Double-Stage Delay Multiply and Sum Beamforming Algorithm: Application to Linear-Array Photoacoustic Imaging.

PubMed

Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Adabi, Saba; Nasiriavanaki, Mohammadreza

2018-01-01

Photoacoustic imaging (PAI) is an emerging medical imaging modality capable of providing high spatial resolution of Ultrasound (US) imaging and high contrast of optical imaging. Delay-and-Sum (DAS) is the most common beamforming algorithm in PAI. However, using DAS beamformer leads to low resolution images and considerable contribution of off-axis signals. A new paradigm namely delay-multiply-and-sum (DMAS), which was originally used as a reconstruction algorithm in confocal microwave imaging, was introduced to overcome the challenges in DAS. DMAS was used in PAI systems and it was shown that this algorithm results in resolution improvement and sidelobe degrading. However, DMAS is still sensitive to high levels of noise, and resolution improvement is not satisfying. Here, we propose a novel algorithm based on DAS algebra inside DMAS formula expansion, double stage DMAS (DS-DMAS), which improves the image resolution and levels of sidelobe, and is much less sensitive to high level of noise compared to DMAS. The performance of DS-DMAS algorithm is evaluated numerically and experimentally. The resulted images are evaluated qualitatively and quantitatively using established quality metrics including signal-to-noise ratio (SNR), full-width-half-maximum (FWHM) and contrast ratio (CR). It is shown that DS-DMAS outperforms DAS and DMAS at the expense of higher computational load. DS-DMAS reduces the lateral valley for about 15 dB and improves the SNR and FWHM better than 13% and 30%, respectively. Moreover, the levels of sidelobe are reduced for about 10 dB in comparison with those in DMAS.

Processing of Fear and Anger Facial Expressions: The Role of Spatial Frequency

PubMed Central

Comfort, William E.; Wang, Meng; Benton, Christopher P.; Zana, Yossi

2013-01-01

Spatial frequency (SF) components encode a portion of the affective value expressed in face images. The aim of this study was to estimate the relative weight of specific frequency spectrum bandwidth on the discrimination of anger and fear facial expressions. The general paradigm was a classification of the expression of faces morphed at varying proportions between anger and fear images in which SF adaptation and SF subtraction are expected to shift classification of facial emotion. A series of three experiments was conducted. In Experiment 1 subjects classified morphed face images that were unfiltered or filtered to remove either low (<8 cycles/face), middle (12–28 cycles/face), or high (>32 cycles/face) SF components. In Experiment 2 subjects were adapted to unfiltered or filtered prototypical (non-morphed) fear face images and subsequently classified morphed face images. In Experiment 3 subjects were adapted to unfiltered or filtered prototypical fear face images with the phase component randomized before classifying morphed face images. Removing mid frequency components from the target images shifted classification toward fear. The same shift was observed under adaptation condition to unfiltered and low- and middle-range filtered fear images. However, when the phase spectrum of the same adaptation stimuli was randomized, no adaptation effect was observed. These results suggest that medium SF components support the perception of fear more than anger at both low and high level of processing. They also suggest that the effect at high-level processing stage is related more to high-level featural and/or configural information than to the low-level frequency spectrum. PMID:23637687

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.

High dynamic range CMOS-based mammography detector for FFDM and DBT

NASA Astrophysics Data System (ADS)

Peters, Inge M.; Smit, Chiel; Miller, James J.; Lomako, Andrey

2016-03-01

Digital Breast Tomosynthesis (DBT) requires excellent image quality in a dynamic mode at very low dose levels while Full Field Digital Mammography (FFDM) is a static imaging modality that requires high saturation dose levels. These opposing requirements can only be met by a dynamic detector with a high dynamic range. This paper will discuss a wafer-scale CMOS-based mammography detector with 49.5 μm pixels and a CsI scintillator. Excellent image quality is obtained for FFDM as well as DBT applications, comparing favorably with a-Se detectors that dominate the X-ray mammography market today. The typical dynamic range of a mammography detector is not high enough to accommodate both the low noise and the high saturation dose requirements for DBT and FFDM applications, respectively. An approach based on gain switching does not provide the signal-to-noise benefits in the low-dose DBT conditions. The solution to this is to add frame summing functionality to the detector. In one X-ray pulse several image frames will be acquired and summed. The requirements to implement this into a detector are low noise levels, high frame rates and low lag performance, all of which are unique characteristics of CMOS detectors. Results are presented to prove that excellent image quality is achieved, using a single detector for both DBT as well as FFDM dose conditions. This method of frame summing gave the opportunity to optimize the detector noise and saturation level for DBT applications, to achieve high DQE level at low dose, without compromising the FFDM performance.

On Max-Plus Algebra and Its Application on Image Steganography

PubMed Central

Santoso, Kiswara Agung

2018-01-01

We propose a new steganography method to hide an image into another image using matrix multiplication operations on max-plus algebra. This is especially interesting because the matrix used in encoding or information disguises generally has an inverse, whereas matrix multiplication operations in max-plus algebra do not have an inverse. The advantages of this method are the size of the image that can be hidden into the cover image, larger than the previous method. The proposed method has been tested on many secret images, and the results are satisfactory which have a high level of strength and a high level of security and can be used in various operating systems. PMID:29887761

On Max-Plus Algebra and Its Application on Image Steganography.

PubMed

Santoso, Kiswara Agung; Fatmawati; Suprajitno, Herry

2018-01-01

We propose a new steganography method to hide an image into another image using matrix multiplication operations on max-plus algebra. This is especially interesting because the matrix used in encoding or information disguises generally has an inverse, whereas matrix multiplication operations in max-plus algebra do not have an inverse. The advantages of this method are the size of the image that can be hidden into the cover image, larger than the previous method. The proposed method has been tested on many secret images, and the results are satisfactory which have a high level of strength and a high level of security and can be used in various operating systems.

A fast, robust pattern recognition asystem for low light level image registration and its application to retinal imaging

NASA Astrophysics Data System (ADS)

Wade, Alex Robert; Fitzke, Frederick W.

1998-08-01

We describe an image processing system which we have developed to align autofluorescence and high-magnification images taken with a laser scanning ophthalmoscope. The low signal to noise ratio of these images makes pattern recognition a non-trivial task. However, once n images are aligned and averaged, the noise levels drop by a factor of n and the image quality is improved. We include examples of autofluorescence images and images of the cone photoreceptor mosaic obtained using this system.

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

NASA Astrophysics Data System (ADS)

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

2010-01-01

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

Fully Convolutional Architecture for Low-Dose CT Image Noise Reduction

NASA Astrophysics Data System (ADS)

Badretale, S.; Shaker, F.; Babyn, P.; Alirezaie, J.

2017-10-01

One of the critical topics in medical low-dose Computed Tomography (CT) imaging is how best to maintain image quality. As the quality of images decreases with lowering the X-ray radiation dose, improving image quality is extremely important and challenging. We have proposed a novel approach to denoise low-dose CT images. Our algorithm learns directly from an end-to-end mapping from the low-dose Computed Tomography images for denoising the normal-dose CT images. Our method is based on a deep convolutional neural network with rectified linear units. By learning various low-level to high-level features from a low-dose image the proposed algorithm is capable of creating a high-quality denoised image. We demonstrate the superiority of our technique by comparing the results with two other state-of-the-art methods in terms of the peak signal to noise ratio, root mean square error, and a structural similarity index.

High-performance compression and double cryptography based on compressive ghost imaging with the fast Fourier transform

NASA Astrophysics Data System (ADS)

Leihong, Zhang; Zilan, Pan; Luying, Wu; Xiuhua, Ma

2016-11-01

To solve the problem that large images can hardly be retrieved for stringent hardware restrictions and the security level is low, a method based on compressive ghost imaging (CGI) with Fast Fourier Transform (FFT) is proposed, named FFT-CGI. Initially, the information is encrypted by the sender with FFT, and the FFT-coded image is encrypted by the system of CGI with a secret key. Then the receiver decrypts the image with the aid of compressive sensing (CS) and FFT. Simulation results are given to verify the feasibility, security, and compression of the proposed encryption scheme. The experiment suggests the method can improve the quality of large images compared with conventional ghost imaging and achieve the imaging for large-sized images, further the amount of data transmitted largely reduced because of the combination of compressive sensing and FFT, and improve the security level of ghost images through ciphertext-only attack (COA), chosen-plaintext attack (CPA), and noise attack. This technique can be immediately applied to encryption and data storage with the advantages of high security, fast transmission, and high quality of reconstructed information.

A high-level 3D visualization API for Java and ImageJ.

PubMed

Schmid, Benjamin; Schindelin, Johannes; Cardona, Albert; Longair, Mark; Heisenberg, Martin

2010-05-21

Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set. Here we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts. Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.

Fast algorithm of low power image reformation for OLED display

NASA Astrophysics Data System (ADS)

Lee, Myungwoo; Kim, Taewhan

2014-04-01

We propose a fast algorithm of low-power image reformation for organic light-emitting diode (OLED) display. The proposed algorithm scales the image histogram in a way to reduce power consumption in OLED display by remapping the gray levels of the pixels in the image based on the fast analysis of the histogram of the input image while maintaining contrast of the image. The key idea is that a large number of gray levels are never used in the images and these gray levels can be effectively exploited to reduce power consumption. On the other hand, to maintain the image contrast the gray level remapping is performed by taking into account the object size in the image to which each gray level is applied, that is, reforming little for the gray levels in the objects of large size. Through experiments with 24 Kodak images, it is shown that our proposed algorithm is able to reduce the power consumption by 10% even with 9% contrast enhancement. Our algorithm runs in a linear time so that it can be applied to moving pictures with high resolution.

Design of a new type synchronous focusing mechanism

NASA Astrophysics Data System (ADS)

Zhang, Jintao; Tan, Ruijun; Chen, Zhou; Zhang, Yongqi; Fu, Panlong; Qu, Yachen

2018-05-01

Aiming at the dual channel telescopic imaging system composed of infrared imaging system, low-light-level imaging system and image fusion module, In the fusion of low-light-level images and infrared images, it is obvious that using clear source images is easier to obtain high definition fused images. When the target is imaged at 15m to infinity, focusing is needed to ensure the imaging quality of the dual channel imaging system; therefore, a new type of synchronous focusing mechanism is designed. The synchronous focusing mechanism realizes the focusing function through the synchronous translational imaging devices, mainly including the structure of the screw rod nut, the shaft hole coordination structure and the spring steel ball eliminating clearance structure, etc. Starting from the synchronous focusing function of two imaging devices, the structure characteristics of the synchronous focusing mechanism are introduced in detail, and the focusing range is analyzed. The experimental results show that the synchronous focusing mechanism has the advantages of ingenious design, high focusing accuracy and stable and reliable operation.

Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

PubMed

Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

2017-08-25

We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

Automated condition-invariable neurite segmentation and synapse classification using textural analysis-based machine-learning algorithms

PubMed Central

Kandaswamy, Umasankar; Rotman, Ziv; Watt, Dana; Schillebeeckx, Ian; Cavalli, Valeria; Klyachko, Vitaly

2013-01-01

High-resolution live-cell imaging studies of neuronal structure and function are characterized by large variability in image acquisition conditions due to background and sample variations as well as low signal-to-noise ratio. The lack of automated image analysis tools that can be generalized for varying image acquisition conditions represents one of the main challenges in the field of biomedical image analysis. Specifically, segmentation of the axonal/dendritic arborizations in brightfield or fluorescence imaging studies is extremely labor-intensive and still performed mostly manually. Here we describe a fully automated machine-learning approach based on textural analysis algorithms for segmenting neuronal arborizations in high-resolution brightfield images of live cultured neurons. We compare performance of our algorithm to manual segmentation and show that it combines 90% accuracy, with similarly high levels of specificity and sensitivity. Moreover, the algorithm maintains high performance levels under a wide range of image acquisition conditions indicating that it is largely condition-invariable. We further describe an application of this algorithm to fully automated synapse localization and classification in fluorescence imaging studies based on synaptic activity. Textural analysis-based machine-learning approach thus offers a high performance condition-invariable tool for automated neurite segmentation. PMID:23261652

Varying ultrasound power level to distinguish surgical instruments and tissue.

PubMed

Ren, Hongliang; Anuraj, Banani; Dupont, Pierre E

2018-03-01

We investigate a new framework of surgical instrument detection based on power-varying ultrasound images with simple and efficient pixel-wise intensity processing. Without using complicated feature extraction methods, we identified the instrument with an estimated optimal power level and by comparing pixel values of varying transducer power level images. The proposed framework exploits the physics of ultrasound imaging system by varying the transducer power level to effectively distinguish metallic surgical instruments from tissue. This power-varying image-guidance is motivated from our observations that ultrasound imaging at different power levels exhibit different contrast enhancement capabilities between tissue and instruments in ultrasound-guided robotic beating-heart surgery. Using lower transducer power levels (ranging from 40 to 75% of the rated lowest ultrasound power levels of the two tested ultrasound scanners) can effectively suppress the strong imaging artifacts from metallic instruments and thus, can be utilized together with the images from normal transducer power levels to enhance the separability between instrument and tissue, improving intraoperative instrument tracking accuracy from the acquired noisy ultrasound volumetric images. We performed experiments in phantoms and ex vivo hearts in water tank environments. The proposed multi-level power-varying ultrasound imaging approach can identify robotic instruments of high acoustic impedance from low-signal-to-noise-ratio ultrasound images by power adjustments.

Hierarchical layered and semantic-based image segmentation using ergodicity map

NASA Astrophysics Data System (ADS)

Yadegar, Jacob; Liu, Xiaoqing

2010-04-01

Image segmentation plays a foundational role in image understanding and computer vision. Although great strides have been made and progress achieved on automatic/semi-automatic image segmentation algorithms, designing a generic, robust, and efficient image segmentation algorithm is still challenging. Human vision is still far superior compared to computer vision, especially in interpreting semantic meanings/objects in images. We present a hierarchical/layered semantic image segmentation algorithm that can automatically and efficiently segment images into hierarchical layered/multi-scaled semantic regions/objects with contextual topological relationships. The proposed algorithm bridges the gap between high-level semantics and low-level visual features/cues (such as color, intensity, edge, etc.) through utilizing a layered/hierarchical ergodicity map, where ergodicity is computed based on a space filling fractal concept and used as a region dissimilarity measurement. The algorithm applies a highly scalable, efficient, and adaptive Peano- Cesaro triangulation/tiling technique to decompose the given image into a set of similar/homogenous regions based on low-level visual cues in a top-down manner. The layered/hierarchical ergodicity map is built through a bottom-up region dissimilarity analysis. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level of detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanisms for contextual topological object/region relationship generation. Experiments have been conducted within the maritime image environment where the segmented layered semantic objects include the basic level objects (i.e. sky/land/water) and deeper level objects in the sky/land/water surfaces. Experimental results demonstrate the proposed algorithm has the capability to robustly and efficiently segment images into layered semantic objects/regions with contextual topological relationships.

Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

NASA Astrophysics Data System (ADS)

Zhang, Xue; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Li, Xianye; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-01-01

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

Hubble Provides Infrared View of Jupiter's Moon, Ring, and Clouds

NASA Technical Reports Server (NTRS)

1997-01-01

Probing Jupiter's atmosphere for the first time, the Hubble Space Telescope's new Near Infrared Camera and Multi-Object Spectrometer (NICMOS) provides a sharp glimpse of the planet's ring, moon, and high-altitude clouds.

The presence of methane in Jupiter's hydrogen- and helium-rich atmosphere has allowed NICMOS to plumb Jupiter's atmosphere, revealing bands of high-altitude clouds. Visible light observations cannot provide a clear view of these high clouds because the underlying clouds reflect so much visible light that the higher level clouds are indistinguishable from the lower layer. The methane gas between the main cloud deck and the high clouds absorbs the reflected infrared light, allowing those clouds that are above most of the atmosphere to appear bright. Scientists will use NICMOS to study the high altitude portion of Jupiter's atmosphere to study clouds at lower levels. They will then analyze those images along with visible light information to compile a clearer picture of the planet's weather. Clouds at different levels tell unique stories. On Earth, for example, ice crystal (cirrus) clouds are found at high altitudes while water (cumulus) clouds are at lower levels.

Besides showing details of the planet's high-altitude clouds, NICMOS also provides a clear view of the ring and the moon, Metis. Jupiter's ring plane, seen nearly edge-on, is visible as a faint line on the upper right portion of the NICMOS image. Metis can be seen in the ring plane (the bright circle on the ring's outer edge). The moon is 25 miles wide and about 80,000 miles from Jupiter.

Because of the near-infrared camera's narrow field of view, this image is a mosaic constructed from three individual images taken Sept. 17, 1997. The color intensity was adjusted to accentuate the high-altitude clouds. The dark circle on the disk of Jupiter (center of image) is an artifact of the imaging system.

This image and other images and data received from the Hubble Space Telescope are posted on the World Wide Web on the Space Telescope Science Institute home page at URL http://oposite.stsci.edu/pubinfo/

Multispectral simulation environment for modeling low-light-level sensor systems

NASA Astrophysics Data System (ADS)

Ientilucci, Emmett J.; Brown, Scott D.; Schott, John R.; Raqueno, Rolando V.

1998-11-01

Image intensifying cameras have been found to be extremely useful in low-light-level (LLL) scenarios including military night vision and civilian rescue operations. These sensors utilize the available visible region photons and an amplification process to produce high contrast imagery. It has been demonstrated that processing techniques can further enhance the quality of this imagery. For example, fusion with matching thermal IR imagery can improve image content when very little visible region contrast is available. To aid in the improvement of current algorithms and the development of new ones, a high fidelity simulation environment capable of producing radiometrically correct multi-band imagery for low- light-level conditions is desired. This paper describes a modeling environment attempting to meet these criteria by addressing the task as two individual components: (1) prediction of a low-light-level radiance field from an arbitrary scene, and (2) simulation of the output from a low- light-level sensor for a given radiance field. The radiance prediction engine utilized in this environment is the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model which is a first principles based multi-spectral synthetic image generation model capable of producing an arbitrary number of bands in the 0.28 to 20 micrometer region. The DIRSIG model is utilized to produce high spatial and spectral resolution radiance field images. These images are then processed by a user configurable multi-stage low-light-level sensor model that applies the appropriate noise and modulation transfer function (MTF) at each stage in the image processing chain. This includes the ability to reproduce common intensifying sensor artifacts such as saturation and 'blooming.' Additionally, co-registered imagery in other spectral bands may be simultaneously generated for testing fusion and exploitation algorithms. This paper discusses specific aspects of the DIRSIG radiance prediction for low- light-level conditions including the incorporation of natural and man-made sources which emphasizes the importance of accurate BRDF. A description of the implementation of each stage in the image processing and capture chain for the LLL model is also presented. Finally, simulated images are presented and qualitatively compared to lab acquired imagery from a commercial system.

A novel imaging method for photonic crystal fiber fusion splicer

NASA Astrophysics Data System (ADS)

Bi, Weihong; Fu, Guangwei; Guo, Xuan

2007-01-01

Because the structure of Photonic Crystal Fiber (PCF) is very complex, and it is very difficult that traditional fiber fusion splice obtains optical axial information of PCF. Therefore, we must search for a bran-new optical imaging method to get section information of Photonic Crystal Fiber. Based on complex trait of PCF, a novel high-precision optics imaging system is presented in this article. The system uses a thinned electron-bombarded CCD (EBCCD) which is a kind of image sensor as imaging element, the thinned electron-bombarded CCD can offer low light level performance superior to conventional image intensifier coupled CCD approaches, this high-performance device can provide high contrast high resolution in low light level surveillance imaging; in order to realize precision focusing of image, we use a ultra-highprecision pace motor to adjust position of imaging lens. In this way, we can obtain legible section information of PCF. We may realize further concrete analysis for section information of PCF by digital image processing technology. Using this section information may distinguish different sorts of PCF, compute some parameters such as the size of PCF ventage, cladding structure of PCF and so on, and provide necessary analysis data for PCF fixation, adjustment, regulation, fusion and cutting system.

Semantic classification of business images

NASA Astrophysics Data System (ADS)

Erol, Berna; Hull, Jonathan J.

2006-01-01

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.

Magnetomotive Molecular Nanoprobes

PubMed Central

John, Renu; Boppart, Stephen A.

2012-01-01

Tremendous developments in the field of biomedical imaging in the past two decades have resulted in the transformation of anatomical imaging to molecular-specific imaging. The main approaches towards imaging at a molecular level are the development of high resolution imaging modalities with high penetration depths and increased sensitivity, and the development of molecular probes with high specificity. The development of novel molecular contrast agents and their success in molecular optical imaging modalities have lead to the emergence of molecular optical imaging as a more versatile and capable technique for providing morphological, spatial, and functional information at the molecular level with high sensitivity and precision, compared to other imaging modalities. In this review, we discuss a new class of dynamic contrast agents called magnetomotive molecular nanoprobes for molecular-specific imaging. Magnetomotive agents are superparamagnetic nanoparticles, typically iron-oxide, that are physically displaced by the application of a small modulating external magnetic field. Dynamic phase-sensitive position measurements are performed using any high resolution imaging modality, including optical coherence tomography (OCT), ultrasonography, or magnetic resonance imaging (MRI). The dynamics of the magnetomotive agents can be used to extract the biomechanical tissue properties in which the nanoparticles are bound, and the agents can be used to deliver therapy via magnetomotive displacements to modulate or disrupt cell function, or hyperthermia to kill cells. These agents can be targeted via conjugation to antibodies, and in vivo targeted imaging has been shown in a carcinogen-induced rat mammary tumor model. The iron-oxide nanoparticles also exhibit negative T2 contrast in MRI, and modulations can produce ultrasound imaging contrast for multimodal imaging applications. PMID:21517766

Low Voltage Low Light Imager and Photodetector

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Martin, Chris (Inventor); Hoenk, Michael E. (Inventor)

2013-01-01

Highly efficient, low energy, low light level imagers and photodetectors are provided. In particular, a novel class of Della-Doped Electron Bombarded Array (DDEBA) photodetectors that will reduce the size, mass, power, complexity, and cost of conventional imaging systems while improving performance by using a thinned imager that is capable of detecting low-energy electrons, has high gain, and is of low noise.

Sensitivity and Specificity of Long Wave Infrared Imaging for Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Coben, Robert; Myers, Thomas E.

2009-01-01

Objective: This study was the first to investigate the efficacy of long wave infrared (LWIR) imaging as a diagnostic tool for ADHD. Method: with ADHD and a high level of specificity (94%) in discriminating those with ADHD from those with other diagnoses. The overall classification rate was 73.16%. This was indicative of a high level of…

Image quality evaluation for smart-phone displays at lighting levels of indoor and outdoor conditions

NASA Astrophysics Data System (ADS)

Gong, Rui; Xu, Haisong; Wang, Binyu; Luo, Ming Ronnier

2012-08-01

The image quality of two active matrix organic light emitting diode (AMOLED) smart-phone displays and two in-plane switching (IPS) ones was visually assessed at two levels of ambient lighting conditions corresponding to indoor and outdoor applications, respectively. Naturalness, colorfulness, brightness, contrast, sharpness, and overall image quality were evaluated via psychophysical experiment by categorical judgment method using test images selected from different application categories. The experimental results show that the AMOLED displays perform better on colorfulness because of their wide color gamut, while the high pixel resolution and high peak luminance of the IPS panels help the perception of brightness, contrast, and sharpness. Further statistical analysis of ANOVA indicates that ambient lighting levels have significant influences on the attributes of brightness and contrast.

Gray-scale transform and evaluation for digital x-ray chest images on CRT monitor

NASA Astrophysics Data System (ADS)

Furukawa, Isao; Suzuki, Junji; Ono, Sadayasu; Kitamura, Masayuki; Ando, Yutaka

1997-04-01

In this paper, an experimental evaluation of a super high definition (SHD) imaging system for digital x-ray chest images is presented. The SHD imaging system is proposed as a platform for integrating conventional image media. We are involved in the use of SHD images in the total digitizing of medical records that include chest x-rays and pathological microscopic images, both which demand the highest level of quality among the various types of medical images. SHD images use progressive scanning and have a spatial resolution of 2000 by 2000 pixels or more and a temporal resolution (frame rate) of 60 frames/sec or more. For displaying medical x-ray images on a CRT, we derived gray scale transform characteristics based on radiologists' comments during the experiment, and elucidated the relationship between that gray scale transform and the linearization transform for maintaining the linear relationship with the luminance of film on a light box (luminance linear transform). We then carried out viewing experiments based on a five-stage evaluation. Nine radiologists participated in our experiment, and the ten cases evaluated included pulmonary fibrosis, lung cancer, and pneumonia. The experimental results indicated that conventional film images and those on super high definition CRT monitors have nearly the same quality. They also show that the gray scale transform for CRT images decided according to radiologists' comments agrees with the luminance linear transform in the high luminance region. And in the low luminance region, it was found that the gray scale transform had the characteristics of level expansion to increase the number of levels that can be expressed.

Interactive classification and content-based retrieval of tissue images

NASA Astrophysics Data System (ADS)

Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

2002-11-01

We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

Study on polarization image methods in turbid medium

NASA Astrophysics Data System (ADS)

Fu, Qiang; Mo, Chunhe; Liu, Boyu; Duan, Jin; Zhang, Su; Zhu, Yong

2014-11-01

Polarization imaging detection technology in addition to the traditional imaging information, also can get polarization multi-dimensional information, thus improve the probability of target detection and recognition.Image fusion in turbid medium target polarization image research, is helpful to obtain high quality images. Based on visible light wavelength of light wavelength of laser polarization imaging, through the rotation Angle of polaroid get corresponding linear polarized light intensity, respectively to obtain the concentration range from 5% to 10% of turbid medium target stocks of polarization parameters, introduces the processing of image fusion technology, main research on access to the polarization of the image by using different polarization image fusion methods for image processing, discusses several kinds of turbid medium has superior performance of polarization image fusion method, and gives the treatment effect and analysis of data tables. Then use pixel level, feature level and decision level fusion algorithm on three levels of information fusion, DOLP polarization image fusion, the results show that: with the increase of the polarization Angle, polarization image will be more and more fuzzy, quality worse and worse. Than a single fused image contrast of the image be improved obviously, the finally analysis on reasons of the increase the image contrast and polarized light.

Entangled-photon compressive ghost imaging

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

Zerom, Petros; Chan, Kam Wai Clifford; Howell, John C.

2011-12-15

We have experimentally demonstrated high-resolution compressive ghost imaging at the single-photon level using entangled photons produced by a spontaneous parametric down-conversion source and using single-pixel detectors. For a given mean-squared error, the number of photons needed to reconstruct a two-dimensional image is found to be much smaller than that in quantum ghost imaging experiments employing a raster scan. This procedure not only shortens the data acquisition time, but also suggests a more economical use of photons for low-light-level and quantum image formation.

Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features

PubMed Central

Corredor, Germán; Whitney, Jon; Arias, Viviana; Madabhushi, Anant; Romero, Eduardo

2017-01-01

Abstract. Computational histomorphometric approaches typically use low-level image features for building machine learning classifiers. However, these approaches usually ignore high-level expert knowledge. A computational model (M_im) combines low-, mid-, and high-level image information to predict the likelihood of cancer in whole slide images. Handcrafted low- and mid-level features are computed from area, color, and spatial nuclei distributions. High-level information is implicitly captured from the recorded navigations of pathologists while exploring whole slide images during diagnostic tasks. This model was validated by predicting the presence of cancer in a set of unseen fields of view. The available database was composed of 24 cases of basal-cell carcinoma, from which 17 served to estimate the model parameters and the remaining 7 comprised the evaluation set. A total of 274 fields of view of size 1024×1024  pixels were extracted from the evaluation set. Then 176 patches from this set were used to train a support vector machine classifier to predict the presence of cancer on a patch-by-patch basis while the remaining 98 image patches were used for independent testing, ensuring that the training and test sets do not comprise patches from the same patient. A baseline model (M_ex) estimated the cancer likelihood for each of the image patches. M_ex uses the same visual features as M_im, but its weights are estimated from nuclei manually labeled as cancerous or noncancerous by a pathologist. M_im achieved an accuracy of 74.49% and an F-measure of 80.31%, while M_ex yielded corresponding accuracy and F-measures of 73.47% and 77.97%, respectively. PMID:28382314

Impact of Primary Spherical Aberration, Spatial Frequency and Stiles Crawford Apodization on Wavefront determined Refractive Error: A Computational Study

PubMed Central

Xu, Renfeng; Bradley, Arthur; Thibos, Larry N.

2013-01-01

Purpose We tested the hypothesis that pupil apodization is the basis for central pupil bias of spherical refractions in eyes with spherical aberration. Methods We employed Fourier computational optics in which we vary spherical aberration levels, pupil size, and pupil apodization (Stiles Crawford Effect) within the pupil function, from which point spread functions and optical transfer functions were computed. Through-focus analysis determined the refractive correction that optimized retinal image quality. Results For a large pupil (7 mm), as spherical aberration levels increase, refractions that optimize the visual Strehl ratio mirror refractions that maximize high spatial frequency modulation in the image and both focus a near paraxial region of the pupil. These refractions are not affected by Stiles Crawford Effect apodization. Refractions that optimize low spatial frequency modulation come close to minimizing wavefront RMS, and vary with level of spherical aberration and Stiles Crawford Effect. In the presence of significant levels of spherical aberration (e.g. C40 = 0.4 µm, 7mm pupil), low spatial frequency refractions can induce −0.7D myopic shift compared to high SF refraction, and refractions that maximize image contrast of a 3 cycle per degree square-wave grating can cause −0.75D myopic drift relative to refractions that maximize image sharpness. Discussion Because of small depth of focus associated with high spatial frequency stimuli, the large change in dioptric power across the pupil caused by spherical aberration limits the effective aperture contributing to the image of high spatial frequencies. Thus, when imaging high spatial frequencies, spherical aberration effectively induces an annular aperture defining that portion of the pupil contributing to a well-focused image. As spherical focus is manipulated during the refraction procedure, the dimensions of the annular aperture change. Image quality is maximized when the inner radius of the induced annulus falls to zero, thus defining a circular near paraxial region of the pupil that determines refraction outcome. PMID:23683093

A summary of image segmentation techniques

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly

1993-01-01

Machine vision systems are often considered to be composed of two subsystems: low-level vision and high-level vision. Low level vision consists primarily of image processing operations performed on the input image to produce another image with more favorable characteristics. These operations may yield images with reduced noise or cause certain features of the image to be emphasized (such as edges). High-level vision includes object recognition and, at the highest level, scene interpretation. The bridge between these two subsystems is the segmentation system. Through segmentation, the enhanced input image is mapped into a description involving regions with common features which can be used by the higher level vision tasks. There is no theory on image segmentation. Instead, image segmentation techniques are basically ad hoc and differ mostly in the way they emphasize one or more of the desired properties of an ideal segmenter and in the way they balance and compromise one desired property against another. These techniques can be categorized in a number of different groups including local vs. global, parallel vs. sequential, contextual vs. noncontextual, interactive vs. automatic. In this paper, we categorize the schemes into three main groups: pixel-based, edge-based, and region-based. Pixel-based segmentation schemes classify pixels based solely on their gray levels. Edge-based schemes first detect local discontinuities (edges) and then use that information to separate the image into regions. Finally, region-based schemes start with a seed pixel (or group of pixels) and then grow or split the seed until the original image is composed of only homogeneous regions. Because there are a number of survey papers available, we will not discuss all segmentation schemes. Rather than a survey, we take the approach of a detailed overview. We focus only on the more common approaches in order to give the reader a flavor for the variety of techniques available yet present enough details to facilitate implementation and experimentation.

A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

PubMed Central

Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao

2017-01-01

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181

Fusion of Deep Learning and Compressed Domain features for Content Based Image Retrieval.

PubMed

Liu, Peizhong; Guo, Jing-Ming; Wu, Chi-Yi; Cai, Danlin

2017-08-29

This paper presents an effective image retrieval method by combining high-level features from Convolutional Neural Network (CNN) model and low-level features from Dot-Diffused Block Truncation Coding (DDBTC). The low-level features, e.g., texture and color, are constructed by VQ-indexed histogram from DDBTC bitmap, maximum, and minimum quantizers. Conversely, high-level features from CNN can effectively capture human perception. With the fusion of the DDBTC and CNN features, the extended deep learning two-layer codebook features (DL-TLCF) is generated using the proposed two-layer codebook, dimension reduction, and similarity reweighting to improve the overall retrieval rate. Two metrics, average precision rate (APR) and average recall rate (ARR), are employed to examine various datasets. As documented in the experimental results, the proposed schemes can achieve superior performance compared to the state-of-the-art methods with either low- or high-level features in terms of the retrieval rate. Thus, it can be a strong candidate for various image retrieval related applications.

Development of high-spatial and high-mass resolution mass spectrometric imaging (MSI) and its application to the study of small metabolites and endogenous molecules of plants

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

Jun, Ji Hyun

High-spatial and high-mass resolution laser desorption ionization (LDI) mass spectrometric (MS) imaging technology was developed for the attainment of MS images of higher quality containing more information on the relevant cellular and molecular biology in unprecedented depth. The distribution of plant metabolites is asymmetric throughout the cells and tissues, and therefore the increase in the spatial resolution was pursued to reveal the localization of plant metabolites at the cellular level by MS imaging. For achieving high-spatial resolution, the laser beam size was reduced by utilizing an optical fiber with small core diameter (25 μm) in a vacuum matrix-assisted laser desorptionmore » ionization-linear ion trap (vMALDI-LTQ) mass spectrometer. Matrix application was greatly improved using oscillating capillary nebulizer. As a result, single cell level spatial resolution of ~ 12 μm was achieved. MS imaging at this high spatial resolution was directly applied to a whole Arabidopsis flower and the substructures of an anther and single pollen grains at the stigma and anther were successfully visualized. MS imaging of high spatial resolution was also demonstrated to the secondary roots of Arabidopsis thaliana and a high degree of localization of detected metabolites was successfully unveiled. This was the first MS imaging on the root for molecular species. MS imaging with high mass resolution was also achieved by utilizing the LTQ-Orbitrap mass spectrometer for the direct identification of the surface metabolites on the Arabidopsis stem and root and differentiation of isobaric ions having the same nominal mass with no need of tandem mass spectrometry (MS/MS). MS imaging at high-spatial and high-mass resolution was also applied to cer1 mutant of the model system Arabidopsis thaliana to demonstrate its usefulness in biological studies and reveal associated metabolite changes in terms of spatial distribution and/or abundances compared to those of wild-type. The spatial distribution of targeted metabolites, mainly waxes and flavonoids, was systematically explored on various organs, including flowers, leaves, stems, and roots at high spatial resolution of ~ 12-50 μm and the changes in the abundance level of these metabolites were monitored on the cer1 mutant with respect to the wild-type. This study revealed the metabolic biology of CER1 gene on each individual organ level with very detailed high spatial resolution. The separate MS images of isobaric metabolites, i.e. C29 alkane vs. C28 aldehyde could be constructed on both genotypes from MS imaging at high mass resolution. This allows tracking of abundance changes for those compounds along with the genetic mutation, which is not achievable with low mass resolution mass spectrometry. This study supported previous hypothesis of molecular function of CER1 gene as aldehyde decarbonylase, especially by displaying hyper accumulation of aldehydes and C30 fatty acid and decrease in abundance of alkanes and ketones in several plant organs of cer1 mutant. The scope of analytes was further directed toward internal cell metabolites from the surface metabolites of the plant. MS profiling and imaging of internal cell metabolites were performed on the vibratome section of Arabidopsis leaf. Vibratome sectioning of the leaf was first conducted to remove the surface cuticle layer and it was followed by enzymatic treatment of the section to induce the digestion of primary cell walls, middle lamella, and expose the internal cells underneath to the surface for detection with the laser by LDI-MS. The subsequent MS imaging onto the enzymatically treated vibratome section allowed us to map the distribution of the metabolites in the internal cell layers, linolenic acid (C18:3 FA) and linoleic acid (C18:2 FA). The development of an assay for relative quantification of analytes at the single subcellular/organelle level by LDI-MS imaging was attempted and both plausibility and significant obstacles were seen. As a test system, native plant organelle, chloroplasts isolated from the spinach leaves were used and the localization of isolated chloroplasts dispersed on the target plate in low density was monitored by detecting the ion signal of chlorophyll a (Chl a) degradation products such as pheophytin a and pheophobide a by LDI-MS imaging in combination with fluorescence microscopy. The number of chloroplasts and their localization visualized in the MS image exactly matched those in the fluorescence image especially at low density, which first shows the plausibility of single-organelle level quantification of analytes by LDI-MS. The accumulation level of Chl a within a single chloroplast detected by LDI-MS was compared to the fluorescence signal on a pixel-to-pixel basis to further confirm the correlations of the accumulation levels measured by two methods. The proportional correlation was observed only for the chloroplasts which do not show the significant leakage of chlorophyll indicated by MS ion signal of Chl a degradation products and fluorescence signal, which was presumably caused by the prior fluorescence measurement before MS imaging. Further investigation is necessary to make this method more complete and develop LDI-MS imaging as an effective analytical tool to evaluate a relative accumulation of analytes of interest at the single subcellular/organelle level.« less

Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.

PubMed

Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan

2015-01-01

Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.

External optical imaging of freely moving mice with green fluorescent protein-expressing metastatic tumors

NASA Astrophysics Data System (ADS)

Yang, Meng; Baranov, Eugene; Shimada, Hiroshi; Moossa, A. R.; Hoffman, Robert M.

2000-04-01

We report here a new approach to genetically engineering tumors to become fluorescence such that they can be imaged externally in freely-moving animals. We describe here external high-resolution real-time fluorescent optical imaging of metastatic tumors in live mice. Stable high-level green flourescent protein (GFP)-expressing human and rodent cell lines enable tumors and metastasis is formed from them to be externally imaged from freely-moving mice. Real-time tumor and metastatic growth were quantitated from whole-body real-time imaging in GFP-expressing melanoma and colon carcinoma models. This GFP optical imaging system is highly appropriate for high throughput in vivo drug screening.

An orthogonal oriented quadrature hexagonal image pyramid

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Ahumada, Albert J., Jr.

1987-01-01

An image pyramid has been developed with basis functions that are orthogonal, self-similar, and localized in space, spatial frequency, orientation, and phase. The pyramid operates on a hexagonal sample lattice. The set of seven basis functions consist of three even high-pass kernels, three odd high-pass kernels, and one low-pass kernel. The three even kernels are identified when rotated by 60 or 120 deg, and likewise for the odd. The seven basis functions occupy a point and a hexagon of six nearest neighbors on a hexagonal sample lattice. At the lowest level of the pyramid, the input lattice is the image sample lattice. At each higher level, the input lattice is provided by the low-pass coefficients computed at the previous level. At each level, the output is subsampled in such a way as to yield a new hexagonal lattice with a spacing sq rt 7 larger than the previous level, so that the number of coefficients is reduced by a factor of 7 at each level. The relationship between this image code and the processing architecture of the primate visual cortex is discussed.

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

PubMed

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results show that the proposed method achieves an accuracy of 93.26% for classification of AD vs. NC and 82.95% for classification pMCI vs. NC, demonstrating the promising classification performance.

A novel biomedical image indexing and retrieval system via deep preference learning.

