important. The high performance, data-parallel architecture of modern graphical processing units (GPUs) can reduce computational times by orders of magnitude. However, its massively threaded architecture introduces challenges when GPU resources are exceeded. This paper presents optimization strategies for compute- and memory-bound algorithms for the CUDA architecture. For compute-bound algorithms, the registers are reduced through variable reuse via shared memory and the data throughput is increased through heavier thread workloads and maximizing the thread configuration for a single thread block per multiprocessor. For memory-bound algorithms, fitting the data into the fast but limited GPU resources is achieved through reorganizing the data into self-contained structures and employing a multi-pass approach. Memory latencies are reduced by selecting memory resources whose cache performance are optimized for the algorithm's access patterns. We demonstrate the strategies on two computationally expensive algorithms and achieve optimized GPU implementations that perform up to 6× faster than unoptimized ones. Compared to CPU implementations, we achieve peak GPU speedups of 129× for the 3D unbiased nonlinear image registration technique and 93× for the non-local means surface denoising algorithm. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Single-image-based Modelling Architecture from a Historical Photograph

NASA Astrophysics Data System (ADS)

Dzwierzynska, Jolanta

2017-10-01

Historical photographs are proved to be very useful to provide a dimensional and geometrical analysis of buildings as well as to generate 3D reconstruction of the whole structure. The paper addresses the problem of single historical photograph analysis and modelling of an architectural object from it. Especially, it focuses on reconstruction of the original look of New-Town synagogue from the single historic photograph, when camera calibration is completely unknown. Due to the fact that the photograph faithfully followed the geometric rules of perspective, it was possible to develop and apply the method to obtain a correct 3D reconstruction of the building. The modelling process consisted of a series of familiar steps: feature extraction, determination of base elements of perspective, dimensional analyses and 3D reconstruction. Simple formulas were proposed in order to estimate location of characteristic points of the building in 3D Cartesian system of axes on the base of their location in 2D Cartesian system of axes. The reconstruction process proceeded well, although slight corrections were necessary. It was possible to reconstruct the shape of the building in general, and two of its facades in detail. The reconstruction of the other two facades requires some additional information or the additional picture. The success of the presented reconstruction method depends on the geometrical content of the photograph as well as quality of the picture, which ensures the legibility of building edges. The presented method of reconstruction is a combination of the descriptive method of reconstruction and computer aid; therefore, it seems to be universal. It can prove useful for single-image-based modelling architecture.

An acceleration system for Laplacian image fusion based on SoC

NASA Astrophysics Data System (ADS)

Gao, Liwen; Zhao, Hongtu; Qu, Xiujie; Wei, Tianbo; Du, Peng

2018-04-01

Based on the analysis of Laplacian image fusion algorithm, this paper proposes a partial pipelining and modular processing architecture, and a SoC based acceleration system is implemented accordingly. Full pipelining method is used for the design of each module, and modules in series form the partial pipelining with unified data formation, which is easy for management and reuse. Integrated with ARM processor, DMA and embedded bare-mental program, this system achieves 4 layers of Laplacian pyramid on the Zynq-7000 board. Experiments show that, with small resources consumption, a couple of 256×256 images can be fused within 1ms, maintaining a fine fusion effect at the same time.

Implementation of the 2-D Wavelet Transform into FPGA for Image

NASA Astrophysics Data System (ADS)

León, M.; Barba, L.; Vargas, L.; Torres, C. O.

2011-01-01

This paper presents a hardware system implementation of the of discrete wavelet transform algoritm in two dimensions for FPGA, using the Daubechies filter family of order 2 (db2). The decomposition algorithm of this transform is designed and simulated with the Hardware Description Language VHDL and is implemented in a programmable logic device (FPGA) XC3S1200E reference, Spartan IIIE family, by Xilinx, take advantage the parallels properties of these gives us and speeds processing that can reach them. The architecture is evaluated using images input of different sizes. This implementation is done with the aim of developing a future images encryption hardware system using wavelet transform for security information.

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

Shin, Kyung -Wook; Karim, Karim S.

Direct conversion crystalline silicon X-ray imagers are used for low-energy X-ray photon (4-20 keV) detection in scientific research applications such as protein crystallography. In this paper, we demonstrate a novel pixel architecture that integrates a crystalline silicon X-ray detector with a thin-film transistor amorphous silicon pixel readout circuit. We describe a simplified two-mask process to fabricate a complete imaging array and present preliminary results that show the fabricated pixel to be sensitive to 5.89-keV photons from a low activity Fe-55 gamma source. Furthermore, this paper presented can expedite the development of high spatial resolution, low cost, direct conversion imagers formore » X-ray diffraction and crystallography applications.« less

HALO: a reconfigurable image enhancement and multisensor fusion system

NASA Astrophysics Data System (ADS)

Wu, F.; Hickman, D. L.; Parker, Steve J.

2014-06-01

Contemporary high definition (HD) cameras and affordable infrared (IR) imagers are set to dramatically improve the effectiveness of security, surveillance and military vision systems. However, the quality of imagery is often compromised by camera shake, or poor scene visibility due to inadequate illumination or bad atmospheric conditions. A versatile vision processing system called HALO™ is presented that can address these issues, by providing flexible image processing functionality on a low size, weight and power (SWaP) platform. Example processing functions include video distortion correction, stabilisation, multi-sensor fusion and image contrast enhancement (ICE). The system is based around an all-programmable system-on-a-chip (SoC), which combines the computational power of a field-programmable gate array (FPGA) with the flexibility of a CPU. The FPGA accelerates computationally intensive real-time processes, whereas the CPU provides management and decision making functions that can automatically reconfigure the platform based on user input and scene content. These capabilities enable a HALO™ equipped reconnaissance or surveillance system to operate in poor visibility, providing potentially critical operational advantages in visually complex and challenging usage scenarios. The choice of an FPGA based SoC is discussed, and the HALO™ architecture and its implementation are described. The capabilities of image distortion correction, stabilisation, fusion and ICE are illustrated using laboratory and trials data.

Multi-Beam Radio Frequency (RF) Aperture Arrays Using Multiplierless Approximate Fast Fourier Transform (FFT)

DTIC Science & Technology

2017-08-01

filtering, correlation and radio- astronomy . In this report approximate transforms that closely follow the DFT have been studied and found. The approximate...communications, data networks, sensor networks, cognitive radio, radar and beamforming, imaging, filtering, correlation and radio- astronomy . FFTs efficiently...public release; distribution is unlimited. 4.3 Digital Hardware and Design Architectures Collaboration for Astronomy Signal Processing and Electronics

Metamaterial and Metastructural Architectures for Novel C4ISR Devices and Sensors

DTIC Science & Technology

2015-03-01

2.7 The SEM pictures of the fabricated metastructure cage waveguide a) before and b) after the thermal oxidization and HF etching process ..10 Fig...of the hollow core. (Bottom) The SiO2 shell in the core was removed by buffered high-frequency etch...28 Fig. 3.9 SEM images of the waveguides after etching in CR-9 and buffered oxide etchant

An Architecture for Integrated Regional Health Telematics Networks

DTIC Science & Technology

2001-10-25

that enables informed citizens to have an impact on the healthcare system and to be more concerned and care for their own health . The current...resource, educational, integrated electronic health record (I- EHR ), and added value services [2]. These classes of telematic services are applica...cally distributed clinical information systems . 5) Finally, added-value services (e.g. image processing, information indexing, data pre-fetching

Optical and Electric Multifunctional CMOS Image Sensors for On-Chip Biosensing Applications.

PubMed

Tokuda, Takashi; Noda, Toshihiko; Sasagawa, Kiyotaka; Ohta, Jun

2010-12-29

In this review, the concept, design, performance, and a functional demonstration of multifunctional complementary metal-oxide-semiconductor (CMOS) image sensors dedicated to on-chip biosensing applications are described. We developed a sensor architecture that allows flexible configuration of a sensing pixel array consisting of optical and electric sensing pixels, and designed multifunctional CMOS image sensors that can sense light intensity and electric potential or apply a voltage to an on-chip measurement target. We describe the sensors' architecture on the basis of the type of electric measurement or imaging functionalities.

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation.

PubMed

Kamnitsas, Konstantinos; Ledig, Christian; Newcombe, Virginia F J; Simpson, Joanna P; Kane, Andrew D; Menon, David K; Rueckert, Daniel; Glocker, Ben

2017-02-01

We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation. The devised architecture is the result of an in-depth analysis of the limitations of current networks proposed for similar applications. To overcome the computational burden of processing 3D medical scans, we have devised an efficient and effective dense training scheme which joins the processing of adjacent image patches into one pass through the network while automatically adapting to the inherent class imbalance present in the data. Further, we analyze the development of deeper, thus more discriminative 3D CNNs. In order to incorporate both local and larger contextual information, we employ a dual pathway architecture that processes the input images at multiple scales simultaneously. For post-processing of the network's soft segmentation, we use a 3D fully connected Conditional Random Field which effectively removes false positives. Our pipeline is extensively evaluated on three challenging tasks of lesion segmentation in multi-channel MRI patient data with traumatic brain injuries, brain tumours, and ischemic stroke. We improve on the state-of-the-art for all three applications, with top ranking performance on the public benchmarks BRATS 2015 and ISLES 2015. Our method is computationally efficient, which allows its adoption in a variety of research and clinical settings. The source code of our implementation is made publicly available. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Implementation of Multi-Agent Object Attention System Based on Biologically Inspired Attractor Selection

NASA Astrophysics Data System (ADS)

Hashimoto, Ryoji; Matsumura, Tomoya; Nozato, Yoshihiro; Watanabe, Kenji; Onoye, Takao

A multi-agent object attention system is proposed, which is based on biologically inspired attractor selection model. Object attention is facilitated by using a video sequence and a depth map obtained through a compound-eye image sensor TOMBO. Robustness of the multi-agent system over environmental changes is enhanced by utilizing the biological model of adaptive response by attractor selection. To implement the proposed system, an efficient VLSI architecture is employed with reducing enormous computational costs and memory accesses required for depth map processing and multi-agent attractor selection process. According to the FPGA implementation result of the proposed object attention system, which is accomplished by using 7,063 slices, 640×512 pixel input images can be processed in real-time with three agents at a rate of 9fps in 48MHz operation.

Single organelle dynamics linked to 3D structure by correlative live-cell imaging and 3D electron microscopy.

PubMed

Fermie, Job; Liv, Nalan; Ten Brink, Corlinda; van Donselaar, Elly G; Müller, Wally H; Schieber, Nicole L; Schwab, Yannick; Gerritsen, Hans C; Klumperman, Judith

2018-05-01

Live-cell correlative light-electron microscopy (live-cell-CLEM) integrates live movies with the corresponding electron microscopy (EM) image, but a major challenge is to relate the dynamic characteristics of single organelles to their 3-dimensional (3D) ultrastructure. Here, we introduce focused ion beam scanning electron microscopy (FIB-SEM) in a modular live-cell-CLEM pipeline for a single organelle CLEM. We transfected cells with lysosomal-associated membrane protein 1-green fluorescent protein (LAMP-1-GFP), analyzed the dynamics of individual GFP-positive spots, and correlated these to their corresponding fine-architecture and immediate cellular environment. By FIB-SEM we quantitatively assessed morphological characteristics, like number of intraluminal vesicles and contact sites with endoplasmic reticulum and mitochondria. Hence, we present a novel way to integrate multiple parameters of subcellular dynamics and architecture onto a single organelle, which is relevant to address biological questions related to membrane trafficking, organelle biogenesis and positioning. Furthermore, by using CLEM to select regions of interest, our method allows for targeted FIB-SEM, which significantly reduces time required for image acquisition and data processing. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Thin-Film Quantum Dot Photodiode for Monolithic Infrared Image Sensors.

PubMed

Malinowski, Pawel E; Georgitzikis, Epimitheas; Maes, Jorick; Vamvaka, Ioanna; Frazzica, Fortunato; Van Olmen, Jan; De Moor, Piet; Heremans, Paul; Hens, Zeger; Cheyns, David

2017-12-10

Imaging in the infrared wavelength range has been fundamental in scientific, military and surveillance applications. Currently, it is a crucial enabler of new industries such as autonomous mobility (for obstacle detection), augmented reality (for eye tracking) and biometrics. Ubiquitous deployment of infrared cameras (on a scale similar to visible cameras) is however prevented by high manufacturing cost and low resolution related to the need of using image sensors based on flip-chip hybridization. One way to enable monolithic integration is by replacing expensive, small-scale III-V-based detector chips with narrow bandgap thin-films compatible with 8- and 12-inch full-wafer processing. This work describes a CMOS-compatible pixel stack based on lead sulfide quantum dots (PbS QD) with tunable absorption peak. Photodiode with a 150-nm thick absorber in an inverted architecture shows dark current of 10 -6 A/cm² at -2 V reverse bias and EQE above 20% at 1440 nm wavelength. Optical modeling for top illumination architecture can improve the contact transparency to 70%. Additional cooling (193 K) can improve the sensitivity to 60 dB. This stack can be integrated on a CMOS ROIC, enabling order-of-magnitude cost reduction for infrared sensors.

MO-C-BRCD-03: The Role of Informatics in Medical Physics and Vice Versa.

PubMed

Andriole, K

2012-06-01

Like Medical Physics, Imaging Informatics encompasses concepts touching every aspect of the imaging chain from image creation, acquisition, management and archival, to image processing, analysis, display and interpretation. The two disciplines are in fact quite complementary, with similar goals to improve the quality of care provided to patients using an evidence-based approach, to assure safety in the clinical and research environments, to facilitate efficiency in the workplace, and to accelerate knowledge discovery. Use-cases describing several areas of informatics activity will be given to illustrate current limitations that would benefit from medical physicist participation, and conversely areas in which informaticists may contribute to the solution. Topics to be discussed include radiation dose monitoring, process management and quality control, display technologies, business analytics techniques, and quantitative imaging. Quantitative imaging is increasingly becoming an essential part of biomedicalresearch as well as being incorporated into clinical diagnostic activities. Referring clinicians are asking for more objective information to be gleaned from the imaging tests that they order so that they may make the best clinical management decisions for their patients. Medical Physicists may be called upon to identify existing issues as well as develop, validate and implement new approaches and technologies to help move the field further toward quantitative imaging methods for the future. Biomedical imaging informatics tools and techniques such as standards, integration, data mining, cloud computing and new systems architectures, ontologies and lexicons, data visualization and navigation tools, and business analytics applications can be used to overcome some of the existing limitations. 1. Describe what is meant by Medical Imaging Informatics and understand why the medical physicist should care. 2. Identify existing limitations in information technologies with respect to Medical Physics, and conversely see how Informatics may assist the medical physicist in filling some of the current gaps in their activities. 3. Understand general informatics concepts and areas of investigation including imaging and workflow standards, systems integration, computing architectures, ontologies, data mining and business analytics, data visualization and human-computer interface tools, and the importance of quantitative imaging for the future of Medical Physics and Imaging Informatics. 4. Become familiar with on-going efforts to address current challenges facing future research into and clinical implementation of quantitative imaging applications. © 2012 American Association of Physicists in Medicine.

Generating Accurate 3d Models of Architectural Heritage Structures Using Low-Cost Camera and Open Source Algorithms

NASA Astrophysics Data System (ADS)

Zacharek, M.; Delis, P.; Kedzierski, M.; Fryskowska, A.

2017-05-01

These studies have been conductedusing non-metric digital camera and dense image matching algorithms, as non-contact methods of creating monuments documentation.In order toprocess the imagery, few open-source software and algorithms of generating adense point cloud from images have been executed. In the research, the OSM Bundler, VisualSFM software, and web application ARC3D were used. Images obtained for each of the investigated objects were processed using those applications, and then dense point clouds and textured 3D models were created. As a result of post-processing, obtained models were filtered and scaled.The research showedthat even using the open-source software it is possible toobtain accurate 3D models of structures (with an accuracy of a few centimeters), but for the purpose of documentation and conservation of cultural and historical heritage, such accuracy can be insufficient.

Techniques and Tools for Estimating Ionospheric Effects in Interferometric and Polarimetric SAR Data

NASA Technical Reports Server (NTRS)

Rosen, P.; Lavalle, M.; Pi, X.; Buckley, S.; Szeliga, W.; Zebker, H.; Gurrola, E.

2011-01-01

The InSAR Scientific Computing Environment (ISCE) is a flexible, extensible software tool designed for the end-to-end processing and analysis of synthetic aperture radar data. ISCE inherits the core of the ROI_PAC interferometric tool, but contains improvements at all levels of the radar processing chain, including a modular and extensible architecture, new focusing approach, better geocoding of the data, handling of multi-polarization data, radiometric calibration, and estimation and correction of ionospheric effects. In this paper we describe the characteristics of ISCE with emphasis on the ionospheric modules. To detect ionospheric anomalies, ISCE implements the Faraday rotation method using quadpolarimetric images, and the split-spectrum technique using interferometric single-, dual- and quad-polarimetric images. The ability to generate co-registered time series of quad-polarimetric images makes ISCE also an ideal tool to be used for polarimetric-interferometric radar applications.

Imaging of the interaction of low frequency electric fields with biological tissues by optical coherence tomography

NASA Astrophysics Data System (ADS)

Peña, Adrian F.; Devine, Jack; Doronin, Alexander; Meglinski, Igor

2014-03-01

We report the use of conventional Optical Coherence Tomography (OCT) for visualization of propagation of low frequency electric field in soft biological tissues ex vivo. To increase the overall quality of the experimental images an adaptive Wiener filtering technique has been employed. Fourier domain correlation has been subsequently applied to enhance spatial resolution of images of biological tissues influenced by low frequency electric field. Image processing has been performed on Graphics Processing Units (GPUs) utilizing Compute Unified Device Architecture (CUDA) framework in the frequencydomain. The results show that variation in voltage and frequency of the applied electric field relates exponentially to the magnitude of its influence on biological tissue. The magnitude of influence is about twice more for fresh tissue samples in comparison to non-fresh ones. The obtained results suggest that OCT can be used for observation and quantitative evaluation of the electro-kinetic changes in biological tissues under different physiological conditions, functional electrical stimulation, and potentially can be used non-invasively for food quality control.

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

NASA Technical Reports Server (NTRS)

Solarna, David; Moser, Gabriele; Le Moigne-Stewart, Jacqueline; Serpico, Sebastiano B.

2017-01-01

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Accelerating image reconstruction in dual-head PET system by GPU and symmetry properties.

PubMed

Chou, Cheng-Ying; Dong, Yun; Hung, Yukai; Kao, Yu-Jiun; Wang, Weichung; Kao, Chien-Min; Chen, Chin-Tu

2012-01-01

Positron emission tomography (PET) is an important imaging modality in both clinical usage and research studies. We have developed a compact high-sensitivity PET system that consisted of two large-area panel PET detector heads, which produce more than 224 million lines of response and thus request dramatic computational demands. In this work, we employed a state-of-the-art graphics processing unit (GPU), NVIDIA Tesla C2070, to yield an efficient reconstruction process. Our approaches ingeniously integrate the distinguished features of the symmetry properties of the imaging system and GPU architectures, including block/warp/thread assignments and effective memory usage, to accelerate the computations for ordered subset expectation maximization (OSEM) image reconstruction. The OSEM reconstruction algorithms were implemented employing both CPU-based and GPU-based codes, and their computational performance was quantitatively analyzed and compared. The results showed that the GPU-accelerated scheme can drastically reduce the reconstruction time and thus can largely expand the applicability of the dual-head PET system.

An image processing and analysis tool for identifying and analysing complex plant root systems in 3D soil using non-destructive analysis: Root1.

PubMed

Flavel, Richard J; Guppy, Chris N; Rabbi, Sheikh M R; Young, Iain M

2017-01-01

The objective of this study was to develop a flexible and free image processing and analysis solution, based on the Public Domain ImageJ platform, for the segmentation and analysis of complex biological plant root systems in soil from x-ray tomography 3D images. Contrasting root architectures from wheat, barley and chickpea root systems were grown in soil and scanned using a high resolution micro-tomography system. A macro (Root1) was developed that reliably identified with good to high accuracy complex root systems (10% overestimation for chickpea, 1% underestimation for wheat, 8% underestimation for barley) and provided analysis of root length and angle. In-built flexibility allowed the user interaction to (a) amend any aspect of the macro to account for specific user preferences, and (b) take account of computational limitations of the platform. The platform is free, flexible and accurate in analysing root system metrics.

A CMOS image sensor with programmable pixel-level analog processing.