PubMed

Pang, Shuchao; Orgun, Mehmet A; Yu, Zhezhou

2018-05-01

The traditional biomedical image retrieval methods as well as content-based image retrieval (CBIR) methods originally designed for non-biomedical images either only consider using pixel and low-level features to describe an image or use deep features to describe images but still leave a lot of room for improving both accuracy and efficiency. In this work, we propose a new approach, which exploits deep learning technology to extract the high-level and compact features from biomedical images. The deep feature extraction process leverages multiple hidden layers to capture substantial feature structures of high-resolution images and represent them at different levels of abstraction, leading to an improved performance for indexing and retrieval of biomedical images. We exploit the current popular and multi-layered deep neural networks, namely, stacked denoising autoencoders (SDAE) and convolutional neural networks (CNN) to represent the discriminative features of biomedical images by transferring the feature representations and parameters of pre-trained deep neural networks from another domain. Moreover, in order to index all the images for finding the similarly referenced images, we also introduce preference learning technology to train and learn a kind of a preference model for the query image, which can output the similarity ranking list of images from a biomedical image database. To the best of our knowledge, this paper introduces preference learning technology for the first time into biomedical image retrieval. We evaluate the performance of two powerful algorithms based on our proposed system and compare them with those of popular biomedical image indexing approaches and existing regular image retrieval methods with detailed experiments over several well-known public biomedical image databases. Based on different criteria for the evaluation of retrieval performance, experimental results demonstrate that our proposed algorithms outperform the state-of-the-art techniques in indexing biomedical images. We propose a novel and automated indexing system based on deep preference learning to characterize biomedical images for developing computer aided diagnosis (CAD) systems in healthcare. Our proposed system shows an outstanding indexing ability and high efficiency for biomedical image retrieval applications and it can be used to collect and annotate the high-resolution images in a biomedical database for further biomedical image research and applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Visual object imagery and autobiographical memory: Object Imagers are better at remembering their personal past.

PubMed

Vannucci, Manila; Pelagatti, Claudia; Chiorri, Carlo; Mazzoni, Giuliana

2016-01-01

In the present study we examined whether higher levels of object imagery, a stable characteristic that reflects the ability and preference in generating pictorial mental images of objects, facilitate involuntary and voluntary retrieval of autobiographical memories (ABMs). Individuals with high (High-OI) and low (Low-OI) levels of object imagery were asked to perform an involuntary and a voluntary ABM task in the laboratory. Results showed that High-OI participants generated more involuntary and voluntary ABMs than Low-OI, with faster retrieval times. High-OI also reported more detailed memories compared to Low-OI and retrieved memories as visual images. Theoretical implications of these findings for research on voluntary and involuntary ABMs are discussed.

Change detection of polarimetric SAR images based on the KummerU Distribution

NASA Astrophysics Data System (ADS)

Chen, Quan; Zou, Pengfei; Li, Zhen; Zhang, Ping

2014-11-01

In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

High resolution FTIR imaging provides automated discrimination and detection of single malaria parasite infected erythrocytes on glass.

PubMed

Perez-Guaita, David; Andrew, Dean; Heraud, Philip; Beeson, James; Anderson, David; Richards, Jack; Wood, Bayden R

2016-06-23

New highly sensitive tools for malaria diagnostics are urgently needed to enable the detection of infection in asymptomatic carriers and patients with low parasitemia. In pursuit of a highly sensitive diagnostic tool that can identify parasite infections at the single cell level, we have been exploring Fourier transform infrared (FTIR) microscopy using a Focal Plane Array (FPA) imaging detector. Here we report for the first time the application of a new optic configuration developed by Agilent that incorporates 25× condenser and objective Cassegrain optics with a high numerical aperture (NA = 0.81) along with additional high magnification optics within the microscope to provide 0.66 micron pixel resolution (total IR system magnification of 61×) to diagnose malaria parasites at the single cell level on a conventional glass microscope slide. The high quality images clearly resolve the parasite's digestive vacuole demonstrating sub-cellular resolution using this approach. Moreover, we have developed an algorithm that first detects the cells in the infrared image, and secondly extracts the average spectrum. The average spectrum is then run through a model based on Partial Least Squares-Discriminant Analysis (PLS-DA), which diagnoses unequivocally the infected from normal cells. The high quality images, and the fact this measurement can be achieved without a synchrotron source on a conventional glass slide, shows promise as a potential gold standard for malaria detection at the single cell level.

Endemic Images and the Desensitization Process.

ERIC Educational Resources Information Center

Saigh, Philip A.; Antoun, Fouad T.

1984-01-01

Examined the effects of endemic images on levels of anxiety and achievement of 48 high school students. Results suggested that a combination of endemic images and study skills training was as effective as desensitization plus study skills training. Includes the endemic image questionnaire. (JAC)

Breast ultrasound image segmentation: an optimization approach based on super-pixels and high-level descriptors

NASA Astrophysics Data System (ADS)

Massich, Joan; Lemaître, Guillaume; Martí, Joan; Mériaudeau, Fabrice

2015-04-01

Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the breast are essential for CAD systems in order to extract information needed to perform diagnosis. This article proposes a highly modular and flexible framework for segmenting lesions and tissues present in BUS images. The proposal takes advantage of optimization strategies using super-pixels and high-level descriptors, which are analogous to the visual cues used by radiologists. Qualitative and quantitative results are provided stating a performance within the range of the state-of-the-art.

Body Talk: Body Image Commentary on Queerty.com.

PubMed

Schwartz, Joseph; Grimm, Josh

2016-08-01

In this study, we conducted a content analysis of 243 photographic images of men published on the gay male-oriented blog Queerty.com. We also analyzed 435 user-generated comments from a randomly selected 1-year sample. Focusing on images' body types, we found that the range of body types featured on the blog was quite narrow-the vast majority of images had very low levels of body fat and very high levels of muscularity. Users' body image-related comments typically endorsed and celebrated images; critiques of images were comparatively rare. Perspectives from objectification theory and social comparison theory suggest that the images and commentary found on the blog likely reinforce unhealthy body image in gay male communities.

Multiscale approach to contour fitting for MR images

NASA Astrophysics Data System (ADS)

Rueckert, Daniel; Burger, Peter

1996-04-01

We present a new multiscale contour fitting process which combines information about the image and the contour of the object at different levels of scale. The algorithm is based on energy minimizing deformable models but avoids some of the problems associated with these models. The segmentation algorithm starts by constructing a linear scale-space of an image through convolution of the original image with a Gaussian kernel at different levels of scale, where the scale corresponds to the standard deviation of the Gaussian kernel. At high levels of scale large scale features of the objects are preserved while small scale features, like object details as well as noise, are suppressed. In order to maximize the accuracy of the segmentation, the contour of the object of interest is then tracked in scale-space from coarse to fine scales. We propose a hybrid multi-temperature simulated annealing optimization to minimize the energy of the deformable model. At high levels of scale the SA optimization is started at high temperatures, enabling the SA optimization to find a global optimal solution. At lower levels of scale the SA optimization is started at lower temperatures (at the lowest level the temperature is close to 0). This enforces a more deterministic behavior of the SA optimization at lower scales and leads to an increasingly local optimization as high energy barriers cannot be crossed. The performance and robustness of the algorithm have been tested on spin-echo MR images of the cardiovascular system. The task was to segment the ascending and descending aorta in 15 datasets of different individuals in order to measure regional aortic compliance. The results show that the algorithm is able to provide more accurate segmentation results than the classic contour fitting process and is at the same time very robust to noise and initialization.

Ultra high resolution imaging of the human head at 8 tesla: 2K x 2K for Y2K.

PubMed

Robitaille, P M; Abduljalil, A M; Kangarlu, A

2000-01-01

To acquire ultra high resolution MRI images of the human brain at 8 Tesla within a clinically acceptable time frame. Gradient echo images were acquired from the human head of normal subjects using a transverse electromagnetic resonator operating in quadrature and tuned to 340 MHz. In each study, a group of six images was obtained containing a total of 208 MB of unprocessed information. Typical acquisition parameters were as follows: matrix = 2,000 x 2,000, field of view = 20 cm, slice thickness = 2 mm, number of excitations (NEX) = 1, flip angle = 45 degrees, TR = 750 ms, TE = 17 ms, receiver bandwidth = 69.4 kHz. This resulted in a total scan time of 23 minutes, an in-plane resolution of 100 microm, and a pixel volume of 0.02 mm3. The ultra high resolution images acquired in this study represent more than a 50-fold increase in in-plane resolution relative to conventional 256 x 256 images obtained with a 20 cm field of view and a 5 mm slice thickness. Nonetheless, the ultra high resolution images could be acquired both with adequate image quality and signal to noise. They revealed numerous small venous structures throughout the image plane and provided reasonable delineation between gray and white matter. The elevated signal-to-noise ratio observed in ultra high field magnetic resonance imaging can be utilized to acquire images with a level of resolution approaching the histological level under in vivo conditions. However, brain motion is likely to degrade the useful resolution. This situation may be remedied in part with cardiac gating. Nonetheless, these images represent a significant advance in our ability to examine small anatomical features with noninvasive imaging methods.

Investigations of high-speed digital imaging of low-light-level events using pulsed near-infrared laser light sources

NASA Astrophysics Data System (ADS)

Jantzen, Connie; Slagle, Rick

1997-05-01

The distinction between exposure time and sample rate is often the first point raised in any discussion of high speed imaging. Many high speed events require exposure times considerably shorter than those that can be achieved solely by the sample rate of the camera, where exposure time equals 1/sample rate. Gating, a method of achieving short exposure times in digital cameras, is often difficult to achieve for exposure time requirements shorter than 100 microseconds. This paper discusses the advantages and limitations of using the short duration light pulse of a near infrared laser with high speed digital imaging systems. By closely matching the output wavelength of the pulsed laser to the peak near infrared response of current sensors, high speed image capture can be accomplished at very low (visible) light levels of illumination. By virtue of the short duration light pulse, adjustable to as short as two microseconds, image capture of very high speed events can be achieved at relatively low sample rates of less than 100 pictures per second, without image blur. For our initial investigations, we chose a ballistic subject. The results of early experimentation revealed the limitations of applying traditional ballistic imaging methods when using a pulsed infrared lightsource with a digital imaging system. These early disappointing results clarified the need to further identify the unique system characteristics of the digital imager and pulsed infrared combination. It was also necessary to investigate how the infrared reflectance and transmittance of common materials affects the imaging process. This experimental work yielded a surprising, successful methodology which will prove useful in imaging ballistic and weapons tests, as well as forensics, flow visualizations, spray pattern analyses, and nocturnal animal behavioral studies.

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

PubMed

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

2018-05-03

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

Interactive Display of High-Resolution Images on the World Wide Web.

ERIC Educational Resources Information Center

Clyde, Stephen W.; Hirschi, Gregory W.

Viewing high-resolution images on the World Wide Web at a level of detail necessary for collaborative research is still a problem today, given the Internet's current bandwidth limitations and its ever increasing network traffic. ImageEyes is an interactive display tool being developed at Utah State University that addresses this problem by…

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.

A memory learning framework for effective image retrieval.

PubMed

Han, Junwei; Ngan, King N; Li, Mingjing; Zhang, Hong-Jiang

2005-04-01

Most current content-based image retrieval systems are still incapable of providing users with their desired results. The major difficulty lies in the gap between low-level image features and high-level image semantics. To address the problem, this study reports a framework for effective image retrieval by employing a novel idea of memory learning. It forms a knowledge memory model to store the semantic information by simply accumulating user-provided interactions. A learning strategy is then applied to predict the semantic relationships among images according to the memorized knowledge. Image queries are finally performed based on a seamless combination of low-level features and learned semantics. One important advantage of our framework is its ability to efficiently annotate images and also propagate the keyword annotation from the labeled images to unlabeled images. The presented algorithm has been integrated into a practical image retrieval system. Experiments on a collection of 10,000 general-purpose images demonstrate the effectiveness of the proposed framework.

BMC Ecology image competition 2014: the winning images

PubMed Central

2014-01-01

BMC Ecology showcases the winning entries from its second Ecology Image Competition. More than 300 individual images were submitted from an international array of research scientists, depicting life on every continent on earth. The journal’s Editorial Board and guest judge Caspar Henderson outline why their winning selections demonstrated high levels of technical skill and aesthetic sense in depicting the science of ecology, and we also highlight a small selection of highly commended images that we simply couldn’t let you miss out on. PMID:25178017

BMC Ecology image competition 2014: the winning images.

PubMed

Harold, Simon; Henderson, Caspar; Baguette, Michel; Bonsall, Michael B; Hughes, David; Settele, Josef

2014-08-29

BMC Ecology showcases the winning entries from its second Ecology Image Competition. More than 300 individual images were submitted from an international array of research scientists, depicting life on every continent on earth. The journal's Editorial Board and guest judge Caspar Henderson outline why their winning selections demonstrated high levels of technical skill and aesthetic sense in depicting the science of ecology, and we also highlight a small selection of highly commended images that we simply couldn't let you miss out on.

Robust algebraic image enhancement for intelligent control systems

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morrelli, Michael

1993-01-01

Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

Adaptive correction procedure for TVL1 image deblurring under impulse noise

NASA Astrophysics Data System (ADS)

Bai, Minru; Zhang, Xiongjun; Shao, Qianqian

2016-08-01

For the problem of image restoration of observed images corrupted by blur and impulse noise, the widely used TVL1 model may deviate from both the data-acquisition model and the prior model, especially for high noise levels. In order to seek a solution of high recovery quality beyond the reach of the TVL1 model, we propose an adaptive correction procedure for TVL1 image deblurring under impulse noise. Then, a proximal alternating direction method of multipliers (ADMM) is presented to solve the corrected TVL1 model and its convergence is also established under very mild conditions. It is verified by numerical experiments that our proposed approach outperforms the TVL1 model in terms of signal-to-noise ratio (SNR) values and visual quality, especially for high noise levels: it can handle salt-and-pepper noise as high as 90% and random-valued noise as high as 70%. In addition, a comparison with a state-of-the-art method, the two-phase method, demonstrates the superiority of the proposed approach.

Robust image registration for multiple exposure high dynamic range image synthesis

NASA Astrophysics Data System (ADS)

Yao, Susu

2011-03-01

Image registration is an important preprocessing technique in high dynamic range (HDR) image synthesis. This paper proposed a robust image registration method for aligning a group of low dynamic range images (LDR) that are captured with different exposure times. Illumination change and photometric distortion between two images would result in inaccurate registration. We propose to transform intensity image data into phase congruency to eliminate the effect of the changes in image brightness and use phase cross correlation in the Fourier transform domain to perform image registration. Considering the presence of non-overlapped regions due to photometric distortion, evolutionary programming is applied to search for the accurate translation parameters so that the accuracy of registration is able to be achieved at a hundredth of a pixel level. The proposed algorithm works well for under and over-exposed image registration. It has been applied to align LDR images for synthesizing high quality HDR images..

a Novel Framework for Remote Sensing Image Scene Classification

NASA Astrophysics Data System (ADS)

Jiang, S.; Zhao, H.; Wu, W.; Tan, Q.

2018-04-01

High resolution remote sensing (HRRS) images scene classification aims to label an image with a specific semantic category. HRRS images contain more details of the ground objects and their spatial distribution patterns than low spatial resolution images. Scene classification can bridge the gap between low-level features and high-level semantics. It can be applied in urban planning, target detection and other fields. This paper proposes a novel framework for HRRS images scene classification. This framework combines the convolutional neural network (CNN) and XGBoost, which utilizes CNN as feature extractor and XGBoost as a classifier. Then, this framework is evaluated on two different HRRS images datasets: UC-Merced dataset and NWPU-RESISC45 dataset. Our framework achieved satisfying accuracies on two datasets, which is 95.57 % and 83.35 % respectively. From the experiments result, our framework has been proven to be effective for remote sensing images classification. Furthermore, we believe this framework will be more practical for further HRRS scene classification, since it costs less time on training stage.

Pediatric chest HRCT using the iDose4 Hybrid Iterative Reconstruction Algorithm: Which iDose level to choose?

NASA Astrophysics Data System (ADS)

Smarda, M.; Alexopoulou, E.; Mazioti, A.; Kordolaimi, S.; Ploussi, A.; Priftis, K.; Efstathopoulos, E.

2015-09-01

Purpose of the study is to determine the appropriate iterative reconstruction (IR) algorithm level that combines image quality and diagnostic confidence, for pediatric patients undergoing high-resolution computed tomography (HRCT). During the last 2 years, a total number of 20 children up to 10 years old with a clinical presentation of chronic bronchitis underwent HRCT in our department's 64-detector row CT scanner using the iDose IR algorithm, with almost similar image settings (80kVp, 40-50 mAs). CT images were reconstructed with all iDose levels (level 1 to 7) as well as with filtered-back projection (FBP) algorithm. Subjective image quality was evaluated by 2 experienced radiologists in terms of image noise, sharpness, contrast and diagnostic acceptability using a 5-point scale (1=excellent image, 5=non-acceptable image). Artifacts existance was also pointed out. All mean scores from both radiologists corresponded to satisfactory image quality (score ≤3), even with the FBP algorithm use. Almost excellent (score <2) overall image quality was achieved with iDose levels 5 to 7, but oversmoothing artifacts appearing with iDose levels 6 and 7 affected the diagnostic confidence. In conclusion, the use of iDose level 5 enables almost excellent image quality without considerable artifacts affecting the diagnosis. Further evaluation is needed in order to draw more precise conclusions.

A comparative study of 2 computer-assisted methods of quantifying brightfield microscopy images.

PubMed

Tse, George H; Marson, Lorna P

2013-10-01

Immunohistochemistry continues to be a powerful tool for the detection of antigens. There are several commercially available software packages that allow image analysis; however, these can be complex, require relatively high level of computer skills, and can be expensive. We compared 2 commonly available software packages, Adobe Photoshop CS6 and ImageJ, in their ability to quantify percentage positive area after picrosirius red (PSR) staining and 3,3'-diaminobenzidine (DAB) staining. On analysis of DAB-stained B cells in the mouse spleen, with a biotinylated primary rat anti-mouse-B220 antibody, there was no significant difference on converting images from brightfield microscopy to binary images to measure black and white pixels using ImageJ compared with measuring a range of brown pixels with Photoshop (Student t test, P=0.243, correlation r=0.985). When analyzing mouse kidney allografts stained with PSR, Photoshop achieved a greater interquartile range while maintaining a lower 10th percentile value compared with analysis with ImageJ. A lower 10% percentile reflects that Photoshop analysis is better at analyzing tissues with low levels of positive pixels; particularly relevant for control tissues or negative controls, whereas after ImageJ analysis the same images would result in spuriously high levels of positivity. Furthermore comparing the 2 methods by Bland-Altman plot revealed that these 2 methodologies did not agree when measuring images with a higher percentage of positive staining and correlation was poor (r=0.804). We conclude that for computer-assisted analysis of images of DAB-stained tissue there is no difference between using Photoshop or ImageJ. However, for analysis of color images where differentiation into a binary pattern is not easy, such as with PSR, Photoshop is superior at identifying higher levels of positivity while maintaining differentiation of low levels of positive staining.

A Procedure for High Resolution Satellite Imagery Quality Assessment

PubMed Central

Crespi, Mattia; De Vendictis, Laura

2009-01-01

Data products generated from High Resolution Satellite Imagery (HRSI) are routinely evaluated during the so-called in-orbit test period, in order to verify if their quality fits the desired features and, if necessary, to obtain the image correction parameters to be used at the ground processing center. Nevertheless, it is often useful to have tools to evaluate image quality also at the final user level. Image quality is defined by some parameters, such as the radiometric resolution and its accuracy, represented by the noise level, and the geometric resolution and sharpness, described by the Modulation Transfer Function (MTF). This paper proposes a procedure to evaluate these image quality parameters; the procedure was implemented in a suitable software and tested on high resolution imagery acquired by the QuickBird, WorldView-1 and Cartosat-1 satellites. PMID:22412312

High-Precision Image Aided Inertial Navigation with Known Features: Observability Analysis and Performance Evaluation

PubMed Central

Jiang, Weiping; Wang, Li; Niu, Xiaoji; Zhang, Quan; Zhang, Hui; Tang, Min; Hu, Xiangyun

2014-01-01

A high-precision image-aided inertial navigation system (INS) is proposed as an alternative to the carrier-phase-based differential Global Navigation Satellite Systems (CDGNSSs) when satellite-based navigation systems are unavailable. In this paper, the image/INS integrated algorithm is modeled by a tightly-coupled iterative extended Kalman filter (IEKF). Tightly-coupled integration ensures that the integrated system is reliable, even if few known feature points (i.e., less than three) are observed in the images. A new global observability analysis of this tightly-coupled integration is presented to guarantee that the system is observable under the necessary conditions. The analysis conclusions were verified by simulations and field tests. The field tests also indicate that high-precision position (centimeter-level) and attitude (half-degree-level)-integrated solutions can be achieved in a global reference. PMID:25330046

SU-F-I-41: Calibration-Free Material Decomposition for Dual-Energy CT

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

Zhao, W; Xing, L; Zhang, Q

2016-06-15

Purpose: To eliminate tedious phantom calibration or manually region of interest (ROI) selection as required in dual-energy CT material decomposition, we establish a new projection-domain material decomposition framework with incorporation of energy spectrum. Methods: Similar to the case of dual-energy CT, the integral of the basis material image in our model is expressed as a linear combination of basis functions, which are the polynomials of high- and low-energy raw projection data. To yield the unknown coefficients of the linear combination, the proposed algorithm minimizes the quadratic error between the high- and low-energy raw projection data and the projection calculated usingmore » material images. We evaluate the algorithm with an iodine concentration numerical phantom at different dose and iodine concentration levels. The x-ray energy spectra of the high and low energy are estimated using an indirect transmission method. The derived monochromatic images are compared with the high- and low-energy CT images to demonstrate beam hardening artifacts reduction. Quantitative results were measured and compared to the true values. Results: The differences between the true density value used for simulation and that were obtained from the monochromatic images, are 1.8%, 1.3%, 2.3%, and 2.9% for the dose levels from standard dose to 1/8 dose, and are 0.4%, 0.7%, 1.5%, and 1.8% for the four iodine concentration levels from 6 mg/mL to 24 mg/mL. For all of the cases, beam hardening artifacts, especially streaks shown between dense inserts, are almost completely removed in the monochromatic images. Conclusion: The proposed algorithm provides an effective way to yield material images and artifacts-free monochromatic images at different dose levels without the need for phantom calibration or ROI selection. Furthermore, the approach also yields accurate results when the concentration of the iodine concentrate insert is very low, suggesting the algorithm is robust with respect to the low-contrast scenario.« less

Dual-energy digital mammography for calcification imaging: scatter and nonuniformity corrections.

PubMed

Kappadath, S Cheenu; Shaw, Chris C

2005-11-01

Mammographic images of small calcifications, which are often the earliest signs of breast cancer, can be obscured by overlapping fibroglandular tissue. We have developed and implemented a dual-energy digital mammography (DEDM) technique for calcification imaging under full-field imaging conditions using a commercially available aSi:H/CsI:Tl flat-panel based digital mammography system. The low- and high-energy images were combined using a nonlinear mapping function to cancel the tissue structures and generate the dual-energy (DE) calcification images. The total entrance-skin exposure and mean-glandular dose from the low- and high-energy images were constrained so that they were similar to screening-examination levels. To evaluate the DE calcification image, we designed a phantom using calcium carbonate crystals to simulate calcifications of various sizes (212-425 microm) overlaid with breast-tissue-equivalent material 5 cm thick with a continuously varying glandular-tissue ratio from 0% to 100%. We report on the effects of scatter radiation and nonuniformity in x-ray intensity and detector response on the DE calcification images. The nonuniformity was corrected by normalizing the low- and high-energy images with full-field reference images. Correction of scatter in the low- and high-energy images significantly reduced the background signal in the DE calcification image. Under the current implementation of DEDM, utilizing the mammography system and dose level tested, calcifications in the 300-355 microm size range were clearly visible in DE calcification images. Calcification threshold sizes decreased to the 250-280 microm size range when the visibility criteria were lowered to barely visible. Calcifications smaller than approximately 250 microm were usually not visible in most cases. The visibility of calcifications with our DEDM imaging technique was limited by quantum noise, not system noise.

Dual-energy digital mammography for calcification imaging: Scatter and nonuniformity corrections

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

Kappadath, S. Cheenu; Shaw, Chris C.

Mammographic images of small calcifications, which are often the earliest signs of breast cancer, can be obscured by overlapping fibroglandular tissue. We have developed and implemented a dual-energy digital mammography (DEDM) technique for calcification imaging under full-field imaging conditions using a commercially available aSi:H/CsI:Tl flat-panel based digital mammography system. The low- and high-energy images were combined using a nonlinear mapping function to cancel the tissue structures and generate the dual-energy (DE) calcification images. The total entrance-skin exposure and mean-glandular dose from the low- and high-energy images were constrained so that they were similar to screening-examination levels. To evaluate the DEmore » calcification image, we designed a phantom using calcium carbonate crystals to simulate calcifications of various sizes (212-425 {mu}m) overlaid with breast-tissue-equivalent material 5 cm thick with a continuously varying glandular-tissue ratio from 0% to 100%. We report on the effects of scatter radiation and nonuniformity in x-ray intensity and detector response on the DE calcification images. The nonuniformity was corrected by normalizing the low- and high-energy images with full-field reference images. Correction of scatter in the low- and high-energy images significantly reduced the background signal in the DE calcification image. Under the current implementation of DEDM, utilizing the mammography system and dose level tested, calcifications in the 300-355 {mu}m size range were clearly visible in DE calcification images. Calcification threshold sizes decreased to the 250-280 {mu}m size range when the visibility criteria were lowered to barely visible. Calcifications smaller than {approx}250 {mu}m were usually not visible in most cases. The visibility of calcifications with our DEDM imaging technique was limited by quantum noise, not system noise.« less

Naturalness and interestingness of test images for visual quality evaluation

NASA Astrophysics Data System (ADS)

Halonen, Raisa; Westman, Stina; Oittinen, Pirkko

2011-01-01

Balanced and representative test images are needed to study perceived visual quality in various application domains. This study investigates naturalness and interestingness as image quality attributes in the context of test images. Taking a top-down approach we aim to find the dimensions which constitute naturalness and interestingness in test images and the relationship between these high-level quality attributes. We compare existing collections of test images (e.g. Sony sRGB images, ISO 12640 images, Kodak images, Nokia images and test images developed within our group) in an experiment combining quality sorting and structured interviews. Based on the data gathered we analyze the viewer-supplied criteria for naturalness and interestingness across image types, quality levels and judges. This study advances our understanding of subjective image quality criteria and enables the validation of current test images, furthering their development.

Deep Sky Imaging: Workflow 2

NASA Astrophysics Data System (ADS)

Schedler, Johannes

As astrophotographers we are living in a golden age. In recent years CCD technology and the quality of amateur telescopes have reached a level of perfection, giving amateurs the chance to produce images rivaling those taken from mountaintops by large professional systems as recently as two decades ago. However hardware and good imaging location is only a part of the game. A high level of skill with image processing can offer amateurs an edge and provide a chance to compensate for the limited aperture of our telescopes.

Image Alignment for Multiple Camera High Dynamic Range Microscopy.

PubMed

Eastwood, Brian S; Childs, Elisabeth C

2012-01-09

This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability for HDR alignment of three exposure-robust techniques. We conclude that image alignment based on matching feature descriptors extracted from radiant power images from calibrated cameras yields the most accurate and robust solution. We demonstrate the use of this alignment technique in a high dynamic range video microscope that enables live specimen imaging with a greater level of detail than can be captured with a single camera.

Image Alignment for Multiple Camera High Dynamic Range Microscopy

PubMed Central

Eastwood, Brian S.; Childs, Elisabeth C.

2012-01-01

This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability for HDR alignment of three exposure-robust techniques. We conclude that image alignment based on matching feature descriptors extracted from radiant power images from calibrated cameras yields the most accurate and robust solution. We demonstrate the use of this alignment technique in a high dynamic range video microscope that enables live specimen imaging with a greater level of detail than can be captured with a single camera. PMID:22545028

Evidence-Based Imaging Guidelines and Medicare Payment Policy

PubMed Central

Sistrom, Christopher L; McKay, Niccie L

2008-01-01

Objective This study examines the relationship between evidence-based appropriateness criteria for neurologic imaging procedures and Medicare payment determinations. The primary research question is whether Medicare is more likely to pay for imaging procedures as the level of appropriateness increases. Data Sources The American College of Radiology Appropriateness Criteria (ACRAC) for neurological imaging, ICD-9-CM codes, CPT codes, and payment determinations by the Medicare Part B carrier for Florida and Connecticut. Study Design Cross-sectional study of appropriateness criteria and Medicare Part B payment policy for neurological imaging. In addition to descriptive and bivariate statistics, multivariate logistic regression on payment determination (yes or no) was performed. Data Collection Methods The American College of Radiology Appropriateness Criteria (ACRAC) documents specific to neurological imaging, ICD-9-CM codes, and CPT codes were used to create 2,510 medical condition/imaging procedure combinations, with associated appropriateness scores (coded as low/middle/high). Principal Findings As the level of appropriateness increased, more medical condition/imaging procedure combinations were payable (low = 61 percent, middle = 70 percent, and high = 74 percent). Logistic regression indicated that the odds of a medical condition/imaging procedure combination with a middle level of appropriateness being payable was 48 percent higher than for an otherwise similar combination with a low appropriateness score (95 percent CI on odds ratio=1.19–1.84). The odds ratio for being payable between high and low levels of appropriateness was 2.25 (95 percent CI: 1.66–3.04). Conclusions Medicare could improve its payment determinations by taking advantage of existing clinical guidelines, appropriateness criteria, and other authoritative resources for evidence-based practice. Such an approach would give providers a financial incentive that is aligned with best-practice medicine. In particular, Medicare should review and update its payment policies to reflect current information on the appropriateness of alternative imaging procedures for the same medical condition. PMID:18454778

High-energy x-ray Talbot-Lau radiography of a human knee

NASA Astrophysics Data System (ADS)

Horn, F.; Gelse, K.; Jabari, S.; Hauke, C.; Kaeppler, S.; Ludwig, V.; Meyer, P.; Michel, T.; Mohr, J.; Pelzer, G.; Rieger, J.; Riess, C.; Seifert, M.; Anton, G.

2017-08-01

We report on a radiographic measurement of an ex vivo human knee using a grating-based phase-contrast imaging setup and a medical x-ray tube at a tube voltage of 70 kV. The measurement has been carried out using a Talbot-Lau setup that is suitable to achieve a high visibility in the energy regime of medical imaging. In a medical reading by an experienced trauma surgeon signatures of chondrocalcinosis in the medial meniscus have been identified more evidently using the dark-field image in comparison to the conventional attenuation image. The analysis has been carried out at various dose levels down to 0.14 mGy measured as air kerma, which is a dose comparable to clinically used radiographic devices. The diagnosis has been confirmed by a histological analysis of the meniscus tissue. In the introduced high-frequency filtered phase-contrast image the anterior and posterior horn of the medial meniscus and the posterior cruciate ligament have also been visible. Furthermore, atherosclerotic plaque is visible in both imaging modalities, attenuation and dark-field, despite the presence of overlaying bone. This measurement, for the first time, proves the feasibility of Talbot-Lau x-ray imaging at high-energy spectra above 40 kVp and reasonable dose levels with regard to spacious and dense objects.

Plaque levels of patients with fixed orthodontic appliances measured by digital plaque image analysis.

PubMed

Klukowska, Malgorzata; Bader, Annike; Erbe, Christina; Bellamy, Philip; White, Donald J; Anastasia, Mary Kay; Wehrbein, Heiner

2011-05-01

A digital plaque image analysis system was developed to objectively assess dental plaque formation and coverage in patients treated with fixed orthodontic appliances. The technique was used to assess plaque levels of 52 patients undergoing treatment with fixed appliances in the Department of Orthodontics at Johannes Gutenberg University in Mainz, Germany. Plaque levels ranged from 5.1% to 85.3% of the analyzed tooth areas. About 37% of the patients had plaque levels over 50% of the dentition, but only 10% exhibited plaque levels below 15% of tooth coverage. The mean plaque coverage was 41.9% ± 18.8%. Plaque was mostly present along the gum line and around the orthodontic brackets and wires. The digital plaque image analysis system might provide a convenient quantitative technique to assess oral hygiene in orthodontic patients with multi-bracket appliances. Plaque coverage in orthodontic patients is extremely high and is 2 to 3 times higher than levels observed in high plaque-forming adults without appliances participating in clinical studies of the digital plaque image analysis system. Improved hygiene, chemotherapeutic regimens, and compliance are necessary in these patients. Copyright © 2011 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

Towards building high performance medical image management system for clinical trials

NASA Astrophysics Data System (ADS)

Wang, Fusheng; Lee, Rubao; Zhang, Xiaodong; Saltz, Joel

2011-03-01

Medical image based biomarkers are being established for therapeutic cancer clinical trials, where image assessment is among the essential tasks. Large scale image assessment is often performed by a large group of experts by retrieving images from a centralized image repository to workstations to markup and annotate images. In such environment, it is critical to provide a high performance image management system that supports efficient concurrent image retrievals in a distributed environment. There are several major challenges: high throughput of large scale image data over the Internet from the server for multiple concurrent client users, efficient communication protocols for transporting data, and effective management of versioning of data for audit trails. We study the major bottlenecks for such a system, propose and evaluate a solution by using a hybrid image storage with solid state drives and hard disk drives, RESTfulWeb Services based protocols for exchanging image data, and a database based versioning scheme for efficient archive of image revision history. Our experiments show promising results of our methods, and our work provides a guideline for building enterprise level high performance medical image management systems.

Socioeconomic status and the utilization of diagnostic imaging in an urban setting

PubMed Central

Demeter, Sandor; Reed, Martin; Lix, Lisa; MacWilliam, Leonard; Leslie, William D.

2005-01-01

Background In publicly funded health care systems, the utilization of health care services should be equitable, irrespective of socioeconomic status (SES). Although the association between SES and health care utilization has been examined in Canada relative to surgical, cardiac and preventive health care services, no published studies have specifically explored the association between SES and diagnostic imaging. Methods We examined over 300 000 diagnostic imaging claims made in the Winnipeg Regional Health Authority between Apr. 1, 2001, and Mar. 31, 2002. Using patient postal codes, we assigned SES on the basis of average household incomes in Canada's 1996 census. Using multiple regression, we examined the association between income quintile, patient age group (≤16, 17–64, ≥ 65 years), patient morbidity level according to the Johns Hopkins University Adjusted Clinical Group method (high, moderate, low), and imaging modality (general radiology, vascular, computed tomography, magnetic resonance, and general and obstetric ultrasound). Results Relative rates (RR) of diagnostic imaging utilization (highest v. lowest income quintile) were significantly increased in pediatric and adult patient groups at all morbidity levels receiving general radiology (highest RR 2.47, 95% confidence interval [CI] 2.07–2.93); pediatric and adult patient groups at high and low morbidity levels and elderly patient groups at low morbidity levels receiving general ultrasound (highest RR 2.26, 95% CI 1.20–4.26); pediatric and adult patient groups at all morbidity levels and elderly patients at high and moderate morbidity levels receiving magnetic resonance imaging (highest RR 2.51, 95% CI 1.78– 3.52); and adult patient groups at all morbidity levels receiving computed tomography (highest RR 1.46, 95% CI 1.35– 1.59). A lower RR of diagnostic imaging utilization in the highest income quintile was found only among patients receiving obstetric ultrasound (RR 0.80, 95% CI 0.73–0.87). No significant associations were found among elderly patients receiving general radiology or computed tomography or adult patients receiving vascular imaging. Interpretation We found a pattern of increased diagnostic imaging utilization in patient groups with a higher SES. Further research is needed to better understand the nature of this finding and how it contributes to health outcomes. PMID:16275968

Multispectral Palmprint Recognition Using a Quaternion Matrix

PubMed Central

Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

2012-01-01

Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%. PMID:22666049

Multispectral palmprint recognition using a quaternion matrix.

PubMed

Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

2012-01-01

Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

Investigation of Image Reconstruction Parameters of the Mediso nanoScan PC Small-Animal PET/CT Scanner for Two Different Positron Emitters Under NEMA NU 4-2008 Standards.

PubMed

Gaitanis, Anastasios; Kastis, George A; Vlastou, Elena; Bouziotis, Penelope; Verginis, Panayotis; Anagnostopoulos, Constantinos D

2017-08-01

The Tera-Tomo 3D image reconstruction algorithm (a version of OSEM), provided with the Mediso nanoScan® PC (PET8/2) small-animal positron emission tomograph (PET)/x-ray computed tomography (CT) scanner, has various parameter options such as total level of regularization, subsets, and iterations. Also, the acquisition time in PET plays an important role. This study aims to assess the performance of this new small-animal PET/CT scanner for different acquisition times and reconstruction parameters, for 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) and Ga-68, under the NEMA NU 4-2008 standards. Various image quality metrics were calculated for different realizations of [ 18 F]FDG and Ga-68 filled image quality (IQ) phantoms. [ 18 F]FDG imaging produced improved images over Ga-68. The best compromise for the optimization of all image quality factors is achieved for at least 30 min acquisition and image reconstruction with 52 iteration updates combined with a high regularization level. A high regularization level at 52 iteration updates and 30 min acquisition time were found to optimize most of the figures of merit investigated.

MToS: A Tree of Shapes for Multivariate Images.

PubMed

Carlinet, Edwin; Géraud, Thierry

2015-12-01

The topographic map of a gray-level image, also called tree of shapes, provides a high-level hierarchical representation of the image contents. This representation, invariant to contrast changes and to contrast inversion, has been proved very useful to achieve many image processing and pattern recognition tasks. Its definition relies on the total ordering of pixel values, so this representation does not exist for color images, or more generally, multivariate images. Common workarounds, such as marginal processing, or imposing a total order on data, are not satisfactory and yield many problems. This paper presents a method to build a tree-based representation of multivariate images, which features marginally the same properties of the gray-level tree of shapes. Briefly put, we do not impose an arbitrary ordering on values, but we only rely on the inclusion relationship between shapes in the image definition domain. The interest of having a contrast invariant and self-dual representation of multivariate image is illustrated through several applications (filtering, segmentation, and object recognition) on different types of data: color natural images, document images, satellite hyperspectral imaging, multimodal medical imaging, and videos.

Comparison of lifetime-based methods for 2D phosphor thermometry in high-temperature environment

NASA Astrophysics Data System (ADS)

Peng, Di; Liu, Yingzheng; Zhao, Xiaofeng; Kim, Kyung Chun

2016-09-01

This paper discusses the currently available techniques for 2D phosphor thermometry, and compares the performance of two lifetime-based methods: high-speed imaging and the dual-gate. High-speed imaging resolves luminescent decay with a fast frame rate, and has become a popular method for phosphor thermometry in recent years. But it has disadvantages such as high equipment cost and long data processing time, and it would fail at sufficiently high temperature due to a low signal-to-noise ratio and short lifetime. The dual-gate method only requires two images on the decay curve and therefore greatly reduces cost in hardware and processing time. A dual-gate method for phosphor thermometry has been developed and compared with the high-speed imaging method through both calibration and a jet impingement experiment. Measurement uncertainty has been evaluated for a temperature range of 473-833 K. The effects of several key factors on uncertainty have been discussed, including the luminescent signal level, the decay lifetime and temperature sensitivity. The results show that both methods are valid for 2D temperature sensing within the given range. The high-speed imaging method shows less uncertainty at low temperatures where the signal level and the lifetime are both sufficient, but its performance is degraded at higher temperatures due to a rapidly reduced signal and lifetime. For T  >  750 K, the dual-gate method outperforms the high-speed imaging method thanks to its superiority in signal-to-noise ratio and temperature sensitivity. The dual-gate method has great potential for applications in high-temperature environments where the high-speed imaging method is not applicable.