PubMed

Massari, Nicola; Gottardi, Massimo; Gonzo, Lorenzo; Stoppa, David; Simoni, Andrea

2005-11-01

A prototype of a 34 x 34 pixel image sensor, implementing real-time analog image processing, is presented. Edge detection, motion detection, image amplification, and dynamic-range boosting are executed at pixel level by means of a highly interconnected pixel architecture based on the absolute value of the difference among neighbor pixels. The analog operations are performed over a kernel of 3 x 3 pixels. The square pixel, consisting of 30 transistors, has a pitch of 35 microm with a fill-factor of 20%. The chip was fabricated in a 0.35 microm CMOS technology, and its power consumption is 6 mW with 3.3 V power supply. The device was fully characterized and achieves a dynamic range of 50 dB with a light power density of 150 nW/mm2 and a frame rate of 30 frame/s. The measured fixed pattern noise corresponds to 1.1% of the saturation level. The sensor's dynamic range can be extended up to 96 dB using the double-sampling technique.

Dynamic Photorefractive Memory and its Application for Opto-Electronic Neural Networks.

NASA Astrophysics Data System (ADS)

Sasaki, Hironori

This dissertation describes the analysis of the photorefractive crystal dynamics and its application for opto-electronic neural network systems. The realization of the dynamic photorefractive memory is investigated in terms of the following aspects: fast memory update, uniform grating multiplexing schedules and the prevention of the partial erasure of existing gratings. The fast memory update is realized by the selective erasure process that superimposes a new grating on the original one with an appropriate phase shift. The dynamics of the selective erasure process is analyzed using the first-order photorefractive material equations and experimentally confirmed. The effects of beam coupling and fringe bending on the selective erasure dynamics are also analyzed by numerically solving a combination of coupled wave equations and the photorefractive material equation. Incremental recording technique is proposed as a uniform grating multiplexing schedule and compared with the conventional scheduled recording technique in terms of phase distribution in the presence of an external dc electric field, as well as the image gray scale dependence. The theoretical analysis and experimental results proved the superiority of the incremental recording technique over the scheduled recording. Novel recirculating information memory architecture is proposed and experimentally demonstrated to prevent partial degradation of the existing gratings by accessing the memory. Gratings are circulated through a memory feed back loop based on the incremental recording dynamics and demonstrate robust read/write/erase capabilities. The dynamic photorefractive memory is applied to opto-electronic neural network systems. Module architecture based on the page-oriented dynamic photorefractive memory is proposed. This module architecture can implement two complementary interconnection organizations, fan-in and fan-out. The module system scalability and the learning capabilities are theoretically investigated using the photorefractive dynamics described in previous chapters of the dissertation. The implementation of the feed-forward image compression network with 900 input and 9 output neurons with 6-bit interconnection accuracy is experimentally demonstrated. Learning of the Perceptron network that determines sex based on input face images of 900 pixels is also successfully demonstrated.

Use of Daylight and Aesthetic Image of Glass Facades in Contemporary Buildings

NASA Astrophysics Data System (ADS)

Roginska-Niesluchowska, Malgorzata

2017-10-01

The paper deals with the architecture of contemporary buildings in respect to their aesthetic image created by the use of natural light. Sustainability is regarded as a governing principle of contemporary architecture, where daylighting is an important factor as it affects energy consumption and environmental quality of the space inside a building. Environmental awareness of architecture, however, involves a much wider and more holistic view of design. The quality of sustainable architecture can be considered in its aesthetic and cultural context with regard to landscape, local tradition, and connection to the surrounding world. This approach is associated with the social mission of architecture, i.e. providing appropriate space for living, facilitating social relations and having positive impact on people. The purpose of the research is to study the use of daylight in creating an aesthetic image of contemporary buildings. The author focuses mainly on public buildings largely dedicated to art and culture which satisfy high functional and aesthetic requirements. The paper examines the genesis and current trends in the aesthetic image of modern buildings which use daylight as the main design strategy, focusing on the issues of glass facades. The main attention is given to the shaping of representative public areas which feature the glass facades. The research has been based on a case study, critical review of literature review, observation and synthesis. The study identifies and classifies different approaches to using daylight in these areas and highlights changes in the aesthetics of architecture made of glass, which uses daylight as the main design strategy. These changes are primarily caused by the development and spreading of new glazing materials and the use of digital method of design. The influence of light and its mode depends on glass materials but also on the local conditions of the site, and has a significant impact on the relationship between architecture and its natural and cultural environment. The subordination of architectural concept to the idea of natural lighting builds the relationship between form, function and the context of architecture, and is expressed in its structural, material and spatial properties, and in the resulting aesthetic order. Search for new architectural solutions is defined by local topographical, climatic, biological and cultural conditions. The architecture subordinate to the conception of contribution of light corresponds to the aesthetic aspirations of sustainability.

An effective detection algorithm for region duplication forgery in digital images

NASA Astrophysics Data System (ADS)

Yavuz, Fatih; Bal, Abdullah; Cukur, Huseyin

2016-04-01

Powerful image editing tools are very common and easy to use these days. This situation may cause some forgeries by adding or removing some information on the digital images. In order to detect these types of forgeries such as region duplication, we present an effective algorithm based on fixed-size block computation and discrete wavelet transform (DWT). In this approach, the original image is divided into fixed-size blocks, and then wavelet transform is applied for dimension reduction. Each block is processed by Fourier Transform and represented by circle regions. Four features are extracted from each block. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks are detected according to comparison metric results. The experimental results show that the proposed algorithm presents computational efficiency due to fixed-size circle block architecture.

A Versatile High-Vacuum Cryo-transfer System for Cryo-microscopy and Analytics

PubMed Central

Tacke, Sebastian; Krzyzanek, Vladislav; Nüsse, Harald; Wepf, Roger Albert; Klingauf, Jürgen; Reichelt, Rudolf

2016-01-01

Cryogenic microscopy methods have gained increasing popularity, as they offer an unaltered view on the architecture of biological specimens. As a prerequisite, samples must be handled under cryogenic conditions below their recrystallization temperature, and contamination during sample transfer and handling must be prevented. We present a high-vacuum cryo-transfer system that streamlines the entire handling of frozen-hydrated samples from the vitrification process to low temperature imaging for scanning transmission electron microscopy and transmission electron microscopy. A template for cryo-electron microscopy and multimodal cryo-imaging approaches with numerous sample transfer steps is presented. PMID:26910419

Research on Multi-Temporal PolInSAR Modeling and Applications

NASA Astrophysics Data System (ADS)

Hong, Wen; Pottier, Eric; Chen, Erxue

2014-11-01

In the study of theory and processing methodology, we apply accurate topographic phase to the Freeman-Durden decomposition for PolInSAR data. On the other hand, we present a TomoSAR imaging method based on convex optimization regularization theory. The target decomposition and reconstruction performance will be evaluated by multi-temporal Land P-band fully polarimetric images acquired in BioSAR campaigns. In the study of hybrid Quad-Pol system performance, we analyse the expression of range ambiguity to signal ratio (RASR) in this architecture. Simulations are used to testify its advantage in the improvement of range ambiguities.

Research on Multi-Temporal PolInSAR Modeling and Applications

NASA Astrophysics Data System (ADS)

Hong, Wen; Pottier, Eric; Chen, Erxue

2014-11-01

In the study of theory and processing methodology, we apply accurate topographic phase to the Freeman- Durden decomposition for PolInSAR data. On the other hand, we present a TomoSAR imaging method based on convex optimization regularization theory. The target decomposition and reconstruction performance will be evaluated by multi-temporal L- and P-band fully polarimetric images acquired in BioSAR campaigns. In the study of hybrid Quad-Pol system performance, we analyse the expression of range ambiguity to signal ratio (RASR) in this architecture. Simulations are used to testify its advantage in the improvement of range ambiguities.

System engineering for image and video systems

NASA Astrophysics Data System (ADS)

Talbot, Raymond J., Jr.

1997-02-01

The National Law Enforcement and Corrections Technology Centers (NLECTC) support public law enforcement agencies with technology development, evaluation, planning, architecture, and implementation. The NLECTC Western Region has a particular emphasis on surveillance and imaging issues. Among its activities, working with government and industry, NLECTC-WR produces 'Guides to Best Practices and Acquisition Methodologies' that facilitate government organizations in making better informed purchasing and operational decisions. This presentation includes specific examples from current activities. Through these systematic procedures, it is possible to design solutions optimally matched to the desired outcomes and provide a process for continuous improvement and greater public awareness of success.

Waveform-Diverse Multiple-Input Multiple-Output Radar Imaging Measurements

NASA Astrophysics Data System (ADS)

Stewart, Kyle B.

Multiple-input multiple-output (MIMO) radar is an emerging set of technologies designed to extend the capabilities of multi-channel radar systems. While conventional radar architectures emphasize the use of antenna array beamforming to maximize real-time power on target, MIMO radar systems instead attempt to preserve some degree of independence between their received signals and to exploit this expanded matrix of target measurements in the signal-processing domain. Specifically the use of sparse “virtual” antenna arrays may allow MIMO radars to achieve gains over traditional multi-channel systems by post-processing diverse received signals to implement both transmit and receive beamforming at all points of interest within a given scene. MIMO architectures have been widely examined for use in radar target detection, but these systems may yet be ideally suited to real and synthetic aperture radar imaging applications where their proposed benefits include improved resolutions, expanded area coverage, novel modes of operation, and a reduction in hardware size, weight, and cost. While MIMO radar's theoretical benefits have been well established in the literature, its practical limitations have not received great attention thus far. The effective use of MIMO radar techniques requires a diversity of signals, and to date almost all MIMO system demonstrations have made use of time-staggered transmission to satisfy this requirement. Doing so is reliable but can be prohibitively slow. Waveform-diverse systems have been proposed as an alternative in which multiple, independent waveforms are broadcast simultaneously over a common bandwidth and separated on receive using signal processing. Operating in this way is much faster than its time-diverse equivalent, but finding a set of suitable waveforms for this technique has proven to be a difficult problem. In light of this, many have questioned the practicality of MIMO radar imaging and whether or not its theoretical benefits may be extended to real systems. Work in this writing focuses specifically on the practical aspects of MIMO radar imaging systems and provides performance data sourced from experimental measurements made using a four-channel software-defined MIMO radar platform. Demonstrations of waveform-diverse imaging data products are provided and compared directly against time-diverse equivalents in order to assess the performance of prospective MIMO waveforms. These are sourced from the pseudo-noise, short-term shift orthogonal, and orthogonal frequency multiplexing signal families while experimental results demonstrate waveform-diverse measurements of polarimetric radar cross section, top-down stationary target images, and finally volumetric MIMO synthetic aperture radar imagery. The data presented represents some of the first available concerning the overall practicality of waveform-diverse MIMO radar architectures, and results suggest that such configurations may achieve a reasonable degree of performance even in the presence of significant practical limitations.