Neural network fusion: a novel CT-MR aortic aneurysm image segmentation method

NASA Astrophysics Data System (ADS)

Wang, Duo; Zhang, Rui; Zhu, Jin; Teng, Zhongzhao; Huang, Yuan; Spiga, Filippo; Du, Michael Hong-Fei; Gillard, Jonathan H.; Lu, Qingsheng; Liò, Pietro

2018-03-01

Medical imaging examination on patients usually involves more than one imaging modalities, such as Computed Tomography (CT), Magnetic Resonance (MR) and Positron Emission Tomography(PET) imaging. Multimodal imaging allows examiners to benefit from the advantage of each modalities. For example, for Abdominal Aortic Aneurysm, CT imaging shows calcium deposits in the aorta clearly while MR imaging distinguishes thrombus and soft tissues better.1 Analysing and segmenting both CT and MR images to combine the results will greatly help radiologists and doctors to treat the disease. In this work, we present methods on using deep neural network models to perform such multi-modal medical image segmentation. As CT image and MR image of the abdominal area cannot be well registered due to non-affine deformations, a naive approach is to train CT and MR segmentation network separately. However, such approach is time-consuming and resource-inefficient. We propose a new approach to fuse the high-level part of the CT and MR network together, hypothesizing that neurons recognizing the high level concepts of Aortic Aneurysm can be shared across multiple modalities. Such network is able to be trained end-to-end with non-registered CT and MR image using shorter training time. Moreover network fusion allows a shared representation of Aorta in both CT and MR images to be learnt. Through experiments we discovered that for parts of Aorta showing similar aneurysm conditions, their neural presentations in neural network has shorter distances. Such distances on the feature level is helpful for registering CT and MR image.

Software-based high-level synthesis design of FPGA beamformers for synthetic aperture imaging.

PubMed

Amaro, Joao; Yiu, Billy Y S; Falcao, Gabriel; Gomes, Marco A C; Yu, Alfred C H

2015-05-01

Field-programmable gate arrays (FPGAs) can potentially be configured as beamforming platforms for ultrasound imaging, but a long design time and skilled expertise in hardware programming are typically required. In this article, we present a novel approach to the efficient design of FPGA beamformers for synthetic aperture (SA) imaging via the use of software-based high-level synthesis techniques. Software kernels (coded in OpenCL) were first developed to stage-wise handle SA beamforming operations, and their corresponding FPGA logic circuitry was emulated through a high-level synthesis framework. After design space analysis, the fine-tuned OpenCL kernels were compiled into register transfer level descriptions to configure an FPGA as a beamformer module. The processing performance of this beamformer was assessed through a series of offline emulation experiments that sought to derive beamformed images from SA channel-domain raw data (40-MHz sampling rate, 12 bit resolution). With 128 channels, our FPGA-based SA beamformer can achieve 41 frames per second (fps) processing throughput (3.44 × 10(8) pixels per second for frame size of 256 × 256 pixels) at 31.5 W power consumption (1.30 fps/W power efficiency). It utilized 86.9% of the FPGA fabric and operated at a 196.5 MHz clock frequency (after optimization). Based on these findings, we anticipate that FPGA and high-level synthesis can together foster rapid prototyping of real-time ultrasound processor modules at low power consumption budgets.

High speed imager test station

DOEpatents

Yates, George J.; Albright, Kevin L.; Turko, Bojan T.

1995-01-01

A test station enables the performance of a solid state imager (herein called a focal plane array or FPA) to be determined at high image frame rates. A programmable waveform generator is adapted to generate clock pulses at determinable rates for clock light-induced charges from a FPA. The FPA is mounted on an imager header board for placing the imager in operable proximity to level shifters for receiving the clock pulses and outputting pulses effective to clock charge from the pixels forming the FPA. Each of the clock level shifters is driven by leading and trailing edge portions of the clock pulses to reduce power dissipation in the FPA. Analog circuits receive output charge pulses clocked from the FPA pixels. The analog circuits condition the charge pulses to cancel noise in the pulses and to determine and hold a peak value of the charge for digitizing. A high speed digitizer receives the peak signal value and outputs a digital representation of each one of the charge pulses. A video system then displays an image associated with the digital representation of the output charge pulses clocked from the FPA. In one embodiment, the FPA image is formatted to a standard video format for display on conventional video equipment.

High speed imager test station

DOEpatents

Yates, G.J.; Albright, K.L.; Turko, B.T.

1995-11-14

A test station enables the performance of a solid state imager (herein called a focal plane array or FPA) to be determined at high image frame rates. A programmable waveform generator is adapted to generate clock pulses at determinable rates for clock light-induced charges from a FPA. The FPA is mounted on an imager header board for placing the imager in operable proximity to level shifters for receiving the clock pulses and outputting pulses effective to clock charge from the pixels forming the FPA. Each of the clock level shifters is driven by leading and trailing edge portions of the clock pulses to reduce power dissipation in the FPA. Analog circuits receive output charge pulses clocked from the FPA pixels. The analog circuits condition the charge pulses to cancel noise in the pulses and to determine and hold a peak value of the charge for digitizing. A high speed digitizer receives the peak signal value and outputs a digital representation of each one of the charge pulses. A video system then displays an image associated with the digital representation of the output charge pulses clocked from the FPA. In one embodiment, the FPA image is formatted to a standard video format for display on conventional video equipment. 12 figs.

Built-Up Area Detection from High-Resolution Satellite Images Using Multi-Scale Wavelet Transform and Local Spatial Statistics

NASA Astrophysics Data System (ADS)

Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.

2018-04-01

Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.

Progressive Vector Quantization on a massively parallel SIMD machine with application to multispectral image data

NASA Technical Reports Server (NTRS)

Manohar, Mareboyana; Tilton, James C.

1994-01-01

A progressive vector quantization (VQ) compression approach is discussed which decomposes image data into a number of levels using full search VQ. The final level is losslessly compressed, enabling lossless reconstruction. The computational difficulties are addressed by implementation on a massively parallel SIMD machine. We demonstrate progressive VQ on multispectral imagery obtained from the Advanced Very High Resolution Radiometer instrument and other Earth observation image data, and investigate the trade-offs in selecting the number of decomposition levels and codebook training method.

Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

NASA Astrophysics Data System (ADS)

Ostir, K.; Cotar, K.; Marsetic, A.; Pehani, P.; Perse, M.; Zaksek, K.; Zaletelj, J.; Rodic, T.

2015-04-01

In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data.

Image Retrieval by Color Semantics with Incomplete Knowledge.

ERIC Educational Resources Information Center

Corridoni, Jacopo M.; Del Bimbo, Alberto; Vicario, Enrico

1998-01-01

Presents a system which supports image retrieval by high-level chromatic contents, the sensations that color accordances generate on the observer. Surveys Itten's theory of color semantics and discusses image description and query specification. Presents examples of visual querying. (AEF)

Recognition Alters the Spatial Pattern of fMRI Activation in Early Retinotopic Cortex

PubMed Central

Vul, E.; Kanwisher, N.

2010-01-01

Early retinotopic cortex has traditionally been viewed as containing a veridical representation of the low-level properties of the image, not imbued by high-level interpretation and meaning. Yet several recent results indicate that neural representations in early retinotopic cortex reflect not just the sensory properties of the image, but also the perceived size and brightness of image regions. Here we used functional magnetic resonance imaging pattern analyses to ask whether the representation of an object in early retinotopic cortex changes when the object is recognized compared with when the same stimulus is presented but not recognized. Our data confirmed this hypothesis: the pattern of response in early retinotopic visual cortex to a two-tone “Mooney” image of an object was more similar to the response to the full grayscale photo version of the same image when observers knew what the two-tone image represented than when they did not. Further, in a second experiment, high-level interpretations actually overrode bottom-up stimulus information, such that the pattern of response in early retinotopic cortex to an identified two-tone image was more similar to the response to the photographic version of that stimulus than it was to the response to the identical two-tone image when it was not identified. Our findings are consistent with prior results indicating that perceived size and brightness affect representations in early retinotopic visual cortex and, further, show that even higher-level information—knowledge of object identity—also affects the representation of an object in early retinotopic cortex. PMID:20071627

Imaging metallic samples using electrical capacitance tomography: forward modelling and reconstruction algorithms

NASA Astrophysics Data System (ADS)

Hosani, E. Al; Zhang, M.; Abascal, J. F. P. J.; Soleimani, M.

2016-11-01

Electrical capacitance tomography (ECT) is an imaging technology used to reconstruct the permittivity distribution within the sensing region. So far, ECT has been primarily used to image non-conductive media only, since if the conductivity of the imaged object is high, the capacitance measuring circuit will be almost shortened by the conductivity path and a clear image cannot be produced using the standard image reconstruction approaches. This paper tackles the problem of imaging metallic samples using conventional ECT systems by investigating the two main aspects of image reconstruction algorithms, namely the forward problem and the inverse problem. For the forward problem, two different methods to model the region of high conductivity in ECT is presented. On the other hand, for the inverse problem, three different algorithms to reconstruct the high contrast images are examined. The first two methods are the linear single step Tikhonov method and the iterative total variation regularization method, and use two sets of ECT data to reconstruct the image in time difference mode. The third method, namely the level set method, uses absolute ECT measurements and was developed using a metallic forward model. The results indicate that the applications of conventional ECT systems can be extended to metal samples using the suggested algorithms and forward model, especially using a level set algorithm to find the boundary of the metal.

Evaluation of conventional imaging performance in a research whole-body CT system with a photon-counting detector array.

PubMed

Yu, Zhicong; Leng, Shuai; Jorgensen, Steven M; Li, Zhoubo; Gutjahr, Ralf; Chen, Baiyu; Halaweish, Ahmed F; Kappler, Steffen; Yu, Lifeng; Ritman, Erik L; McCollough, Cynthia H

2016-02-21

This study evaluated the conventional imaging performance of a research whole-body photon-counting CT system and investigated its feasibility for imaging using clinically realistic levels of x-ray photon flux. This research system was built on the platform of a 2nd generation dual-source CT system: one source coupled to an energy integrating detector (EID) and the other coupled to a photon-counting detector (PCD). Phantom studies were conducted to measure CT number accuracy and uniformity for water, CT number energy dependency for high-Z materials, spatial resolution, noise, and contrast-to-noise ratio. The results from the EID and PCD subsystems were compared. The impact of high photon flux, such as pulse pile-up, was assessed by studying the noise-to-tube-current relationship using a neonate water phantom and high x-ray photon flux. Finally, clinical feasibility of the PCD subsystem was investigated using anthropomorphic phantoms, a cadaveric head, and a whole-body cadaver, which were scanned at dose levels equivalent to or higher than those used clinically. Phantom measurements demonstrated that the PCD subsystem provided comparable image quality to the EID subsystem, except that the PCD subsystem provided slightly better longitudinal spatial resolution and about 25% improvement in contrast-to-noise ratio for iodine. The impact of high photon flux was found to be negligible for the PCD subsystem: only subtle high-flux effects were noticed for tube currents higher than 300 mA in images of the neonate water phantom. Results of the anthropomorphic phantom and cadaver scans demonstrated comparable image quality between the EID and PCD subsystems. There were no noticeable ring, streaking, or cupping/capping artifacts in the PCD images. In addition, the PCD subsystem provided spectral information. Our experiments demonstrated that the research whole-body photon-counting CT system is capable of providing clinical image quality at clinically realistic levels of x-ray photon flux.

Evaluation of conventional imaging performance in a research whole-body CT system with a photon-counting detector array

NASA Astrophysics Data System (ADS)

Yu, Zhicong; Leng, Shuai; Jorgensen, Steven M.; Li, Zhoubo; Gutjahr, Ralf; Chen, Baiyu; Halaweish, Ahmed F.; Kappler, Steffen; Yu, Lifeng; Ritman, Erik L.; McCollough, Cynthia H.

2016-02-01

This study evaluated the conventional imaging performance of a research whole-body photon-counting CT system and investigated its feasibility for imaging using clinically realistic levels of x-ray photon flux. This research system was built on the platform of a 2nd generation dual-source CT system: one source coupled to an energy integrating detector (EID) and the other coupled to a photon-counting detector (PCD). Phantom studies were conducted to measure CT number accuracy and uniformity for water, CT number energy dependency for high-Z materials, spatial resolution, noise, and contrast-to-noise ratio. The results from the EID and PCD subsystems were compared. The impact of high photon flux, such as pulse pile-up, was assessed by studying the noise-to-tube-current relationship using a neonate water phantom and high x-ray photon flux. Finally, clinical feasibility of the PCD subsystem was investigated using anthropomorphic phantoms, a cadaveric head, and a whole-body cadaver, which were scanned at dose levels equivalent to or higher than those used clinically. Phantom measurements demonstrated that the PCD subsystem provided comparable image quality to the EID subsystem, except that the PCD subsystem provided slightly better longitudinal spatial resolution and about 25% improvement in contrast-to-noise ratio for iodine. The impact of high photon flux was found to be negligible for the PCD subsystem: only subtle high-flux effects were noticed for tube currents higher than 300 mA in images of the neonate water phantom. Results of the anthropomorphic phantom and cadaver scans demonstrated comparable image quality between the EID and PCD subsystems. There were no noticeable ring, streaking, or cupping/capping artifacts in the PCD images. In addition, the PCD subsystem provided spectral information. Our experiments demonstrated that the research whole-body photon-counting CT system is capable of providing clinical image quality at clinically realistic levels of x-ray photon flux.

Hierarchical tone mapping for high dynamic range image visualization

NASA Astrophysics Data System (ADS)

Qiu, Guoping; Duan, Jiang

2005-07-01

In this paper, we present a computationally efficient, practically easy to use tone mapping techniques for the visualization of high dynamic range (HDR) images in low dynamic range (LDR) reproduction devices. The new method, termed hierarchical nonlinear linear (HNL) tone-mapping operator maps the pixels in two hierarchical steps. The first step allocates appropriate numbers of LDR display levels to different HDR intensity intervals according to the pixel densities of the intervals. The second step linearly maps the HDR intensity intervals to theirs allocated LDR display levels. In the developed HNL scheme, the assignment of LDR display levels to HDR intensity intervals is controlled by a very simple and flexible formula with a single adjustable parameter. We also show that our new operators can be used for the effective enhancement of ordinary images.

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images.

PubMed

Xu, Jun; Xiang, Lei; Liu, Qingshan; Gilmore, Hannah; Wu, Jianzhong; Tang, Jinghai; Madabhushi, Anant

2016-01-01

Automated nuclear detection is a critical step for a number of computer assisted pathology related image analysis algorithms such as for automated grading of breast cancer tissue specimens. The Nottingham Histologic Score system is highly correlated with the shape and appearance of breast cancer nuclei in histopathological images. However, automated nucleus detection is complicated by 1) the large number of nuclei and the size of high resolution digitized pathology images, and 2) the variability in size, shape, appearance, and texture of the individual nuclei. Recently there has been interest in the application of "Deep Learning" strategies for classification and analysis of big image data. Histopathology, given its size and complexity, represents an excellent use case for application of deep learning strategies. In this paper, a Stacked Sparse Autoencoder (SSAE), an instance of a deep learning strategy, is presented for efficient nuclei detection on high-resolution histopathological images of breast cancer. The SSAE learns high-level features from just pixel intensities alone in order to identify distinguishing features of nuclei. A sliding window operation is applied to each image in order to represent image patches via high-level features obtained via the auto-encoder, which are then subsequently fed to a classifier which categorizes each image patch as nuclear or non-nuclear. Across a cohort of 500 histopathological images (2200 × 2200) and approximately 3500 manually segmented individual nuclei serving as the groundtruth, SSAE was shown to have an improved F-measure 84.49% and an average area under Precision-Recall curve (AveP) 78.83%. The SSAE approach also out-performed nine other state of the art nuclear detection strategies.

Imaging with a small number of photons

PubMed Central

Morris, Peter A.; Aspden, Reuben S.; Bell, Jessica E. C.; Boyd, Robert W.; Padgett, Miles J.

2015-01-01

Low-light-level imaging techniques have application in many diverse fields, ranging from biological sciences to security. A high-quality digital camera based on a multi-megapixel array will typically record an image by collecting of order 105 photons per pixel, but by how much could this photon flux be reduced? In this work we demonstrate a single-photon imaging system based on a time-gated intensified camera from which the image of an object can be inferred from very few detected photons. We show that a ghost-imaging configuration, where the image is obtained from photons that have never interacted with the object, is a useful approach for obtaining images with high signal-to-noise ratios. The use of heralded single photons ensures that the background counts can be virtually eliminated from the recorded images. By applying principles of image compression and associated image reconstruction, we obtain high-quality images of objects from raw data formed from an average of fewer than one detected photon per image pixel. PMID:25557090

Research-grade CMOS image sensors for remote sensing applications

NASA Astrophysics Data System (ADS)

Saint-Pe, Olivier; Tulet, Michel; Davancens, Robert; Larnaudie, Franck; Magnan, Pierre; Martin-Gonthier, Philippe; Corbiere, Franck; Belliot, Pierre; Estribeau, Magali

2004-11-01

Imaging detectors are key elements for optical instruments and sensors on board space missions dedicated to Earth observation (high resolution imaging, atmosphere spectroscopy...), Solar System exploration (micro cameras, guidance for autonomous vehicle...) and Universe observation (space telescope focal planes, guiding sensors...). This market has been dominated by CCD technology for long. Since the mid-90s, CMOS Image Sensors (CIS) have been competing with CCDs for consumer domains (webcams, cell phones, digital cameras...). Featuring significant advantages over CCD sensors for space applications (lower power consumption, smaller system size, better radiations behaviour...), CMOS technology is also expanding in this field, justifying specific R&D and development programs funded by national and European space agencies (mainly CNES, DGA and ESA). All along the 90s and thanks to their increasingly improving performances, CIS have started to be successfully used for more and more demanding space applications, from vision and control functions requiring low-level performances to guidance applications requiring medium-level performances. Recent technology improvements have made possible the manufacturing of research-grade CIS that are able to compete with CCDs in the high-performances arena. After an introduction outlining the growing interest of optical instruments designers for CMOS image sensors, this paper will present the existing and foreseen ways to reach high-level electro-optics performances for CIS. The developments and performances of CIS prototypes built using an imaging CMOS process will be presented in the corresponding section.

Body Image of Highly Trained Female Athletes Engaged in Different Types of Sport.

PubMed

Kantanista, Adam; Glapa, Agata; Banio, Adrianna; Firek, Wiesław; Ingarden, Anna; Malchrowicz-Mośko, Ewa; Markiewicz, Paweł; Płoszaj, Katarzyna; Ingarden, Mateusz; Maćkowiak, Zuzanna

2018-01-01

The aim of the study was to evaluate differences in body image across different types of sports in highly trained female athletes. 242 female individuals, aged 13-30 years (M = 20.0, SD = 4.5), representing aesthetic sports ( n = 56) and nonaesthetic sports ( n = 186), were recruited from different sports clubs in Poland. Body image, BMI, age, the level of competition attained, and the training background of participants were recorded. One-way ANOVA showed differences in the body image of athletes engaged in different types of sport ( F (11,230) = 4.10, p < 0.001, and η 2 = 0.16). The model predicting the body image of female athletes was significant ( F (5,236) = 10.40, p < 0.001); the adjusted R 2 = 0.163. Type of sport explained 7.1% ( β = -0.263, p < 0.001), age explained 4.5% ( β = 0.341, p < 0.001), BMI explained 3.6% ( β = -0.230, p < 0.001), and level of competition explained 0.9% ( β = 0.153, p < 0.05) of variance in body image. The findings provide vital new knowledge which can be used by researchers and practitioners in designing educational programs on weight-related behaviors in female athletes. Such programs should be implemented especially in young female athletes participating in high-level sporting activities at an early stage.

Body Image of Highly Trained Female Athletes Engaged in Different Types of Sport

PubMed Central

Glapa, Agata; Banio, Adrianna; Firek, Wiesław; Ingarden, Anna; Malchrowicz-Mośko, Ewa; Markiewicz, Paweł; Płoszaj, Katarzyna; Ingarden, Mateusz; Maćkowiak, Zuzanna

2018-01-01

Background The aim of the study was to evaluate differences in body image across different types of sports in highly trained female athletes. Methods 242 female individuals, aged 13–30 years (M = 20.0, SD = 4.5), representing aesthetic sports (n = 56) and nonaesthetic sports (n = 186), were recruited from different sports clubs in Poland. Body image, BMI, age, the level of competition attained, and the training background of participants were recorded. Results One-way ANOVA showed differences in the body image of athletes engaged in different types of sport (F(11,230) = 4.10, p < 0.001, and η2 = 0.16). The model predicting the body image of female athletes was significant (F(5,236) = 10.40, p < 0.001); the adjusted R2 = 0.163. Type of sport explained 7.1% (β = –0.263, p < 0.001), age explained 4.5% (β = 0.341, p < 0.001), BMI explained 3.6% (β = –0.230, p < 0.001), and level of competition explained 0.9% (β = 0.153, p < 0.05) of variance in body image. Conclusions The findings provide vital new knowledge which can be used by researchers and practitioners in designing educational programs on weight-related behaviors in female athletes. Such programs should be implemented especially in young female athletes participating in high-level sporting activities at an early stage. PMID:29662894

Optical diagnostics of mercury jet for an intense proton target.

PubMed

Park, H; Tsang, T; Kirk, H G; Ladeinde, F; Graves, V B; Spampinato, P T; Carroll, A J; Titus, P H; McDonald, K T

2008-04-01

An optical diagnostic system is designed and constructed for imaging a free mercury jet interacting with a high intensity proton beam in a pulsed high-field solenoid magnet. The optical imaging system employs a backilluminated, laser shadow photography technique. Object illumination and image capture are transmitted through radiation-hard multimode optical fibers and flexible coherent imaging fibers. A retroreflected illumination design allows the entire passive imaging system to fit inside the bore of the solenoid magnet. A sequence of synchronized short laser light pulses are used to freeze the transient events, and the images are recorded by several high speed charge coupled devices. Quantitative and qualitative data analysis using image processing based on probability approach is described. The characteristics of free mercury jet as a high power target for beam-jet interaction at various levels of the magnetic induction field is reported in this paper.

Automatic classification of tissue malignancy for breast carcinoma diagnosis.

PubMed

Fondón, Irene; Sarmiento, Auxiliadora; García, Ana Isabel; Silvestre, María; Eloy, Catarina; Polónia, António; Aguiar, Paulo

2018-05-01

Breast cancer is the second leading cause of cancer death among women. Its early diagnosis is extremely important to prevent avoidable deaths. However, malignancy assessment of tissue biopsies is complex and dependent on observer subjectivity. Moreover, hematoxylin and eosin (H&E)-stained histological images exhibit a highly variable appearance, even within the same malignancy level. In this paper, we propose a computer-aided diagnosis (CAD) tool for automated malignancy assessment of breast tissue samples based on the processing of histological images. We provide four malignancy levels as the output of the system: normal, benign, in situ and invasive. The method is based on the calculation of three sets of features related to nuclei, colour regions and textures considering local characteristics and global image properties. By taking advantage of well-established image processing techniques, we build a feature vector for each image that serves as an input to an SVM (Support Vector Machine) classifier with a quadratic kernel. The method has been rigorously evaluated, first with a 5-fold cross-validation within an initial set of 120 images, second with an external set of 30 different images and third with images with artefacts included. Accuracy levels range from 75.8% when the 5-fold cross-validation was performed to 75% with the external set of new images and 61.11% when the extremely difficult images were added to the classification experiment. The experimental results indicate that the proposed method is capable of distinguishing between four malignancy levels with high accuracy. Our results are close to those obtained with recent deep learning-based methods. Moreover, it performs better than other state-of-the-art methods based on feature extraction, and it can help improve the CAD of breast cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

A comprehensive study on the relationship between the image quality and imaging dose in low-dose cone beam CT

NASA Astrophysics Data System (ADS)

Yan, Hao; Cervino, Laura; Jia, Xun; Jiang, Steve B.

2012-04-01

While compressed sensing (CS)-based algorithms have been developed for the low-dose cone beam CT (CBCT) reconstruction, a clear understanding of the relationship between the image quality and imaging dose at low-dose levels is needed. In this paper, we qualitatively investigate this subject in a comprehensive manner with extensive experimental and simulation studies. The basic idea is to plot both the image quality and imaging dose together as functions of the number of projections and mAs per projection over the whole clinically relevant range. On this basis, a clear understanding of the tradeoff between the image quality and imaging dose can be achieved and optimal low-dose CBCT scan protocols can be developed to maximize the dose reduction while minimizing the image quality loss for various imaging tasks in image-guided radiation therapy (IGRT). Main findings of this work include (1) under the CS-based reconstruction framework, image quality has little degradation over a large range of dose variation. Image quality degradation becomes evident when the imaging dose (approximated with the x-ray tube load) is decreased below 100 total mAs. An imaging dose lower than 40 total mAs leads to a dramatic image degradation, and thus should be used cautiously. Optimal low-dose CBCT scan protocols likely fall in the dose range of 40-100 total mAs, depending on the specific IGRT applications. (2) Among different scan protocols at a constant low-dose level, the super sparse-view reconstruction with the projection number less than 50 is the most challenging case, even with strong regularization. Better image quality can be acquired with low mAs protocols. (3) The optimal scan protocol is the combination of a medium number of projections and a medium level of mAs/view. This is more evident when the dose is around 72.8 total mAs or below and when the ROI is a low-contrast or high-resolution object. Based on our results, the optimal number of projections is around 90 to 120. (4) The clinically acceptable lowest imaging dose level is task dependent. In our study, 72.8 mAs is a safe dose level for visualizing low-contrast objects, while 12.2 total mAs is sufficient for detecting high-contrast objects of diameter greater than 3 mm.

A new instrument of VUV laser desorption/ionization mass spectrometry imaging with micrometer spatial resolution and low level of molecular fragmentation.

PubMed

Wang, Jia; Liu, Feng; Mo, Yuxiang; Wang, Zhaoying; Zhang, Sichun; Zhang, Xinrong

2017-11-01

Mass spectrometry imaging (MSI) has important applications in material research, biology, and medicine. The MSI method based on UV laser desorption/ionization (UVLDI) can obtain images of intact samples, but has a high level of molecular fragmentation. In this work, we report a new MSI instrument that uses a VUV laser (125.3 nm) as a desorption/ionization source to exploit its advantages of high single photon energy and small focus size. The new instrument was tested by the mass spectra of Nile red and FGB (Fibrinogen beta chain) samples and mass spectrometric images of a fly brain section. For the tested samples, the VUVDI method offers lower levels of molecular fragmentations and higher sensitivities than those of the UVLDI method and second ion mass spectrometry imaging method using a Bi 3 + beam. The ablation crater produced by the focused VUV laser on a quartz plate has an area of 10 μm 2 . The VUV laser is prepared based on the four-wave mixing method using three collimated laser beams and a heated Hg cell.

A new instrument of VUV laser desorption/ionization mass spectrometry imaging with micrometer spatial resolution and low level of molecular fragmentation

NASA Astrophysics Data System (ADS)

Wang, Jia; Liu, Feng; Mo, Yuxiang; Wang, Zhaoying; Zhang, Sichun; Zhang, Xinrong

2017-11-01

Mass spectrometry imaging (MSI) has important applications in material research, biology, and medicine. The MSI method based on UV laser desorption/ionization (UVLDI) can obtain images of intact samples, but has a high level of molecular fragmentation. In this work, we report a new MSI instrument that uses a VUV laser (125.3 nm) as a desorption/ionization source to exploit its advantages of high single photon energy and small focus size. The new instrument was tested by the mass spectra of Nile red and FGB (Fibrinogen beta chain) samples and mass spectrometric images of a fly brain section. For the tested samples, the VUVDI method offers lower levels of molecular fragmentations and higher sensitivities than those of the UVLDI method and second ion mass spectrometry imaging method using a Bi3+ beam. The ablation crater produced by the focused VUV laser on a quartz plate has an area of 10 μm2. The VUV laser is prepared based on the four-wave mixing method using three collimated laser beams and a heated Hg cell.

A novel encryption scheme for high-contrast image data in the Fresnelet domain

PubMed Central

Bibi, Nargis; Farwa, Shabieh; Jahngir, Adnan; Usman, Muhammad

2018-01-01

In this paper, a unique and more distinctive encryption algorithm is proposed. This is based on the complexity of highly nonlinear S box in Flesnelet domain. The nonlinear pattern is transformed further to enhance the confusion in the dummy data using Fresnelet technique. The security level of the encrypted image boosts using the algebra of Galois field in Fresnelet domain. At first level, the Fresnelet transform is used to propagate the given information with desired wavelength at specified distance. It decomposes given secret data into four complex subbands. These complex sub-bands are separated into two components of real subband data and imaginary subband data. At second level, the net subband data, produced at the first level, is deteriorated to non-linear diffused pattern using the unique S-box defined on the Galois field F28. In the diffusion process, the permuted image is substituted via dynamic algebraic S-box substitution. We prove through various analysis techniques that the proposed scheme enhances the cipher security level, extensively. PMID:29608609

PIV-DCNN: cascaded deep convolutional neural networks for particle image velocimetry

NASA Astrophysics Data System (ADS)

Lee, Yong; Yang, Hua; Yin, Zhouping

2017-12-01

Velocity estimation (extracting the displacement vector information) from the particle image pairs is of critical importance for particle image velocimetry. This problem is mostly transformed into finding the sub-pixel peak in a correlation map. To address the original displacement extraction problem, we propose a different evaluation scheme (PIV-DCNN) with four-level regression deep convolutional neural networks. At each level, the networks are trained to predict a vector from two input image patches. The low-level network is skilled at large displacement estimation and the high- level networks are devoted to improving the accuracy. Outlier replacement and symmetric window offset operation glue the well- functioning networks in a cascaded manner. Through comparison with the standard PIV methods (one-pass cross-correlation method, three-pass window deformation), the practicability of the proposed PIV-DCNN is verified by the application to a diversity of synthetic and experimental PIV images.

Detecting Edges in Images by Use of Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steve

2003-01-01

A method of processing digital image data to detect edges includes the use of fuzzy reasoning. The method is completely adaptive and does not require any advance knowledge of an image. During initial processing of image data at a low level of abstraction, the nature of the data is indeterminate. Fuzzy reasoning is used in the present method because it affords an ability to construct useful abstractions from approximate, incomplete, and otherwise imperfect sets of data. Humans are able to make some sense of even unfamiliar objects that have imperfect high-level representations. It appears that to perceive unfamiliar objects or to perceive familiar objects in imperfect images, humans apply heuristic algorithms to understand the images

An automated image processing routine for segmentation of cell cytoplasms in high-resolution autofluorescence images

NASA Astrophysics Data System (ADS)

Walsh, Alex J.; Skala, Melissa C.

2014-02-01

The heterogeneity of genotypes and phenotypes within cancers is correlated with disease progression and drug-resistant cellular sub-populations. Therefore, robust techniques capable of probing majority and minority cell populations are important both for cancer diagnostics and therapy monitoring. Herein, we present a modified CellProfiler routine to isolate cytoplasmic fluorescence signal on a single cell level from high resolution auto-fluorescence microscopic images.

Estimation of signal-dependent noise level function in transform domain via a sparse recovery model.

PubMed

Yang, Jingyu; Gan, Ziqiao; Wu, Zhaoyang; Hou, Chunping

2015-05-01

This paper proposes a novel algorithm to estimate the noise level function (NLF) of signal-dependent noise (SDN) from a single image based on the sparse representation of NLFs. Noise level samples are estimated from the high-frequency discrete cosine transform (DCT) coefficients of nonlocal-grouped low-variation image patches. Then, an NLF recovery model based on the sparse representation of NLFs under a trained basis is constructed to recover NLF from the incomplete noise level samples. Confidence levels of the NLF samples are incorporated into the proposed model to promote reliable samples and weaken unreliable ones. We investigate the behavior of the estimation performance with respect to the block size, sampling rate, and confidence weighting. Simulation results on synthetic noisy images show that our method outperforms existing state-of-the-art schemes. The proposed method is evaluated on real noisy images captured by three types of commodity imaging devices, and shows consistently excellent SDN estimation performance. The estimated NLFs are incorporated into two well-known denoising schemes, nonlocal means and BM3D, and show significant improvements in denoising SDN-polluted images.

Pipeline for illumination correction of images for high-throughput microscopy.

PubMed

Singh, S; Bray, M-A; Jones, T R; Carpenter, A E

2014-12-01

The presence of systematic noise in images in high-throughput microscopy experiments can significantly impact the accuracy of downstream results. Among the most common sources of systematic noise is non-homogeneous illumination across the image field. This often adds an unacceptable level of noise, obscures true quantitative differences and precludes biological experiments that rely on accurate fluorescence intensity measurements. In this paper, we seek to quantify the improvement in the quality of high-content screen readouts due to software-based illumination correction. We present a straightforward illumination correction pipeline that has been used by our group across many experiments. We test the pipeline on real-world high-throughput image sets and evaluate the performance of the pipeline at two levels: (a) Z'-factor to evaluate the effect of the image correction on a univariate readout, representative of a typical high-content screen, and (b) classification accuracy on phenotypic signatures derived from the images, representative of an experiment involving more complex data mining. We find that applying the proposed post-hoc correction method improves performance in both experiments, even when illumination correction has already been applied using software associated with the instrument. To facilitate the ready application and future development of illumination correction methods, we have made our complete test data sets as well as open-source image analysis pipelines publicly available. This software-based solution has the potential to improve outcomes for a wide-variety of image-based HTS experiments. © 2014 The Authors. Journal of Microscopy published by John Wiley & Sons Ltd on behalf of Royal Microscopical Society.

Development of ultra-high temperature material characterization capabilities using digital image correlation analysis

NASA Astrophysics Data System (ADS)

Cline, Julia Elaine

2011-12-01

Ultra-high temperature deformation measurements are required to characterize the thermo-mechanical response of material systems for thermal protection systems for aerospace applications. The use of conventional surface-contacting strain measurement techniques is not practical in elevated temperature conditions. Technological advancements in digital imaging provide impetus to measure full-field displacement and determine strain fields with sub-pixel accuracy by image processing. In this work, an Instron electromechanical axial testing machine with a custom-designed high temperature gripping mechanism is used to apply quasi-static tensile loads to graphite specimens heated to 2000°F (1093°C). Specimen heating via Joule effect is achieved and maintained with a custom-designed temperature control system. Images are captured at monotonically increasing load levels throughout the test duration using an 18 megapixel Canon EOS Rebel T2i digital camera with a modified Schneider Kreutznach telecentric lens and a combination of blue light illumination and narrow band-pass filter system. Images are processed using an open-source Matlab-based digital image correlation (DIC) code. Validation of source code is performed using Mathematica generated images with specified known displacement fields in order to gain confidence in accurate software tracking capabilities. Room temperature results are compared with extensometer readings. Ultra-high temperature strain measurements for graphite are obtained at low load levels, demonstrating the potential for non-contacting digital image correlation techniques to accurately determine full-field strain measurements at ultra-high temperature. Recommendations are given to improve the experimental set-up to achieve displacement field measurements accurate to 1/10 pixel and strain field accuracy of less than 2%.

A Global Covariance Descriptor for Nuclear Atypia Scoring in Breast Histopathology Images.

PubMed

Khan, Adnan Mujahid; Sirinukunwattana, Korsuk; Rajpoot, Nasir

2015-09-01

Nuclear atypia scoring is a diagnostic measure commonly used to assess tumor grade of various cancers, including breast cancer. It provides a quantitative measure of deviation in visual appearance of cell nuclei from those in normal epithelial cells. In this paper, we present a novel image-level descriptor for nuclear atypia scoring in breast cancer histopathology images. The method is based on the region covariance descriptor that has recently become a popular method in various computer vision applications. The descriptor in its original form is not suitable for classification of histopathology images as cancerous histopathology images tend to possess diversely heterogeneous regions in a single field of view. Our proposed image-level descriptor, which we term as the geodesic mean of region covariance descriptors, possesses all the attractive properties of covariance descriptors lending itself to tractable geodesic-distance-based k-nearest neighbor classification using efficient kernels. The experimental results suggest that the proposed image descriptor yields high classification accuracy compared to a variety of widely used image-level descriptors.

X-ray imaging using amorphous selenium: a photoinduced discharge readout method for digital mammography.

PubMed

Rowlands, J A; Hunter, D M; Araj, N

1991-01-01

A new digital image readout method for electrostatic charge images on photoconductive plates is described. The method can be used to read out images on selenium plates similar to those used in xeromammography. The readout method, called the air-gap photoinduced discharge method (PID), discharges the latent image pixel by pixel and measures the charge. The PID readout method, like electrometer methods, is linear. However, the PID method permits much better resolution than scanning electrometers while maintaining quantum limited performance at high radiation exposure levels. Thus the air-gap PID method appears to be uniquely superior for high-resolution digital imaging tasks such as mammography.

Robustifying blind image deblurring methods by simple filters

NASA Astrophysics Data System (ADS)

Liu, Yan; Zeng, Xiangrong; Huangpeng, Qizi; Fan, Jun; Zhou, Jinglun; Feng, Jing

2016-07-01

The state-of-the-art blind image deblurring (BID) methods are sensitive to noise, and most of them can deal with only small levels of Gaussian noise. In this paper, we use simple filters to present a robust BID framework which is able to robustify exiting BID methods to high-level Gaussian noise or/and Non-Gaussian noise. Experiments on images in presence of Gaussian noise, impulse noise (salt-and-pepper noise and random-valued noise) and mixed Gaussian-impulse noise, and a real-world blurry and noisy image show that the proposed method can faster estimate sharper kernels and better images, than that obtained by other methods.

Automated Segmentation of High-Resolution Photospheric Images of Active Regions

NASA Astrophysics Data System (ADS)

Yang, Meng; Tian, Yu; Rao, Changhui

2018-02-01

Due to the development of ground-based, large-aperture solar telescopes with adaptive optics (AO) resulting in increasing resolving ability, more accurate sunspot identifications and characterizations are required. In this article, we have developed a set of automated segmentation methods for high-resolution solar photospheric images. Firstly, a local-intensity-clustering level-set method is applied to roughly separate solar granulation and sunspots. Then reinitialization-free level-set evolution is adopted to adjust the boundaries of the photospheric patch; an adaptive intensity threshold is used to discriminate between umbra and penumbra; light bridges are selected according to their regional properties from candidates produced by morphological operations. The proposed method is applied to the solar high-resolution TiO 705.7-nm images taken by the 151-element AO system and Ground-Layer Adaptive Optics prototype system at the 1-m New Vacuum Solar Telescope of the Yunnan Observatory. Experimental results show that the method achieves satisfactory robustness and efficiency with low computational cost on high-resolution images. The method could also be applied to full-disk images, and the calculated sunspot areas correlate well with the data given by the National Oceanic and Atmospheric Administration (NOAA).

Image Statistics and the Representation of Material Properties in the Visual Cortex

PubMed Central

Baumgartner, Elisabeth; Gegenfurtner, Karl R.

2016-01-01

We explored perceived material properties (roughness, texturedness, and hardness) with a novel approach that compares perception, image statistics and brain activation, as measured with fMRI. We initially asked participants to rate 84 material images with respect to the above mentioned properties, and then scanned 15 of the participants with fMRI while they viewed the material images. The images were analyzed with a set of image statistics capturing their spatial frequency and texture properties. Linear classifiers were then applied to the image statistics as well as the voxel patterns of visually responsive voxels and early visual areas to discriminate between images with high and low perceptual ratings. Roughness and texturedness could be classified above chance level based on image statistics. Roughness and texturedness could also be classified based on the brain activation patterns in visual cortex, whereas hardness could not. Importantly, the agreement in classification based on image statistics and brain activation was also above chance level. Our results show that information about visual material properties is to a large degree contained in low-level image statistics, and that these image statistics are also partially reflected in brain activity patterns induced by the perception of material images. PMID:27582714

Image Statistics and the Representation of Material Properties in the Visual Cortex.

PubMed

Baumgartner, Elisabeth; Gegenfurtner, Karl R

2016-01-01

We explored perceived material properties (roughness, texturedness, and hardness) with a novel approach that compares perception, image statistics and brain activation, as measured with fMRI. We initially asked participants to rate 84 material images with respect to the above mentioned properties, and then scanned 15 of the participants with fMRI while they viewed the material images. The images were analyzed with a set of image statistics capturing their spatial frequency and texture properties. Linear classifiers were then applied to the image statistics as well as the voxel patterns of visually responsive voxels and early visual areas to discriminate between images with high and low perceptual ratings. Roughness and texturedness could be classified above chance level based on image statistics. Roughness and texturedness could also be classified based on the brain activation patterns in visual cortex, whereas hardness could not. Importantly, the agreement in classification based on image statistics and brain activation was also above chance level. Our results show that information about visual material properties is to a large degree contained in low-level image statistics, and that these image statistics are also partially reflected in brain activity patterns induced by the perception of material images.

A new kernel-based fuzzy level set method for automated segmentation of medical images in the presence of intensity inhomogeneity.

PubMed

Rastgarpour, Maryam; Shanbehzadeh, Jamshid

2014-01-01

Researchers recently apply an integrative approach to automate medical image segmentation for benefiting available methods and eliminating their disadvantages. Intensity inhomogeneity is a challenging and open problem in this area, which has received less attention by this approach. It has considerable effects on segmentation accuracy. This paper proposes a new kernel-based fuzzy level set algorithm by an integrative approach to deal with this problem. It can directly evolve from the initial level set obtained by Gaussian Kernel-Based Fuzzy C-Means (GKFCM). The controlling parameters of level set evolution are also estimated from the results of GKFCM. Moreover the proposed algorithm is enhanced with locally regularized evolution based on an image model that describes the composition of real-world images, in which intensity inhomogeneity is assumed as a component of an image. Such improvements make level set manipulation easier and lead to more robust segmentation in intensity inhomogeneity. The proposed algorithm has valuable benefits including automation, invariant of intensity inhomogeneity, and high accuracy. Performance evaluation of the proposed algorithm was carried on medical images from different modalities. The results confirm its effectiveness for medical image segmentation.

Evaluation of the impact of the image used in a communication campaign to raise awareness about the effects of alcohol use during pregnancy.

PubMed

Bazzo, Stefania; Battistella, Giuseppe; Riscica, Patrizia; Moino, Giuliana; Marini, Francesco; Geromel, Mariasole; Czerwinsky, Loredana

2012-01-01

To assess the impact of the advertising image used in the health communication campaign 'Mummy Drinks Baby Drinks', aimed to raise awareness about the effects of drinking alcohol during pregnancy in the childbearing-aged population of the Local Health Authority of Treviso (Italy). The image depicted a foetus inside a glass of a local alcoholic drink. A survey using a semi-structured self-reported questionnaire was carried out. The questionnaire was administered to a consecutive series of 690 parents or caregivers who accompanied children aged 0-2 years in the vaccination clinics of the Local Health Unit, during a 30-day period 1 year after the start of the campaign. The questionnaire measured the level of exposure to the image, emotional reactions and awareness of the health messages conveyed by the image. Overall, 84% of the respondents said that they remembered the image. Almost all (93%) recalled the warning message and 53% recalled the health behaviours suggested by the campaign. The image generally seemed to arouse a high emotive impact: 38% indicated distress and 40% liking as a general opinion, while ∼50% expressed distress emotions and 13% were pleasantly affected when reflecting on the feelings evoked. We did not find unequivocal relationships between the level and kind of emotional reactions and the recalling of the health behaviours. The image obtained a high level of visibility. It was effective in spreading the health message conveyed by the campaign, regardless of the level and kind of emotive impact evoked.

Calibrating a hydraulic model using water levels derived from time series high-resolution Radarsat-2 synthetic aperture radar images and elevation data

NASA Astrophysics Data System (ADS)

Trudel, M.; Desrochers, N.; Leconte, R.

2017-12-01

Knowledge of water extent (WE) and level (WL) of rivers is necessary to calibrate and validate hydraulic models and thus to better simulate and forecast floods. Synthetic aperture radar (SAR) has demonstrated its potential for delineating water bodies, as backscattering of water is much lower than that of other natural surfaces. The ability of SAR to obtain information despite cloud cover makes it an interesting tool for temporal monitoring of water bodies. The delineation of WE combined with a high-resolution digital terrain model (DTM) allows extracting WL. However, most research using SAR data to calibrate hydraulic models has been carried out using one or two images. The objectives of this study is to use WL derived from time series high resolution Radarsat-2 SAR images for the calibration of a 1-D hydraulic model (HEC-RAS). Twenty high-resolution (5 m) Radarsat-2 images were acquired over a 40 km reach of the Athabasca River, in northern Alberta, Canada, between 2012 and 2016, covering both low and high flow regimes. A high-resolution (2m) DTM was generated combining information from LIDAR data and bathymetry acquired between 2008 and 2016 by boat surveying. The HEC-RAS model was implemented on the Athabasca River to simulate WL using cross-sections spaced by 100 m. An image histogram thresholding method was applied on each Radarsat-2 image to derive WE. WE were then compared against each cross-section to identify those were the slope of the banks is not too abrupt and therefore amenable to extract WL. 139 observations of WL at different locations along the river reach and with streamflow measurements were used to calibrate the HEC-RAS model. The RMSE between SAR-derived and simulated WL is under 0.35 m. Validation was performed using in situ observations of WL measured in 2008, 2012 and 2016. The RMSE between the simulated water levels calibrated with SAR images and in situ observations is less than 0.20 m. In addition, a critical success index (CSI) was performed to compare the WE simulated by HEC-RAS and that derived from SARs images. The CSI is higher than 0.85 for each date, which means that simulated WE is highly similar to the WE derived from SARs images. Thereby, the results of our analysis indicate that calibration of a hydraulic model can be performed from WL derived from time series of high-resolution SAR images.

A Hybrid Probabilistic Model for Unified Collaborative and Content-Based Image Tagging.

PubMed

Zhou, Ning; Cheung, William K; Qiu, Guoping; Xue, Xiangyang

2011-07-01

The increasing availability of large quantities of user contributed images with labels has provided opportunities to develop automatic tools to tag images to facilitate image search and retrieval. In this paper, we present a novel hybrid probabilistic model (HPM) which integrates low-level image features and high-level user provided tags to automatically tag images. For images without any tags, HPM predicts new tags based solely on the low-level image features. For images with user provided tags, HPM jointly exploits both the image features and the tags in a unified probabilistic framework to recommend additional tags to label the images. The HPM framework makes use of the tag-image association matrix (TIAM). However, since the number of images is usually very large and user-provided tags are diverse, TIAM is very sparse, thus making it difficult to reliably estimate tag-to-tag co-occurrence probabilities. We developed a collaborative filtering method based on nonnegative matrix factorization (NMF) for tackling this data sparsity issue. Also, an L1 norm kernel method is used to estimate the correlations between image features and semantic concepts. The effectiveness of the proposed approach has been evaluated using three databases containing 5,000 images with 371 tags, 31,695 images with 5,587 tags, and 269,648 images with 5,018 tags, respectively.

High-sensitivity, high-speed continuous imaging system

DOEpatents

Watson, Scott A; Bender, III, Howard A

2014-11-18

A continuous imaging system for recording low levels of light typically extending over small distances with high-frame rates and with a large number of frames is described. Photodiode pixels disposed in an array having a chosen geometry, each pixel having a dedicated amplifier, analog-to-digital convertor, and memory, provide parallel operation of the system. When combined with a plurality of scintillators responsive to a selected source of radiation, in a scintillator array, the light from each scintillator being directed to a single corresponding photodiode in close proximity or lens-coupled thereto, embodiments of the present imaging system may provide images of x-ray, gamma ray, proton, and neutron sources with high efficiency.

Cryogenic x-ray diffraction microscopy utilizing high-pressure cryopreservation

NASA Astrophysics Data System (ADS)

Lima, Enju; Chushkin, Yuriy; van der Linden, Peter; Kim, Chae Un; Zontone, Federico; Carpentier, Philippe; Gruner, Sol M.; Pernot, Petra

2014-10-01

We present cryo x-ray diffraction microscopy of high-pressure-cryofixed bacteria and report high-convergence imaging with multiple image reconstructions. Hydrated D. radiodurans cells were cryofixed at 200 MPa pressure into ˜10-μm-thick water layers and their unstained, hydrated cellular environments were imaged by phasing diffraction patterns, reaching sub-30-nm resolutions with hard x-rays. Comparisons were made with conventional ambient-pressure-cryofixed samples, with respect to both coherent small-angle x-ray scattering and the image reconstruction. The results show a correlation between the level of background ice signal and phasing convergence, suggesting that phasing difficulties with frozen-hydrated specimens may be caused by high-background ice scattering.

High Field Small Animal Magnetic Resonance Oncology Studies

PubMed Central

Bokacheva, Louisa; Ackerstaff, Ellen; LeKaye, H. Carl; Zakian, Kristen; Koutcher, Jason A.

2014-01-01

This review focuses on the applications of high magnetic field magnetic resonance imaging (MRI) and spectroscopy (MRS) to cancer studies in small animals. High field MRI can provide information about tumor physiology, the microenvironment, metabolism, vascularity and cellularity. Such studies are invaluable for understanding tumor growth and proliferation, response to treatment and drug development. The MR techniques reviewed here include 1H, 31P, Chemical Exchange Saturation Transfer (CEST) imaging, and hyperpolarized 13C MR spectroscopy as well as diffusion-weighted, Blood Oxygen Level Dependent (BOLD) contrast imaging, and dynamic contrast-enhanced MR imaging. These methods have been proven effective in animal studies and are highly relevant to human clinical studies. PMID:24374985

Research on image complexity evaluation method based on color information

NASA Astrophysics Data System (ADS)

Wang, Hao; Duan, Jin; Han, Xue-hui; Xiao, Bo

2017-11-01

In order to evaluate the complexity of a color image more effectively and find the connection between image complexity and image information, this paper presents a method to compute the complexity of image based on color information.Under the complexity ,the theoretical analysis first divides the complexity from the subjective level, divides into three levels: low complexity, medium complexity and high complexity, and then carries on the image feature extraction, finally establishes the function between the complexity value and the color characteristic model. The experimental results show that this kind of evaluation method can objectively reconstruct the complexity of the image from the image feature research. The experimental results obtained by the method of this paper are in good agreement with the results of human visual perception complexity,Color image complexity has a certain reference value.

Prospective and retrospective high order eddy current mitigation for diffusion weighted echo planar imaging.

PubMed

Xu, Dan; Maier, Joseph K; King, Kevin F; Collick, Bruce D; Wu, Gaohong; Peters, Robert D; Hinks, R Scott

2013-11-01

The proposed method is aimed at reducing eddy current (EC) induced distortion in diffusion weighted echo planar imaging, without the need to perform further image coregistration between diffusion weighted and T2 images. These ECs typically have significant high order spatial components that cannot be compensated by preemphasis. High order ECs are first calibrated at the system level in a protocol independent fashion. The resulting amplitudes and time constants of high order ECs can then be used to calculate imaging protocol specific corrections. A combined prospective and retrospective approach is proposed to apply correction during data acquisition and image reconstruction. Various phantom, brain, body, and whole body diffusion weighted images with and without the proposed method are acquired. Significantly reduced image distortion and misregistration are consistently seen in images with the proposed method compared with images without. The proposed method is a powerful (e.g., effective at 48 cm field of view and 30 cm slice coverage) and flexible (e.g., compatible with other image enhancements and arbitrary scan plane) technique to correct high order ECs induced distortion and misregistration for various diffusion weighted echo planar imaging applications, without the need for further image post processing, protocol dependent prescan, or sacrifice in signal-to-noise ratio. Copyright © 2013 Wiley Periodicals, Inc.

High-speed AFM and the reduction of tip-sample forces

NASA Astrophysics Data System (ADS)

Miles, Mervyn; Sharma, Ravi; Picco, Loren

High-speed DC-mode AFM has been shown to be routinely capable of imaging at video rate, and, if required, at over 1000 frames per second. At sufficiently high tip-sample velocities in ambient conditions, the tip lifts off the sample surface in a superlubricity process which reduces the level of shear forces imposed on the sample by the tip and therefore reduces the potential damage and distortion of the sample being imaged. High-frequency mechanical oscillations, both lateral and vertical, have been reported to reduced the tip-sample frictional forces. We have investigated the effect of combining linear high-speed scanning with these small amplitude high-frequency oscillations with the aim of reducing further the force interaction in high-speed imaging. Examples of this new version of high-speed AFM imaging will be presented for biological samples.

Preparation of Ultracold Atom Clouds at the Shot Noise Level.

PubMed

Gajdacz, M; Hilliard, A J; Kristensen, M A; Pedersen, P L; Klempt, C; Arlt, J J; Sherson, J F

2016-08-12

We prepare number stabilized ultracold atom clouds through the real-time analysis of nondestructive images and the application of feedback. In our experiments, the atom number N∼10^{6} is determined by high precision Faraday imaging with uncertainty ΔN below the shot noise level, i.e., ΔN

Inventory and monitoring of natural vegetation and related resources in an arid environment: A comprehensive evaluation of ERTS-1 imagery. [Arizona

NASA Technical Reports Server (NTRS)

Schrumpf, B. J. (Principal Investigator); Johnson, J. R.; Mouat, D. A.; Pyott, W. T.

1974-01-01

The author has identified the following significant results. A vegetation classification, with 31 types and compatible with remote sensing applications, was developed for the test site. Terrain features can be used to discriminate vegetation types. Elevation and macrorelief interpretations were successful on ERTS photos, although for macrorelief, high sun angle stereoscopic interpretations were better than low sun angle monoscopic interpretations. Using spectral reflectivity, several vegetation types were characterized in terms of patterns of signature change. ERTS MSS digital data were used to discriminate vegetation classes at the association level and at the alliance level when image contrasts were high or low, respectively. An imagery comparison technique was developed to test image complexity and image groupability. In two stage sampling of vegetation types, ERTS plus high altitude photos were highly satisfactory for estimating kind and extent of types present, and for providing a mapping base.

Quantification of chromatin condensation level by image processing.

PubMed

Irianto, Jerome; Lee, David A; Knight, Martin M

2014-03-01

The level of chromatin condensation is related to the silencing/activation of chromosomal territories and therefore impacts on gene expression. Chromatin condensation changes during cell cycle, progression and differentiation, and is influenced by various physicochemical and epigenetic factors. This study describes a validated experimental technique to quantify chromatin condensation. A novel image processing procedure is developed using Sobel edge detection to quantify the level of chromatin condensation from nuclei images taken by confocal microscopy. The algorithm was developed in MATLAB and used to quantify different levels of chromatin condensation in chondrocyte nuclei achieved through alteration in osmotic pressure. The resulting chromatin condensation parameter (CCP) is in good agreement with independent multi-observer qualitative visual assessment. This image processing technique thereby provides a validated unbiased parameter for rapid and highly reproducible quantification of the level of chromatin condensation. Copyright © 2013 IPEM. Published by Elsevier Ltd. All rights reserved.

Use of a highly sensitive two-dimensional luminescence imaging system to monitor endogenous bioluminescence in plant leaves

PubMed Central

Flor-Henry, Michel; McCabe, Tulene C; de Bruxelles, Guy L; Roberts, Michael R

2004-01-01

Background All living organisms emit spontaneous low-level bioluminescence, which can be increased in response to stress. Methods for imaging this ultra-weak luminescence have previously been limited by the sensitivity of the detection systems used. Results We developed a novel configuration of a cooled charge-coupled device (CCD) for 2-dimensional imaging of light emission from biological material. In this study, we imaged photon emission from plant leaves. The equipment allowed short integration times for image acquisition, providing high resolution spatial and temporal information on bioluminescence. We were able to carry out time course imaging of both delayed chlorophyll fluorescence from whole leaves, and of low level wound-induced luminescence that we showed to be localised to sites of tissue damage. We found that wound-induced luminescence was chlorophyll-dependent and was enhanced at higher temperatures. Conclusions The data gathered on plant bioluminescence illustrate that the equipment described here represents an improvement in 2-dimensional luminescence imaging technology. Using this system, we identify chlorophyll as the origin of wound-induced luminescence from leaves. PMID:15550176

Geographical topic learning for social images with a deep neural network

NASA Astrophysics Data System (ADS)

Feng, Jiangfan; Xu, Xin

2017-03-01

The use of geographical tagging in social-media images is becoming a part of image metadata and a great interest for geographical information science. It is well recognized that geographical topic learning is crucial for geographical annotation. Existing methods usually exploit geographical characteristics using image preprocessing, pixel-based classification, and feature recognition. How to effectively exploit the high-level semantic feature and underlying correlation among different types of contents is a crucial task for geographical topic learning. Deep learning (DL) has recently demonstrated robust capabilities for image tagging and has been introduced into geoscience. It extracts high-level features computed from a whole image component, where the cluttered background may dominate spatial features in the deep representation. Therefore, a method of spatial-attentional DL for geographical topic learning is provided and we can regard it as a special case of DL combined with various deep networks and tuning tricks. Results demonstrated that the method is discriminative for different types of geographical topic learning. In addition, it outperforms other sequential processing models in a tagging task for a geographical image dataset.

MR pyelography and conventional MR imaging in urinary tract obstruction.

PubMed

Catalano, C; Pavone, P; Laghi, A; Scipioni, A; Panebianco, V; Brillo, R; Fraioli, F; Passariello, R

1999-03-01

To evaluate the possible role of MR imaging in the assessment of patients with urinary tract obstruction by combining conventional MR imaging and MR pyelography (MRP). Forty-three patients with dilated upper urinary tract were studied with a high gradient strength 0.5 T magnet. Respiratory compensated T1-weighted, SE and T2-weighted TSE sequences were acquired in all patients. MRP images were obtained by using a respiratory compensated 3D T2-weighted TSE sequence. MRP images were reconstructed with a MIP algorithm. In all cases, urography and/or ascending pyelography were also performed. Images were independently evaluated by two radiologists. The dilated tract ureter and the level of the obstruction could be correctly demonstrated in all cases. The cause of the obstruction was correctly demonstrated by examiner 1 in 90% and by examiner 2 in 88%. The interobserver agreement was high with a kappa-value of 0.96. In cases of obstructive hydroureteronephrosis MR imaging, combining MRP and conventional sequences, can be proposed as an accurate technique in the assessment of level and cause of obstruction.

Enhanced Beetle Luciferase for High-Resolution Bioluminescence Imaging

PubMed Central

Nakajima, Yoshihiro; Yamazaki, Tomomi; Nishii, Shigeaki; Noguchi, Takako; Hoshino, Hideto; Niwa, Kazuki; Viviani, Vadim R.; Ohmiya, Yoshihiro

2010-01-01

We developed an enhanced green-emitting luciferase (ELuc) to be used as a bioluminescence imaging (BLI) probe. ELuc exhibits a light signal in mammalian cells that is over 10-fold stronger than that of the firefly luciferase (FLuc), which is the most widely used luciferase reporter gene. We showed that ELuc produces a strong light signal in primary cells and tissues and that it enables the visualization of gene expression with high temporal resolution at the single-cell level. Moreover, we successfully imaged the nucleocytoplasmic shuttling of importin α by fusing ELuc at the intracellular level. These results demonstrate that the use of ELuc allows a BLI spatiotemporal resolution far greater than that provided by FLuc. PMID:20368807

Cat-Eyed Saturn

NASA Image and Video Library

2006-04-13

Bright, high altitude clouds, like those imaged here, often appear more filamentary or streak-like than clouds imaged at slightly deeper levels in Saturn atmosphere. This view also shows one of the many cat eye vortices.

On combining image-based and ontological semantic dissimilarities for medical image retrieval applications

PubMed Central

Kurtz, Camille; Depeursinge, Adrien; Napel, Sandy; Beaulieu, Christopher F.; Rubin, Daniel L.

2014-01-01

Computer-assisted image retrieval applications can assist radiologists by identifying similar images in archives as a means to providing decision support. In the classical case, images are described using low-level features extracted from their contents, and an appropriate distance is used to find the best matches in the feature space. However, using low-level image features to fully capture the visual appearance of diseases is challenging and the semantic gap between these features and the high-level visual concepts in radiology may impair the system performance. To deal with this issue, the use of semantic terms to provide high-level descriptions of radiological image contents has recently been advocated. Nevertheless, most of the existing semantic image retrieval strategies are limited by two factors: they require manual annotation of the images using semantic terms and they ignore the intrinsic visual and semantic relationships between these annotations during the comparison of the images. Based on these considerations, we propose an image retrieval framework based on semantic features that relies on two main strategies: (1) automatic “soft” prediction of ontological terms that describe the image contents from multi-scale Riesz wavelets and (2) retrieval of similar images by evaluating the similarity between their annotations using a new term dissimilarity measure, which takes into account both image-based and ontological term relations. The combination of these strategies provides a means of accurately retrieving similar images in databases based on image annotations and can be considered as a potential solution to the semantic gap problem. We validated this approach in the context of the retrieval of liver lesions from computed tomographic (CT) images and annotated with semantic terms of the RadLex ontology. The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs of images on a 25-images dataset, and evaluation relative to the diagnoses of the retrieved images on a 72-images dataset. A normalized discounted cumulative gain (NDCG) score of more than 0.92 was obtained with the first protocol, while AUC scores of more than 0.77 were obtained with the second protocol. This automatical approach could provide real-time decision support to radiologists by showing them similar images with associated diagnoses and, where available, responses to therapies. PMID:25036769

Color image definition evaluation method based on deep learning method

NASA Astrophysics Data System (ADS)

Liu, Di; Li, YingChun

2018-01-01

In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

Influence of spherical aberration, stimulus spatial frequency, and pupil apodisation on subjective refractions

PubMed Central

Bradley, Arthur; Xu, Renfeng; Thibos, Larry; Marin, Gildas; Hernandez, Martha

2014-01-01

Purpose To test competing hypotheses (Stiles Crawford pupil apodising or superior imaging of high spatial frequencies by the central pupil) for the pupil size independence of subjective refractions in the presence of primary spherical aberration. Methods Subjective refractions were obtained with a variety of test stimuli (high contrast letters, urban cityscape, high and low spatial frequency gratings) while modulating pupil diameter, levels of primary spherical aberration and pupil apodisation. Subjective refractions were also obtained with low-pass and high-pass stimuli and using “darker” and “sharper” subjective criteria. Results Subjective refractions for stimuli containing high spatial frequencies focus a near paraxial region of the pupil and are affected only slightly by level of Seidel spherical aberration, degree of pupil apodisation and pupil diameter, and generally focused a radius of about 1 to 1.5 mm from the pupil centre. Low spatial frequency refractions focus a marginal region of the pupil, and are significantly affected by level of spherical aberration, amount of pupil apodisation, and pupil size. Clinical refractions that employ the “darker” or “sharper” subjective criteria bias the patient to use lower or higher spatial frequencies respectively. Conclusions In the presence of significant levels of spherical aberration, the pupil size independence of subjective refractions occurs with or without Stiles Crawford apodisation for refractions that optimise high spatial frequency content in the image. If low spatial frequencies are optimised by a subjective refraction, spherical refractive error varies with spherical aberration, pupil size, and level of apodisation. As light levels drop from photopic to scotopic, therefore, we expect a shift from pupil size independent to pupil size dependent subjective refractions. Emphasising a “sharper” criterion during subjective refractions will improve image quality for high spatial frequencies and generate pupil size independent refractions. PMID:24397356

Research-grade CMOS image sensors for demanding space applications

NASA Astrophysics Data System (ADS)

Saint-Pé, Olivier; Tulet, Michel; Davancens, Robert; Larnaudie, Franck; Magnan, Pierre; Corbière, Franck; Martin-Gonthier, Philippe; Belliot, Pierre

2004-06-01

Imaging detectors are key elements for optical instruments and sensors on board space missions dedicated to Earth observation (high resolution imaging, atmosphere spectroscopy...), Solar System exploration (micro cameras, guidance for autonomous vehicle...) and Universe observation (space telescope focal planes, guiding sensors...). This market has been dominated by CCD technology for long. Since the mid-90s, CMOS Image Sensors (CIS) have been competing with CCDs for more and more consumer domains (webcams, cell phones, digital cameras...). Featuring significant advantages over CCD sensors for space applications (lower power consumption, smaller system size, better radiations behaviour...), CMOS technology is also expanding in this field, justifying specific R&D and development programs funded by national and European space agencies (mainly CNES, DGA, and ESA). All along the 90s and thanks to their increasingly improving performances, CIS have started to be successfully used for more and more demanding applications, from vision and control functions requiring low-level performances to guidance applications requiring medium-level performances. Recent technology improvements have made possible the manufacturing of research-grade CIS that are able to compete with CCDs in the high-performances arena. After an introduction outlining the growing interest of optical instruments designers for CMOS image sensors, this talk will present the existing and foreseen ways to reach high-level electro-optics performances for CIS. The developments of CIS prototypes built using an imaging CMOS process and of devices based on improved designs will be presented.

Research-grade CMOS image sensors for demanding space applications

NASA Astrophysics Data System (ADS)

Saint-Pé, Olivier; Tulet, Michel; Davancens, Robert; Larnaudie, Franck; Magnan, Pierre; Corbière, Franck; Martin-Gonthier, Philippe; Belliot, Pierre

2017-11-01

Imaging detectors are key elements for optical instruments and sensors on board space missions dedicated to Earth observation (high resolution imaging, atmosphere spectroscopy...), Solar System exploration (micro cameras, guidance for autonomous vehicle...) and Universe observation (space telescope focal planes, guiding sensors...). This market has been dominated by CCD technology for long. Since the mid- 90s, CMOS Image Sensors (CIS) have been competing with CCDs for more and more consumer domains (webcams, cell phones, digital cameras...). Featuring significant advantages over CCD sensors for space applications (lower power consumption, smaller system size, better radiations behaviour...), CMOS technology is also expanding in this field, justifying specific R&D and development programs funded by national and European space agencies (mainly CNES, DGA, and ESA). All along the 90s and thanks to their increasingly improving performances, CIS have started to be successfully used for more and more demanding applications, from vision and control functions requiring low-level performances to guidance applications requiring medium-level performances. Recent technology improvements have made possible the manufacturing of research-grade CIS that are able to compete with CCDs in the high-performances arena. After an introduction outlining the growing interest of optical instruments designers for CMOS image sensors, this talk will present the existing and foreseen ways to reach high-level electro-optics performances for CIS. The developments of CIS prototypes built using an imaging CMOS process and of devices based on improved designs will be presented.

[Fractional vegetation cover of invasive Spartina alterniflora in coastal wetland using unmanned aerial vehicle (UAV)remote sensing].

PubMed

Zhou, Zai Ming; Yang, Yan Ming; Chen, Ben Qing

2016-12-01

The effective management and utilization of resources and ecological environment of coastal wetland require investigation and analysis in high precision of the fractional vegetation cover of invasive species Spartina alterniflora. In this study, Sansha Bay was selected as the experimental region, and visible and multi-spectral images obtained by low-altitude UAV in the region were used to monitor the fractional vegetation cover of S. alterniflora. Fractional vegetation cover parameters in the multi-spectral images were then estimated by NDVI index model, and the accuracy was tested against visible images as references. Results showed that vegetation covers of S. alterniflora in the image area were mainly at medium high level (40%-60%) and high level (60%-80%). Root mean square error (RMSE) between the NDVI model estimation values and true values was 0.06, while the determination coefficient R 2 was 0.92, indicating a good consistency between the estimation value and the true value.

High-polarization-discriminating infrared detection using a single quantum well sandwiched in plasmonic micro-cavity.

PubMed

Li, Qian; Li, ZhiFeng; Li, Ning; Chen, XiaoShuang; Chen, PingPing; Shen, XueChu; Lu, Wei

2014-09-11

Polarimetric imaging has proved its value in medical diagnostics, bionics, remote sensing, astronomy, and in many other wide fields. Pixel-level solid monolithically integrated polarimetric imaging photo-detectors are the trend for infrared polarimetric imaging devices. For better polarimetric imaging performance the high polarization discriminating detectors are very much critical. Here we demonstrate the high infrared light polarization resolving capabilities of a quantum well (QW) detector in hybrid structure of single QW and plasmonic micro-cavity that uses QW as an active structure in the near field regime of plasmonic effect enhanced cavity, in which the photoelectric conversion in such a plasmonic micro-cavity has been realized. The detector's extinction ratio reaches 65 at the wavelength of 14.7 μm, about 6 times enhanced in such a type of pixel-level polarization long wave infrared photodetectors. The enhancement mechanism is attributed to artificial plasmonic modulation on optical propagation and distribution in the plasmonic micro-cavities.

High-Polarization-Discriminating Infrared Detection Using a Single Quantum Well Sandwiched in Plasmonic Micro-Cavity

PubMed Central

Li, Qian; Li, ZhiFeng; Li, Ning; Chen, XiaoShuang; Chen, PingPing; Shen, XueChu; Lu, Wei

2014-01-01

Polarimetric imaging has proved its value in medical diagnostics, bionics, remote sensing, astronomy, and in many other wide fields. Pixel-level solid monolithically integrated polarimetric imaging photo-detectors are the trend for infrared polarimetric imaging devices. For better polarimetric imaging performance the high polarization discriminating detectors are very much critical. Here we demonstrate the high infrared light polarization resolving capabilities of a quantum well (QW) detector in hybrid structure of single QW and plasmonic micro-cavity that uses QW as an active structure in the near field regime of plasmonic effect enhanced cavity, in which the photoelectric conversion in such a plasmonic micro-cavity has been realized. The detector's extinction ratio reaches 65 at the wavelength of 14.7 μm, about 6 times enhanced in such a type of pixel-level polarization long wave infrared photodetectors. The enhancement mechanism is attributed to artificial plasmonic modulation on optical propagation and distribution in the plasmonic micro-cavities. PMID:25208580

Scanning Probe Platform | Materials Science | NREL

Science.gov Websites

level; this image obtained using a scanning tunneling microscope shows gray and white clusters of produce high-resolution color images or maps like this one obtained using scanning tunneling luminescence gray clusters. Gold substrate: (Left) STM image reveals the terraces of the H2 flamed substrate. (Right

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

NASA Astrophysics Data System (ADS)

Lv, Xiupin; Liao, Xiaofeng; Yang, Bo

2018-04-01

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

Diderot: a Domain-Specific Language for Portable Parallel Scientific Visualization and Image Analysis.

PubMed

Kindlmann, Gordon; Chiw, Charisee; Seltzer, Nicholas; Samuels, Lamont; Reppy, John

2016-01-01

Many algorithms for scientific visualization and image analysis are rooted in the world of continuous scalar, vector, and tensor fields, but are programmed in low-level languages and libraries that obscure their mathematical foundations. Diderot is a parallel domain-specific language that is designed to bridge this semantic gap by providing the programmer with a high-level, mathematical programming notation that allows direct expression of mathematical concepts in code. Furthermore, Diderot provides parallel performance that takes advantage of modern multicore processors and GPUs. The high-level notation allows a concise and natural expression of the algorithms and the parallelism allows efficient execution on real-world datasets.

Image segmentation via foreground and background semantic descriptors

NASA Astrophysics Data System (ADS)

Yuan, Ding; Qiang, Jingjing; Yin, Jihao

2017-09-01

In the field of image processing, it has been a challenging task to obtain a complete foreground that is not uniform in color or texture. Unlike other methods, which segment the image by only using low-level features, we present a segmentation framework, in which high-level visual features, such as semantic information, are used. First, the initial semantic labels were obtained by using the nonparametric method. Then, a subset of the training images, with a similar foreground to the input image, was selected. Consequently, the semantic labels could be further refined according to the subset. Finally, the input image was segmented by integrating the object affinity and refined semantic labels. State-of-the-art performance was achieved in experiments with the challenging MSRC 21 dataset.

Do we understand high-level vision?

PubMed

Cox, David Daniel

2014-04-01

'High-level' vision lacks a single, agreed upon definition, but it might usefully be defined as those stages of visual processing that transition from analyzing local image structure to analyzing structure of the external world that produced those images. Much work in the last several decades has focused on object recognition as a framing problem for the study of high-level visual cortex, and much progress has been made in this direction. This approach presumes that the operational goal of the visual system is to read-out the identity of an object (or objects) in a scene, in spite of variation in the position, size, lighting and the presence of other nearby objects. However, while object recognition as a operational framing of high-level is intuitive appealing, it is by no means the only task that visual cortex might do, and the study of object recognition is beset by challenges in building stimulus sets that adequately sample the infinite space of possible stimuli. Here I review the successes and limitations of this work, and ask whether we should reframe our approaches to understanding high-level vision. Copyright © 2014. Published by Elsevier Ltd.

FDR-controlled metabolite annotation for high-resolution imaging mass spectrometry.

PubMed

Palmer, Andrew; Phapale, Prasad; Chernyavsky, Ilya; Lavigne, Regis; Fay, Dominik; Tarasov, Artem; Kovalev, Vitaly; Fuchser, Jens; Nikolenko, Sergey; Pineau, Charles; Becker, Michael; Alexandrov, Theodore

2017-01-01

High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry (https://github.com/alexandrovteam/pySM). We introduce a metabolite-signal match score and a target-decoy FDR estimate for spatial metabolomics.

High-Resolution X-Ray Telescopes

NASA Technical Reports Server (NTRS)

ODell, Stephen L.; Brissenden, Roger J.; Davis, William; Elsner, Ronald F.; Elvis, Martin; Freeman, Mark; Gaetz, Terry; Gorenstein, Paul; Gubarev, Mikhail V.

2010-01-01

Fundamental needs for future x-ray telescopes: a) Sharp images => excellent angular resolution. b) High throughput => large aperture areas. Generation-X optics technical challenges: a) High resolution => precision mirrors & alignment. b) Large apertures => lots of lightweight mirrors. Innovation needed for technical readiness: a) 4 top-level error terms contribute to image size. b) There are approaches to controlling those errors. Innovation needed for manufacturing readiness. Programmatic issues are comparably challenging.

Image matching as a data source for forest inventory - Comparison of Semi-Global Matching and Next-Generation Automatic Terrain Extraction algorithms in a typical managed boreal forest environment

NASA Astrophysics Data System (ADS)

Kukkonen, M.; Maltamo, M.; Packalen, P.

2017-08-01

Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant.

High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

NASA Astrophysics Data System (ADS)

Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

2018-04-01

With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

High-energy proton imaging for biomedical applications

DOE PAGES

Prall, Matthias; Durante, Marco; Berger, Thomas; ...

2016-06-10

The charged particle community is looking for techniques exploiting proton interactions instead of X-ray absorption for creating images of human tissue. Due to multiple Coulomb scattering inside the measured object it has shown to be highly non-trivial to achieve sufficient spatial resolution. We present imaging of biological tissue with a proton microscope. This device relies on magnetic optics, distinguishing it from most published proton imaging methods. For these methods reducing the data acquisition time to a clinically acceptable level has turned out to be challenging. In a proton microscope, data acquisition and processing are much simpler. This device even allowsmore » imaging in real time. The primary medical application will be image guidance in proton radiosurgery. Proton images demonstrating the potential for this application are presented. As a result, tomographic reconstructions are included to raise awareness of the possibility of high-resolution proton tomography using magneto-optics.« less

High-energy proton imaging for biomedical applications

NASA Astrophysics Data System (ADS)

Prall, M.; Durante, M.; Berger, T.; Przybyla, B.; Graeff, C.; Lang, P. M.; Latessa, C.; Shestov, L.; Simoniello, P.; Danly, C.; Mariam, F.; Merrill, F.; Nedrow, P.; Wilde, C.; Varentsov, D.

2016-06-01

The charged particle community is looking for techniques exploiting proton interactions instead of X-ray absorption for creating images of human tissue. Due to multiple Coulomb scattering inside the measured object it has shown to be highly non-trivial to achieve sufficient spatial resolution. We present imaging of biological tissue with a proton microscope. This device relies on magnetic optics, distinguishing it from most published proton imaging methods. For these methods reducing the data acquisition time to a clinically acceptable level has turned out to be challenging. In a proton microscope, data acquisition and processing are much simpler. This device even allows imaging in real time. The primary medical application will be image guidance in proton radiosurgery. Proton images demonstrating the potential for this application are presented. Tomographic reconstructions are included to raise awareness of the possibility of high-resolution proton tomography using magneto-optics.

High-energy proton imaging for biomedical applications

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

Prall, Matthias; Durante, Marco; Berger, Thomas

The charged particle community is looking for techniques exploiting proton interactions instead of X-ray absorption for creating images of human tissue. Due to multiple Coulomb scattering inside the measured object it has shown to be highly non-trivial to achieve sufficient spatial resolution. We present imaging of biological tissue with a proton microscope. This device relies on magnetic optics, distinguishing it from most published proton imaging methods. For these methods reducing the data acquisition time to a clinically acceptable level has turned out to be challenging. In a proton microscope, data acquisition and processing are much simpler. This device even allowsmore » imaging in real time. The primary medical application will be image guidance in proton radiosurgery. Proton images demonstrating the potential for this application are presented. As a result, tomographic reconstructions are included to raise awareness of the possibility of high-resolution proton tomography using magneto-optics.« less

Evaluation of the radiolabeled boronic acid-based FAP inhibitor MIP-1232 for atherosclerotic plaque imaging.

PubMed

Meletta, Romana; Müller Herde, Adrienne; Chiotellis, Aristeidis; Isa, Malsor; Rancic, Zoran; Borel, Nicole; Ametamey, Simon M; Krämer, Stefanie D; Schibli, Roger

2015-01-27

Research towards the non-invasive imaging of atherosclerotic plaques is of high clinical priority as early recognition of vulnerable plaques may reduce the incidence of cardiovascular events. The fibroblast activation protein alpha (FAP) was recently proposed as inflammation-induced protease involved in the process of plaque vulnerability. In this study, FAP mRNA and protein levels were investigated by quantitative polymerase chain reaction and immunohistochemistry, respectively, in human endarterectomized carotid plaques. A published boronic-acid based FAP inhibitor, MIP-1232, was synthetized and radiolabeled with iodine-125. The potential of this radiotracer to image plaques was evaluated by in vitro autoradiography with human carotid plaques. Specificity was assessed with a xenograft with high and one with low FAP level, grown in mice. Target expression analyses revealed a moderately higher protein level in atherosclerotic plaques than normal arteries correlating with plaque vulnerability. No difference in expression was determined on mRNA level. The radiotracer was successfully produced and accumulated strongly in the FAP-positive SK-Mel-187 melanoma xenograft in vitro while accumulation was negligible in an NCI-H69 xenograft with low FAP levels. Binding of the tracer to endarterectomized tissue was similar in plaques and normal arteries, hampering its use for atherosclerosis imaging.