A functional model of sensemaking in a neurocognitive architecture.

PubMed

Lebiere, Christian; Pirolli, Peter; Thomson, Robert; Paik, Jaehyon; Rutledge-Taylor, Matthew; Staszewski, James; Anderson, John R

2013-01-01

Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cognitive model of core information-foraging and hypothesis-updating sensemaking processes applied to complex spatial probability estimation and decision-making tasks. While the model was developed in a hybrid symbolic-statistical cognitive architecture, its correspondence to neural frameworks in terms of both structure and mechanisms provided a direct bridge between rational and neural levels of description. Compared against data from two participant groups, the model correctly predicted both the presence and degree of four biases: confirmation, anchoring and adjustment, representativeness, and probability matching. It also favorably predicted human performance in generating probability distributions across categories, assigning resources based on these distributions, and selecting relevant features given a prior probability distribution. This model provides a constrained theoretical framework describing cognitive biases as arising from three interacting factors: the structure of the task environment, the mechanisms and limitations of the cognitive architecture, and the use of strategies to adapt to the dual constraints of cognition and the environment.

Fabrication of Trabecular Bone-Templated Tissue-Engineered Constructs by 3D Inkjet Printing.

PubMed

Vanderburgh, Joseph P; Fernando, Shanik J; Merkel, Alyssa R; Sterling, Julie A; Guelcher, Scott A

2017-11-01

3D printing enables the creation of scaffolds with precisely controlled morphometric properties for multiple tissue types, including musculoskeletal tissues such as cartilage and bone. Computed tomography (CT) imaging has been combined with 3D printing to fabricate anatomically scaled patient-specific scaffolds for bone regeneration. However, anatomically scaled scaffolds typically lack sufficient resolution to recapitulate the <100 micrometer-scale trabecular architecture essential for investigating the cellular response to the morphometric properties of bone. In this study, it is hypothesized that the architecture of trabecular bone regulates osteoblast differentiation and mineralization. To test this hypothesis, human bone-templated 3D constructs are fabricated via a new micro-CT/3D inkjet printing process. It is shown that this process reproducibly fabricates bone-templated constructs that recapitulate the anatomic site-specific morphometric properties of trabecular bone. A significant correlation is observed between the structure model index (a morphometric parameter related to surface curvature) and the degree of mineralization of human mesenchymal stem cells, with more concave surfaces promoting more extensive osteoblast differentiation and mineralization compared to predominately convex surfaces. These findings highlight the significant effects of trabecular architecture on osteoblast function. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Load-adaptive scaffold architecturing: a bioinspired approach to the design of porous additively manufactured scaffolds with optimized mechanical properties.

PubMed

Rainer, Alberto; Giannitelli, Sara M; Accoto, Dino; De Porcellinis, Stefano; Guglielmelli, Eugenio; Trombetta, Marcella

2012-04-01

Computer-Aided Tissue Engineering (CATE) is based on a set of additive manufacturing techniques for the fabrication of patient-specific scaffolds, with geometries obtained from medical imaging. One of the main issues regarding the application of CATE concerns the definition of the internal architecture of the fabricated scaffolds, which, in turn, influences their porosity and mechanical strength. The present study envisages an innovative strategy for the fabrication of highly optimized structures, based on the a priori finite element analysis (FEA) of the physiological load set at the implant site. The resulting scaffold micro-architecture does not follow a regular geometrical pattern; on the contrary, it is based on the results of a numerical study. The algorithm was applied to a solid free-form fabrication process, using poly(ε-caprolactone) as the starting material for the processing of additive manufactured structures. A simple and intuitive geometry was chosen as a proof-of-principle application, on which finite element simulations and mechanical testing were performed. Then, to demonstrate the capability in creating mechanically biomimetic structures, the proximal femur subjected to physiological loading conditions was considered and a construct fitting a femur head portion was designed and manufactured.

A Functional Model of Sensemaking in a Neurocognitive Architecture

PubMed Central

Lebiere, Christian; Paik, Jaehyon; Rutledge-Taylor, Matthew; Staszewski, James; Anderson, John R.

2013-01-01

Sensemaking is the active process of constructing a meaningful representation (i.e., making sense) of some complex aspect of the world. In relation to intelligence analysis, sensemaking is the act of finding and interpreting relevant facts amongst the sea of incoming reports, images, and intelligence. We present a cognitive model of core information-foraging and hypothesis-updating sensemaking processes applied to complex spatial probability estimation and decision-making tasks. While the model was developed in a hybrid symbolic-statistical cognitive architecture, its correspondence to neural frameworks in terms of both structure and mechanisms provided a direct bridge between rational and neural levels of description. Compared against data from two participant groups, the model correctly predicted both the presence and degree of four biases: confirmation, anchoring and adjustment, representativeness, and probability matching. It also favorably predicted human performance in generating probability distributions across categories, assigning resources based on these distributions, and selecting relevant features given a prior probability distribution. This model provides a constrained theoretical framework describing cognitive biases as arising from three interacting factors: the structure of the task environment, the mechanisms and limitations of the cognitive architecture, and the use of strategies to adapt to the dual constraints of cognition and the environment. PMID:24302930

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

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

Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

3D sorghum reconstructions from depth images identify QTL regulating shoot architecture

DOE PAGES

Mccormick, Ryan F.; Truong, Sandra K.; Mullet, John E.

2016-08-15

Dissecting the genetic basis of complex traits is aided by frequent and nondestructive measurements. Advances in range imaging technologies enable the rapid acquisition of three-dimensional (3D) data from an imaged scene. A depth camera was used to acquire images of sorghum (Sorghum bicolor), an important grain, forage, and bioenergy crop, at multiple developmental time points from a greenhouse-grown recombinant inbred line population. A semiautomated software pipeline was developed and used to generate segmented, 3D plant reconstructions from the images. Automated measurements made from 3D plant reconstructions identified quantitative trait loci for standard measures of shoot architecture, such as shoot height,more » leaf angle, and leaf length, and for novel composite traits, such as shoot compactness. The phenotypic variability associated with some of the quantitative trait loci displayed differences in temporal prevalence; for example, alleles closely linked with the sorghum Dwarf3 gene, an auxin transporter and pleiotropic regulator of both leaf inclination angle and shoot height, influence leaf angle prior to an effect on shoot height. Furthermore, variability in composite phenotypes that measure overall shoot architecture, such as shoot compactness, is regulated by loci underlying component phenotypes like leaf angle. As such, depth imaging is an economical and rapid method to acquire shoot architecture phenotypes in agriculturally important plants like sorghum to study the genetic basis of complex traits.« less

ConfocalVR: Immersive Visualization Applied to Confocal Microscopy.

PubMed

Stefani, Caroline; Lacy-Hulbert, Adam; Skillman, Thomas

2018-06-24

ConfocalVR is a virtual reality (VR) application created to improve the ability of researchers to study the complexity of cell architecture. Confocal microscopes take pictures of fluorescently labeled proteins or molecules at different focal planes to create a stack of 2D images throughout the specimen. Current software applications reconstruct the 3D image and render it as a 2D projection onto a computer screen where users need to rotate the image to expose the full 3D structure. This process is mentally taxing, breaks down if you stop the rotation, and does not take advantage of the eye's full field of view. ConfocalVR exploits consumer-grade virtual reality (VR) systems to fully immerse the user in the 3D cellular image. In this virtual environment the user can: 1) adjust image viewing parameters without leaving the virtual space, 2) reach out and grab the image to quickly rotate and scale the image to focus on key features, and 3) interact with other users in a shared virtual space enabling real-time collaborative exploration and discussion. We found that immersive VR technology allows the user to rapidly understand cellular architecture and protein or molecule distribution. We note that it is impossible to understand the value of immersive visualization without experiencing it first hand, so we encourage readers to get access to a VR system, download this software, and evaluate it for yourself. The ConfocalVR software is available for download at http://www.confocalvr.com, and is free for nonprofits. Copyright © 2018. Published by Elsevier Ltd.

Segmentation of fluorescence microscopy images for quantitative analysis of cell nuclear architecture.

PubMed

Russell, Richard A; Adams, Niall M; Stephens, David A; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S

2009-04-22

Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments.

Segmentation of Fluorescence Microscopy Images for Quantitative Analysis of Cell Nuclear Architecture

PubMed Central

Russell, Richard A.; Adams, Niall M.; Stephens, David A.; Batty, Elizabeth; Jensen, Kirsten; Freemont, Paul S.

2009-01-01

Abstract Considerable advances in microscopy, biophysics, and cell biology have provided a wealth of imaging data describing the functional organization of the cell nucleus. Until recently, cell nuclear architecture has largely been assessed by subjective visual inspection of fluorescently labeled components imaged by the optical microscope. This approach is inadequate to fully quantify spatial associations, especially when the patterns are indistinct, irregular, or highly punctate. Accurate image processing techniques as well as statistical and computational tools are thus necessary to interpret this data if meaningful spatial-function relationships are to be established. Here, we have developed a thresholding algorithm, stable count thresholding (SCT), to segment nuclear compartments in confocal laser scanning microscopy image stacks to facilitate objective and quantitative analysis of the three-dimensional organization of these objects using formal statistical methods. We validate the efficacy and performance of the SCT algorithm using real images of immunofluorescently stained nuclear compartments and fluorescent beads as well as simulated images. In all three cases, the SCT algorithm delivers a segmentation that is far better than standard thresholding methods, and more importantly, is comparable to manual thresholding results. By applying the SCT algorithm and statistical analysis, we quantify the spatial configuration of promyelocytic leukemia nuclear bodies with respect to irregular-shaped SC35 domains. We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state. The methods reported are general and can readily be applied to quantify the spatial interactions of other nuclear compartments. PMID:19383481

Design of CMOS imaging system based on FPGA

NASA Astrophysics Data System (ADS)

Hu, Bo; Chen, Xiaolai

2017-10-01

In order to meet the needs of engineering applications for high dynamic range CMOS camera under the rolling shutter mode, a complete imaging system is designed based on the CMOS imaging sensor NSC1105. The paper decides CMOS+ADC+FPGA+Camera Link as processing architecture and introduces the design and implementation of the hardware system. As for camera software system, which consists of CMOS timing drive module, image acquisition module and transmission control module, the paper designs in Verilog language and drives it to work properly based on Xilinx FPGA. The ISE 14.6 emulator ISim is used in the simulation of signals. The imaging experimental results show that the system exhibits a 1280*1024 pixel resolution, has a frame frequency of 25 fps and a dynamic range more than 120dB. The imaging quality of the system satisfies the requirement of the index.

Expanding the spectrum: 20 years of advances in MMW imagery

NASA Astrophysics Data System (ADS)

Martin, Christopher A.; Lovberg, John A.; Kolinko, Valdimir G.

2017-05-01

Millimeter-wave imaging has expanded from the single-pixel swept imagers developed in the 1960s to large field-ofview real-time systems in use today. Trex Enterprises has been developing millimeter-wave imagers since 1991 for aviation and security applications, as well as millimeter-wave communications devices. As MMIC device development was stretching into the MMW band in the 1990s, Trex developed novel imaging architectures to create 2-D staring systems with large pixel counts and no moving parts while using a minimal number of devices. Trex also contributed to the device development in amplifiers, switches, and detectors to enable the next generation of passive MMW imaging systems. The architectures and devices developed continue to be employed in security imagers, radar, and radios produced by Trex. This paper reviews the development of the initial real-time MMW imagers and associated devices by Trex Enterprises from the 1990s through the 2000s. The devices include W-band MMIC amplifiers, switches, and detector didoes, and MMW circuit boards and optical processors. The imaging systems discussed include two different real-time passive MMW imagers flown on helicopters and a MMW radar system, as well as implementation of the devices and architectures in simpler stand-off and gateway security imagers.

Reconfigurable Hardware for Compressing Hyperspectral Image Data

NASA Technical Reports Server (NTRS)

Aranki, Nazeeh; Namkung, Jeffrey; Villapando, Carlos; Kiely, Aaron; Klimesh, Matthew; Xie, Hua

2010-01-01

High-speed, low-power, reconfigurable electronic hardware has been developed to implement ICER-3D, an algorithm for compressing hyperspectral-image data. The algorithm and parts thereof have been the topics of several NASA Tech Briefs articles, including Context Modeler for Wavelet Compression of Hyperspectral Images (NPO-43239) and ICER-3D Hyperspectral Image Compression Software (NPO-43238), which appear elsewhere in this issue of NASA Tech Briefs. As described in more detail in those articles, the algorithm includes three main subalgorithms: one for computing wavelet transforms, one for context modeling, and one for entropy encoding. For the purpose of designing the hardware, these subalgorithms are treated as modules to be implemented efficiently in field-programmable gate arrays (FPGAs). The design takes advantage of industry- standard, commercially available FPGAs. The implementation targets the Xilinx Virtex II pro architecture, which has embedded PowerPC processor cores with flexible on-chip bus architecture. It incorporates an efficient parallel and pipelined architecture to compress the three-dimensional image data. The design provides for internal buffering to minimize intensive input/output operations while making efficient use of offchip memory. The design is scalable in that the subalgorithms are implemented as independent hardware modules that can be combined in parallel to increase throughput. The on-chip processor manages the overall operation of the compression system, including execution of the top-level control functions as well as scheduling, initiating, and monitoring processes. The design prototype has been demonstrated to be capable of compressing hyperspectral data at a rate of 4.5 megasamples per second at a conservative clock frequency of 50 MHz, with a potential for substantially greater throughput at a higher clock frequency. The power consumption of the prototype is less than 6.5 W. The reconfigurability (by means of reprogramming) of the FPGAs makes it possible to effectively alter the design to some extent to satisfy different requirements without adding hardware. The implementation could be easily propagated to future FPGA generations and/or to custom application-specific integrated circuits.

Design and DSP implementation of star image acquisition and star point fast acquiring and tracking

NASA Astrophysics Data System (ADS)

Zhou, Guohui; Wang, Xiaodong; Hao, Zhihang

2006-02-01

Star sensor is a special high accuracy photoelectric sensor. Attitude acquisition time is an important function index of star sensor. In this paper, the design target is to acquire 10 samples per second dynamic performance. On the basis of analyzing CCD signals timing and star image processing, a new design and a special parallel architecture for improving star image processing are presented in this paper. In the design, the operation moving the data in expanded windows including the star to the on-chip memory of DSP is arranged in the invalid period of CCD frame signal. During the CCD saving the star image to memory, DSP processes the data in the on-chip memory. This parallelism greatly improves the efficiency of processing. The scheme proposed here results in enormous savings of memory normally required. In the scheme, DSP HOLD mode and CPLD technology are used to make a shared memory between CCD and DSP. The efficiency of processing is discussed in numerical tests. Only in 3.5ms is acquired the five lightest stars in the star acquisition stage. In 43us, the data in five expanded windows including stars are moved into the internal memory of DSP, and in 1.6ms, five star coordinates are achieved in the star tracking stage.

3D X-Ray Nanotomography of Cells Grown on Electrospun Scaffolds.

PubMed

Bradley, Robert S; Robinson, Ian K; Yusuf, Mohammed

2017-02-01

Here, it is demonstrated that X-ray nanotomography with Zernike phase contrast can be used for 3D imaging of cells grown on electrospun polymer scaffolds. The scaffold fibers and cells are simultaneously imaged, enabling the influence of scaffold architecture on cell location and morphology to be studied. The high resolution enables subcellular details to be revealed. The X-ray imaging conditions were optimized to reduce scan times, making it feasible to scan multiple regions of interest in relatively large samples. An image processing procedure is presented which enables scaffold characteristics and cell location to be quantified. The procedure is demonstrated by comparing the ingrowth of cells after culture for 3 and 6 days. © 2016 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design of low noise imaging system

NASA Astrophysics Data System (ADS)

Hu, Bo; Chen, Xiaolai

2017-10-01

In order to meet the needs of engineering applications for low noise imaging system under the mode of global shutter, a complete imaging system is designed based on the SCMOS (Scientific CMOS) image sensor CIS2521F. The paper introduces hardware circuit and software system design. Based on the analysis of key indexes and technologies about the imaging system, the paper makes chips selection and decides SCMOS + FPGA+ DDRII+ Camera Link as processing architecture. Then it introduces the entire system workflow and power supply and distribution unit design. As for the software system, which consists of the SCMOS control module, image acquisition module, data cache control module and transmission control module, the paper designs in Verilog language and drives it to work properly based on Xilinx FPGA. The imaging experimental results show that the imaging system exhibits a 2560*2160 pixel resolution, has a maximum frame frequency of 50 fps. The imaging quality of the system satisfies the requirement of the index.

ROI-Based On-Board Compression for Hyperspectral Remote Sensing Images on GPU.

PubMed

Giordano, Rossella; Guccione, Pietro

2017-05-19

In recent years, hyperspectral sensors for Earth remote sensing have become very popular. Such systems are able to provide the user with images having both spectral and spatial information. The current hyperspectral spaceborne sensors are able to capture large areas with increased spatial and spectral resolution. For this reason, the volume of acquired data needs to be reduced on board in order to avoid a low orbital duty cycle due to limited storage space. Recently, literature has focused the attention on efficient ways for on-board data compression. This topic is a challenging task due to the difficult environment (outer space) and due to the limited time, power and computing resources. Often, the hardware properties of Graphic Processing Units (GPU) have been adopted to reduce the processing time using parallel computing. The current work proposes a framework for on-board operation on a GPU, using NVIDIA's CUDA (Compute Unified Device Architecture) architecture. The algorithm aims at performing on-board compression using the target's related strategy. In detail, the main operations are: the automatic recognition of land cover types or detection of events in near real time in regions of interest (this is a user related choice) with an unsupervised classifier; the compression of specific regions with space-variant different bit rates including Principal Component Analysis (PCA), wavelet and arithmetic coding; and data volume management to the Ground Station. Experiments are provided using a real dataset taken from an AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) airborne sensor in a harbor area.

Microtomographic imaging in the process of bone modeling and simulation

NASA Astrophysics Data System (ADS)

Mueller, Ralph

1999-09-01

Micro-computed tomography ((mu) CT) is an emerging technique to nondestructively image and quantify trabecular bone in three dimensions. Where the early implementations of (mu) CT focused more on technical aspects of the systems and required equipment not normally available to the general public, a more recent development emphasized practical aspects of micro- tomographic imaging. That system is based on a compact fan- beam type of tomograph, also referred to as desktop (mu) CT. Desk-top (mu) CT has been used extensively for the investigation of osteoporosis related health problems gaining new insight into the organization of trabecular bone and the influence of osteoporotic bone loss on bone architecture and the competence of bone. Osteoporosis is a condition characterized by excessive bone loss and deterioration in bone architecture. The reduced quality of bone increases the risk of fracture. Current imaging technologies do not allow accurate in vivo measurements of bone structure over several decades or the investigation of the local remodeling stimuli at the tissue level. Therefore, computer simulations and new experimental modeling procedures are necessary for determining the long-term effects of age, menopause, and osteoporosis on bone. Microstructural bone models allow us to study not only the effects of osteoporosis on the skeleton but also to assess and monitor the effectiveness of new treatment regimens. The basis for such approaches are realistic models of bone and a sound understanding of the underlying biological and mechanical processes in bone physiology. In this article, strategies for new approaches to bone modeling and simulation in the study and treatment of osteoporosis and age-related bone loss are presented. The focus is on the bioengineering and imaging aspects of osteoporosis research. With the introduction of desk-top (mu) CT, a new generation of imaging instruments has entered the arena allowing easy and relatively inexpensive access to the three-dimensional microstructure of bone, thereby giving bone researchers a powerful tool for the exploration of age-related bone loss and osteoporosis.

Single-snapshot 2D color measurement by plenoptic imaging system

NASA Astrophysics Data System (ADS)

Masuda, Kensuke; Yamanaka, Yuji; Maruyama, Go; Nagai, Sho; Hirai, Hideaki; Meng, Lingfei; Tosic, Ivana

2014-03-01

Plenoptic cameras enable capture of directional light ray information, thus allowing applications such as digital refocusing, depth estimation, or multiband imaging. One of the most common plenoptic camera architectures contains a microlens array at the conventional image plane and a sensor at the back focal plane of the microlens array. We leverage the multiband imaging (MBI) function of this camera and develop a single-snapshot, single-sensor high color fidelity camera. Our camera is based on a plenoptic system with XYZ filters inserted in the pupil plane of the main lens. To achieve high color measurement precision of this system, we perform an end-to-end optimization of the system model that includes light source information, object information, optical system information, plenoptic image processing and color estimation processing. Optimized system characteristics are exploited to build an XYZ plenoptic colorimetric camera prototype that achieves high color measurement precision. We describe an application of our colorimetric camera to color shading evaluation of display and show that it achieves color accuracy of ΔE<0.01.