Adapting to blur produced by ocular high-order aberrations

PubMed Central

Sawides, Lucie; de Gracia, Pablo; Dorronsoro, Carlos; Webster, Michael; Marcos, Susana

2011-01-01

The perceived focus of an image can be strongly biased by prior adaptation to a blurred or sharpened image. We examined whether these adaptation effects can occur for the natural patterns of retinal image blur produced by high-order aberrations (HOAs) in the optics of the eye. Focus judgments were measured for 4 subjects to estimate in a forced choice procedure (sharp/blurred) their neutral point after adaptation to different levels of blur produced by scaled increases or decreases in their HOAs. The optical blur was simulated by convolution of the PSFs from the 4 different HOA patterns, with Zernike coefficients (excluding tilt, defocus, and astigmatism) multiplied by a factor between 0 (diffraction limited) and 2 (double amount of natural blur). Observers viewed the images through an Adaptive Optics system that corrected their aberrations and made settings under neutral adaptation to a gray field or after adapting to 5 different blur levels. All subjects adapted to changes in the level of blur imposed by HOA regardless of which observer’s HOA was used to generate the stimuli, with the perceived neutral point proportional to the amount of blur in the adapting image. PMID:21712375

Adapting to blur produced by ocular high-order aberrations.

PubMed

Sawides, Lucie; de Gracia, Pablo; Dorronsoro, Carlos; Webster, Michael; Marcos, Susana

2011-06-28

The perceived focus of an image can be strongly biased by prior adaptation to a blurred or sharpened image. We examined whether these adaptation effects can occur for the natural patterns of retinal image blur produced by high-order aberrations (HOAs) in the optics of the eye. Focus judgments were measured for 4 subjects to estimate in a forced choice procedure (sharp/blurred) their neutral point after adaptation to different levels of blur produced by scaled increases or decreases in their HOAs. The optical blur was simulated by convolution of the PSFs from the 4 different HOA patterns, with Zernike coefficients (excluding tilt, defocus, and astigmatism) multiplied by a factor between 0 (diffraction limited) and 2 (double amount of natural blur). Observers viewed the images through an Adaptive Optics system that corrected their aberrations and made settings under neutral adaptation to a gray field or after adapting to 5 different blur levels. All subjects adapted to changes in the level of blur imposed by HOA regardless of which observer's HOA was used to generate the stimuli, with the perceived neutral point proportional to the amount of blur in the adapting image.

Automated Adaptive Brightness in Wireless Capsule Endoscopy Using Image Segmentation and Sigmoid Function.

PubMed

Shrestha, Ravi; Mohammed, Shahed K; Hasan, Md Mehedi; Zhang, Xuechao; Wahid, Khan A

2016-08-01

Wireless capsule endoscopy (WCE) plays an important role in the diagnosis of gastrointestinal (GI) diseases by capturing images of human small intestine. Accurate diagnosis of endoscopic images depends heavily on the quality of captured images. Along with image and frame rate, brightness of the image is an important parameter that influences the image quality which leads to the design of an efficient illumination system. Such design involves the choice and placement of proper light source and its ability to illuminate GI surface with proper brightness. Light emitting diodes (LEDs) are normally used as sources where modulated pulses are used to control LED's brightness. In practice, instances like under- and over-illumination are very common in WCE, where the former provides dark images and the later provides bright images with high power consumption. In this paper, we propose a low-power and efficient illumination system that is based on an automated brightness algorithm. The scheme is adaptive in nature, i.e., the brightness level is controlled automatically in real-time while the images are being captured. The captured images are segmented into four equal regions and the brightness level of each region is calculated. Then an adaptive sigmoid function is used to find the optimized brightness level and accordingly a new value of duty cycle of the modulated pulse is generated to capture future images. The algorithm is fully implemented in a capsule prototype and tested with endoscopic images. Commercial capsules like Pillcam and Mirocam were also used in the experiment. The results show that the proposed algorithm works well in controlling the brightness level accordingly to the environmental condition, and as a result, good quality images are captured with an average of 40% brightness level that saves power consumption of the capsule.

A 256×256 low-light-level CMOS imaging sensor with digital CDS

NASA Astrophysics Data System (ADS)

Zou, Mei; Chen, Nan; Zhong, Shengyou; Li, Zhengfen; Zhang, Jicun; Yao, Li-bin

2016-10-01

In order to achieve high sensitivity for low-light-level CMOS image sensors (CIS), a capacitive transimpedance amplifier (CTIA) pixel circuit with a small integration capacitor is used. As the pixel and the column area are highly constrained, it is difficult to achieve analog correlated double sampling (CDS) to remove the noise for low-light-level CIS. So a digital CDS is adopted, which realizes the subtraction algorithm between the reset signal and pixel signal off-chip. The pixel reset noise and part of the column fixed-pattern noise (FPN) can be greatly reduced. A 256×256 CIS with CTIA array and digital CDS is implemented in the 0.35μm CMOS technology. The chip size is 7.7mm×6.75mm, and the pixel size is 15μm×15μm with a fill factor of 20.6%. The measured pixel noise is 24LSB with digital CDS in RMS value at dark condition, which shows 7.8× reduction compared to the image sensor without digital CDS. Running at 7fps, this low-light-level CIS can capture recognizable images with the illumination down to 0.1lux.

A ganglion-cell-based primary image representation method and its contribution to object recognition

NASA Astrophysics Data System (ADS)

Wei, Hui; Dai, Zhi-Long; Zuo, Qing-Song

2016-10-01

A visual stimulus is represented by the biological visual system at several levels: in the order from low to high levels, they are: photoreceptor cells, ganglion cells (GCs), lateral geniculate nucleus cells and visual cortical neurons. Retinal GCs at the early level need to represent raw data only once, but meet a wide number of diverse requests from different vision-based tasks. This means the information representation at this level is general and not task-specific. Neurobiological findings have attributed this universal adaptation to GCs' receptive field (RF) mechanisms. For the purposes of developing a highly efficient image representation method that can facilitate information processing and interpretation at later stages, here we design a computational model to simulate the GC's non-classical RF. This new image presentation method can extract major structural features from raw data, and is consistent with other statistical measures of the image. Based on the new representation, the performances of other state-of-the-art algorithms in contour detection and segmentation can be upgraded remarkably. This work concludes that applying sophisticated representation schema at early state is an efficient and promising strategy in visual information processing.

Rapid Disaster Damage Estimation

NASA Astrophysics Data System (ADS)

Vu, T. T.

2012-07-01

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

Mediaprocessors in medical imaging for high performance and flexibility

NASA Astrophysics Data System (ADS)

Managuli, Ravi; Kim, Yongmin

2002-05-01

New high performance programmable processors, called mediaprocessors, have been emerging since the early 1990s for various digital media applications, such as digital TV, set-top boxes, desktop video conferencing, and digital camcorders. Modern mediaprocessors, e.g., TI's TMS320C64x and Hitachi/Equator Technologies MAP-CA, can offer high performance utilizing both instruction-level and data-level parallelism. During this decade, with continued performance improvement and cost reduction, we believe that the mediaprocessors will become a preferred choice in designing imaging and video systems due to their flexibility in incorporating new algorithms and applications via programming and faster-time-to-market. In this paper, we will evaluate the suitability of these mediaprocessors in medical imaging. We will review the core routines of several medical imaging modalities, such as ultrasound and DR, and present how these routines can be mapped to mediaprocessors and their resultant performance. We will analyze the architecture of several leading mediaprocessors. By carefully mapping key imaging routines, such as 2D convolution, unsharp masking, and 2D FFT, to the mediaprocessor, we have been able to achieve comparable (if not better) performance to that of traditional hardwired approaches. Thus, we believe that future medical imaging systems will benefit greatly from these advanced mediaprocessors, offering significantly increased flexibility and adaptability, reducing the time-to-market, and improving the cost/performance ratio compared to the existing systems while meeting the high computing requirements.

Understanding bone responses in B-mode ultrasound images and automatic bone surface extraction using a Bayesian probabilistic framework

NASA Astrophysics Data System (ADS)

Jain, Ameet K.; Taylor, Russell H.

2004-04-01

The registration of preoperative CT to intra-operative reality systems is a crucial step in Computer Assisted Orthopedic Surgery (CAOS). The intra-operative sensors include 3D digitizers, fiducials, X-rays and Ultrasound (US). Although US has many advantages over others, tracked US for Orthopedic Surgery has been researched by only a few authors. An important factor limiting the accuracy of tracked US to CT registration (1-3mm) has been the difficulty in determining the exact location of the bone surfaces in the US images (the response could range from 2-4mm). Thus it is crucial to localize the bone surface accurately from these images. Moreover conventional US imaging systems are known to have certain inherent inaccuracies, mainly due to the fact that the imaging model is assumed planar. This creates the need to develop a bone segmentation framework that can couple information from various post-processed spatially separated US images (of the bone) to enhance the localization of the bone surface. In this paper we discuss the various reasons that cause inherent uncertainties in the bone surface localization (in B-mode US images) and suggest methods to account for these. We also develop a method for automatic bone surface detection. To do so, we account objectively for the high-level understanding of the various bone surface features visible in typical US images. A combination of these features would finally decide the surface position. We use a Bayesian probabilistic framework, which strikes a fair balance between high level understanding from features in an image and the low level number crunching of standard image processing techniques. It also provides us with a mathematical approach that facilitates combining multiple images to augment the bone surface estimate.

Medical imaging dose optimisation from ground up: expert opinion of an international summit.

PubMed

Samei, Ehsan; Järvinen, Hannu; Kortesniemi, Mika; Simantirakis, George; Goh, Charles; Wallace, Anthony; Vano, Eliseo; Bejan, Adrian; Rehani, Madan; Vassileva, Jenia

2018-05-17

As in any medical intervention, there is either a known or an anticipated benefit to the patient from undergoing a medical imaging procedure. This benefit is generally significant, as demonstrated by the manner in which medical imaging has transformed clinical medicine. At the same time, when it comes to imaging that deploys ionising radiation, there is a potential associated risk from radiation. Radiation risk has been recognised as a key liability in the practice of medical imaging, creating a motivation for radiation dose optimisation. The level of radiation dose and risk in imaging varies but is generally low. Thus, from the epidemiological perspective, this makes the estimation of the precise level of associated risk highly uncertain. However, in spite of the low magnitude and high uncertainty of this risk, its possibility cannot easily be refuted. Therefore, given the moral obligation of healthcare providers, 'first, do no harm,' there is an ethical obligation to mitigate this risk. Precisely how to achieve this goal scientifically and practically within a coherent system has been an open question. To address this need, in 2016, the International Atomic Energy Agency (IAEA) organised a summit to clarify the role of Diagnostic Reference Levels to optimise imaging dose, summarised into an initial report (Järvinen et al 2017 Journal of Medical Imaging 4 031214). Through a consensus building exercise, the summit further concluded that the imaging optimisation goal goes beyond dose alone, and should include image quality as a means to include both the benefit and the safety of the exam. The present, second report details the deliberation of the summit on imaging optimisation.

Use of image analysis to estimate anthocyanin and UV-excited fluorescent phenolic compound levels in strawberry fruit

PubMed Central

Yoshioka, Yosuke; Nakayama, Masayoshi; Noguchi, Yuji; Horie, Hideki

2013-01-01

Strawberry is rich in anthocyanins, which are responsible for the red color, and contains several colorless phenolic compounds. Among the colorless phenolic compounds, some, such as hydroxycinammic acid derivatives, emit blue-green fluorescence when excited with ultraviolet (UV) light. Here, we investigated the effectiveness of image analyses for estimating the levels of anthocyanins and UV-excited fluorescent phenolic compounds in fruit. The fruit skin and cut surface of 12 cultivars were photographed under visible and UV light conditions; colors were evaluated based on the color components of images. The levels of anthocyanins and UV-excited fluorescent compounds in each fruit were also evaluated by spectrophotometric and high performance liquid chromatography (HPLC) analyses, respectively and relationships between these levels and the image data were investigated. Red depth of the fruits differed greatly among the cultivars and anthocyanin content was well estimated based on the color values of the cut surface images. Strong UV-excited fluorescence was observed on the cut surfaces of several cultivars, and the grayscale values of the UV-excited fluorescence images were markedly correlated with the levels of those fluorescent compounds as evaluated by HPLC analysis. These results indicate that image analyses can select promising genotypes rich in anthocyanins and fluorescent phenolic compounds. PMID:23853516

A database system to support image algorithm evaluation

NASA Technical Reports Server (NTRS)

Lien, Y. E.

1977-01-01

The design is given of an interactive image database system IMDB, which allows the user to create, retrieve, store, display, and manipulate images through the facility of a high-level, interactive image query (IQ) language. The query language IQ permits the user to define false color functions, pixel value transformations, overlay functions, zoom functions, and windows. The user manipulates the images through generic functions. The user can direct images to display devices for visual and qualitative analysis. Image histograms and pixel value distributions can also be computed to obtain a quantitative analysis of images.

The comparison between SVD-DCT and SVD-DWT digital image watermarking

NASA Astrophysics Data System (ADS)

Wira Handito, Kurniawan; Fauzi, Zulfikar; Aminy Ma’ruf, Firda; Widyaningrum, Tanti; Muslim Lhaksmana, Kemas

2018-03-01

With internet, anyone can publish their creation into digital data simply, inexpensively, and absolutely easy to be accessed by everyone. However, the problem appears when anyone else claims that the creation is their property or modifies some part of that creation. It causes necessary protection of copyrights; one of the examples is with watermarking method in digital image. The application of watermarking technique on digital data, especially on image, enables total invisibility if inserted in carrier image. Carrier image will not undergo any decrease of quality and also the inserted image will not be affected by attack. In this paper, watermarking will be implemented on digital image using Singular Value Decomposition based on Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) by expectation in good performance of watermarking result. In this case, trade-off happen between invisibility and robustness of image watermarking. In embedding process, image watermarking has a good quality for scaling factor < 0.1. The quality of image watermarking in decomposition level 3 is better than level 2 and level 1. Embedding watermark in low-frequency is robust to Gaussian blur attack, rescale, and JPEG compression, but in high-frequency is robust to Gaussian noise.

Background derivation and image flattening: getimages

NASA Astrophysics Data System (ADS)

Men'shchikov, A.

2017-11-01

Modern high-resolution images obtained with space observatories display extremely strong intensity variations across images on all spatial scales. Source extraction in such images with methods based on global thresholding may bring unacceptably large numbers of spurious sources in bright areas while failing to detect sources in low-background or low-noise areas. It would be highly beneficial to subtract background and equalize the levels of small-scale fluctuations in the images before extracting sources or filaments. This paper describes getimages, a new method of background derivation and image flattening. It is based on median filtering with sliding windows that correspond to a range of spatial scales from the observational beam size up to a maximum structure width Xλ. The latter is a single free parameter of getimages that can be evaluated manually from the observed image ℐλ. The median filtering algorithm provides a background image \\tilde{Bλ} for structures of all widths below Xλ. The same median filtering procedure applied to an image of standard deviations 𝓓λ derived from a background-subtracted image \\tilde{Sλ} results in a flattening image \\tilde{Fλ}. Finally, a flattened detection image I{λD} = \\tilde{Sλ}/\\tilde{Fλ} is computed, whose standard deviations are uniform outside sources and filaments. Detecting sources in such greatly simplified images results in much cleaner extractions that are more complete and reliable. As a bonus, getimages reduces various observational and map-making artifacts and equalizes noise levels between independent tiles of mosaicked images.

Target-Oriented High-Resolution SAR Image Formation via Semantic Information Guided Regularizations

NASA Astrophysics Data System (ADS)

Hou, Biao; Wen, Zaidao; Jiao, Licheng; Wu, Qian

2018-04-01

Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of some visual features in the underlying image. However, since the simple prior of low level features are insufficient to describe different semantic contents in the image, this type of regularizer will be incapable of distinguishing between the target of interest and unconcerned background clutters. As a consequence, the features belonging to the target and clutters are simultaneously affected in the generated image without concerning their underlying semantic labels. To address this problem, we propose a novel semantic information guided framework for target oriented SAR image formation, which aims at enhancing the interested target scatters while suppressing the background clutters. Firstly, we develop a new semantics-specific regularizer for image formation by exploiting the statistical properties of different semantic categories in a target scene SAR image. In order to infer the semantic label for each pixel in an unsupervised way, we moreover induce a novel high-level prior-driven regularizer and some semantic causal rules from the prior knowledge. Finally, our regularized framework for image formation is further derived as a simple iteratively reweighted $\\ell_1$ minimization problem which can be conveniently solved by many off-the-shelf solvers. Experimental results demonstrate the effectiveness and superiority of our framework for SAR image formation in terms of target enhancement and clutters suppression, compared with the state of the arts. Additionally, the proposed framework opens a new direction of devoting some machine learning strategies to image formation, which can benefit the subsequent decision making tasks.

Sunlight-readable display technology: a dual-use case study

NASA Astrophysics Data System (ADS)

Blanchard, Randall D.

1996-05-01

This paper describes our vision of sunlight readable color display requirements, an alternate technology that offers a high level of performance, and how we implemented it for the military avionics display market. This knowledge base and product development experience was then applied with a comparable level of performance to commercial applications. The successful dual use of this technology for these two diverse markets is presented. Details of the technical commonality and a comparison of the design and performance differences are presented. A basis for specifying the required level of performance for a sunlight readable full color display is discussed. With the objective of providing a high level of image brightness and high ambient light rejection, a display architecture using collimated light is used. The resulting designs of two military cockpit display products, with contrast ratios above 20:1 in sunlight are shown. The performance of a commercial display providing several thousand foot- Lamberts of image brightness is presented.

Application of LANDSAT images to the study of level soils for recognizing drainage areas. Thesis Paper

NASA Technical Reports Server (NTRS)

Espinoza, M. U.

1977-01-01

Photographic images from LANDSAT 1 were applied to the study of soil in Desaguadero, Bolivia, in order to locate areas with high agricultural and livestock potential. Photointerpretation techniques were emphasized and advantages of information obtained via multispectral satellite images in various bands and combinations were demonstrated.

Ultrasound strain imaging using Barker code

NASA Astrophysics Data System (ADS)

Peng, Hui; Tie, Juhong; Guo, Dequan

2017-01-01

Ultrasound strain imaging is showing promise as a new way of imaging soft tissue elasticity in order to help clinicians detect lesions or cancers in tissues. In this paper, Barker code is applied to strain imaging to improve its quality. Barker code as a coded excitation signal can be used to improve the echo signal-to-noise ratio (eSNR) in ultrasound imaging system. For the Baker code of length 13, the sidelobe level of the matched filter output is -22dB, which is unacceptable for ultrasound strain imaging, because high sidelobe level will cause high decorrelation noise. Instead of using the conventional matched filter, we use the Wiener filter to decode the Barker-coded echo signal to suppress the range sidelobes. We also compare the performance of Barker code and the conventional short pulse in simulation method. The simulation results demonstrate that the performance of the Wiener filter is much better than the matched filter, and Baker code achieves higher elastographic signal-to-noise ratio (SNRe) than the short pulse in low eSNR or great depth conditions due to the increased eSNR with it.

Secure distribution for high resolution remote sensing images

NASA Astrophysics Data System (ADS)

Liu, Jin; Sun, Jing; Xu, Zheng Q.

2010-09-01

The use of remote sensing images collected by space platforms is becoming more and more widespread. The increasing value of space data and its use in critical scenarios call for adoption of proper security measures to protect these data against unauthorized access and fraudulent use. In this paper, based on the characteristics of remote sensing image data and application requirements on secure distribution, a secure distribution method is proposed, including users and regions classification, hierarchical control and keys generation, and multi-level encryption based on regions. The combination of the three parts can make that the same remote sensing images after multi-level encryption processing are distributed to different permission users through multicast, but different permission users can obtain different degree information after decryption through their own decryption keys. It well meets user access control and security needs in the process of high resolution remote sensing image distribution. The experimental results prove the effectiveness of the proposed method which is suitable for practical use in the secure transmission of remote sensing images including confidential information over internet.

Image wavelet decomposition and applications

NASA Technical Reports Server (NTRS)

Treil, N.; Mallat, S.; Bajcsy, R.

1989-01-01

The general problem of computer vision has been investigated for more that 20 years and is still one of the most challenging fields in artificial intelligence. Indeed, taking a look at the human visual system can give us an idea of the complexity of any solution to the problem of visual recognition. This general task can be decomposed into a whole hierarchy of problems ranging from pixel processing to high level segmentation and complex objects recognition. Contrasting an image at different representations provides useful information such as edges. An example of low level signal and image processing using the theory of wavelets is introduced which provides the basis for multiresolution representation. Like the human brain, we use a multiorientation process which detects features independently in different orientation sectors. So, images of the same orientation but of different resolutions are contrasted to gather information about an image. An interesting image representation using energy zero crossings is developed. This representation is shown to be experimentally complete and leads to some higher level applications such as edge and corner finding, which in turn provides two basic steps to image segmentation. The possibilities of feedback between different levels of processing are also discussed.

Optimal Monochromatic Energy Levels in Spectral CT Pulmonary Angiography for the Evaluation of Pulmonary Embolism

PubMed Central

Wu, Huawei; Zhang, Qing; Hua, Jia; Hua, Xiaolan; Xu, Jianrong

2013-01-01

Background The aim of this study was to determine the optimal monochromatic spectral CT pulmonary angiography (sCTPA) levels to obtain the highest image quality and diagnostic confidence for pulmonary embolism detection. Methods The Institutional Review Board of the Shanghai Jiao Tong University School of Medicine approved this study, and written informed consent was obtained from all participating patients. Seventy-two patients with pulmonary embolism were scanned with spectral CT mode in the arterial phase. One hundred and one sets of virtual monochromatic spectral (VMS) images were generated ranging from 40 keV to 140 keV. Image noise, clot diameter and clot to artery contrast-to-noise ratio (CNR) from seven sets of VMS images at selected monochromatic levels in sCTPA were measured and compared. Subjective image quality and diagnostic confidence for these images were also assessed and compared. Data were analyzed by paired t test and Wilcoxon rank sum test. Results The lowest noise and the highest image quality score for the VMS images were obtained at 65 keV. The VMS images at 65 keV also had the second highest CNR value behind that of 50 keV VMS images. There was no difference in the mean noise and CNR between the 65 keV and 70 keV VMS images. The apparent clot diameter correlated with the keV levels. Conclusions The optimal energy level for detecting pulmonary embolism using dual-energy spectral CT pulmonary angiography was 65–70 keV. Virtual monochromatic spectral images at approximately 65–70 keV yielded the lowest image noise, high CNR and highest diagnostic confidence for the detection of pulmonary embolism. PMID:23667583

The impact of using visual images of the body within a personalized health risk assessment: an experimental study.

PubMed

Hollands, Gareth J; Marteau, Theresa M

2013-05-01

To examine the motivational impact of the addition of a visual image to a personalized health risk assessment and the underlying cognitive and emotional mechanisms. An online experimental study in which participants (n = 901; mean age = 27.2 years; 61.5% female) received an assessment and information focusing on the health implications of internal body fat and highlighting the protective benefits of physical activity. Participants were randomized to receive this in either (a) solely text form (control arm) or (b) text plus a visual image of predicted internal body fat (image arm). Participants received information representing one of three levels of health threat, determined by how physically active they were: high, moderate or benign. Main outcome measures were physical activity intentions (assessed pre- and post-intervention), worry, coherence and believability of the information. Intentions to undertake recommended levels of physical activity were significantly higher in the image arm, but only amongst those participants who received a high-threat communication. Believability of the results received was greater in the image arm and mediated the intervention effect on intentions. The addition of a visual image to a risk assessment led to small but significant increases in intentions to undertake recommended levels of physical activity in those at increased health risk. Limitations of the study and implications for future research are discussed. What is already known on this subject? Health risk information that is personalized to the individual may more strongly motivate risk-reducing behaviour change. Little prior research attention has been paid specifically to the motivational impact of personalized visual images and underlying mechanisms. What does this study add? In an experimental design, it is shown that receipt of visual images increases intentions to engage in risk-reducing behaviour, although only when a significant level of threat is presented. The study suggests that images increase the believability of health risk information and this may underlie motivational impact. © 2012 The British Psychological Society.

A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

NASA Astrophysics Data System (ADS)

Tatar, Nurollah; Saadatseresht, Mohammad; Arefi, Hossein; Hadavand, Ahmad

2018-06-01

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C4 index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.

Resonant imaging of carotenoid pigments in the human retina

NASA Astrophysics Data System (ADS)

Gellermann, Werner; Emakov, Igor V.; McClane, Robert W.

2002-06-01

We have generated high spatial resolution images showing the distribution of carotenoid macular pigments in the human retina using Raman spectroscopy. A low level of macular pigments is associated with an increased risk of developing age-related macular degeneration, a leading cause of irreversible blindness. Using excised human eyecups and resonant excitation of the pigment molecules with narrow bandwidth blue light from a mercury arc lamp, we record Raman images originating from the carbon-carbon double bond stretch vibrations of lutein and zeaxanthin, the carotenoids comprising human macular pigments. Our Raman images reveal significant differences among subjects, both in regard to absolute levels as well as spatial distribution within the macula. Since the light levels used to obtain these images are well below established safety limits, this technique holds promise for developing a rapid screening diagnostic in large populations at risk for vision loss from age-related macular degeneration.

Example-Based Image Colorization Using Locality Consistent Sparse Representation.

PubMed

Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

2017-11-01

Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

Development of a CCD based solar speckle imaging system

NASA Astrophysics Data System (ADS)

Nisenson, Peter; Stachnik, Robert V.; Noyes, Robert W.

1986-02-01

A program to develop software and hardware for the purpose of obtaining high angular resolution images of the solar surface is described. The program included the procurement of a Charge Coupled Devices imaging system; an extensive laboratory and remote site testing of the camera system; the development of a software package for speckle image reconstruction which was eventually installed and tested at the Sacramento Peak Observatory; and experiments of the CCD system (coupled to an image intensifier) for low light level, narrow spectral band solar imaging.

Compression for radiological images

NASA Astrophysics Data System (ADS)

Wilson, Dennis L.

1992-07-01

The viewing of radiological images has peculiarities that must be taken into account in the design of a compression technique. The images may be manipulated on a workstation to change the contrast, to change the center of the brightness levels that are viewed, and even to invert the images. Because of the possible consequences of losing information in a medical application, bit preserving compression is used for the images used for diagnosis. However, for archiving the images may be compressed to 10 of their original size. A compression technique based on the Discrete Cosine Transform (DCT) takes the viewing factors into account by compressing the changes in the local brightness levels. The compression technique is a variation of the CCITT JPEG compression that suppresses the blocking of the DCT except in areas of very high contrast.

Digital identification of cartographic control points

NASA Technical Reports Server (NTRS)

Gaskell, R. W.

1988-01-01

Techniques have been developed for the sub-pixel location of control points in satellite images returned by the Voyager spacecraft. The procedure uses digital imaging data in the neighborhood of the point to form a multipicture model of a piece of the surface. Comparison of this model with the digital image in each picture determines the control point locations to about a tenth of a pixel. At this level of precision, previously insignificant effects must be considered, including chromatic aberration, high level imaging distortions, and systematic errors due to navigation uncertainties. Use of these methods in the study of Jupiter's satellite Io has proven very fruitful.

Using AI Planning Techniques to Automatically Generate Image Processing Procedures: A Preliminary Report

NASA Technical Reports Server (NTRS)

Chien, S.

1994-01-01

This paper describes work on the Multimission VICAR Planner (MVP) system to automatically construct executable image processing procedures for custom image processing requests for the JPL Multimission Image Processing Lab (MIPL). This paper focuses on two issues. First, large search spaces caused by complex plans required the use of hand encoded control information. In order to address this in a manner similar to that used by human experts, MVP uses a decomposition-based planner to implement hierarchical/skeletal planning at the higher level and then uses a classical operator based planner to solve subproblems in contexts defined by the high-level decomposition.

Molecular imaging needles: dual-modality optical coherence tomography and fluorescence imaging of labeled antibodies deep in tissue

PubMed Central

Scolaro, Loretta; Lorenser, Dirk; Madore, Wendy-Julie; Kirk, Rodney W.; Kramer, Anne S.; Yeoh, George C.; Godbout, Nicolas; Sampson, David D.; Boudoux, Caroline; McLaughlin, Robert A.

2015-01-01

Molecular imaging using optical techniques provides insight into disease at the cellular level. In this paper, we report on a novel dual-modality probe capable of performing molecular imaging by combining simultaneous three-dimensional optical coherence tomography (OCT) and two-dimensional fluorescence imaging in a hypodermic needle. The probe, referred to as a molecular imaging (MI) needle, may be inserted tens of millimeters into tissue. The MI needle utilizes double-clad fiber to carry both imaging modalities, and is interfaced to a 1310-nm OCT system and a fluorescence imaging subsystem using an asymmetrical double-clad fiber coupler customized to achieve high fluorescence collection efficiency. We present, to the best of our knowledge, the first dual-modality OCT and fluorescence needle probe with sufficient sensitivity to image fluorescently labeled antibodies. Such probes enable high-resolution molecular imaging deep within tissue. PMID:26137379

Waif goodbye! Average-size female models promote positive body image and appeal to consumers.

PubMed

Diedrichs, Phillippa C; Lee, Christina

2011-10-01

Despite consensus that exposure to media images of thin fashion models is associated with poor body image and disordered eating behaviours, few attempts have been made to enact change in the media. This study sought to investigate an effective alternative to current media imagery, by exploring the advertising effectiveness of average-size female fashion models, and their impact on the body image of both women and men. A sample of 171 women and 120 men were assigned to one of three advertisement conditions: no models, thin models and average-size models. Women and men rated average-size models as equally effective in advertisements as thin and no models. For women with average and high levels of internalisation of cultural beauty ideals, exposure to average-size female models was associated with a significantly more positive body image state in comparison to exposure to thin models and no models. For men reporting high levels of internalisation, exposure to average-size models was also associated with a more positive body image state in comparison to viewing thin models. These findings suggest that average-size female models can promote positive body image and appeal to consumers.

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor

PubMed Central

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-01-01

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies. PMID:29695113

Presentation Attack Detection for Iris Recognition System Using NIR Camera Sensor.

PubMed

Nguyen, Dat Tien; Baek, Na Rae; Pham, Tuyen Danh; Park, Kang Ryoung

2018-04-24

Among biometric recognition systems such as fingerprint, finger-vein, or face, the iris recognition system has proven to be effective for achieving a high recognition accuracy and security level. However, several recent studies have indicated that an iris recognition system can be fooled by using presentation attack images that are recaptured using high-quality printed images or by contact lenses with printed iris patterns. As a result, this potential threat can reduce the security level of an iris recognition system. In this study, we propose a new presentation attack detection (PAD) method for an iris recognition system (iPAD) using a near infrared light (NIR) camera image. To detect presentation attack images, we first localized the iris region of the input iris image using circular edge detection (CED). Based on the result of iris localization, we extracted the image features using deep learning-based and handcrafted-based methods. The input iris images were then classified into real and presentation attack categories using support vector machines (SVM). Through extensive experiments with two public datasets, we show that our proposed method effectively solves the iris recognition presentation attack detection problem and produces detection accuracy superior to previous studies.

Glucose test (image)

MedlinePlus

... person with diabetes constantly manages their blood's sugar (glucose) levels. After a blood sample is taken and tested, it is determined whether the glucose levels are low or high. Following your health ...

High-precision γ -ray spectroscopy of the cardiac PET imaging isotope Rb 82 and its impact on dosimetry

DOE PAGES

Nino, M. N.; McCutchan, E. A.; Smith, S. V.; ...

2016-02-01

82Rb is a positron-emitting isotope used in cardiac positron emission tomography (PET) imaging which has been reported to deliver a significantly lower effective radiation dose than analogous imaging isotopes like 201Tl and 99mTc sestamibi. High-quality β-decay data are essential to accurately appraise the total dose received by the patients. A source of 82Sr was produced at the Brookhaven Linac Isotope Producer (BLIP), transported to Argonne National Laboratory, and studied with the Gammasphere facility. Significant revisions have been made to the level scheme of 82Kr including 12 new levels, 50 new γ-ray transitions, and the determination of many new spin assignmentsmore » through angular correlations. Lastly, these new high-quality data allow a precise reappraisal of the β-decay strength function and thus the consequent dose received by patients.« less

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2001-01-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Self-adaptive relevance feedback based on multilevel image content analysis

NASA Astrophysics Data System (ADS)

Gao, Yongying; Zhang, Yujin; Fu, Yu

2000-12-01

In current content-based image retrieval systems, it is generally accepted that obtaining high-level image features is a key to improve the querying. Among the related techniques, relevance feedback has become a hot research aspect because it combines the information from the user to refine the querying results. In practice, many methods have been proposed to achieve the goal of relevance feedback. In this paper, a new scheme for relevance feedback is proposed. Unlike previous methods for relevance feedback, our scheme provides a self-adaptive operation. First, based on multi- level image content analysis, the relevant images from the user could be automatically analyzed in different levels and the querying could be modified in terms of different analysis results. Secondly, to make it more convenient to the user, the procedure of relevance feedback could be led with memory or without memory. To test the performance of the proposed method, a practical semantic-based image retrieval system has been established, and the querying results gained by our self-adaptive relevance feedback are given.

Use of zerotree coding in a high-speed pyramid image multiresolution decomposition

NASA Astrophysics Data System (ADS)

Vega-Pineda, Javier; Cabrera, Sergio D.; Lucero, Aldo

1995-03-01

A Zerotree (ZT) coding scheme is applied as a post-processing stage to avoid transmitting zero data in the High-Speed Pyramid (HSP) image compression algorithm. This algorithm has features that increase the capability of the ZT coding to give very high compression rates. In this paper the impact of the ZT coding scheme is analyzed and quantified. The HSP algorithm creates a discrete-time multiresolution analysis based on a hierarchical decomposition technique that is a subsampling pyramid. The filters used to create the image residues and expansions can be related to wavelet representations. According to the pixel coordinates and the level in the pyramid, N2 different wavelet basis functions of various sizes and rotations are linearly combined. The HSP algorithm is computationally efficient because of the simplicity of the required operations, and as a consequence, it can be very easily implemented with VLSI hardware. This is the HSP's principal advantage over other compression schemes. The ZT coding technique transforms the different quantized image residual levels created by the HSP algorithm into a bit stream. The use of ZT's compresses even further the already compressed image taking advantage of parent-child relationships (trees) between the pixels of the residue images at different levels of the pyramid. Zerotree coding uses the links between zeros along the hierarchical structure of the pyramid, to avoid transmission of those that form branches of all zeros. Compression performance and algorithm complexity of the combined HSP-ZT method are compared with those of the JPEG standard technique.

Large-format InGaAs focal plane arrays for SWIR imaging

NASA Astrophysics Data System (ADS)

Hood, Andrew D.; MacDougal, Michael H.; Manzo, Juan; Follman, David; Geske, Jonathan C.

2012-06-01

FLIR Electro Optical Components will present our latest developments in large InGaAs focal plane arrays, which are used for low light level imaging in the short wavelength infrared (SWIR) regime. FLIR will present imaging from their latest small pitch (15 μm) focal plane arrays in VGA and High Definition (HD) formats. FLIR will present characterization of the FPA including dark current measurements as well as the use of correlated double sampling to reduce read noise. FLIR will show imagery as well as FPA-level characterization data.

Subjective and physiological reactivity to chocolate images in high and low chocolate cravers.

PubMed

Rodríguez, Sonia; Fernández, María Carmen; Cepeda-Benito, Antonio; Vila, Jaime

2005-09-01

Cue-reactivity to chocolate images was assessed using self-report and physiological measures. From a pre-screening sample of 454, young women were selected and assigned to high and low chocolate craving groups (N = 36/group). The experimental procedure consisted in the elicitation and measurement of the cardiac defense and startle reflexes while viewing chocolate and standard affective images selected from the International Affective Picture System. In response to chocolate images, high cravers reported more pleasure and arousal but less control than low cravers. In high cravers, viewing chocolate images inhibited the cardiac defense but potentiated the startle reflex, as compared to low cravers. The results confirmed at the physiological level that the motivational state that underlies the experience of chocolate craving include both appetitive (inhibition of the defense reflex) and aversive (potentiation of the startle response) components. The findings supported a motivational conflict theory of chocolate craving.

High-level intuitive features (HLIFs) for intuitive skin lesion description.

PubMed

Amelard, Robert; Glaister, Jeffrey; Wong, Alexander; Clausi, David A

2015-03-01

A set of high-level intuitive features (HLIFs) is proposed to quantitatively describe melanoma in standard camera images. Melanoma is the deadliest form of skin cancer. With rising incidence rates and subjectivity in current clinical detection methods, there is a need for melanoma decision support systems. Feature extraction is a critical step in melanoma decision support systems. Existing feature sets for analyzing standard camera images are comprised of low-level features, which exist in high-dimensional feature spaces and limit the system's ability to convey intuitive diagnostic rationale. The proposed HLIFs were designed to model the ABCD criteria commonly used by dermatologists such that each HLIF represents a human-observable characteristic. As such, intuitive diagnostic rationale can be conveyed to the user. Experimental results show that concatenating the proposed HLIFs with a full low-level feature set increased classification accuracy, and that HLIFs were able to separate the data better than low-level features with statistical significance. An example of a graphical interface for providing intuitive rationale is given.

Development of an omnidirectional gamma-ray imaging Compton camera for low-radiation-level environmental monitoring

NASA Astrophysics Data System (ADS)

Watanabe, Takara; Enomoto, Ryoji; Muraishi, Hiroshi; Katagiri, Hideaki; Kagaya, Mika; Fukushi, Masahiro; Kano, Daisuke; Satoh, Wataru; Takeda, Tohoru; Tanaka, Manobu M.; Tanaka, Souichi; Uchida, Tomohisa; Wada, Kiyoto; Wakamatsu, Ryo

2018-02-01

We have developed an omnidirectional gamma-ray imaging Compton camera for environmental monitoring at low levels of radiation. The camera consisted of only six CsI(Tl) scintillator cubes of 3.5 cm, each of which was readout by super-bialkali photo-multiplier tubes (PMTs). Our camera enables the visualization of the position of gamma-ray sources in all directions (∼4π sr) over a wide energy range between 300 and 1400 keV. The angular resolution (σ) was found to be ∼11°, which was realized using an image-sharpening technique. A high detection efficiency of 18 cps/(µSv/h) for 511 keV (1.6 cps/MBq at 1 m) was achieved, indicating the capability of this camera to visualize hotspots in areas with low-radiation-level contamination from the order of µSv/h to natural background levels. Our proposed technique can be easily used as a low-radiation-level imaging monitor in radiation control areas, such as medical and accelerator facilities.

High Frequency Active Auroral Research Program (HAARP) imager. Final report, 29 August 1991-29 August 1993

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

Lance, C.; Eather, R.