High-throughput neuroimaging-genetics computational infrastructure

PubMed Central

Dinov, Ivo D.; Petrosyan, Petros; Liu, Zhizhong; Eggert, Paul; Hobel, Sam; Vespa, Paul; Woo Moon, Seok; Van Horn, John D.; Franco, Joseph; Toga, Arthur W.

2014-01-01

Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core infrastructure necessary to plan, organize, orchestrate, validate, and disseminate novel scientific methods, computational resources, and translational healthcare findings. Data management includes protocols for data acquisition, archival, query, transfer, retrieval, and aggregation. Computational processing involves the necessary software, hardware, and networking infrastructure required to handle large amounts of heterogeneous neuroimaging, genetics, clinical, and phenotypic data and meta-data. Data mining refers to the process of automatically extracting data features, characteristics and associations, which are not readily visible by human exploration of the raw dataset. Result interpretation includes scientific visualization, community validation of findings and reproducible findings. In this manuscript we describe the novel high-throughput neuroimaging-genetics computational infrastructure available at the Institute for Neuroimaging and Informatics (INI) and the Laboratory of Neuro Imaging (LONI) at University of Southern California (USC). INI and LONI include ultra-high-field and standard-field MRI brain scanners along with an imaging-genetics database for storing the complete provenance of the raw and derived data and meta-data. In addition, the institute provides a large number of software tools for image and shape analysis, mathematical modeling, genomic sequence processing, and scientific visualization. A unique feature of this architecture is the Pipeline environment, which integrates the data management, processing, transfer, and visualization. Through its client-server architecture, the Pipeline environment provides a graphical user interface for designing, executing, monitoring validating, and disseminating of complex protocols that utilize diverse suites of software tools and web-services. These pipeline workflows are represented as portable XML objects which transfer the execution instructions and user specifications from the client user machine to remote pipeline servers for distributed computing. Using Alzheimer's and Parkinson's data, we provide several examples of translational applications using this infrastructure1. PMID:24795619

MACCS : Multi-Mission Atmospheric Correction and Cloud Screening tool for high-frequency revisit data processing

NASA Astrophysics Data System (ADS)

Petrucci, B.; Huc, M.; Feuvrier, T.; Ruffel, C.; Hagolle, O.; Lonjou, V.; Desjardins, C.

2015-10-01

For the production of Level2A products during Sentinel-2 commissioning in the Technical Expertise Center Sentinel-2 in CNES, CESBIO proposed to adapt the Venus Level-2 , taking advantage of the similarities between the two missions: image acquisition at a high frequency (2 days for Venus, 5 days with the two Sentinel-2), high resolution (5m for Venus, 10, 20 and 60m for Sentinel-2), images acquisition under constant viewing conditions. The Multi-Mission Atmospheric Correction and Cloud Screening (MACCS) tool was born: based on CNES Orfeo Toolbox Library, Venμs processor which was already able to process Formosat2 and VENμS data, was adapted to process Sentinel-2 and Landsat5-7 data; since then, a great effort has been made reviewing MACCS software architecture in order to ease the add-on of new missions that have also the peculiarity of acquiring images at high resolution, high revisit and under constant viewing angles, such as Spot4/Take5 and Landsat8. The recursive and multi-temporal algorithm is implemented in a core that is the same for all the sensors and that combines several processing steps: estimation of cloud cover, cloud shadow, water, snow and shadows masks, of water vapor content, aerosol optical thickness, atmospheric correction. This core is accessed via a number of plug-ins where the specificity of the sensor and of the user project are taken into account: products format, algorithmic processing chaining and parameters. After a presentation of MACCS architecture and functionalities, the paper will give an overview of the production facilities integrating MACCS and the associated specificities: the interest for this tool has grown worldwide and MACCS will be used for extensive production within the THEIA land data center and Agri-S2 project. Finally the paper will zoom on the use of MACCS during Sentinel-2 In Orbit Test phase showing the first Level-2A products.

Application of Multiprotocol Medical Imaging Communications and an Extended DICOM WADO Service in a Teleradiology Architecture

PubMed Central

Koutelakis, George V.; Anastassopoulos, George K.; Lymberopoulos, Dimitrios K.

2012-01-01

Multiprotocol medical imaging communication through the Internet is more flexible than the tight DICOM transfers. This paper introduces a modular multiprotocol teleradiology architecture that integrates DICOM and common Internet services (based on web, FTP, and E-mail) into a unique operational domain. The extended WADO service (a web extension of DICOM) and the other proposed services allow access to all levels of the DICOM information hierarchy as opposed to solely Object level. A lightweight client site is considered adequate, because the server site of the architecture provides clients with service interfaces through the web as well as invulnerable space for temporary storage, called as User Domains, so that users fulfill their applications' tasks. The proposed teleradiology architecture is pilot implemented using mainly Java-based technologies and is evaluated by engineers in collaboration with doctors. The new architecture ensures flexibility in access, user mobility, and enhanced data security. PMID:22489237

Determination of mouse skeletal muscle architecture using three-dimensional diffusion tensor imaging.

PubMed

Heemskerk, Anneriet M; Strijkers, Gustav J; Vilanova, Anna; Drost, Maarten R; Nicolay, Klaas

2005-06-01

Muscle architecture is the main determinant of the mechanical behavior of skeletal muscles. This study explored the feasibility of diffusion tensor imaging (DTI) and fiber tracking to noninvasively determine the in vivo three-dimensional (3D) architecture of skeletal muscle in mouse hind leg. In six mice, the hindlimb was imaged with a diffusion-weighted (DW) 3D fast spin-echo (FSE) sequence followed by the acquisition of an exercise-induced, T(2)-enhanced data set. The data showed the expected fiber organization, from which the physiological cross-sectional area (PCSA), fiber length, and pennation angle for the tibialis anterior (TA) were obtained. The values of these parameters ranged from 5.4-9.1 mm(2), 5.8-7.8 mm, and 21-24 degrees , respectively, which is in agreement with values obtained previously with the use of invasive methods. This study shows that 3D DT acquisition and fiber tracking is feasible for the skeletal muscle of mice, and thus enables the quantitative determination of muscle architecture.

Fast-responder: Rapid mobile-phone access to recent remote sensing imagery for first responders

NASA Astrophysics Data System (ADS)

Talbot, L. M.; Talbot, B. G.

We introduce Fast-Responder, a novel prototype data-dissemination application and architecture concept to rapidly deliver remote sensing imagery to smartphones to enable situational awareness. The architecture implements a Fast-Earth image caching system on the phone and interacts with a Fast-Earth server. Prototype evaluation successfully demonstrated that National Guard users could select a location, download multiple remote sensing images, and flicker between images, all in less than a minute on a 3G mobile commercial link. The Fast-Responder architecture is a significant advance that is designed to meet the needs of mobile users, such as National Guard response units, to rapidly access information during a crisis, such as a natural or man-made disaster. This paper focuses on the architecture design and advanced user interface concepts for small-screens for highly active mobile users. Novel Fast-Responder concepts can also enable rapid dissemination and evaluation of imagery on the desktop, opening new technology horizons for both desktop and mobile users.

A Mission Control Architecture for robotic lunar sample return as field tested in an analogue deployment to the sudbury impact structure

NASA Astrophysics Data System (ADS)

Moores, John E.; Francis, Raymond; Mader, Marianne; Osinski, G. R.; Barfoot, T.; Barry, N.; Basic, G.; Battler, M.; Beauchamp, M.; Blain, S.; Bondy, M.; Capitan, R.-D.; Chanou, A.; Clayton, J.; Cloutis, E.; Daly, M.; Dickinson, C.; Dong, H.; Flemming, R.; Furgale, P.; Gammel, J.; Gharfoor, N.; Hussein, M.; Grieve, R.; Henrys, H.; Jaziobedski, P.; Lambert, A.; Leung, K.; Marion, C.; McCullough, E.; McManus, C.; Neish, C. D.; Ng, H. K.; Ozaruk, A.; Pickersgill, A.; Preston, L. J.; Redman, D.; Sapers, H.; Shankar, B.; Singleton, A.; Souders, K.; Stenning, B.; Stooke, P.; Sylvester, P.; Tornabene, L.

2012-12-01

A Mission Control Architecture is presented for a Robotic Lunar Sample Return Mission which builds upon the experience of the landed missions of the NASA Mars Exploration Program. This architecture consists of four separate processes working in parallel at Mission Control and achieving buy-in for plans sequentially instead of simultaneously from all members of the team. These four processes were: science processing, science interpretation, planning and mission evaluation. science processing was responsible for creating products from data downlinked from the field and is organized by instrument. Science Interpretation was responsible for determining whether or not science goals are being met and what measurements need to be taken to satisfy these goals. The Planning process, responsible for scheduling and sequencing observations, and the Evaluation process that fostered inter-process communications, reporting and documentation assisted these processes. This organization is advantageous for its flexibility as shown by the ability of the structure to produce plans for the rover every two hours, for the rapidity with which Mission Control team members may be trained and for the relatively small size of each individual team. This architecture was tested in an analogue mission to the Sudbury impact structure from June 6-17, 2011. A rover was used which was capable of developing a network of locations that could be revisited using a teach and repeat method. This allowed the science team to process several different outcrops in parallel, downselecting at each stage to ensure that the samples selected for caching were the most representative of the site. Over the course of 10 days, 18 rock samples were collected from 5 different outcrops, 182 individual field activities - such as roving or acquiring an image mosaic or other data product - were completed within 43 command cycles, and the rover travelled over 2200 m. Data transfer from communications passes were filled to 74%. Sample triage was simulated to allow down-selection to 1 kg of material for return to Earth.

Evaluation of Sidestream Darkfield Microscopy for Real-Time Imaging Acellular Dermal Matrix Revascularization.

PubMed

DeGeorge, Brent R; Olenczak, J Bryce; Cottler, Patrick S; Drake, David B; Lin, Kant Y; Morgan, Raymond F; Campbell, Christopher A

2016-06-01

Acellular dermal matrices (ADMs) serve as a regenerative framework for host cell integration and collagen deposition to augment the soft tissue envelope in ADM-assisted breast reconstruction-a process dependent on vascular ingrowth. To date noninvasive intra-operative imaging techniques have been inadequate to evaluate the revascularization of ADM. We investigated the safety, feasibility, and efficacy of sidestream darkfield (SDF) microscopy to assess the status of ADM microvascular architecture in 8 patients at the time of tissue expander to permanent implant exchange during 2-stage ADM-assisted breast reconstruction. The SDF microscopy is a handheld device, which can be used intraoperatively for the real-time assessment of ADM blood flow, vessel density, vessel size, and branching pattern. The SDF microscopy was used to assess the microvascular architecture in the center and border zone of the ADM and to compare the native, non-ADM-associated capsule in each patient as a within-subject control. No incidences of periprosthetic infection, explantation, or adverse events were reported after SDF image acquisition. Native capsules demonstrate a complex, layered architecture with an average vessel area density of 14.9 mm/mm and total vessel length density of 12.3 mm/mm. In contrast to native periprosthetic capsules, ADM-associated capsules are not uniformly vascularized structures and demonstrate 2 zones of microvascular architecture. The ADM and native capsule border zone demonstrates palisading peripheral vascular arcades with continuous antegrade flow. The central zone of the ADM demonstrates punctate perforating vascular plexi with intermittent, sluggish flow, and intervening 2- to 3-cm watershed zones. Sidestream darkfield microscopy allows for real-time intraoperative assessment of ADM revascularization and serves as a potential methodology to compare revascularization parameters among commercially available ADMs. Thr SDF microscopy demonstrates that the periprosthetic capsule in ADM-assisted implant-based breast reconstruction is not a uniformly vascularized structure.

Low Temperature Performance of High-Speed Neural Network Circuits

NASA Technical Reports Server (NTRS)

Duong, T.; Tran, M.; Daud, T.; Thakoor, A.

1995-01-01

Artificial neural networks, derived from their biological counterparts, offer a new and enabling computing paradigm specially suitable for such tasks as image and signal processing with feature classification/object recognition, global optimization, and adaptive control. When implemented in fully parallel electronic hardware, it offers orders of magnitude speed advantage. Basic building blocks of the new architecture are the processing elements called neurons implemented as nonlinear operational amplifiers with sigmoidal transfer function, interconnected through weighted connections called synapses implemented using circuitry for weight storage and multiply functions either in an analog, digital, or hybrid scheme.

Framework for Development and Distribution of Hardware Acceleration

NASA Astrophysics Data System (ADS)

Thomas, David B.; Luk, Wayne W.

2002-07-01

This paper describes IGOL, a framework for developing reconfigurable data processing applications. While IGOL was originally designed to target imaging and graphics systems, its structure is sufficiently general to support a broad range of applications. IGOL adopts a four-layer architecture: application layer, operation layer, appliance layer and configuration layer. This architecture is intended to separate and co-ordinate both the development and execution of hardware and software components. Hardware developers can use IGOL as an instance testbed for verification and benchmarking, as well as for distribution. Software application developers can use IGOL to discover hardware accelerated data processors, and to access them in a transparent, non-hardware specific manner. IGOL provides extensive support for the RC1000-PP board via the Handel-C language, and a wide selection of image processing filters have been developed. IGOL also supplies plug-ins to enable such filters to be incorporated in popular applications such as Premiere, Winamp, VirtualDub and DirectShow. Moreover, IGOL allows the automatic use of multiple cards to accelerate an application, demonstrated using DirectShow. To enable transparent acceleration without sacrificing performance, a three-tiered COM (Component Object Model) API has been designed and implemented. This API provides a well-defined and extensible interface which facilitates the development of hardware data processors that can accelerate multiple applications.

Implementation of MPEG-2 encoder to multiprocessor system using multiple MVPs (TMS320C80)

NASA Astrophysics Data System (ADS)

Kim, HyungSun; Boo, Kenny; Chung, SeokWoo; Choi, Geon Y.; Lee, YongJin; Jeon, JaeHo; Park, Hyun Wook

1997-05-01

This paper presents the efficient algorithm mapping for the real-time MPEG-2 encoding on the KAIST image computing system (KICS), which has a parallel architecture using five multimedia video processors (MVPs). The MVP is a general purpose digital signal processor (DSP) of Texas Instrument. It combines one floating-point processor and four fixed- point DSPs on a single chip. The KICS uses the MVP as a primary processing element (PE). Two PEs form a cluster, and there are two processing clusters in the KICS. Real-time MPEG-2 encoder is implemented through the spatial and the functional partitioning strategies. Encoding process of spatially partitioned half of the video input frame is assigned to ne processing cluster. Two PEs perform the functionally partitioned MPEG-2 encoding tasks in the pipelined operation mode. One PE of a cluster carries out the transform coding part and the other performs the predictive coding part of the MPEG-2 encoding algorithm. One MVP among five MVPs is used for system control and interface with host computer. This paper introduces an implementation of the MPEG-2 algorithm with a parallel processing architecture.

Optical and Electric Multifunctional CMOS Image Sensors for On-Chip Biosensing Applications

PubMed Central

Tokuda, Takashi; Noda, Toshihiko; Sasagawa, Kiyotaka; Ohta, Jun

2010-01-01

In this review, the concept, design, performance, and a functional demonstration of multifunctional complementary metal-oxide-semiconductor (CMOS) image sensors dedicated to on-chip biosensing applications are described. We developed a sensor architecture that allows flexible configuration of a sensing pixel array consisting of optical and electric sensing pixels, and designed multifunctional CMOS image sensors that can sense light intensity and electric potential or apply a voltage to an on-chip measurement target. We describe the sensors’ architecture on the basis of the type of electric measurement or imaging functionalities. PMID:28879978

Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patients

NASA Astrophysics Data System (ADS)

Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J.

2018-02-01

Predicting mutation/loss of alpha-thalassemia/mental retardation syndrome X-linked (ATRX) gene utilizing MR imaging is of high importance since it is a predictor of response and prognosis in brain tumors. In this study, we compare a deep neural network approach based on a residual deep neural network (ResNet) architecture and one based on a classical machine learning approach and evaluate their ability in predicting ATRX mutation status without the need for a distinct tumor segmentation step. We found that the ResNet50 (50 layers) architecture, pre trained on ImageNet data was the best performing model, achieving an accuracy of 0.91 for the test set (classification of a slice as no tumor, ATRX mutated, or mutated) in terms of f1 score in a test set of 35 cases. The SVM classifier achieved 0.63 for differentiating the Flair signal abnormality regions from the test patients based on their mutation status. We report a method that alleviates the need for extensive preprocessing and acts as a proof of concept that deep neural network architectures can be used to predict molecular biomarkers from routine medical images.

Neural networks for data compression and invariant image recognition

NASA Technical Reports Server (NTRS)

Gardner, Sheldon

1989-01-01

An approach to invariant image recognition (I2R), based upon a model of biological vision in the mammalian visual system (MVS), is described. The complete I2R model incorporates several biologically inspired features: exponential mapping of retinal images, Gabor spatial filtering, and a neural network associative memory. In the I2R model, exponentially mapped retinal images are filtered by a hierarchical set of Gabor spatial filters (GSF) which provide compression of the information contained within a pixel-based image. A neural network associative memory (AM) is used to process the GSF coded images. We describe a 1-D shape function method for coding of scale and rotationally invariant shape information. This method reduces image shape information to a periodic waveform suitable for coding as an input vector to a neural network AM. The shape function method is suitable for near term applications on conventional computing architectures equipped with VLSI FFT chips to provide a rapid image search capability.

Habitable Exoplanet Imaging Mission (HabEx): Architecture of the 4m Mission Concept

NASA Astrophysics Data System (ADS)

Kuan, Gary M.; Warfield, Keith R.; Mennesson, Bertrand; Kiessling, Alina; Stahl, H. Philip; Martin, Stefan; Shaklan, Stuart B.; amini, rashied

2018-01-01

The Habitable Exoplanet Imaging Mission (HabEx) study is tasked by NASA to develop a scientifically compelling and technologically feasible exoplanet direct imaging mission concept, with extensive general astrophysics capabilities, for the 2020 Decadal Survey in Astrophysics. The baseline architecture of this space-based observatory concept encompasses an unobscured 4m diameter aperture telescope flying in formation with a 72-meter diameter starshade occulter. This large aperture, ultra-stable observatory concept extends and enhances upon the legacy of the Hubble Space Telescope by allowing us to probe even fainter objects and peer deeper into the Universe in the same ultraviolet, visible, and near infrared wavelengths, and gives us the capability, for the first time, to image and characterize potentially habitable, Earth-sized exoplanets orbiting nearby stars. Revolutionary direct imaging of exoplanets will be undertaken using a high-contrast coronagraph and a starshade imager. General astrophysics science will be undertaken with two world-class instruments – a wide-field workhorse camera for imaging and multi-object grism spectroscopy, and a multi-object, multi-resolution ultraviolet spectrograph. This poster outlines the baseline architecture of the HabEx flagship mission concept.

Utilizing data grid architecture for the backup and recovery of clinical image data.

PubMed

Liu, Brent J; Zhou, M Z; Documet, J

2005-01-01

Grid Computing represents the latest and most exciting technology to evolve from the familiar realm of parallel, peer-to-peer and client-server models. However, there has been limited investigation into the impact of this emerging technology in medical imaging and informatics. In particular, PACS technology, an established clinical image repository system, while having matured significantly during the past ten years, still remains weak in the area of clinical image data backup. Current solutions are expensive or time consuming and the technology is far from foolproof. Many large-scale PACS archive systems still encounter downtime for hours or days, which has the critical effect of crippling daily clinical operations. In this paper, a review of current backup solutions will be presented along with a brief introduction to grid technology. Finally, research and development utilizing the grid architecture for the recovery of clinical image data, in particular, PACS image data, will be presented. The focus of this paper is centered on applying a grid computing architecture to a DICOM environment since DICOM has become the standard for clinical image data and PACS utilizes this standard. A federation of PACS can be created allowing a failed PACS archive to recover its image data from others in the federation in a seamless fashion. The design reflects the five-layer architecture of grid computing: Fabric, Resource, Connectivity, Collective, and Application Layers. The testbed Data Grid is composed of one research laboratory and two clinical sites. The Globus 3.0 Toolkit (Co-developed by the Argonne National Laboratory and Information Sciences Institute, USC) for developing the core and user level middleware is utilized to achieve grid connectivity. The successful implementation and evaluation of utilizing data grid architecture for clinical PACS data backup and recovery will provide an understanding of the methodology for using Data Grid in clinical image data backup for PACS, as well as establishment of benchmarks for performance from future grid technology improvements. In addition, the testbed can serve as a road map for expanded research into large enterprise and federation level data grids to guarantee CA (Continuous Availability, 99.999% up time) in a variety of medical data archiving, retrieval, and distribution scenarios.