1993-09-30

A low-light-level monochromatic imaging system was designed and fabricated which was optimized to detect and record optical emissions associated with high-power rf heating of the ionosphere. The instrument is capable of detecting very low intensities, of the order of 1 Rayleigh, from typical ionospheric atomic and molecular emissions. This is achieved through co-adding of ON images during heater pulses and subtraction of OFF (background) images between pulses. Images can be displayed and analyzed in real time and stored in optical disc for later analysis. Full image processing software is provided which was customized for this application and uses menu ormore » mouse user interaction.« less

A Low-Power High-Speed Smart Sensor Design for Space Exploration Missions

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi

1997-01-01

A low-power high-speed smart sensor system based on a large format active pixel sensor (APS) integrated with a programmable neural processor for space exploration missions is presented. The concept of building an advanced smart sensing system is demonstrated by a system-level microchip design that is composed with an APS sensor, a programmable neural processor, and an embedded microprocessor in a SOI CMOS technology. This ultra-fast smart sensor system-on-a-chip design mimics what is inherent in biological vision systems. Moreover, it is programmable and capable of performing ultra-fast machine vision processing in all levels such as image acquisition, image fusion, image analysis, scene interpretation, and control functions. The system provides about one tera-operation-per-second computing power which is a two order-of-magnitude increase over that of state-of-the-art microcomputers. Its high performance is due to massively parallel computing structures, high data throughput rates, fast learning capabilities, and advanced VLSI system-on-a-chip implementation.

High-order noise analysis for low dose iterative image reconstruction methods: ASIR, IRIS, and MBAI

NASA Astrophysics Data System (ADS)

Do, Synho; Singh, Sarabjeet; Kalra, Mannudeep K.; Karl, W. Clem; Brady, Thomas J.; Pien, Homer

2011-03-01

Iterative reconstruction techniques (IRTs) has been shown to suppress noise significantly in low dose CT imaging. However, medical doctors hesitate to accept this new technology because visual impression of IRT images are different from full-dose filtered back-projection (FBP) images. Most common noise measurements such as the mean and standard deviation of homogeneous region in the image that do not provide sufficient characterization of noise statistics when probability density function becomes non-Gaussian. In this study, we measure L-moments of intensity values of images acquired at 10% of normal dose and reconstructed by IRT methods of two state-of-art clinical scanners (i.e., GE HDCT and Siemens DSCT flash) by keeping dosage level identical to each other. The high- and low-dose scans (i.e., 10% of high dose) were acquired from each scanner and L-moments of noise patches were calculated for the comparison.

Imaging Axl expression in pancreatic and prostate cancer xenografts

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

Nimmagadda, Sridhar, E-mail: snimmag1@jhmi.edu; Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, MD 21287; Pullambhatla, Mrudula

2014-01-10

Highlights: •Axl is overexpressed in a variety of cancers. •Axl overexpression confers invasive phenotype. •Axl imaging would be useful for therapeutic guidance and monitoring. •Axl expression imaging is demonstrated in pancreatic and prostate cancer xenografts. •Graded levels of Axl expression imaging is feasible. -- Abstract: The receptor tyrosine kinase Axl is overexpressed in and leads to patient morbidity and mortality in a variety of cancers. Axl–Gas6 interactions are critical for tumor growth, angiogenesis and metastasis. The goal of this study was to investigate the feasibility of imaging graded levels of Axl expression in tumors using a radiolabeled antibody. We radiolabeledmore » anti-human Axl (Axl mAb) and control IgG1 antibodies with {sup 125}I with high specific radioactivity and radiochemical purity, resulting in an immunoreactive fraction suitable for in vivo studies. Radiolabeled antibodies were investigated in severe combined immunodeficient mice harboring subcutaneous CFPAC (Axl{sup high}) and Panc1 (Axl{sup low}) pancreatic cancer xenografts by ex vivo biodistribution and imaging. Based on these results, the specificity of [{sup 125}I]Axl mAb was also validated in mice harboring orthotopic Panc1 or CFPAC tumors and in mice harboring subcutaneous 22Rv1 (Axl{sup low}) or DU145 (Axl{sup high}) prostate tumors by ex vivo biodistribution and imaging studies at 72 h post-injection of the antibody. Both imaging and biodistribution studies demonstrated specific and persistent accumulation of [{sup 125}I]Axl mAb in Axl{sup high} (CFPAC and DU145) expression tumors compared to the Axl{sup low} (Panc1 and 22Rv1) expression tumors. Axl expression in these tumors was further confirmed by immunohistochemical studies. No difference in the uptake of radioactivity was observed between the control [{sup 125}I]IgG1 antibody in the Axl{sup high} and Axl{sup low} expression tumors. These data demonstrate the feasibility of imaging Axl expression in pancreatic and prostate tumor xenografts.« less

Mass-storage management for distributed image/video archives

NASA Astrophysics Data System (ADS)

Franchi, Santina; Guarda, Roberto; Prampolini, Franco

1993-04-01

The realization of image/video database requires a specific design for both database structures and mass storage management. This issue has addressed the project of the digital image/video database system that has been designed at IBM SEMEA Scientific & Technical Solution Center. Proper database structures have been defined to catalog image/video coding technique with the related parameters, and the description of image/video contents. User workstations and servers are distributed along a local area network. Image/video files are not managed directly by the DBMS server. Because of their wide size, they are stored outside the database on network devices. The database contains the pointers to the image/video files and the description of the storage devices. The system can use different kinds of storage media, organized in a hierarchical structure. Three levels of functions are available to manage the storage resources. The functions of the lower level provide media management. They allow it to catalog devices and to modify device status and device network location. The medium level manages image/video files on a physical basis. It manages file migration between high capacity media and low access time media. The functions of the upper level work on image/video file on a logical basis, as they archive, move and copy image/video data selected by user defined queries. These functions are used to support the implementation of a storage management strategy. The database information about characteristics of both storage devices and coding techniques are used by the third level functions to fit delivery/visualization requirements and to reduce archiving costs.

A multiresolution processing method for contrast enhancement in portal imaging.

PubMed

Gonzalez-Lopez, Antonio

2018-06-18

Portal images have a unique feature among the imaging modalities used in radiotherapy: they provide direct visualization of the irradiated volumes. However, contrast and spatial resolution are strongly limited due to the high energy of the radiation sources. Because of this, imaging modalities using x-ray energy beams have gained importance in the verification of patient positioning, replacing portal imaging. The purpose of this work was to develop a method for the enhancement of local contrast in portal images. The method operates in the subbands of a wavelet decomposition of the image, re-scaling them in such a way that coefficients in the high and medium resolution subbands are amplified, an approach totally different of those operating on the image histogram, widely used nowadays. Portal images of an anthropomorphic phantom were acquired in an electronic portal imaging device (EPID). Then, different re-scaling strategies were investigated, studying the effects of the scaling parameters on the enhanced images. Also, the effect of using different types of transforms was studied. Finally, the implemented methods were combined with histogram equalization methods like the contrast limited adaptive histogram equalization (CLAHE), and these combinations were compared. Uniform amplification of the detail subbands shows the best results in contrast enhancement. On the other hand, linear re-escalation of the high resolution subbands increases the visibility of fine detail of the images, at the expense of an increase in noise levels. Also, since processing is applied only to detail subbands, not to the approximation, the mean gray level of the image is minimally modified and no further display adjustments are required. It is shown that re-escalation of the detail subbands of portal images can be used as an efficient method for the enhancement of both, the local contrast and the resolution of these images. © 2018 Institute of Physics and Engineering in Medicine.

Coherent nonlinear optical imaging: beyond fluorescence microscopy.

PubMed

Min, Wei; Freudiger, Christian W; Lu, Sijia; Xie, X Sunney

2011-01-01

The quest for ultrahigh detection sensitivity with spectroscopic contrasts other than fluorescence has led to various novel approaches to optical microscopy of biological systems. Coherent nonlinear optical imaging, especially the recently developed nonlinear dissipation microscopy (including stimulated Raman scattering and two-photon absorption) and pump-probe microscopy (including excited-state absorption, stimulated emission, and ground-state depletion), provides new image contrasts for nonfluorescent species. Thanks to the high-frequency modulation transfer scheme, these imaging techniques exhibit superb detection sensitivity. By directly interrogating vibrational and/or electronic energy levels of molecules, they offer high molecular specificity. Here we review the underlying principles and excitation and detection schemes, as well as exemplary biomedical applications of this emerging class of molecular imaging techniques.

Hyperspectral microscope for in vivo imaging of microstructures and cells in tissues

DOEpatents

Demos,; Stavros, G [Livermore, CA

2011-05-17

An optical hyperspectral/multimodal imaging method and apparatus is utilized to provide high signal sensitivity for implementation of various optical imaging approaches. Such a system utilizes long working distance microscope objectives so as to enable off-axis illumination of predetermined tissue thereby allowing for excitation at any optical wavelength, simplifies design, reduces required optical elements, significantly reduces spectral noise from the optical elements and allows for fast image acquisition enabling high quality imaging in-vivo. Such a technology provides a means of detecting disease at the single cell level such as cancer, precancer, ischemic, traumatic or other type of injury, infection, or other diseases or conditions causing alterations in cells and tissue micro structures.

Accelerated dynamic EPR imaging using fast acquisition and compressive recovery

NASA Astrophysics Data System (ADS)

Ahmad, Rizwan; Samouilov, Alexandre; Zweier, Jay L.

2016-12-01

Electron paramagnetic resonance (EPR) allows quantitative imaging of tissue redox status, which provides important information about ischemic syndromes, cancer and other pathologies. For continuous wave EPR imaging, however, poor signal-to-noise ratio and low acquisition efficiency limit its ability to image dynamic processes in vivo including tissue redox, where conditions can change rapidly. Here, we present a data acquisition and processing framework that couples fast acquisition with compressive sensing-inspired image recovery to enable EPR-based redox imaging with high spatial and temporal resolutions. The fast acquisition (FA) allows collecting more, albeit noisier, projections in a given scan time. The composite regularization based processing method, called spatio-temporal adaptive recovery (STAR), not only exploits sparsity in multiple representations of the spatio-temporal image but also adaptively adjusts the regularization strength for each representation based on its inherent level of the sparsity. As a result, STAR adjusts to the disparity in the level of sparsity across multiple representations, without introducing any tuning parameter. Our simulation and phantom imaging studies indicate that a combination of fast acquisition and STAR (FASTAR) enables high-fidelity recovery of volumetric image series, with each volumetric image employing less than 10 s of scan. In addition to image fidelity, the time constants derived from FASTAR also match closely to the ground truth even when a small number of projections are used for recovery. This development will enhance the capability of EPR to study fast dynamic processes that cannot be investigated using existing EPR imaging techniques.

Study of Lead as a Source X-ray Radiation Protection with an Analysis Grey Level Image

NASA Astrophysics Data System (ADS)

Susilo; Rahma, I. N.; Mosik; Masturi

2017-04-01

X-ray utilization in the medical field still has a potential danger for the human. This occurs when exposure to x-ray radiation received exceeds the dose limit value. It required a radiation shielding to prevent the hazard, and lead is one of the metals usually used as x-ray radiation shield. This work aims to determine the metallic lead properties to find out of the step wedge lead radiograph image. The instruments used are the plane x-ray, digital radiography system and personal computer installed by MATLAB, while the material is step wedge lead. The image of radiograph was analysed using GUI applications on MATLAB software to determine the values of grey level from the image and the optical density of the radiograph image. The results showed the greater optical density, the higher the image contrast, and the value of optical density in the image is inversely proportional to the voltage x-ray since the value of grey level at high voltage is smaller than that of at low voltage.

Oxalate-curcumin-based probe for micro- and macroimaging of reactive oxygen species in Alzheimer's disease.

PubMed

Yang, Jian; Zhang, Xueli; Yuan, Peng; Yang, Jing; Xu, Yungen; Grutzendler, Jaime; Shao, Yihan; Moore, Anna; Ran, Chongzhao

2017-11-21

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder that has a progression that is closely associated with oxidative stress. It has long been speculated that the reactive oxygen species (ROS) level in AD brains is much higher than that in healthy brains. However, evidence from living beings is scarce. Inspired by the "chemistry of glow stick," we designed a near-IR fluorescence (NIRF) imaging probe, termed CRANAD-61, for sensing ROS to provide evidence at micro- and macrolevels. In CRANAD-61, an oxalate moiety was utilized to react with ROS and to consequentially produce wavelength shifting. Our in vitro data showed that CRANAD-61 was highly sensitive and rapidly responsive to various ROS. On reacting with ROS, its excitation and emission wavelengths significantly shifted to short wavelengths, and this shifting could be harnessed for dual-color two-photon imaging and transformative NIRF imaging. In this report, we showed that CRANAD-61 could be used to identify "active" amyloid beta (Aβ) plaques and cerebral amyloid angiopathy (CAA) surrounded by high ROS levels with two-photon imaging (microlevel) and to provide relative total ROS concentrations in AD brains via whole-brain NIRF imaging (macrolevel). Lastly, we showed that age-related increases in ROS levels in AD brains could be monitored with our NIRF imaging method. We believe that our imaging with CRANAD-61 could provide evidence of ROS at micro- and macrolevels and could be used for monitoring ROS changes under various AD pathological conditions and during drug treatment.

Contextually guided very-high-resolution imagery classification with semantic segments

NASA Astrophysics Data System (ADS)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

Multiplicative mixing of object identity and image attributes in single inferior temporal neurons.

PubMed

Ratan Murty, N Apurva; Arun, S P

2018-04-03

Object recognition is challenging because the same object can produce vastly different images, mixing signals related to its identity with signals due to its image attributes, such as size, position, rotation, etc. Previous studies have shown that both signals are present in high-level visual areas, but precisely how they are combined has remained unclear. One possibility is that neurons might encode identity and attribute signals multiplicatively so that each can be efficiently decoded without interference from the other. Here, we show that, in high-level visual cortex, responses of single neurons can be explained better as a product rather than a sum of tuning for object identity and tuning for image attributes. This subtle effect in single neurons produced substantially better population decoding of object identity and image attributes in the neural population as a whole. This property was absent both in low-level vision models and in deep neural networks. It was also unique to invariances: when tested with two-part objects, neural responses were explained better as a sum than as a product of part tuning. Taken together, our results indicate that signals requiring separate decoding, such as object identity and image attributes, are combined multiplicatively in IT neurons, whereas signals that require integration (such as parts in an object) are combined additively. Copyright © 2018 the Author(s). Published by PNAS.

The influence of underwater turbulence on optical phase measurements

NASA Astrophysics Data System (ADS)

Redding, Brandon; Davis, Allen; Kirkendall, Clay; Dandridge, Anthony

2016-05-01

Emerging underwater optical imaging and sensing applications rely on phase-sensitive detection to provide added functionality and improved sensitivity. However, underwater turbulence introduces spatio-temporal variations in the refractive index of water which can degrade the performance of these systems. Although the influence of turbulence on traditional, non-interferometric imaging has been investigated, its influence on the optical phase remains poorly understood. Nonetheless, a thorough understanding of the spatio-temporal dynamics of the optical phase of light passing through underwater turbulence are crucial to the design of phase-sensitive imaging and sensing systems. To address this concern, we combined underwater imaging with high speed holography to provide a calibrated characterization of the effects of turbulence on the optical phase. By measuring the modulation transfer function of an underwater imaging system, we were able to calibrate varying levels of optical turbulence intensity using the Simple Underwater Imaging Model (SUIM). We then used high speed holography to measure the temporal dynamics of the optical phase of light passing through varying levels of turbulence. Using this method, we measured the variance in the amplitude and phase of the beam, the temporal correlation of the optical phase, and recorded the turbulence induced phase noise as a function of frequency. By bench marking the effects of varying levels of turbulence on the optical phase, this work provides a basis to evaluate the real-world potential of emerging underwater interferometric sensing modalities.

Efficient random access high resolution region-of-interest (ROI) image retrieval using backward coding of wavelet trees (BCWT)

NASA Astrophysics Data System (ADS)

Corona, Enrique; Nutter, Brian; Mitra, Sunanda; Guo, Jiangling; Karp, Tanja

2008-03-01

Efficient retrieval of high quality Regions-Of-Interest (ROI) from high resolution medical images is essential for reliable interpretation and accurate diagnosis. Random access to high quality ROI from codestreams is becoming an essential feature in many still image compression applications, particularly in viewing diseased areas from large medical images. This feature is easier to implement in block based codecs because of the inherent spatial independency of the code blocks. This independency implies that the decoding order of the blocks is unimportant as long as the position for each is properly identified. In contrast, wavelet-tree based codecs naturally use some interdependency that exploits the decaying spectrum model of the wavelet coefficients. Thus one must keep track of the decoding order from level to level with such codecs. We have developed an innovative multi-rate image subband coding scheme using "Backward Coding of Wavelet Trees (BCWT)" which is fast, memory efficient, and resolution scalable. It offers far less complexity than many other existing codecs including both, wavelet-tree, and block based algorithms. The ROI feature in BCWT is implemented through a transcoder stage that generates a new BCWT codestream containing only the information associated with the user-defined ROI. This paper presents an efficient technique that locates a particular ROI within the BCWT coded domain, and decodes it back to the spatial domain. This technique allows better access and proper identification of pathologies in high resolution images since only a small fraction of the codestream is required to be transmitted and analyzed.

Segmentation of Environmental Time Lapse Image Sequences for the Determination of Shore Lines Captured by Hand-Held Smartphone Cameras

NASA Astrophysics Data System (ADS)

Kröhnert, M.; Meichsner, R.

2017-09-01

The relevance of globally environmental issues gains importance since the last years with still rising trends. Especially disastrous floods may cause in serious damage within very short times. Although conventional gauging stations provide reliable information about prevailing water levels, they are highly cost-intensive and thus just sparsely installed. Smartphones with inbuilt cameras, powerful processing units and low-cost positioning systems seem to be very suitable wide-spread measurement devices that could be used for geo-crowdsourcing purposes. Thus, we aim for the development of a versatile mobile water level measurement system to establish a densified hydrological network of water levels with high spatial and temporal resolution. This paper addresses a key issue of the entire system: the detection of running water shore lines in smartphone images. Flowing water never appears equally in close-range images even if the extrinsics remain unchanged. Its non-rigid behavior impedes the use of good practices for image segmentation as a prerequisite for water line detection. Consequently, we use a hand-held time lapse image sequence instead of a single image that provides the time component to determine a spatio-temporal texture image. Using a region growing concept, the texture is analyzed for immutable shore and dynamic water areas. Finally, the prevalent shore line is examined by the resultant shapes. For method validation, various study areas are observed from several distances covering urban and rural flowing waters with different characteristics. Future work provides a transformation of the water line into object space by image-to-geometry intersection.

Damage extraction of buildings in the 2015 Gorkha, Nepal earthquake from high-resolution SAR data

NASA Astrophysics Data System (ADS)

Yamazaki, Fumio; Bahri, Rendy; Liu, Wen; Sasagawa, Tadashi

2016-05-01

Satellite remote sensing is recognized as one of the effective tools for detecting and monitoring affected areas due to natural disasters. Since SAR sensors can capture images not only at daytime but also at nighttime and under cloud-cover conditions, they are especially useful at an emergency response period. In this study, multi-temporal high-resolution TerraSAR-X images were used for damage inspection of the Kathmandu area, which was severely affected by the April 25, 2015 Gorkha Earthquake. The SAR images obtained before and after the earthquake were utilized for calculating the difference and correlation coefficient of backscatter. The affected areas were identified by high values of the absolute difference and low values of the correlation coefficient. The post-event high-resolution optical satellite images were employed as ground truth data to verify our results. Although it was difficult to estimate the damage levels for individual buildings, the high resolution SAR images could illustrate their capability in detecting collapsed buildings at emergency response times.

Lp(a) (Lipoprotein(a)) Levels Predict Progression of Carotid Atherosclerosis in Subjects With Atherosclerotic Cardiovascular Disease on Intensive Lipid Therapy: An Analysis of the AIM-HIGH (Atherothrombosis Intervention in Metabolic Syndrome With Low HDL/High Triglycerides: Impact on Global Health Outcomes) Carotid Magnetic Resonance Imaging Substudy-Brief Report.

PubMed

Hippe, Daniel S; Phan, Binh An P; Sun, Jie; Isquith, Daniel A; O'Brien, Kevin D; Crouse, John R; Anderson, Todd; Huston, John; Marcovina, Santica M; Hatsukami, Thomas S; Yuan, Chun; Zhao, Xue-Qiao

2018-03-01

To assess whether Lp(a) (lipoprotein(a)) levels and other lipid levels were predictive of progression of atherosclerosis burden as assessed by carotid magnetic resonance imaging in subjects who have been treated with LDL-C (low-density lipoprotein cholesterol)-lowering therapy and participated in the AIM-HIGH trial (Atherothrombosis Intervention in Metabolic Syndrome With Low HDL/High Triglycerides: Impact on Global Health Outcomes). AIM-HIGH was a randomized, double-blind study of subjects with established vascular disease, elevated triglycerides, and low HDL-C (high-density lipoprotein cholesterol). One hundred fifty-two AIM-HIGH subjects underwent both baseline and 2-year follow-up carotid artery magnetic resonance imaging. Plaque burden was measured by the percent wall volume (%WV) of the carotid artery. Associations between annualized change in %WV with baseline and on-study (1 year) lipid variables were evaluated using multivariate linear regression and the Bonferroni correction to account for multiple comparisons. Average %WV at baseline was 41.6±6.8% and annualized change in %WV over 2 years ranged from -3.2% to 3.7% per year (mean: 0.2±1.1% per year; P =0.032). Increases in %WV were significantly associated with higher baseline Lp(a) (β=0.34 per 1-SD increase of Lp(a); 95% confidence interval, 0.15-0.52; P <0.001) after adjusting for clinical risk factors and other lipid levels. On-study Lp(a) had a similar positive association with %WV progression (β=0.33; 95% confidence interval, 0.15-0.52; P <0.001). Despite intensive lipid therapy, aimed at aggressively lowering LDL-C to <70 mg/dL, carotid atherosclerosis continued to progress as assessed by carotid magnetic resonance imaging and that elevated Lp(a) levels were independent predictors of increases in atherosclerosis burden. © 2018 American Heart Association, Inc.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features.

PubMed

Li, Linyi; Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images.

Fuzzy Classification of High Resolution Remote Sensing Scenes Using Visual Attention Features

PubMed Central

Xu, Tingbao; Chen, Yun

2017-01-01

In recent years the spatial resolutions of remote sensing images have been improved greatly. However, a higher spatial resolution image does not always lead to a better result of automatic scene classification. Visual attention is an important characteristic of the human visual system, which can effectively help to classify remote sensing scenes. In this study, a novel visual attention feature extraction algorithm was proposed, which extracted visual attention features through a multiscale process. And a fuzzy classification method using visual attention features (FC-VAF) was developed to perform high resolution remote sensing scene classification. FC-VAF was evaluated by using remote sensing scenes from widely used high resolution remote sensing images, including IKONOS, QuickBird, and ZY-3 images. FC-VAF achieved more accurate classification results than the others according to the quantitative accuracy evaluation indices. We also discussed the role and impacts of different decomposition levels and different wavelets on the classification accuracy. FC-VAF improves the accuracy of high resolution scene classification and therefore advances the research of digital image analysis and the applications of high resolution remote sensing images. PMID:28761440

A microdisplay-based HUD for automotive applications: Backplane design, planarization, and optical implementation

NASA Astrophysics Data System (ADS)

Schuck, Miller Harry

Automotive head-up displays require compact, bright, and inexpensive imaging systems. In this thesis, a compact head-up display (HUD) utilizing liquid-crystal-on-silicon microdisplay technology is presented from concept to implementation. The thesis comprises three primary areas of HUD research: the specification, design and implementation of a compact HUD optical system, the development of a wafer planarization process to enhance reflective device brightness and light immunity and the design, fabrication and testing of an inexpensive 640 x 512 pixel active matrix backplane intended to meet the HUD requirements. The thesis addresses the HUD problem at three levels, the systems level, the device level, and the materials level. At the systems level, the optical design of an automotive HUD must meet several competing requirements, including high image brightness, compact packaging, video-rate performance, and low cost. An optical system design which meets the competing requirements has been developed utilizing a fully-reconfigurable reflective microdisplay. The design consists of two optical stages, the first a projector stage which magnifies the display, and a second stage which forms the virtual image eventually seen by the driver. A key component of the optical system is a diffraction grating/field lens which forms a large viewing eyebox while reducing the optical system complexity. Image quality biocular disparity and luminous efficacy were analyzed and results of the optical implementation are presented. At the device level, the automotive HUD requires a reconfigurable, video-rate, high resolution image source for applications such as navigation and night vision. The design of a 640 x 512 pixel active matrix backplane which meets the requirements of the HUD is described. The backplane was designed to produce digital field sequential color images at video rates utilizing fast switching liquid crystal as the modulation layer. The design methodology is discussed, and the example of a clock generator is described from design to implementation. Electrical and optical test results of the fabricated backplane are presented. At the materials level, a planarization method was developed to meet the stringent brightness requirements of automotive HUD's. The research efforts described here have resulted in a simple, low cost post-processing method for planarizing microdisplay substrates based on a spin-cast polymeric resin, benzocyclobutene (BCB). Six- fold reductions in substrate step height were accomplished with a single coating. Via masking and dry etching methods were developed. High reflectivity metal was deposited and patterned over the planarized substrate to produce high aperture pixel mirrors. The process is simple, rapid, and results in microdisplays better able to meet the stringent requirements of high brightness display systems. Methods and results of the post- processing are described.

High Level of Agreement Between Pretherapeutic 124I PET and Intratherapeutic 131I Imaging in Detecting Iodine-Positive Thyroid Cancer Metastases.

PubMed

Ruhlmann, Marcus; Jentzen, Walter; Ruhlmann, Verena; Pettinato, Cinzia; Rossi, Gloria; Binse, Ina; Bockisch, Andreas; Rosenbaum-Krumme, Sandra

2016-09-01

The aim of this retrospective study was to assess the level of agreement between PET and scintigraphy using diagnostic amounts of (124)I and therapeutic amounts of (131)I, respectively, in detecting iodine-positive metastases in patients with differentiated thyroid carcinoma. The study included patients who underwent PET /: CT 24 and 120 h after administration of approximately 25 MBq of (124)I and subsequently underwent imaging 5-10 d after administration of 1-10 GBq of (131)I. For each patient, the intratherapeutic (131)I imaging comprised a whole-body scintigraphy scan and a SPECT/CT scan of the neck to distinguish between metastatic and thyroid remnant tissues. Iodine uptake was rated as a metastatic focus if located outside the thyroid bed. Lesion- and patient-based analyses were performed. The study included 137 patients with 227 metastases iodine-positive on both functional imaging modalities. In the lesion-based analysis, (124)I PET and (131)I imaging detected 98% (223/227) and 99% (225/227) of the iodine-positive metastases, respectively; the level of agreement between (124)I PET and (131)I imaging was 97% (221/227). Four metastases (3 lymph node and 1 bone) in 4 patients were (124)I-negative but (131)I-positive, and 2 lymph node metastases in 2 patients were (131)I-negative but (124)I-positive. In the patient-based analysis, 61 of the 137 patients presented with iodine-positive metastases. (124)I PET and (131)I imaging detected at least one iodine-positive metastasis in 97% (59/61) and 98% (60/61) of the patients, respectively. The level of agreement was 95% (58/61). Both imaging modalities concordantly identified 76 of 137 patients without pathologic iodine uptake. Because of the high level of agreement, pretherapeutic (124)I PET/CT is an adequate methodology in the detection of iodine-positive metastases and can be used as a reliable tool for staging of thyroid cancer patients and individualized treatment planning. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Different source image fusion based on FPGA

NASA Astrophysics Data System (ADS)

Luo, Xiao; Piao, Yan

2016-03-01

The fusion technology of video image is to make the video obtained by different image sensors complementary to each other by some technical means, so as to obtain the video information which is rich in information and suitable for the human eye system. Infrared cameras in harsh environments such as when smoke, fog and low light situations penetrating power, but the ability to obtain the details of the image is poor, does not meet the human visual system. Single visible light imaging can be rich in detail, high resolution images and for the visual system, but the visible image easily affected by the external environment. Infrared image and visible image fusion process involved in the video image fusion algorithm complexity and high calculation capacity, have occupied more memory resources, high clock rate requirements, such as software, c ++, c, etc. to achieve more, but based on Hardware platform less. In this paper, based on the imaging characteristics of infrared images and visible light images, the software and hardware are combined to obtain the registration parameters through software matlab, and the gray level weighted average method is used to implement the hardware platform. Information fusion, and finally the fusion image can achieve the goal of effectively improving the acquisition of information to increase the amount of information in the image.

Low-level image properties in facial expressions.

PubMed

Menzel, Claudia; Redies, Christoph; Hayn-Leichsenring, Gregor U

2018-06-04

We studied low-level image properties of face photographs and analyzed whether they change with different emotional expressions displayed by an individual. Differences in image properties were measured in three databases that depicted a total of 167 individuals. Face images were used either in their original form, cut to a standard format or superimposed with a mask. Image properties analyzed were: brightness, redness, yellowness, contrast, spectral slope, overall power and relative power in low, medium and high spatial frequencies. Results showed that image properties differed significantly between expressions within each individual image set. Further, specific facial expressions corresponded to patterns of image properties that were consistent across all three databases. In order to experimentally validate our findings, we equalized the luminance histograms and spectral slopes of three images from a given individual who showed two expressions. Participants were significantly slower in matching the expression in an equalized compared to an original image triad. Thus, existing differences in these image properties (i.e., spectral slope, brightness or contrast) facilitate emotion detection in particular sets of face images. Copyright © 2018. Published by Elsevier B.V.

Rapid brain MRI acquisition techniques at ultra-high fields

PubMed Central

Setsompop, Kawin; Feinberg, David A.; Polimeni, Jonathan R.

2017-01-01

Ultra-high-field MRI provides large increases in signal-to-noise ratio as well as enhancement of several contrast mechanisms in both structural and functional imaging. Combined, these gains result in a substantial boost in contrast-to-noise ratio that can be exploited for higher spatial resolution imaging to extract finer-scale information about the brain. With increased spatial resolution, however, is a concurrent increased image encoding burden that can cause unacceptably long scan times for structural imaging and slow temporal sampling of the hemodynamic response in functional MRI—particularly when whole-brain imaging is desired. To address this issue, new directions of imaging technology development—such as the move from conventional 2D slice-by-slice imaging to more efficient Simultaneous MultiSlice (SMS) or MultiBand imaging (which can be viewed as “pseudo-3D” encoding) as well as full 3D imaging—have provided dramatic improvements in acquisition speed. Such imaging paradigms provide higher SNR efficiency as well as improved encoding efficiency. Moreover, SMS and 3D imaging can make better use of coil sensitivity information in multi-channel receiver arrays used for parallel imaging acquisitions through controlled aliasing in multiple spatial directions. This has enabled unprecedented acceleration factors of an order of magnitude or higher in these imaging acquisition schemes, with low image artifact levels and high SNR. Here we review the latest developments of SMS and 3D imaging methods and related technologies at ultra-high field for rapid high-resolution functional and structural imaging of the brain. PMID:26835884

Radiation dose reduction in a neonatal intensive care unit in computed radiography.

PubMed

Frayre, A S; Torres, P; Gaona, E; Rivera, T; Franco, J; Molina, N

2012-12-01

The purpose of this study was to evaluate the dose received by chest x-rays in neonatal care with thermoluminescent dosimetry and to determine the level of exposure where the quantum noise level does not affect the diagnostic image quality in order to reduce the dose to neonates. In pediatric radiology, especially the prematurely born children are highly sensitive to the radiation because of the highly mitotic state of their cells; in general, the sensitivity of a tissue to radiation is directly proportional to its rate of proliferation. The sample consisted of 208 neonatal chest x-rays of 12 neonates admitted and treated in a Neonatal Intensive Care Unit (NICU). All the neonates were preterm in the range of 28-34 weeks, with a mean of 30.8 weeks. Entrance Surface Doses (ESD) values for chest x-rays are higher than the DRL of 50 μGy proposed by the National Radiological Protection Board (NRPB). In order to reduce the dose to neonates, the optimum image quality was achieved by determining the level of ESD where level noise does not affect the diagnostic image quality. The optimum ESD was estimated for additional 20 chest x-rays increasing kVp and reducing mAs until quantum noise affects image quality. Copyright © 2012 Elsevier Ltd. All rights reserved.

LWIR pupil imaging and longer-term calibration stability

NASA Astrophysics Data System (ADS)

LeVan, Paul D.; Sakoglu, Ünal

2016-09-01

A previous paper described LWIR pupil imaging, and an improved understanding of the behavior of this type of sensor for which the high-sensitivity focal plane array (FPA) operated at higher flux levels includes a reversal in signal integration polarity. We have since considered a candidate methodology for efficient, long-term calibration stability that exploits the following two properties of pupil imaging: (1) a fixed pupil position on the FPA, and (2) signal levels from the scene imposed on significant but fixed LWIR background levels. These two properties serve to keep each pixel operating over a limited dynamic range that corresponds to its location in the pupil and to the signal levels generated at this location by the lower and upper calibration flux levels. Exploiting this property for which each pixel of the Pupil Imager operates over its limited dynamic range, the signal polarity reversal between low and high flux pixels, which occurs for a circular region of pixels near the upper edges of the pupil illumination profile, can be rectified to unipolar integration with a two-level non-uniformity correction (NUC). Images corrected real-time with standard non-uniformity correction (NUC) techniques, are still subject to longer-term drifts in pixel offsets between recalibrations. Long-term calibration stability might then be achieved using either a scene-based non-uniformity correction approach, or with periodic repointing for off-source background estimation and subtraction. Either approach requires dithering of the field of view, by sub-pixel amounts for the first method, or by large off-source motions outside the 0.38 milliradian FOV for the latter method. We report on the results of investigations along both these lines.

Using High-Dimensional Image Models to Perform Highly Undetectable Steganography

NASA Astrophysics Data System (ADS)

Pevný, Tomáš; Filler, Tomáš; Bas, Patrick

This paper presents a complete methodology for designing practical and highly-undetectable stegosystems for real digital media. The main design principle is to minimize a suitably-defined distortion by means of efficient coding algorithm. The distortion is defined as a weighted difference of extended state-of-the-art feature vectors already used in steganalysis. This allows us to "preserve" the model used by steganalyst and thus be undetectable even for large payloads. This framework can be efficiently implemented even when the dimensionality of the feature set used by the embedder is larger than 107. The high dimensional model is necessary to avoid known security weaknesses. Although high-dimensional models might be problem in steganalysis, we explain, why they are acceptable in steganography. As an example, we introduce HUGO, a new embedding algorithm for spatial-domain digital images and we contrast its performance with LSB matching. On the BOWS2 image database and in contrast with LSB matching, HUGO allows the embedder to hide 7× longer message with the same level of security level.

Rocking curve imaging of high quality sapphire crystals in backscattering geometry

DOE PAGES

Jafari, A.; European Synchrotron Radiation Facility; Univ. of Liege,; ...

2017-01-23

Here, we report on the characterization of high quality sapphire single crystals suitable for high-resolution X-ray optics at high energy. Investigations using rocking curve imaging reveal the crystals to be of uniformly good quality at the level of ~10 -4 in lattice parameter variations, deltad/d. But, investigations using backscattering rocking curve imaging with lattice spacing resolution of deltad/d ~ 5.10 -8 shows very diverse quality maps for all crystals. Our results highlight nearly ideal areas with edge length of 0.2-0.5 mm in most crystals, but a comparison of the back re ection peak positions shows that even neighboring ideal areasmore » exhibit a relative difference in the lattice parameters on the order of deltad/d = 10-20.10 -8; this is several times larger than the rocking curve width. Furthermore, the stress-strain analysis suggests that an extremely stringent limit on the strain at a level of ~100 kPa in the growth process is required in order to produce crystals with large areas of the quality required for X-ray optics at high energy.« less

Wavelet-based de-noising algorithm for images acquired with parallel magnetic resonance imaging (MRI).

PubMed

Delakis, Ioannis; Hammad, Omer; Kitney, Richard I

2007-07-07

Wavelet-based de-noising has been shown to improve image signal-to-noise ratio in magnetic resonance imaging (MRI) while maintaining spatial resolution. Wavelet-based de-noising techniques typically implemented in MRI require that noise displays uniform spatial distribution. However, images acquired with parallel MRI have spatially varying noise levels. In this work, a new algorithm for filtering images with parallel MRI is presented. The proposed algorithm extracts the edges from the original image and then generates a noise map from the wavelet coefficients at finer scales. The noise map is zeroed at locations where edges have been detected and directional analysis is also used to calculate noise in regions of low-contrast edges that may not have been detected. The new methodology was applied on phantom and brain images and compared with other applicable de-noising techniques. The performance of the proposed algorithm was shown to be comparable with other techniques in central areas of the images, where noise levels are high. In addition, finer details and edges were maintained in peripheral areas, where noise levels are low. The proposed methodology is fully automated and can be applied on final reconstructed images without requiring sensitivity profiles or noise matrices of the receiver coils, therefore making it suitable for implementation in a clinical MRI setting.

Digital shaded relief image of a carbonate platform (northern Great Bahama Bank): Scenery seen and unseen

NASA Astrophysics Data System (ADS)

Boss, Stephen K.

1996-11-01

A mosaic image of the northern Great Bahama Bank was created from separate gray-scale Landsat images using photo-editing and image analysis software that is commercially available for desktop computers. Measurements of pixel gray levels (relative scale from 0 to 255 referred to as digital number, DN) on the mosaic image were compared to bank-top bathymetry (determined from a network of single-channel, high-resolution seismic profiles), bottom type (coarse sand, sandy mud, barren rock, or reef determined from seismic profiles and diver observations), and vegetative cover (presence and/or absence and relative density of the marine angiosperm Thalassia testudinum determined from diver observations). Results of these analyses indicate that bank-top bathymetry is a primary control on observed pixel DN, bottom type is a secondary control on pixel DN, and vegetative cover is a tertiary influence on pixel DN. Consequently, processing of the gray-scale Landsat mosaic with a directional gradient edge-detection filter generated a physiographic shaded relief image resembling bank-top bathymetric patterns related to submerged physiographic features across the platform. The visibility of submerged karst landforms, Pleistocene eolianite ridges, islands, and possible paleo-drainage patterns created during sea-level lowstands is significantly enhanced on processed images relative to the original mosaic. Bank-margin ooid shoals, platform interior sand bodies, reef edifices, and bidirectional sand waves are features resulting from Holocene carbonate deposition that are also more clearly visible on the new physiographic images. Combined with observational data (single-channel, high-resolution seismic profiles, bottom observations by SCUBA divers, sediment and rock cores) across the northern Great Bahama Bank, these physiographic images facilitate comprehension of areal relations among antecedent platform topography, physical processes, and ensuing depositional patterns during sea-level rise.