How predictive quantitative modelling of tissue organisation can inform liver disease pathogenesis.

PubMed

Drasdo, Dirk; Hoehme, Stefan; Hengstler, Jan G

2014-10-01

From the more than 100 liver diseases described, many of those with high incidence rates manifest themselves by histopathological changes, such as hepatitis, alcoholic liver disease, fatty liver disease, fibrosis, and, in its later stages, cirrhosis, hepatocellular carcinoma, primary biliary cirrhosis and other disorders. Studies of disease pathogeneses are largely based on integrating -omics data pooled from cells at different locations with spatial information from stained liver structures in animal models. Even though this has led to significant insights, the complexity of interactions as well as the involvement of processes at many different time and length scales constrains the possibility to condense disease processes in illustrations, schemes and tables. The combination of modern imaging modalities with image processing and analysis, and mathematical models opens up a promising new approach towards a quantitative understanding of pathologies and of disease processes. This strategy is discussed for two examples, ammonia metabolism after drug-induced acute liver damage, and the recovery of liver mass as well as architecture during the subsequent regeneration process. This interdisciplinary approach permits integration of biological mechanisms and models of processes contributing to disease progression at various scales into mathematical models. These can be used to perform in silico simulations to promote unravelling the relation between architecture and function as below illustrated for liver regeneration, and bridging from the in vitro situation and animal models to humans. In the near future novel mechanisms will usually not be directly elucidated by modelling. However, models will falsify hypotheses and guide towards the most informative experimental design. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid

PubMed Central

González, Martin; Sánchez-Pedraza, Antonio; Marfil, Rebeca; Rodríguez, Juan A.; Bandera, Antonio

2016-01-01

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms. PMID:27898029

Data-Driven Multiresolution Camera Using the Foveal Adaptive Pyramid.

PubMed

González, Martin; Sánchez-Pedraza, Antonio; Marfil, Rebeca; Rodríguez, Juan A; Bandera, Antonio

2016-11-26

There exist image processing applications, such as tracking or pattern recognition, that are not necessarily precise enough to maintain the same resolution across the whole image sensor. In fact, they must only keep it as high as possible in a relatively small region, but covering a wide field of view. This is the aim of foveal vision systems. Briefly, they propose to sense a large field of view at a spatially-variant resolution: one relatively small region, the fovea, is mapped at a high resolution, while the rest of the image is captured at a lower resolution. In these systems, this fovea must be moved, from one region of interest to another one, to scan a visual scene. It is interesting that the part of the scene that is covered by the fovea should not be merely spatial, but closely related to perceptual objects. Segmentation and attention are then intimately tied together: while the segmentation process is responsible for extracting perceptively-coherent entities from the scene (proto-objects), attention can guide segmentation. From this loop, the concept of foveal attention arises. This work proposes a hardware system for mapping a uniformly-sampled sensor to a space-variant one. Furthermore, this mapping is tied with a software-based, foveal attention mechanism that takes as input the stream of generated foveal images. The whole hardware/software architecture has been designed to be embedded within an all programmable system on chip (AP SoC). Our results show the flexibility of the data port for exchanging information between the mapping and attention parts of the architecture and the good performance rates of the mapping procedure. Experimental evaluation also demonstrates that the segmentation method and the attention model provide results comparable to other more computationally-expensive algorithms.

Architecture and Implementation of OpenPET Firmware and Embedded Software

PubMed Central

Abu-Nimeh, Faisal T.; Ito, Jennifer; Moses, William W.; Peng, Qiyu; Choong, Woon-Seng

2016-01-01

OpenPET is an open source, modular, extendible, and high-performance platform suitable for multi-channel data acquisition and analysis. Due to the flexibility of the hardware, firmware, and software architectures, the platform is capable of interfacing with a wide variety of detector modules not only in medical imaging but also in homeland security applications. Analog signals from radiation detectors share similar characteristics – a pulse whose area is proportional to the deposited energy and whose leading edge is used to extract a timing signal. As a result, a generic design method of the platform is adopted for the hardware, firmware, and software architectures and implementations. The analog front-end is hosted on a module called a Detector Board, where each board can filter, combine, timestamp, and process multiple channels independently. The processed data is formatted and sent through a backplane bus to a module called Support Board, where 1 Support Board can host up to eight Detector Board modules. The data in the Support Board, coming from 8 Detector Board modules, can be aggregated or correlated (if needed) depending on the algorithm implemented or runtime mode selected. It is then sent out to a computer workstation for further processing. The number of channels (detector modules), to be processed, mandates the overall OpenPET System Configuration, which is designed to handle up to 1,024 channels using 16-channel Detector Boards in the Standard System Configuration and 16,384 channels using 32-channel Detector Boards in the Large System Configuration. PMID:27110034

Assessing the multiscale architecture of muscular tissue with Q-space magnetic resonance imaging: Review.

PubMed

Hoffman, Matthew P; Taylor, Erik N; Aninwene, George E; Sadayappan, Sakthivel; Gilbert, Richard J

2018-02-01

Contraction of muscular tissue requires the synchronized shortening of myofibers arrayed in complex geometrical patterns. Imaging such myofiber patterns with diffusion-weighted MRI reveals architectural ensembles that underlie force generation at the organ scale. Restricted proton diffusion is a stochastic process resulting from random translational motion that may be used to probe the directionality of myofibers in whole tissue. During diffusion-weighted MRI, magnetic field gradients are applied to determine the directional dependence of proton diffusion through the analysis of a diffusional probability distribution function (PDF). The directions of principal (maximal) diffusion within the PDF are associated with similarly aligned diffusion maxima in adjacent voxels to derive multivoxel tracts. Diffusion-weighted MRI with tractography thus constitutes a multiscale method for depicting patterns of cellular organization within biological tissues. We provide in this review, details of the method by which generalized Q-space imaging is used to interrogate multidimensional diffusion space, and thereby to infer the organization of muscular tissue. Q-space imaging derives the lowest possible angular separation of diffusion maxima by optimizing the conditions by which magnetic field gradients are applied to a given tissue. To illustrate, we present the methods and applications associated with Q-space imaging of the multiscale myoarchitecture associated with the human and rodent tongues. These representations emphasize the intricate and continuous nature of muscle fiber organization and suggest a method to depict structural "blueprints" for skeletal and cardiac muscle tissue. © 2016 Wiley Periodicals, Inc.

Moving Multimedia: The Information Value in Images.

ERIC Educational Resources Information Center

Berinstein, Paula

1997-01-01

Discusses the value and use of images as information. Topics include the information in images versus text; a taxonomy of image types; resources related to images; and the use of images in architecture, engineering, advertising, and competitive intelligence. (LRW)

Two-dimensional systolic-array architecture for pixel-level vision tasks

NASA Astrophysics Data System (ADS)

Vijverberg, Julien A.; de With, Peter H. N.

2010-05-01

This paper presents ongoing work on the design of a two-dimensional (2D) systolic array for image processing. This component is designed to operate on a multi-processor system-on-chip. In contrast with other 2D systolic-array architectures and many other hardware accelerators, we investigate the applicability of executing multiple tasks in a time-interleaved fashion on the Systolic Array (SA). This leads to a lower external memory bandwidth and better load balancing of the tasks on the different processing tiles. To enable the interleaving of tasks, we add a shadow-state register for fast task switching. To reduce the number of accesses to the external memory, we propose to share the communication assist between consecutive tasks. A preliminary, non-functional version of the SA has been synthesized for an XV4S25 FPGA device and yields a maximum clock frequency of 150 MHz requiring 1,447 slices and 5 memory blocks. Mapping tasks from video content-analysis applications from literature on the SA yields reductions in the execution time of 1-2 orders of magnitude compared to the software implementation. We conclude that the choice for an SA architecture is useful, but a scaled version of the SA featuring less logic with fewer processing and pipeline stages yielding a lower clock frequency, would be sufficient for a video analysis system-on-chip.

Microscope-integrated optical coherence tomography for image-aided positioning of glaucoma surgery

NASA Astrophysics Data System (ADS)

Li, Xiqi; Wei, Ling; Dong, Xuechuan; Huang, Ping; Zhang, Chun; He, Yi; Shi, Guohua; Zhang, Yudong

2015-07-01

Most glaucoma surgeries involve creating new aqueous outflow pathways with the use of a small surgical instrument. This article reported a microscope-integrated, real-time, high-speed, swept-source optical coherence tomography system (SS-OCT) with a 1310-nm light source for glaucoma surgery. A special mechanism was designed to produce an adjustable system suitable for use in surgery. A two-graphic processing unit architecture was used to speed up the data processing and real-time volumetric rendering. The position of the surgical instrument can be monitored and measured using the microscope and a grid-inserted image of the SS-OCT. Finally, experiments were simulated to assess the effectiveness of this integrated system. Experimental results show that this system is a suitable positioning tool for glaucoma surgery.

Quantification of micro-CT images of textile reinforcements

NASA Astrophysics Data System (ADS)

Straumit, Ilya; Lomov, Stepan V.; Wevers, Martine

2017-10-01

VoxTex software (KU Leuven) employs 3D image processing, which use the local directionality information, retrieved using analysis of local structure tensor. The processing results in a voxel 3D array, with each voxel carrying information on (1) material type (matrix; yarn/ply, with identification of the yarn/ply in the reinforcement architecture; void) and (2) fibre direction for fibrous yarns/plies. The knowledge of the material phase volume and known characterisation of the textile structure allows assigning to the voxels (3) fibre volume fraction. This basic voxel model can be further used for different type of the material analysis: Internal geometry and characterisation of defects; permeability; micromechanics; mesoFE voxel models. Apart from the voxel based analysis, approaches to reconstruction of the yarn paths are presented.

a-Si:H TFT-silicon hybrid low-energy x-ray detector

DOE PAGES

Shin, Kyung -Wook; Karim, Karim S.

2017-03-15

Direct conversion crystalline silicon X-ray imagers are used for low-energy X-ray photon (4-20 keV) detection in scientific research applications such as protein crystallography. In this paper, we demonstrate a novel pixel architecture that integrates a crystalline silicon X-ray detector with a thin-film transistor amorphous silicon pixel readout circuit. We describe a simplified two-mask process to fabricate a complete imaging array and present preliminary results that show the fabricated pixel to be sensitive to 5.89-keV photons from a low activity Fe-55 gamma source. Furthermore, this paper presented can expedite the development of high spatial resolution, low cost, direct conversion imagers formore » X-ray diffraction and crystallography applications.« less

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines

PubMed Central

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-01-01

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately. PMID:27879843