High-speed adaptive optics line scan confocal retinal imaging for human eye

PubMed Central

Wang, Xiaolin; Zhang, Yuhua

2017-01-01

Purpose Continuous and rapid eye movement causes significant intraframe distortion in adaptive optics high resolution retinal imaging. To minimize this artifact, we developed a high speed adaptive optics line scan confocal retinal imaging system. Methods A high speed line camera was employed to acquire retinal image and custom adaptive optics was developed to compensate the wave aberration of the human eye’s optics. The spatial resolution and signal to noise ratio were assessed in model eye and in living human eye. The improvement of imaging fidelity was estimated by reduction of intra-frame distortion of retinal images acquired in the living human eyes with frame rates at 30 frames/second (FPS), 100 FPS, and 200 FPS. Results The device produced retinal image with cellular level resolution at 200 FPS with a digitization of 512×512 pixels/frame in the living human eye. Cone photoreceptors in the central fovea and rod photoreceptors near the fovea were resolved in three human subjects in normal chorioretinal health. Compared with retinal images acquired at 30 FPS, the intra-frame distortion in images taken at 200 FPS was reduced by 50.9% to 79.7%. Conclusions We demonstrated the feasibility of acquiring high resolution retinal images in the living human eye at a speed that minimizes retinal motion artifact. This device may facilitate research involving subjects with nystagmus or unsteady fixation due to central vision loss. PMID:28257458

Highly accelerated cardiovascular MR imaging using many channel technology: concepts and clinical applications

PubMed Central

Sodickson, Daniel K.

2010-01-01

Cardiovascular magnetic resonance imaging (CVMRI) is of proven clinical value in the non-invasive imaging of cardiovascular diseases. CVMRI requires rapid image acquisition, but acquisition speed is fundamentally limited in conventional MRI. Parallel imaging provides a means for increasing acquisition speed and efficiency. However, signal-to-noise (SNR) limitations and the limited number of receiver channels available on most MR systems have in the past imposed practical constraints, which dictated the use of moderate accelerations in CVMRI. High levels of acceleration, which were unattainable previously, have become possible with many-receiver MR systems and many-element, cardiac-optimized RF-coil arrays. The resulting imaging speed improvements can be exploited in a number of ways, ranging from enhancement of spatial and temporal resolution to efficient whole heart coverage to streamlining of CVMRI work flow. In this review, examples of these strategies are provided, following an outline of the fundamentals of the highly accelerated imaging approaches employed in CVMRI. Topics discussed include basic principles of parallel imaging; key requirements for MR systems and RF-coil design; practical considerations of SNR management, supported by multi-dimensional accelerations, 3D noise averaging and high field imaging; highly accelerated clinical state-of-the art cardiovascular imaging applications spanning the range from SNR-rich to SNR-limited; and current trends and future directions. PMID:17562047

High-speed adaptive optics line scan confocal retinal imaging for human eye.

PubMed

Lu, Jing; Gu, Boyu; Wang, Xiaolin; Zhang, Yuhua

2017-01-01

Continuous and rapid eye movement causes significant intraframe distortion in adaptive optics high resolution retinal imaging. To minimize this artifact, we developed a high speed adaptive optics line scan confocal retinal imaging system. A high speed line camera was employed to acquire retinal image and custom adaptive optics was developed to compensate the wave aberration of the human eye's optics. The spatial resolution and signal to noise ratio were assessed in model eye and in living human eye. The improvement of imaging fidelity was estimated by reduction of intra-frame distortion of retinal images acquired in the living human eyes with frame rates at 30 frames/second (FPS), 100 FPS, and 200 FPS. The device produced retinal image with cellular level resolution at 200 FPS with a digitization of 512×512 pixels/frame in the living human eye. Cone photoreceptors in the central fovea and rod photoreceptors near the fovea were resolved in three human subjects in normal chorioretinal health. Compared with retinal images acquired at 30 FPS, the intra-frame distortion in images taken at 200 FPS was reduced by 50.9% to 79.7%. We demonstrated the feasibility of acquiring high resolution retinal images in the living human eye at a speed that minimizes retinal motion artifact. This device may facilitate research involving subjects with nystagmus or unsteady fixation due to central vision loss.

Analysis of Students' Aptitude to Provide Meaning to Images that Represent Cellular Components at the Molecular Level

PubMed Central

Dahmani, Hassen-Reda; Schneeberger, Patricia

2009-01-01

The number of experimentally derived structures of cellular components is rapidly expanding, and this phenomenon is accompanied by the development of a new semiotic system for teaching. The infographic approach is shifting from a schematic toward a more realistic representation of cellular components. By realistic we mean artist-prepared or computer graphic images that closely resemble experimentally derived structures and are characterized by a low level of styling and simplification. This change brings about a new challenge for teachers: designing course instructions that allow students to interpret these images in a meaningful way. To determine how students deal with this change, we designed several image-based, in-course assessments. The images were highly relevant for the cell biology course but did not resemble any of the images in the teaching documents. We asked students to label the cellular components, describe their function, or both. What we learned from these tests is that realistic images, with a higher apparent level of complexity, do not deter students from investigating their meaning. When given a choice, the students do not necessarily choose the most simplified representation, and they were sensitive to functional indications embedded in realistic images. PMID:19723817

Performance of PHOTONIS' low light level CMOS imaging sensor for long range observation

NASA Astrophysics Data System (ADS)

Bourree, Loig E.

2014-05-01

Identification of potential threats in low-light conditions through imaging is commonly achieved through closed-circuit television (CCTV) and surveillance cameras by combining the extended near infrared (NIR) response (800-10000nm wavelengths) of the imaging sensor with NIR LED or laser illuminators. Consequently, camera systems typically used for purposes of long-range observation often require high-power lasers in order to generate sufficient photons on targets to acquire detailed images at night. While these systems may adequately identify targets at long-range, the NIR illumination needed to achieve such functionality can easily be detected and therefore may not be suitable for covert applications. In order to reduce dependency on supplemental illumination in low-light conditions, the frame rate of the imaging sensors may be reduced to increase the photon integration time and thus improve the signal to noise ratio of the image. However, this may hinder the camera's ability to image moving objects with high fidelity. In order to address these particular drawbacks, PHOTONIS has developed a CMOS imaging sensor (CIS) with a pixel architecture and geometry designed specifically to overcome these issues in low-light level imaging. By combining this CIS with field programmable gate array (FPGA)-based image processing electronics, PHOTONIS has achieved low-read noise imaging with enhanced signal-to-noise ratio at quarter moon illumination, all at standard video frame rates. The performance of this CIS is discussed herein and compared to other commercially available CMOS and CCD for long-range observation applications.

A Scientific Workflow Platform for Generic and Scalable Object Recognition on Medical Images

NASA Astrophysics Data System (ADS)

Möller, Manuel; Tuot, Christopher; Sintek, Michael

In the research project THESEUS MEDICO we aim at a system combining medical image information with semantic background knowledge from ontologies to give clinicians fully cross-modal access to biomedical image repositories. Therefore joint efforts have to be made in more than one dimension: Object detection processes have to be specified in which an abstraction is performed starting from low-level image features across landmark detection utilizing abstract domain knowledge up to high-level object recognition. We propose a system based on a client-server extension of the scientific workflow platform Kepler that assists the collaboration of medical experts and computer scientists during development and parameter learning.

Intravital imaging of cardiac function at the single-cell level.

PubMed

Aguirre, Aaron D; Vinegoni, Claudio; Sebas, Matt; Weissleder, Ralph

2014-08-05

Knowledge of cardiomyocyte biology is limited by the lack of methods to interrogate single-cell physiology in vivo. Here we show that contracting myocytes can indeed be imaged with optical microscopy at high temporal and spatial resolution in the beating murine heart, allowing visualization of individual sarcomeres and measurement of the single cardiomyocyte contractile cycle. Collectively, this has been enabled by efficient tissue stabilization, a prospective real-time cardiac gating approach, an image processing algorithm for motion-artifact-free imaging throughout the cardiac cycle, and a fluorescent membrane staining protocol. Quantification of cardiomyocyte contractile function in vivo opens many possibilities for investigating myocardial disease and therapeutic intervention at the cellular level.

A model of attention-guided visual perception and recognition.

PubMed

Rybak, I A; Gusakova, V I; Golovan, A V; Podladchikova, L N; Shevtsova, N A

1998-08-01

A model of visual perception and recognition is described. The model contains: (i) a low-level subsystem which performs both a fovea-like transformation and detection of primary features (edges), and (ii) a high-level subsystem which includes separated 'what' (sensory memory) and 'where' (motor memory) structures. Image recognition occurs during the execution of a 'behavioral recognition program' formed during the primary viewing of the image. The recognition program contains both programmed attention window movements (stored in the motor memory) and predicted image fragments (stored in the sensory memory) for each consecutive fixation. The model shows the ability to recognize complex images (e.g. faces) invariantly with respect to shift, rotation and scale.

Combined 18F-Fluciclovine PET/MRI Shows Potential for Detection and Characterization of High-Risk Prostate Cancer.

PubMed

Elschot, Mattijs; Selnæs, Kirsten M; Sandsmark, Elise; Krüger-Stokke, Brage; Størkersen, Øystein; Giskeødegård, Guro F; Tessem, May-Britt; Moestue, Siver A; Bertilsson, Helena; Bathen, Tone F

2018-05-01

The objective of this study was to investigate whether quantitative imaging features derived from combined 18 F-fluciclovine PET/multiparametric MRI show potential for detection and characterization of primary prostate cancer. Methods: Twenty-eight patients diagnosed with high-risk prostate cancer underwent simultaneous 18 F-fluciclovine PET/MRI before radical prostatectomy. Volumes of interest (VOIs) for prostate tumors, benign prostatic hyperplasia (BPH) nodules, prostatitis, and healthy tissue were delineated on T2-weighted images, using histology as a reference. Tumor VOIs were marked as high-grade (≥Gleason grade group 3) or not. MRI and PET features were extracted on the voxel and VOI levels. Partial least-squared discriminant analysis (PLS-DA) with double leave-one-patient-out cross-validation was performed to distinguish tumors from benign tissue (BPH, prostatitis, or healthy tissue) and high-grade tumors from other tissue (low-grade tumors or benign tissue). The performance levels of PET, MRI, and combined PET/MRI features were compared using the area under the receiver-operating-characteristic curve (AUC). Results: Voxel and VOI features were extracted from 40 tumor VOIs (26 high-grade), 36 BPH VOIs, 6 prostatitis VOIs, and 37 healthy-tissue VOIs. PET/MRI performed better than MRI and PET alone for distinguishing tumors from benign tissue (AUCs of 87%, 81%, and 83%, respectively, at the voxel level and 96%, 93%, and 93%, respectively, at the VOI level) and high-grade tumors from other tissue (AUCs of 85%, 79%, and 81%, respectively, at the voxel level and 93%, 93%, and 91%, respectively, at the VOI level). T2-weighted MRI, diffusion-weighted MRI, and PET features were the most important for classification. Conclusion: Combined 18 F-fluciclovine PET/multiparametric MRI shows potential for improving detection and characterization of high-risk prostate cancer, in comparison to MRI and PET alone. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Automatic Rooftop Extraction in Stereo Imagery Using Distance and Building Shape Regularized Level Set Evolution

NASA Astrophysics Data System (ADS)

Tian, J.; Krauß, T.; d'Angelo, P.

2017-05-01

Automatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper, we show how to fuse the spectral and height information of stereo imagery to achieve an efficient and robust rooftop extraction. In the first step, the digital terrain model (DTM) and in turn the normalized digital surface model (nDSM) is generated by using a newly step-edge approach. In the second step, the initial building locations and rooftop boundaries are derived by removing the low-level pixels and high-level pixels with higher probability to be trees and shadows. This boundary is then served as the initial level set function, which is further refined to fit the best possible boundaries through distance regularized level-set curve evolution. During the fitting procedure, the edge-based active contour model is adopted and implemented by using the edges indicators extracted from panchromatic image. The performance of the proposed approach is tested by using the WorldView-2 satellite data captured over Munich.

Infrared and Visible Image Fusion Based on Different Constraints in the Non-Subsampled Shearlet Transform Domain.

PubMed

Huang, Yan; Bi, Duyan; Wu, Dongpeng

2018-04-11

There are many artificial parameters when fuse infrared and visible images, to overcome the lack of detail in the fusion image because of the artifacts, a novel fusion algorithm for infrared and visible images that is based on different constraints in non-subsampled shearlet transform (NSST) domain is proposed. There are high bands and low bands of images that are decomposed by the NSST. After analyzing the characters of the bands, fusing the high level bands by the gradient constraint, the fused image can obtain more details; fusing the low bands by the constraint of saliency in the images, the targets are more salient. Before the inverse NSST, the Nash equilibrium is used to update the coefficient. The fused images and the quantitative results demonstrate that our method is more effective in reserving details and highlighting the targets when compared with other state-of-the-art methods.

Infrared and Visible Image Fusion Based on Different Constraints in the Non-Subsampled Shearlet Transform Domain

PubMed Central

Huang, Yan; Bi, Duyan; Wu, Dongpeng

2018-01-01

There are many artificial parameters when fuse infrared and visible images, to overcome the lack of detail in the fusion image because of the artifacts, a novel fusion algorithm for infrared and visible images that is based on different constraints in non-subsampled shearlet transform (NSST) domain is proposed. There are high bands and low bands of images that are decomposed by the NSST. After analyzing the characters of the bands, fusing the high level bands by the gradient constraint, the fused image can obtain more details; fusing the low bands by the constraint of saliency in the images, the targets are more salient. Before the inverse NSST, the Nash equilibrium is used to update the coefficient. The fused images and the quantitative results demonstrate that our method is more effective in reserving details and highlighting the targets when compared with other state-of-the-art methods. PMID:29641505

Dual-tracer background subtraction approach for fluorescent molecular tomography

PubMed Central

Holt, Robert W.; El-Ghussein, Fadi; Davis, Scott C.; Samkoe, Kimberley S.; Gunn, Jason R.; Leblond, Frederic

2013-01-01

Abstract. Diffuse fluorescence tomography requires high contrast-to-background ratios to accurately reconstruct inclusions of interest. This is a problem when imaging the uptake of fluorescently labeled molecularly targeted tracers in tissue, which can result in high levels of heterogeneously distributed background uptake. We present a dual-tracer background subtraction approach, wherein signal from the uptake of an untargeted tracer is subtracted from targeted tracer signal prior to image reconstruction, resulting in maps of targeted tracer binding. The approach is demonstrated in simulations, a phantom study, and in a mouse glioma imaging study, demonstrating substantial improvement over conventional and homogenous background subtraction image reconstruction approaches. PMID:23292612

3D Imaging of Microbial Biofilms: Integration of Synchrotron Imaging and an Interactive Visualization Interface

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

Thomas, Mathew; Marshall, Matthew J.; Miller, Erin A.

2014-08-26

Understanding the interactions of structured communities known as “biofilms” and other complex matrixes is possible through the X-ray micro tomography imaging of the biofilms. Feature detection and image processing for this type of data focuses on efficiently identifying and segmenting biofilms and bacteria in the datasets. The datasets are very large and often require manual interventions due to low contrast between objects and high noise levels. Thus new software is required for the effectual interpretation and analysis of the data. This work specifies the evolution and application of the ability to analyze and visualize high resolution X-ray micro tomography datasets.

The effect of microchannel plate gain depression on PAPA photon counting cameras

NASA Astrophysics Data System (ADS)

Sams, Bruce J., III

1991-03-01

PAPA (precision analog photon address) cameras are photon counting imagers which employ microchannel plates (MCPs) for image intensification. They have been used extensively in astronomical speckle imaging. The PAPA camera can produce artifacts when light incident on its MCP is highly concentrated. The effect is exacerbated by adjusting the strobe detection level too low, so that the camera accepts very small MCP pulses. The artifacts can occur even at low total count rates if the image has highly a concentrated bright spot. This paper describes how to optimize PAPA camera electronics, and describes six techniques which can avoid or minimize addressing errors.

Carotid dual-energy CT angiography: Evaluation of low keV calculated monoenergetic datasets by means of a frequency-split approach for noise reduction at low keV levels.

PubMed

Riffel, Philipp; Haubenreisser, Holger; Meyer, Mathias; Sudarski, Sonja; Morelli, John N; Schmidt, Bernhard; Schoenberg, Stefan O; Henzler, Thomas

2016-04-01

Calculated monoenergetic ultra-low keV datasets did not lead to improved contrast-to-noise ratio (CNR) due to the dramatic increase in image noise. The aim of the present study was to evaluate the objective image quality of ultra-low keV monoenergetic images (MEIs) calculated from carotid DECT angiography data with a new monoenergetic imaging algorithm using a frequency-split technique. 20 patients (12 male; mean age 53±17 years) were retrospectively analyzed. MEIs from 40 to 120 keV were reconstructed using the monoenergetic split frequency approach (MFSA). Additionally MEIs were reconstructed for 40 and 50 keV using a conventional monoenergetic (CM) software application. Signal intensity, noise, signal-to-noise ratio (SNR) and CNR were assessed in the basilar, common, internal carotid arteries. Ultra-low keV MEIs at 40 keV and 50 keV demonstrated highest vessel attenuation, significantly greater than those of the polyenergetic images (PEI) (all p-values <0.05). The highest SNR level and CNR level was found at 40 keV and 50 keV (all p-values <0.05). MEIs with MFSA showed significantly lower noise levels than those processed with CM (all p-values <0.05) and no significant differences in vessel attenuation (p>0.05). Thus MEIs with MFSA showed significantly higher SNR and CNR compared to MEIs with CM. Combining the lower spatial frequency stack for contrast at low keV levels with the high spatial frequency stack for noise at high keV levels (frequency-split technique) leads to improved image quality of ultra-low keV monoenergetic DECT datasets when compared to previous monoenergetic reconstruction techniques without the frequency-split technique. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Color line scan camera technology and machine vision: requirements to consider

NASA Astrophysics Data System (ADS)

Paernaenen, Pekka H. T.

1997-08-01

Color machine vision has shown a dynamic uptrend in use within the past few years as the introduction of new cameras and scanner technologies itself underscores. In the future, the movement from monochrome imaging to color will hasten, as machine vision system users demand more knowledge about their product stream. As color has come to the machine vision, certain requirements for the equipment used to digitize color images are needed. Color machine vision needs not only a good color separation but also a high dynamic range and a good linear response from the camera used. Good dynamic range and linear response is necessary for color machine vision. The importance of these features becomes even more important when the image is converted to another color space. There is always lost some information when converting integer data to another form. Traditionally the color image processing has been much slower technique than the gray level image processing due to the three times greater data amount per image. The same has applied for the three times more memory needed. The advancements in computers, memory and processing units has made it possible to handle even large color images today cost efficiently. In some cases he image analysis in color images can in fact even be easier and faster than with a similar gray level image because of more information per pixel. Color machine vision sets new requirements for lighting, too. High intensity and white color light is required in order to acquire good images for further image processing or analysis. New development in lighting technology is bringing eventually solutions for color imaging.

The X-ray properties of high redshift, optically selected QSOs. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Anderson, S. F.

1985-01-01

In order to study the X-ray properties of high redshift QSOs, grism/grens plates covering 17 deg. of sky previously imaged to very sensitive X-ray flux levels with the Einstein Observatory were taken. Following optical selection of the QSO, the archived X-ray image is examined to extract an X-ray flux detection or a sensitive upper limit.

Modulated CMOS camera for fluorescence lifetime microscopy.

PubMed

Chen, Hongtao; Holst, Gerhard; Gratton, Enrico

2015-12-01

Widefield frequency-domain fluorescence lifetime imaging microscopy (FD-FLIM) is a fast and accurate method to measure the fluorescence lifetime of entire images. However, the complexity and high costs involved in construction of such a system limit the extensive use of this technique. PCO AG recently released the first luminescence lifetime imaging camera based on a high frequency modulated CMOS image sensor, QMFLIM2. Here we tested and provide operational procedures to calibrate the camera and to improve the accuracy using corrections necessary for image analysis. With its flexible input/output options, we are able to use a modulated laser diode or a 20 MHz pulsed white supercontinuum laser as the light source. The output of the camera consists of a stack of modulated images that can be analyzed by the SimFCS software using the phasor approach. The nonuniform system response across the image sensor must be calibrated at the pixel level. This pixel calibration is crucial and needed for every camera settings, e.g. modulation frequency and exposure time. A significant dependency of the modulation signal on the intensity was also observed and hence an additional calibration is needed for each pixel depending on the pixel intensity level. These corrections are important not only for the fundamental frequency, but also for the higher harmonics when using the pulsed supercontinuum laser. With these post data acquisition corrections, the PCO CMOS-FLIM camera can be used for various biomedical applications requiring a large frame and high speed acquisition. © 2015 Wiley Periodicals, Inc.

An Investigation of Zimbabwe High School Chemistry Students' Laboratory Work-Based Images of the Nature of Science

ERIC Educational Resources Information Center

Vhurumuku, Elaosi; Holtman, Lorna; Mikalsen, Oyvind; Kolsto, Stein D.

2006-01-01

This study investigates the proximal and distal images of the nature of science (NOS) that A-level students develop from their participation in chemistry laboratory work. We also explored the nature of the interactions among the students' proximal and distal images of the NOS and students' participation in laboratory work. Students' views of the…

Chesapeake Bay plume dynamics from LANDSAT

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.; Fedosh, M. S.

1981-01-01

LANDSAT images with enhancement and density slicing show that the Chesapeake Bay plume usually frequents the Virginia coast south of the Bay mouth. Southwestern (compared to northern) winds spread the plume easterly over a large area. Ebb tide images (compared to flood tide images) show a more dispersed plume. Flooding waters produce high turbidity levels over the shallow northern portion of the Bay mouth.

Temperature-Dependent Photoluminescence Imaging and Characterization of a Multi-Crystalline Silicon Solar Cell Defect Area

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

Johnston, S.; Yan, F.; Li, J.

2011-01-01

Photoluminescence (PL) imaging is used to detect areas in multi-crystalline silicon that appear dark in band-to-band imaging due to high recombination. Steady-state PL intensity can be correlated to effective minority-carrier lifetime, and its temperature dependence can provide additional lifetime-limiting defect information. An area of high defect density has been laser cut from a multi-crystalline silicon solar cell. Both band-to-band and defect-band PL imaging have been collected as a function of temperature from {approx}85 to 350 K. Band-to-band luminescence is collected by an InGaAs camera using a 1200-nm short-pass filter, while defect band luminescence is collected using a 1350-nm long passmore » filter. The defect band luminescence is characterized by cathodoluminescence. Small pieces from adjacent areas within the same wafer are measured by deep-level transient spectroscopy (DLTS). DLTS detects a minority-carrier electron trap level with an activation energy of 0.45 eV on the sample that contained defects as seen by imaging.« less

Temperature-Dependent Photoluminescence Imaging and Characterization of a Multi-Crystalline Silicon Solar Cell Defect Area: Preprint

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

Johnston, S.; Yan, F.; Li, J.

2011-07-01

Photoluminescence (PL) imaging is used to detect areas in multi-crystalline silicon that appear dark in band-to-band imaging due to high recombination. Steady-state PL intensity can be correlated to effective minority-carrier lifetime, and its temperature dependence can provide additional lifetime-limiting defect information. An area of high defect density has been laser cut from a multi-crystalline silicon solar cell. Both band-to-band and defect-band PL imaging have been collected as a function of temperature from ~85 to 350 K. Band-to-band luminescence is collected by an InGaAs camera using a 1200-nm short-pass filter, while defect band luminescence is collected using a 1350-nm long passmore » filter. The defect band luminescence is characterized by cathodo-luminescence. Small pieces from adjacent areas within the same wafer are measured by deep-level transient spectroscopy (DLTS). DLTS detects a minority-carrier electron trap level with an activation energy of 0.45 eV on the sample that contained defects as seen by imaging.« less

A Novel Method to Increase LinLog CMOS Sensors’ Performance in High Dynamic Range Scenarios

PubMed Central

Martínez-Sánchez, Antonio; Fernández, Carlos; Navarro, Pedro J.; Iborra, Andrés

2011-01-01

Images from high dynamic range (HDR) scenes must be obtained with minimum loss of information. For this purpose it is necessary to take full advantage of the quantification levels provided by the CCD/CMOS image sensor. LinLog CMOS sensors satisfy the above demand by offering an adjustable response curve that combines linear and logarithmic responses. This paper presents a novel method to quickly adjust the parameters that control the response curve of a LinLog CMOS image sensor. We propose to use an Adaptive Proportional-Integral-Derivative controller to adjust the exposure time of the sensor, together with control algorithms based on the saturation level and the entropy of the images. With this method the sensor’s maximum dynamic range (120 dB) can be used to acquire good quality images from HDR scenes with fast, automatic adaptation to scene conditions. Adaptation to a new scene is rapid, with a sensor response adjustment of less than eight frames when working in real time video mode. At least 67% of the scene entropy can be retained with this method. PMID:22164083

A novel method to increase LinLog CMOS sensors' performance in high dynamic range scenarios.

PubMed

Martínez-Sánchez, Antonio; Fernández, Carlos; Navarro, Pedro J; Iborra, Andrés

2011-01-01

Images from high dynamic range (HDR) scenes must be obtained with minimum loss of information. For this purpose it is necessary to take full advantage of the quantification levels provided by the CCD/CMOS image sensor. LinLog CMOS sensors satisfy the above demand by offering an adjustable response curve that combines linear and logarithmic responses. This paper presents a novel method to quickly adjust the parameters that control the response curve of a LinLog CMOS image sensor. We propose to use an Adaptive Proportional-Integral-Derivative controller to adjust the exposure time of the sensor, together with control algorithms based on the saturation level and the entropy of the images. With this method the sensor's maximum dynamic range (120 dB) can be used to acquire good quality images from HDR scenes with fast, automatic adaptation to scene conditions. Adaptation to a new scene is rapid, with a sensor response adjustment of less than eight frames when working in real time video mode. At least 67% of the scene entropy can be retained with this method.

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors.

PubMed

Kawahito, Shoji; Seo, Min-Woong

2016-11-06

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e - rms ) when compared with the CMS gain of two (2.4 e - rms ), or 16 (1.1 e - rms ).

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors

PubMed Central

Kawahito, Shoji; Seo, Min-Woong

2016-01-01

This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS) technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs). This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC). The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median): 0.29 e−rms) when compared with the CMS gain of two (2.4 e−rms), or 16 (1.1 e−rms). PMID:27827972

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring.

PubMed

Alirezaie, Marjan; Kiselev, Andrey; Längkvist, Martin; Klügl, Franziska; Loutfi, Amy

2017-11-05

This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment-central Stockholm-in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as "find all regions close to schools and far from the flooded area". The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring

PubMed Central

Alirezaie, Marjan; Klügl, Franziska; Loutfi, Amy

2017-01-01

This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints. PMID:29113073

Multispectral image fusion for illumination-invariant palmprint recognition

PubMed Central

Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied. PMID:28558064

Multispectral image fusion for illumination-invariant palmprint recognition.

PubMed

Lu, Longbin; Zhang, Xinman; Xu, Xuebin; Shang, Dongpeng

2017-01-01

Multispectral palmprint recognition has shown broad prospects for personal identification due to its high accuracy and great stability. In this paper, we develop a novel illumination-invariant multispectral palmprint recognition method. To combine the information from multiple spectral bands, an image-level fusion framework is completed based on a fast and adaptive bidimensional empirical mode decomposition (FABEMD) and a weighted Fisher criterion. The FABEMD technique decomposes the multispectral images into their bidimensional intrinsic mode functions (BIMFs), on which an illumination compensation operation is performed. The weighted Fisher criterion is to construct the fusion coefficients at the decomposition level, making the images be separated correctly in the fusion space. The image fusion framework has shown strong robustness against illumination variation. In addition, a tensor-based extreme learning machine (TELM) mechanism is presented for feature extraction and classification of two-dimensional (2D) images. In general, this method has fast learning speed and satisfying recognition accuracy. Comprehensive experiments conducted on the PolyU multispectral palmprint database illustrate that the proposed method can achieve favorable results. For the testing under ideal illumination, the recognition accuracy is as high as 99.93%, and the result is 99.50% when the lighting condition is unsatisfied.

Single-Scale Fusion: An Effective Approach to Merging Images.

PubMed

Ancuti, Codruta O; Ancuti, Cosmin; De Vleeschouwer, Christophe; Bovik, Alan C

2017-01-01

Due to its robustness and effectiveness, multi-scale fusion (MSF) based on the Laplacian pyramid decomposition has emerged as a popular technique that has shown utility in many applications. Guided by several intuitive measures (weight maps) the MSF process is versatile and straightforward to be implemented. However, the number of pyramid levels increases with the image size, which implies sophisticated data management and memory accesses, as well as additional computations. Here, we introduce a simplified formulation that reduces MSF to only a single level process. Starting from the MSF decomposition, we explain both mathematically and intuitively (visually) a way to simplify the classical MSF approach with minimal loss of information. The resulting single-scale fusion (SSF) solution is a close approximation of the MSF process that eliminates important redundant computations. It also provides insights regarding why MSF is so effective. While our simplified expression is derived in the context of high dynamic range imaging, we show its generality on several well-known fusion-based applications, such as image compositing, extended depth of field, medical imaging, and blending thermal (infrared) images with visible light. Besides visual validation, quantitative evaluations demonstrate that our SSF strategy is able to yield results that are highly competitive with traditional MSF approaches.

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

Li, Ke; Chen, Guang-Hong, E-mail: gchen7@wisc.edu; Garrett, John

Purpose: Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. Methods: The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDI{sub vol} =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIRmore » (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d′. Results: (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Conclusions: Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.« less

Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance.

PubMed

Li, Ke; Garrett, John; Ge, Yongshuai; Chen, Guang-Hong

2014-07-01

Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDIvol =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIR (Veo(®), GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d'. (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.

AutoCNet: A Python library for sparse multi-image correspondence identification for planetary data

NASA Astrophysics Data System (ADS)

Laura, Jason; Rodriguez, Kelvin; Paquette, Adam C.; Dunn, Evin

2018-01-01

In this work we describe the AutoCNet library, written in Python, to support the application of computer vision techniques for n-image correspondence identification in remotely sensed planetary images and subsequent bundle adjustment. The library is designed to support exploratory data analysis, algorithm and processing pipeline development, and application at scale in High Performance Computing (HPC) environments for processing large data sets and generating foundational data products. We also present a brief case study illustrating high level usage for the Apollo 15 Metric camera.

Logo image clustering based on advanced statistics

NASA Astrophysics Data System (ADS)

Wei, Yi; Kamel, Mohamed; He, Yiwei

2007-11-01

In recent years, there has been a growing interest in the research of image content description techniques. Among those, image clustering is one of the most frequently discussed topics. Similar to image recognition, image clustering is also a high-level representation technique. However it focuses on the coarse categorization rather than the accurate recognition. Based on wavelet transform (WT) and advanced statistics, the authors propose a novel approach that divides various shaped logo images into groups according to the external boundary of each logo image. Experimental results show that the presented method is accurate, fast and insensitive to defects.

InGaAs focal plane arrays for low-light-level SWIR imaging

NASA Astrophysics Data System (ADS)

MacDougal, Michael; Hood, Andrew; Geske, Jon; Wang, Jim; Patel, Falgun; Follman, David; Manzo, Juan; Getty, Jonathan

2011-06-01

Aerius Photonics will present their latest developments in large InGaAs focal plane arrays, which are used for low light level imaging in the short wavelength infrared (SWIR) regime. Aerius will present imaging in both 1280x1024 and 640x512 formats. Aerius will present characterization of the FPA including dark current measurements. Aerius will also show the results of development of SWIR FPAs for high temperaures, including imagery and dark current data. Finally, Aerius will show results of using the SWIR camera with Aerius' SWIR illuminators using VCSEL technology.

High-Spatial and High-Mass Resolution Imaging of Surface Metabolites of Arabidopsis thaliana by Laser Desorption-Ionization Mass Spectrometry Using Colloidal Silver

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

Jun, Ji Hyun; Song, Zhihong; Liu, Zhenjiu

High-spatial resolution and high-mass resolution techniques are developed and adopted for the mass spectrometric imaging of epicuticular lipids on the surface of Arabidopsis thaliana. Single cell level spatial resolution of {approx}12 {micro}m was achieved by reducing the laser beam size by using an optical fiber with 25 {micro}m core diameter in a vacuum matrix-assisted laser desorption ionization-linear ion trap (vMALDI-LTQ) mass spectrometer and improved matrix application using an oscillating capillary nebulizer. Fine chemical images of a whole flower were visualized in this high spatial resolution showing substructure of an anther and single pollen grains at the stigma and anthers. Themore » LTQ-Orbitrap with a MALDI ion source was adopted to achieve MS imaging in high mass resolution. Specifically, isobaric silver ion adducts of C29 alkane (m/z 515.3741) and C28 aldehyde (m/z 515.3377), indistinguishable in low-resolution LTQ, can now be clearly distinguished and their chemical images could be separately constructed. In the application to roots, the high spatial resolution allowed molecular MS imaging of secondary roots and the high mass resolution allowed direct identification of lipid metabolites on root surfaces.« less

High resolution microendoscopy with structured illumination and Lugol's iodine staining for evaluation of breast cancer architecture

NASA Astrophysics Data System (ADS)

Dobbs, Jessica; Kyrish, Matthew; Krishnamurthy, Savitri; Grant, Benjamin; Kuerer, Henry; Yang, Wei; Tkaczyk, Tomasz; Richards-Kortum, Rebecca

2016-03-01

Intraoperative margin assessment to evaluate resected tissue margins for neoplastic tissue is performed to prevent reoperations following breast-conserving surgery. High resolution microendoscopy (HRME) can rapidly acquire images of fresh tissue specimens, but is limited by low image contrast in tissues with high optical scattering. In this study we evaluated two techniques to reduce out-of-focus light: HRME image acquisition with structured illumination (SI-HRME) and topical application of Lugol's Iodine. Fresh breast tissue specimens from 19 patients were stained with proflavine alone or Lugol's Iodine and proflavine. Images of tissue specimens were acquired using a confocal microscope and an HRME system with and without structured illumination. Images were evaluated based on visual and quantitative assessment of image contrast. The highest mean contrast was measured in confocal images stained with proflavine. Contrast was significantly lower in HRME images stained with proflavine; however, incorporation of structured illumination significantly increased contrast in HRME images to levels comparable to that in confocal images. The addition of Lugol's Iodine did not increase mean contrast significantly for HRME or SI-HRME images. These findings suggest that structured illumination could potentially be used to increase contrast in HRME images of breast tissue for rapid image acquisition.

Development of a single-shot CCD-based data acquisition system for time-resolved X-ray photoelectron spectroscopy at an X-ray free-electron laser facility

PubMed Central

Oura, Masaki; Wagai, Tatsuya; Chainani, Ashish; Miyawaki, Jun; Sato, Hiromi; Matsunami, Masaharu; Eguchi, Ritsuko; Kiss, Takayuki; Yamaguchi, Takashi; Nakatani, Yasuhiro; Togashi, Tadashi; Katayama, Tetsuo; Ogawa, Kanade; Yabashi, Makina; Tanaka, Yoshihito; Kohmura, Yoshiki; Tamasaku, Kenji; Shin, Shik; Ishikawa, Tetsuya

2014-01-01

In order to utilize high-brilliance photon sources, such as X-ray free-electron lasers (XFELs), for advanced time-resolved photoelectron spectroscopy (TR-PES), a single-shot CCD-based data acquisition system combined with a high-resolution hemispherical electron energy analyzer has been developed. The system’s design enables it to be controlled by an external trigger signal for single-shot pump–probe-type TR-PES. The basic performance of the system is demonstrated with an offline test, followed by online core-level photoelectron and Auger electron spectroscopy in ‘single-shot image’, ‘shot-to-shot image (image-to-image storage or block storage)’ and ‘shot-to-shot sweep’ modes at soft X-ray undulator beamline BL17SU of SPring-8. In the offline test the typical repetition rate for image-to-image storage mode has been confirmed to be about 15 Hz using a conventional pulse-generator. The function for correcting the shot-to-shot intensity fluctuations of the exciting photon beam, an important requirement for the TR-PES experiments at FEL sources, has been successfully tested at BL17SU by measuring Au 4f photoelectrons with intentionally controlled photon flux. The system has also been applied to hard X-ray PES (HAXPES) in ‘ordinary sweep’ mode as well as shot-to-shot image mode at the 27 m-long undulator beamline BL19LXU of SPring-8 and also at the SACLA XFEL facility. The XFEL-induced Ti 1s core-level spectrum of La-doped SrTiO3 is reported as a function of incident power density. The Ti 1s core-level spectrum obtained at low power density is consistent with the spectrum obtained using the synchrotron source. At high power densities the Ti 1s core-level spectra show space-charge effects which are analysed using a known mean-field model for ultrafast electron packet propagation. The results successfully confirm the capability of the present data acquisition system for carrying out the core-level HAXPES studies of condensed matter induced by the XFEL. PMID:24365935

Task-specific image partitioning.

PubMed

Kim, Sungwoong; Nowozin, Sebastian; Kohli, Pushmeet; Yoo, Chang D

2013-02-01

Image partitioning is an important preprocessing step for many of the state-of-the-art algorithms used for performing high-level computer vision tasks. Typically, partitioning is conducted without regard to the task in hand. We propose a task-specific image partitioning framework to produce a region-based image representation that will lead to a higher task performance than that reached using any task-oblivious partitioning framework and existing supervised partitioning framework, albeit few in number. The proposed method partitions the image by means of correlation clustering, maximizing a linear discriminant function defined over a superpixel graph. The parameters of the discriminant function that define task-specific similarity/dissimilarity among superpixels are estimated based on structured support vector machine (S-SVM) using task-specific training data. The S-SVM learning leads to a better generalization ability while the construction of the superpixel graph used to define the discriminant function allows a rich set of features to be incorporated to improve discriminability and robustness. We evaluate the learned task-aware partitioning algorithms on three benchmark datasets. Results show that task-aware partitioning leads to better labeling performance than the partitioning computed by the state-of-the-art general-purpose and supervised partitioning algorithms. We believe that the task-specific image partitioning paradigm is widely applicable to improving performance in high-level image understanding tasks.

Internal representations for face detection: an application of noise-based image classification to BOLD responses.

PubMed

Nestor, Adrian; Vettel, Jean M; Tarr, Michael J

2013-11-01

What basic visual structures underlie human face detection and how can we extract such structures directly from the amplitude of neural responses elicited by face processing? Here, we address these issues by investigating an extension of noise-based image classification to BOLD responses recorded in high-level visual areas. First, we assess the applicability of this classification method to such data and, second, we explore its results in connection with the neural processing of faces. To this end, we construct luminance templates from white noise fields based on the response of face-selective areas in the human ventral cortex. Using behaviorally and neurally-derived classification images, our results reveal a family of simple but robust image structures subserving face representation and detection. Thus, we confirm the role played by classical face selective regions in face detection and we help clarify the representational basis of this perceptual function. From a theory standpoint, our findings support the idea of simple but highly diagnostic neurally-coded features for face detection. At the same time, from a methodological perspective, our work demonstrates the ability of noise-based image classification in conjunction with fMRI to help uncover the structure of high-level perceptual representations. Copyright © 2012 Wiley Periodicals, Inc.

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.

Anatomical-based partial volume correction for low-dose dedicated cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Liu, Hui; Chan, Chung; Grobshtein, Yariv; Ma, Tianyu; Liu, Yaqiang; Wang, Shi; Stacy, Mitchel R.; Sinusas, Albert J.; Liu, Chi

2015-09-01

Due to the limited spatial resolution, partial volume effect has been a major degrading factor on quantitative accuracy in emission tomography systems. This study aims to investigate the performance of several anatomical-based partial volume correction (PVC) methods for a dedicated cardiac SPECT/CT system (GE Discovery NM/CT 570c) with focused field-of-view over a clinically relevant range of high and low count levels for two different radiotracer distributions. These PVC methods include perturbation geometry transfer matrix (pGTM), pGTM followed by multi-target correction (MTC), pGTM with known concentration in blood pool, the former followed by MTC and our newly proposed methods, which perform the MTC method iteratively, where the mean values in all regions are estimated and updated by the MTC-corrected images each time in the iterative process. The NCAT phantom was simulated for cardiovascular imaging with 99mTc-tetrofosmin, a myocardial perfusion agent, and 99mTc-red blood cell (RBC), a pure intravascular imaging agent. Images were acquired at six different count levels to investigate the performance of PVC methods in both high and low count levels for low-dose applications. We performed two large animal in vivo cardiac imaging experiments following injection of 99mTc-RBC for evaluation of intramyocardial blood volume (IMBV). The simulation results showed our proposed iterative methods provide superior performance than other existing PVC methods in terms of image quality, quantitative accuracy, and reproducibility (standard deviation), particularly for low-count data. The iterative approaches are robust for both 99mTc-tetrofosmin perfusion imaging and 99mTc-RBC imaging of IMBV and blood pool activity even at low count levels. The animal study results indicated the effectiveness of PVC to correct the overestimation of IMBV due to blood pool contamination. In conclusion, the iterative PVC methods can achieve more accurate quantification, particularly for low count cardiac SPECT studies, typically obtained from low-dose protocols, gated studies, and dynamic applications.

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging.

PubMed

Lauzier, Pascal Theriault; Tang, Jie; Speidel, Michael A; Chen, Guang-Hong

2012-07-01

To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

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

Lauzier, Pascal Theriault; Tang Jie; Speidel, Michael A.

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise andmore » streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. Conclusions: (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.« less

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

PubMed Central

Lauzier, Pascal Thériault; Tang, Jie; Speidel, Michael A.; Chen, Guang-Hong

2012-01-01

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. Conclusions: (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI. PMID:22830741

A novel image enhancement algorithm based on stationary wavelet transform for infrared thermography to the de-bonding defect in solid rocket motors

NASA Astrophysics Data System (ADS)

Liu, Tao; Zhang, Wei; Yan, Shaoze

2015-10-01

In this paper, a multi-scale image enhancement algorithm based on low-passing filtering and nonlinear transformation is proposed for infrared testing image of the de-bonding defect in solid propellant rocket motors. Infrared testing images with high-level noise and low contrast are foundations for identifying defects and calculating the defects size. In order to improve quality of the infrared image, according to distribution properties of the detection image, within framework of stationary wavelet transform, the approximation coefficients at suitable decomposition level is processed by index low-passing filtering by using Fourier transform, after that, the nonlinear transformation is applied to further process the figure to improve the picture contrast. To verify validity of the algorithm, the image enhancement algorithm is applied to infrared testing pictures of two specimens with de-bonding defect. Therein, one specimen is made of a type of high-strength steel, and the other is a type of carbon fiber composite. As the result shown, in the images processed by the image enhancement algorithm presented in the paper, most of noises are eliminated, and contrast between defect areas and normal area is improved greatly; in addition, by using the binary picture of the processed figure, the continuous defect edges can be extracted, all of which show the validity of the algorithm. The paper provides a well-performing image enhancement algorithm for the infrared thermography.

Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review.

PubMed

Goez, Manuel Mauricio; Torres-Madroñero, Maria Constanza; Röthlisberger, Sarah; Delgado-Trejos, Edilson

2018-02-01

Various methods and specialized software programs are available for processing two-dimensional gel electrophoresis (2-DGE) images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and horizontal streaking, fuzzy spots, and background noise, which greatly complicate computational analysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images: Gaussian, Rayleigh, and exponential, with signal-to-noise ratios (SNRs) ranging 8-20 decibels (dB). We compared the performance of wavelet, contourlet, total variation (TV), and wavelet-total variation (WTTV) techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sensitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10-20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best performance with any level of Gaussian noise and low levels (20-14 dB) of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image. Copyright © 2018 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Production and hosting by Elsevier B.V. All rights reserved.

Hard x-ray imager for the NeXT mission

NASA Astrophysics Data System (ADS)

Nakazawa, Kazuhiro; Fukazawa, Yasushi; Kamae, Tuneyoshi; Kataoka, Jun; Kokubun, Motohide; Makishima, Kazuo; Mizuno, Tsunefumi; Murakami, Toshio; Nomachi, Masaharu; Tajima, Hiroyasu; Takahashi, Tadayuki; Tashiro, Makoto; Tamagawa, Toru; Terada, Yukikatsu; Watanabe, Shin; Yamaoka, Kazutaka; Yonetoku, Daisuke

2006-06-01

The hard X-ray imager (HXI) is the primary detector of the NeXT mission, proposed to explore high-energy non-thermal phenomena in the universe. Combined with a novel hard X-ray mirror optics, the HXI is designed to provide better than arc-minutes imaging capability with 1 keV level spectroscopy, and more than 30 times higher sensitivity compared with any existing hard X-ray instruments. The base-line design of the HXI is improving to secure high sensitivity. The key is to reduce the detector background as far as possible. Based on the experience of the Suzaku satellite launched in July 2005, the current design has a well-type tight active shield and multi layered, multi material imaging detector made of Si and CdTe. Technology has been under development for a few years so that we have reached the level where a basic detector performance is satisfied. Design tuning to further improve the sensitivity and reliability is on-going.

Segmentation methodology for automated classification and differentiation of soft tissues in multiband images of high-resolution ultrasonic transmission tomography.

PubMed

Jeong, Jeong-Won; Shin, Dae C; Do, Synho; Marmarelis, Vasilis Z

2006-08-01

This paper presents a novel segmentation methodology for automated classification and differentiation of soft tissues using multiband data obtained with the newly developed system of high-resolution ultrasonic transmission tomography (HUTT) for imaging biological organs. This methodology extends and combines two existing approaches: the L-level set active contour (AC) segmentation approach and the agglomerative hierarchical kappa-means approach for unsupervised clustering (UC). To prevent the trapping of the current iterative minimization AC algorithm in a local minimum, we introduce a multiresolution approach that applies the level set functions at successively increasing resolutions of the image data. The resulting AC clusters are subsequently rearranged by the UC algorithm that seeks the optimal set of clusters yielding the minimum within-cluster distances in the feature space. The presented results from Monte Carlo simulations and experimental animal-tissue data demonstrate that the proposed methodology outperforms other existing methods without depending on heuristic parameters and provides a reliable means for soft tissue differentiation in HUTT images.

Accelerated dynamic EPR imaging using fast acquisition and compressive recovery.

PubMed

Ahmad, Rizwan; Samouilov, Alexandre; Zweier, Jay L

2016-12-01

Electron paramagnetic resonance (EPR) allows quantitative imaging of tissue redox status, which provides important information about ischemic syndromes, cancer and other pathologies. For continuous wave EPR imaging, however, poor signal-to-noise ratio and low acquisition efficiency limit its ability to image dynamic processes in vivo including tissue redox, where conditions can change rapidly. Here, we present a data acquisition and processing framework that couples fast acquisition with compressive sensing-inspired image recovery to enable EPR-based redox imaging with high spatial and temporal resolutions. The fast acquisition (FA) allows collecting more, albeit noisier, projections in a given scan time. The composite regularization based processing method, called spatio-temporal adaptive recovery (STAR), not only exploits sparsity in multiple representations of the spatio-temporal image but also adaptively adjusts the regularization strength for each representation based on its inherent level of the sparsity. As a result, STAR adjusts to the disparity in the level of sparsity across multiple representations, without introducing any tuning parameter. Our simulation and phantom imaging studies indicate that a combination of fast acquisition and STAR (FASTAR) enables high-fidelity recovery of volumetric image series, with each volumetric image employing less than 10 s of scan. In addition to image fidelity, the time constants derived from FASTAR also match closely to the ground truth even when a small number of projections are used for recovery. This development will enhance the capability of EPR to study fast dynamic processes that cannot be investigated using existing EPR imaging techniques. Copyright © 2016 Elsevier Inc. All rights reserved.

Visualization of angiogenesis during cancer development in the polyoma middle T breast cancer model: molecular imaging with (R)-[11C]PAQ.

PubMed

Samén, Erik; Lu, Li; Mulder, Jan; Thorell, Jan-Olov; Damberg, Peter; Tegnebratt, Tetyana; Holmgren, Lars; Rundqvist, Helene; Stone-Elander, Sharon

2014-03-26

Vascular endothelial growth factor receptor 2 (VEGFR2) is a crucial mediator of tumour angiogenesis. High expression levels of the receptor have been correlated to poor prognosis in cancer patients. Reliable imaging biomarkers for stratifying patients for anti-angiogenic therapy could therefore be valuable for increasing treatment success rates. The aim of this study was to investigate the pharmacokinetics and angiogenesis imaging abilities of the VEGFR2-targeting positron emission tomography (PET) tracer (R)-[11C]PAQ. (R)-[11C]PAQ was evaluated in the mouse mammary tumour virus-polyoma middle T (MMTV-PyMT) model of metastatic breast cancer. Mice at different stages of disease progression were imaged with (R)-[11C]PAQ PET, and results were compared to those obtained with [18 F]FDG PET and magnetic resonance imaging. (R)-[11C]PAQ uptake levels were also compared to ex vivo immunofluorescence analysis of tumour- and angiogenesis-specific biomarkers. Additional pharmacokinetic studies were performed in rat and mouse. A heterogeneous uptake of (R)-[11C]PAQ was observed in the tumorous mammary glands. Ex vivo analysis confirmed the co-localization of areas with high radioactivity uptake and areas with elevated levels of VEGFR2. In some animals, a high focal uptake was observed in the lungs. The lung uptake correlated to metastatic and angiogenic activity, but not to uptake of [18 F]FDG PET. The pharmacokinetic studies revealed a limited metabolism and excretion during the 1-h scan and a distribution of radioactivity mainly to the liver, kidneys and lungs. In rat, a high uptake was additionally observed in adrenal and parathyroid glands. The results indicate that (R)-[11C]PAQ is a promising imaging biomarker for visualization of angiogenesis, based on VEGFR2 expression, in primary tumours and during metastasis development.

Visualization of angiogenesis during cancer development in the polyoma middle T breast cancer model: molecular imaging with (R)-[11C]PAQ

PubMed Central

2014-01-01

Background Vascular endothelial growth factor receptor 2 (VEGFR2) is a crucial mediator of tumour angiogenesis. High expression levels of the receptor have been correlated to poor prognosis in cancer patients. Reliable imaging biomarkers for stratifying patients for anti-angiogenic therapy could therefore be valuable for increasing treatment success rates. The aim of this study was to investigate the pharmacokinetics and angiogenesis imaging abilities of the VEGFR2-targeting positron emission tomography (PET) tracer (R)-[11C]PAQ. Methods (R)-[11C]PAQ was evaluated in the mouse mammary tumour virus-polyoma middle T (MMTV-PyMT) model of metastatic breast cancer. Mice at different stages of disease progression were imaged with (R)-[11C]PAQ PET, and results were compared to those obtained with [18 F]FDG PET and magnetic resonance imaging. (R)-[11C]PAQ uptake levels were also compared to ex vivo immunofluorescence analysis of tumour- and angiogenesis-specific biomarkers. Additional pharmacokinetic studies were performed in rat and mouse. Results A heterogeneous uptake of (R)-[11C]PAQ was observed in the tumorous mammary glands. Ex vivo analysis confirmed the co-localization of areas with high radioactivity uptake and areas with elevated levels of VEGFR2. In some animals, a high focal uptake was observed in the lungs. The lung uptake correlated to metastatic and angiogenic activity, but not to uptake of [18 F]FDG PET. The pharmacokinetic studies revealed a limited metabolism and excretion during the 1-h scan and a distribution of radioactivity mainly to the liver, kidneys and lungs. In rat, a high uptake was additionally observed in adrenal and parathyroid glands. Conclusion The results indicate that (R)-[11C]PAQ is a promising imaging biomarker for visualization of angiogenesis, based on VEGFR2 expression, in primary tumours and during metastasis development. PMID:24670127

Segmentation of mouse dynamic PET images using a multiphase level set method

NASA Astrophysics Data System (ADS)

Cheng-Liao, Jinxiu; Qi, Jinyi

2010-11-01

Image segmentation plays an important role in medical diagnosis. Here we propose an image segmentation method for four-dimensional mouse dynamic PET images. We consider that voxels inside each organ have similar time activity curves. The use of tracer dynamic information allows us to separate regions that have similar integrated activities in a static image but with different temporal responses. We develop a multiphase level set method that utilizes both the spatial and temporal information in a dynamic PET data set. Different weighting factors are assigned to each image frame based on the noise level and activity difference among organs of interest. We used a weighted absolute difference function in the data matching term to increase the robustness of the estimate and to avoid over-partition of regions with high contrast. We validated the proposed method using computer simulated dynamic PET data, as well as real mouse data from a microPET scanner, and compared the results with those of a dynamic clustering method. The results show that the proposed method results in smoother segments with the less number of misclassified voxels.

Region-based multifocus image fusion for the precise acquisition of Pap smear images.

PubMed

Tello-Mijares, Santiago; Bescós, Jesús

2018-05-01

A multifocus image fusion method to obtain a single focused image from a sequence of microscopic high-magnification Papanicolau source (Pap smear) images is presented. These images, captured each in a different position of the microscope lens, frequently show partially focused cells or parts of cells, which makes them unpractical for the direct application of image analysis techniques. The proposed method obtains a focused image with a high preservation of original pixels information while achieving a negligible visibility of the fusion artifacts. The method starts by identifying the best-focused image of the sequence; then, it performs a mean-shift segmentation over this image; the focus level of the segmented regions is evaluated in all the images of the sequence, and best-focused regions are merged in a single combined image; finally, this image is processed with an adaptive artifact removal process. The combination of a region-oriented approach, instead of block-based approaches, and a minimum modification of the value of focused pixels in the original images achieve a highly contrasted image with no visible artifacts, which makes this method especially convenient for the medical imaging domain. The proposed method is compared with several state-of-the-art alternatives over a representative dataset. The experimental results show that our proposal obtains the best and more stable quality indicators. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

High-throughput imaging method for direct assessment of GM1 ganglioside levels in mammalian cells

PubMed Central

Acosta, Walter; Martin, Reid; Radin, David N.; Cramer, Carole L.

2016-01-01

GM1-gangliosidosis is an inherited autosomal recessive disorder caused by mutations in the gene GLB1, which encodes acid β-galactosidase (β-gal). The lack of activity in this lysosomal enzyme leads to accumulation of GM1 gangliosides (GM1) in cells. We have developed a high-content-imaging method to assess GM1 levels in fibroblasts that can be used to evaluate substrate reduction in treated GLB1−/− cells [1]. This assay allows fluorescent quantification in a multi-well system which generates unbiased and statistically significant data. Fluorescently labeled Cholera Toxin B subunit (CTXB), which specifically binds to GM1 gangliosides, was used to detect in situ GM1 levels in a fixed monolayer of fibroblasts. This sensitive, rapid, and inexpensive method facilitates in vitro drug screening in a format that allows a high number of replicates using low working volumes. PMID:26958633

High-throughput imaging method for direct assessment of GM1 ganglioside levels in mammalian cells.

PubMed

Acosta, Walter; Martin, Reid; Radin, David N; Cramer, Carole L

2016-03-01

GM1-gangliosidosis is an inherited autosomal recessive disorder caused by mutations in the gene GLB1, which encodes acid β-galactosidase (β-gal). The lack of activity in this lysosomal enzyme leads to accumulation of GM1 gangliosides (GM1) in cells. We have developed a high-content-imaging method to assess GM1 levels in fibroblasts that can be used to evaluate substrate reduction in treated GLB1(-/-) cells [1]. This assay allows fluorescent quantification in a multi-well system which generates unbiased and statistically significant data. Fluorescently labeled Cholera Toxin B subunit (CTXB), which specifically binds to GM1 gangliosides, was used to detect in situ GM1 levels in a fixed monolayer of fibroblasts. This sensitive, rapid, and inexpensive method facilitates in vitro drug screening in a format that allows a high number of replicates using low working volumes.

Exploring the nutrient inputs and cycles in Tampa Bay and coastal watersheds using MODIS images and data mining

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Xuan, Zhemin

2011-09-01

Excessive nutrients, which may be represented as Total Nitrogen (TN) and Total Phosphorus (TP) levels, in natural water systems have proven to cause high levels of algae production. The process of phytoplankton growth which consumes the excess TN and TP in a water body can also be related to the changing water quality levels, such as Dissolved Oxygen (DO), chlorophyll-a, and turbidity, associated with their changes in absorbance of natural radiation. This paper explores spatiotemporal nutrient patterns in Tampa Bay, Florida with the aid of Moderate Resolution Imaging Spectroradiometer or MODIS images and Genetic Programming (GP) models that are deigned to link those relevant water quality parameters in aquatic environments.

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

NASA Astrophysics Data System (ADS)

Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed ADF features can effectively improve the accuracy of urban scene classification, with a significant increase in overall accuracy (3.8-11.7%) compared to using the spectral bands alone. Furthermore, the results indicated the superiority of the proposed ADFs in distinguishing between the spectrally similar and complex man-made classes, including roads and various types of buildings (e.g., high buildings, urban villages, and residential apartments).

High-dose MVCT image guidance for stereotactic body radiation therapy

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

Westerly, David C.; Schefter, Tracey E.; Kavanagh, Brian D.

Purpose: Stereotactic body radiation therapy (SBRT) is a potent treatment for early stage primary and limited metastatic disease. Accurate tumor localization is essential to administer SBRT safely and effectively. Tomotherapy combines helical IMRT with onboard megavoltage CT (MVCT) imaging and is well suited for SBRT; however, MVCT results in reduced soft tissue contrast and increased image noise compared with kilovoltage CT. The goal of this work was to investigate the use of increased imaging doses on a clinical tomotherapy machine to improve image quality for SBRT image guidance. Methods: Two nonstandard, high-dose imaging modes were created on a tomotherapy machinemore » by increasing the linear accelerator (LINAC) pulse rate from the nominal setting of 80 Hz, to 160 Hz and 300 Hz, respectively. Weighted CT dose indexes (wCTDIs) were measured for the standard, medium, and high-dose modes in a 30 cm solid water phantom using a calibrated A1SL ion chamber. Image quality was assessed from scans of a customized image quality phantom. Metrics evaluated include: contrast-to-noise ratios (CNRs), high-contrast spatial resolution, image uniformity, and percent image noise. In addition, two patients receiving SBRT were localized using high-dose MVCT scans. Raw detector data collected after each scan were used to reconstruct standard-dose images for comparison. Results: MVCT scans acquired using a pitch of 1.0 resulted in wCTDI values of 2.2, 4.7, and 8.5 cGy for the standard, medium, and high-dose modes respectively. CNR values for both low and high-contrast materials were found to increase with the square root of dose. Axial high-contrast spatial resolution was comparable for all imaging modes at 0.5 lp/mm. Image uniformity was improved and percent noise decreased as the imaging dose increased. Similar improvements in image quality were observed in patient images, with decreases in image noise being the most notable. Conclusions: High-dose imaging modes are made possible on a clinical tomotherapy machine by increasing the LINAC pulse rate. Increasing the imaging dose results in increased CNRs; making it easier to distinguish the boundaries of low contrast objects. The imaging dose levels observed in this work are considered acceptable at our institution for SBRT treatments delivered in 3-5 fractions.« less

High-dose MVCT image guidance for stereotactic body radiation therapy.

PubMed

Westerly, David C; Schefter, Tracey E; Kavanagh, Brian D; Chao, Edward; Lucas, Dan; Flynn, Ryan T; Miften, Moyed

2012-08-01

Stereotactic body radiation therapy (SBRT) is a potent treatment for early stage primary and limited metastatic disease. Accurate tumor localization is essential to administer SBRT safely and effectively. Tomotherapy combines helical IMRT with onboard megavoltage CT (MVCT) imaging and is well suited for SBRT; however, MVCT results in reduced soft tissue contrast and increased image noise compared with kilovoltage CT. The goal of this work was to investigate the use of increased imaging doses on a clinical tomotherapy machine to improve image quality for SBRT image guidance. Two nonstandard, high-dose imaging modes were created on a tomotherapy machine by increasing the linear accelerator (LINAC) pulse rate from the nominal setting of 80 Hz, to 160 Hz and 300 Hz, respectively. Weighted CT dose indexes (wCTDIs) were measured for the standard, medium, and high-dose modes in a 30 cm solid water phantom using a calibrated A1SL ion chamber. Image quality was assessed from scans of a customized image quality phantom. Metrics evaluated include: contrast-to-noise ratios (CNRs), high-contrast spatial resolution, image uniformity, and percent image noise. In addition, two patients receiving SBRT were localized using high-dose MVCT scans. Raw detector data collected after each scan were used to reconstruct standard-dose images for comparison. MVCT scans acquired using a pitch of 1.0 resulted in wCTDI values of 2.2, 4.7, and 8.5 cGy for the standard, medium, and high-dose modes respectively. CNR values for both low and high-contrast materials were found to increase with the square root of dose. Axial high-contrast spatial resolution was comparable for all imaging modes at 0.5 lp∕mm. Image uniformity was improved and percent noise decreased as the imaging dose increased. Similar improvements in image quality were observed in patient images, with decreases in image noise being the most notable. High-dose imaging modes are made possible on a clinical tomotherapy machine by increasing the LINAC pulse rate. Increasing the imaging dose results in increased CNRs; making it easier to distinguish the boundaries of low contrast objects. The imaging dose levels observed in this work are considered acceptable at our institution for SBRT treatments delivered in 3-5 fractions.

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.

Multimodality optical imaging of embryonic heart microstructure

PubMed Central

Yelin, Ronit; Yelin, Dvir; Oh, Wang-Yuhl; Yun, Seok H.; Boudoux, Caroline; Vakoc, Benjamin J.; Bouma, Brett E.; Tearney, Guillermo J.

2009-01-01

Study of developmental heart defects requires the visualization of the microstructure and function of the embryonic myocardium, ideally with minimal alterations to the specimen. We demonstrate multiple endogenous contrast optical techniques for imaging the Xenopus laevis tadpole heart. Each technique provides distinct and complementary imaging capabilities, including: 1. 3-D coherence microscopy with subcellular (1 to 2 µm) resolution in fixed embryos, 2. real-time reflectance confocal microscopy with large penetration depth in vivo, and 3. ultra-high speed (up to 900 frames per second) that enables real-time 4-D high resolution imaging in vivo. These imaging modalities can provide a comprehensive picture of the morphologic and dynamic phenotype of the embryonic heart. The potential of endogenous-contrast optical microscopy is demonstrated for investigation of the teratogenic effects of ethanol. Microstructural abnormalities associated with high levels of ethanol exposure are observed, including compromised heart looping and loss of ventricular trabecular mass. PMID:18163837

Multimodality optical imaging of embryonic heart microstructure.

PubMed

Yelin, Ronit; Yelin, Dvir; Oh, Wang-Yuhl; Yun, Seok H; Boudoux, Caroline; Vakoc, Benjamin J; Bouma, Brett E; Tearney, Guillermo J

2007-01-01

Study of developmental heart defects requires the visualization of the microstructure and function of the embryonic myocardium, ideally with minimal alterations to the specimen. We demonstrate multiple endogenous contrast optical techniques for imaging the Xenopus laevis tadpole heart. Each technique provides distinct and complementary imaging capabilities, including: 1. 3-D coherence microscopy with subcellular (1 to 2 microm) resolution in fixed embryos, 2. real-time reflectance confocal microscopy with large penetration depth in vivo, and 3. ultra-high speed (up to 900 frames per second) that enables real-time 4-D high resolution imaging in vivo. These imaging modalities can provide a comprehensive picture of the morphologic and dynamic phenotype of the embryonic heart. The potential of endogenous-contrast optical microscopy is demonstrated for investigation of the teratogenic effects of ethanol. Microstructural abnormalities associated with high levels of ethanol exposure are observed, including compromised heart looping and loss of ventricular trabecular mass.

Digital micromirror device camera with per-pixel coded exposure for high dynamic range imaging.

PubMed

Feng, Wei; Zhang, Fumin; Wang, Weijing; Xing, Wei; Qu, Xinghua

2017-05-01

In this paper, we overcome the limited dynamic range of the conventional digital camera, and propose a method of realizing high dynamic range imaging (HDRI) from a novel programmable imaging system called a digital micromirror device (DMD) camera. The unique feature of the proposed new method is that the spatial and temporal information of incident light in our DMD camera can be flexibly modulated, and it enables the camera pixels always to have reasonable exposure intensity by DMD pixel-level modulation. More importantly, it allows different light intensity control algorithms used in our programmable imaging system to achieve HDRI. We implement the optical system prototype, analyze the theory of per-pixel coded exposure for HDRI, and put forward an adaptive light intensity control algorithm to effectively modulate the different light intensity to recover high dynamic range images. Via experiments, we demonstrate the effectiveness of our method and implement the HDRI on different objects.

Oxalate-curcumin–based probe for micro- and macroimaging of reactive oxygen species in Alzheimer’s disease

PubMed Central

Yang, Jian; Zhang, Xueli; Yang, Jing; Xu, Yungen; Grutzendler, Jaime; Shao, Yihan; Moore, Anna; Ran, Chongzhao

2017-01-01

Alzheimer’s disease (AD) is an irreversible neurodegenerative disorder that has a progression that is closely associated with oxidative stress. It has long been speculated that the reactive oxygen species (ROS) level in AD brains is much higher than that in healthy brains. However, evidence from living beings is scarce. Inspired by the “chemistry of glow stick,” we designed a near-IR fluorescence (NIRF) imaging probe, termed CRANAD-61, for sensing ROS to provide evidence at micro- and macrolevels. In CRANAD-61, an oxalate moiety was utilized to react with ROS and to consequentially produce wavelength shifting. Our in vitro data showed that CRANAD-61 was highly sensitive and rapidly responsive to various ROS. On reacting with ROS, its excitation and emission wavelengths significantly shifted to short wavelengths, and this shifting could be harnessed for dual-color two-photon imaging and transformative NIRF imaging. In this report, we showed that CRANAD-61 could be used to identify “active” amyloid beta (Aβ) plaques and cerebral amyloid angiopathy (CAA) surrounded by high ROS levels with two-photon imaging (microlevel) and to provide relative total ROS concentrations in AD brains via whole-brain NIRF imaging (macrolevel). Lastly, we showed that age-related increases in ROS levels in AD brains could be monitored with our NIRF imaging method. We believe that our imaging with CRANAD-61 could provide evidence of ROS at micro- and macrolevels and could be used for monitoring ROS changes under various AD pathological conditions and during drug treatment. PMID:29109280

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

Recognizable or Not: Towards Image Semantic Quality Assessment for Compression

NASA Astrophysics Data System (ADS)

Liu, Dong; Wang, Dandan; Li, Houqiang

2017-12-01

Traditionally, image compression was optimized for the pixel-wise fidelity or the perceptual quality of the compressed images given a bit-rate budget. But recently, compressed images are more and more utilized for automatic semantic analysis tasks such as recognition and retrieval. For these tasks, we argue that the optimization target of compression is no longer perceptual quality, but the utility of the compressed images in the given automatic semantic analysis task. Accordingly, we propose to evaluate the quality of the compressed images neither at pixel level nor at perceptual level, but at semantic level. In this paper, we make preliminary efforts towards image semantic quality assessment (ISQA), focusing on the task of optical character recognition (OCR) from compressed images. We propose a full-reference ISQA measure by comparing the features extracted from text regions of original and compressed images. We then propose to integrate the ISQA measure into an image compression scheme. Experimental results show that our proposed ISQA measure is much better than PSNR and SSIM in evaluating the semantic quality of compressed images; accordingly, adopting our ISQA measure to optimize compression for OCR leads to significant bit-rate saving compared to using PSNR or SSIM. Moreover, we perform subjective test about text recognition from compressed images, and observe that our ISQA measure has high consistency with subjective recognizability. Our work explores new dimensions in image quality assessment, and demonstrates promising direction to achieve higher compression ratio for specific semantic analysis tasks.

WFIRST-AFTA coronagraph shaped pupil masks: design, fabrication, and characterization

NASA Astrophysics Data System (ADS)

Balasubramanian, Kunjithapatham; White, Victor; Yee, Karl; Echternach, Pierre; Muller, Richard; Dickie, Matthew; Cady, Eric; Prada, Camilo Mejia; Ryan, Daniel; Poberezhskiy, Ilya; Kern, Brian; Zhou, Hanying; Krist, John; Nemati, Bijan; Eldorado Riggs, A. J.; Zimmerman, Neil T.; Kasdin, N. Jeremy

2016-01-01

NASA WFIRST-AFTA mission study includes a coronagraph instrument to find and characterize exoplanets. Various types of masks could be employed to suppress the host starlight to about 10-9 level contrast over a broad spectrum to enable the coronagraph mission objectives. Such masks for high-contrast internal coronagraphic imaging require various fabrication technologies to meet a wide range of specifications, including precise shapes, micron scale island features, ultralow reflectivity regions, uniformity, wave front quality, and achromaticity. We present the approaches employed at JPL to produce pupil plane and image plane coronagraph masks by combining electron beam, deep reactive ion etching, and black silicon technologies with illustrative examples of each, highlighting milestone accomplishments from the High Contrast Imaging Testbed at JPL and from the High Contrast Imaging Lab at Princeton University.

Quantitative Assessment of Fat Levels in Caenorhabditis elegans Using Dark Field Microscopy

PubMed Central

Fouad, Anthony D.; Pu, Shelley H.; Teng, Shelly; Mark, Julian R.; Fu, Moyu; Zhang, Kevin; Huang, Jonathan; Raizen, David M.; Fang-Yen, Christopher

2017-01-01

The roundworm Caenorhabditis elegans is widely used as a model for studying conserved pathways for fat storage, aging, and metabolism. The most broadly used methods for imaging fat in C. elegans require fixing and staining the animal. Here, we show that dark field images acquired through an ordinary light microscope can be used to estimate fat levels in worms. We define a metric based on the amount of light scattered per area, and show that this light scattering metric is strongly correlated with worm fat levels as measured by Oil Red O (ORO) staining across a wide variety of genetic backgrounds and feeding conditions. Dark field imaging requires no exogenous agents or chemical fixation, making it compatible with live worm imaging. Using our method, we track fat storage with high temporal resolution in developing larvae, and show that fat storage in the intestine increases in at least one burst during development. PMID:28404661

Renal magnetic resonance angiography at 3.0 Tesla using a 32-element phased-array coil system and parallel imaging in 2 directions.

PubMed

Fenchel, Michael; Nael, Kambiz; Deshpande, Vibhas S; Finn, J Paul; Kramer, Ulrich; Miller, Stephan; Ruehm, Stefan; Laub, Gerhard

2006-09-01

The aim of the present study was to assess the feasibility of renal magnetic resonance angiography at 3.0 T using a phased-array coil system with 32-coil elements. Specifically, high parallel imaging factors were used for an increased spatial resolution and anatomic coverage of the whole abdomen. Signal-to-noise values and the g-factor distribution of the 32 element coil were examined in phantom studies for the magnetic resonance angiography (MRA) sequence. Eleven volunteers (6 men, median age of 30.0 years) were examined on a 3.0-T MR scanner (Magnetom Trio, Siemens Medical Solutions, Malvern, PA) using a 32-element phased-array coil (prototype from In vivo Corp.). Contrast-enhanced 3D-MRA (TR 2.95 milliseconds, TE 1.12 milliseconds, flip angle 25-30 degrees , bandwidth 650 Hz/pixel) was acquired with integrated generalized autocalibrating partially parallel acquisition (GRAPPA), in both phase- and slice-encoding direction. Images were assessed by 2 independent observers with regard to image quality, noise and presence of artifacts. Signal-to-noise levels of 22.2 +/- 22.0 and 57.9 +/- 49.0 were measured with (GRAPPAx6) and without parallel-imaging, respectively. The mean g-factor of the 32-element coil for GRAPPA with an acceleration of 3 and 2 in the phase-encoding and slice-encoding direction, respectively, was 1.61. High image quality was found in 9 of 11 volunteers (2.6 +/- 0.8) with good overall interobserver agreement (k = 0.87). Relatively low image quality with higher noise levels were encountered in 2 volunteers. MRA at 3.0 T using a 32-element phased-array coil is feasible in healthy volunteers. High diagnostic image quality and extended anatomic coverage could be achieved with application of high parallel imaging factors.

A 3D image sensor with adaptable charge subtraction scheme for background light suppression

NASA Astrophysics Data System (ADS)

Shin, Jungsoon; Kang, Byongmin; Lee, Keechang; Kim, James D. K.

2013-02-01

We present a 3D ToF (Time-of-Flight) image sensor with adaptive charge subtraction scheme for background light suppression. The proposed sensor can alternately capture high resolution color image and high quality depth map in each frame. In depth-mode, the sensor requires enough integration time for accurate depth acquisition, but saturation will occur in high background light illumination. We propose to divide the integration time into N sub-integration times adaptively. In each sub-integration time, our sensor captures an image without saturation and subtracts the charge to prevent the pixel from the saturation. In addition, the subtraction results are cumulated N times obtaining a final result image without background illumination at full integration time. Experimental results with our own ToF sensor show high background suppression performance. We also propose in-pixel storage and column-level subtraction circuit for chiplevel implementation of the proposed method. We believe the proposed scheme will enable 3D sensors to be used in out-door environment.

The impact of thin idealized media images on body satisfaction: does body appreciation protect women from negative effects?

PubMed

Halliwell, Emma

2013-09-01

This article examines whether positive body image can protect women from negative media exposure effects. University women (N=112) were randomly allocated to view advertisements featuring ultra-thin models or control images. Women who reported high levels of body appreciation did not report negative media exposure effects. Furthermore, the protective role of body appreciation was also evident among women known to be vulnerable to media exposure. Women high on thin-ideal internalization and low on body appreciation reported appearance-discrepancies that were more salient and larger when they viewed models compared to the control group. However, women high on thin-ideal internalization and also high on body appreciation rated appearance-discrepancies as less important and no difference in size than the control group. The results support the notion that positive body image protects women from negative environmental appearance messages and suggests that promoting positive body image may be an effective intervention strategy. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the estimation of advanced regional association metrics at the voxel level.

Techniques to derive geometries for image-based Eulerian computations

PubMed Central

Dillard, Seth; Buchholz, James; Vigmostad, Sarah; Kim, Hyunggun; Udaykumar, H.S.

2014-01-01

Purpose The performance of three frequently used level set-based segmentation methods is examined for the purpose of defining features and boundary conditions for image-based Eulerian fluid and solid mechanics models. The focus of the evaluation is to identify an approach that produces the best geometric representation from a computational fluid/solid modeling point of view. In particular, extraction of geometries from a wide variety of imaging modalities and noise intensities, to supply to an immersed boundary approach, is targeted. Design/methodology/approach Two- and three-dimensional images, acquired from optical, X-ray CT, and ultrasound imaging modalities, are segmented with active contours, k-means, and adaptive clustering methods. Segmentation contours are converted to level sets and smoothed as necessary for use in fluid/solid simulations. Results produced by the three approaches are compared visually and with contrast ratio, signal-to-noise ratio, and contrast-to-noise ratio measures. Findings While the active contours method possesses built-in smoothing and regularization and produces continuous contours, the clustering methods (k-means and adaptive clustering) produce discrete (pixelated) contours that require smoothing using speckle-reducing anisotropic diffusion (SRAD). Thus, for images with high contrast and low to moderate noise, active contours are generally preferable. However, adaptive clustering is found to be far superior to the other two methods for images possessing high levels of noise and global intensity variations, due to its more sophisticated use of local pixel/voxel intensity statistics. Originality/value It is often difficult to know a priori which segmentation will perform best for a given image type, particularly when geometric modeling is the ultimate goal. This work offers insight to the algorithm selection process, as well as outlining a practical framework for generating useful geometric surfaces in an Eulerian setting. PMID:25750470

Combined chirp coded tissue harmonic and fundamental ultrasound imaging for intravascular ultrasound: 20–60 MHz phantom and ex vivo results

PubMed Central

Park, Jinhyoung; Li, Xiang; Zhou, Qifa; Shung, K. Kirk

2013-01-01

The application of chirp coded excitation to pulse inversion tissue harmonic imaging can increase signal to noise ratio. On the other hand, the elevation of range side lobe level, caused by leakages of the fundamental signal, has been problematic in mechanical scanners which are still the most prevalent in high frequency intravascular ultrasound imaging. Fundamental chirp coded excitation imaging can achieve range side lobe levels lower than –60 dB with Hanning window, but it yields higher side lobes level than pulse inversion chirp coded tissue harmonic imaging (PI-CTHI). Therefore, in this paper a combined pulse inversion chirp coded tissue harmonic and fundamental imaging mode (CPI-CTHI) is proposed to retain the advantages of both chirp coded harmonic and fundamental imaging modes by demonstrating 20–60 MHz phantom and ex vivo results. A simulation study shows that the range side lobe level of CPI-CTHI is 16 dB lower than PI-CTHI, assuming that the transducer translates incident positions by 50 μm when two beamlines of pulse inversion pair are acquired. CPI-CTHI is implemented for a proto-typed intravascular ultrasound scanner capable of combined data acquisition in real-time. A wire phantom study shows that CPI-CTHI has a 12 dB lower range side lobe level and a 7 dB higher echo signal to noise ratio than PI-CTHI, while the lateral resolution and side lobe level are 50 μm finer and –3 dB less than fundamental chirp coded excitation imaging respectively. Ex vivo scanning of a rabbit trachea demonstrates that CPI-CTHI is capable of visualizing blood vessels as small as 200 μm in diameter with 6 dB better tissue contrast than either PI-CTHI or fundamental chirp coded excitation imaging. These results clearly indicate that CPI-CTHI may enhance tissue contrast with less range side lobe level than PI-CTHI. PMID:22871273

Efficient iterative image reconstruction algorithm for dedicated breast CT

NASA Astrophysics Data System (ADS)

Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan

2016-03-01

Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.

Half-Fan-Based Intensity-Weighted Region-of-Interest Imaging for Low-Dose Cone-Beam CT in Image-Guided Radiation Therapy.

PubMed

Yoo, Boyeol; Son, Kihong; Pua, Rizza; Kim, Jinsung; Solodov, Alexander; Cho, Seungryong

2016-10-01

With the increased use of computed tomography (CT) in clinics, dose reduction is the most important feature people seek when considering new CT techniques or applications. We developed an intensity-weighted region-of-interest (IWROI) imaging method in an exact half-fan geometry to reduce the imaging radiation dose to patients in cone-beam CT (CBCT) for image-guided radiation therapy (IGRT). While dose reduction is highly desirable, preserving the high-quality images of the ROI is also important for target localization in IGRT. An intensity-weighting (IW) filter made of copper was mounted in place of a bowtie filter on the X-ray tube unit of an on-board imager (OBI) system such that the filter can substantially reduce radiation exposure to the outer ROI. In addition to mounting the IW filter, the lead-blade collimation of the OBI was adjusted to produce an exact half-fan scanning geometry for a further reduction of the radiation dose. The chord-based rebinned backprojection-filtration (BPF) algorithm in circular CBCT was implemented for image reconstruction, and a humanoid pelvis phantom was used for the IWROI imaging experiment. The IWROI image of the phantom was successfully reconstructed after beam-quality correction, and it was registered to the reference image within an acceptable level of tolerance. Dosimetric measurements revealed that the dose is reduced by approximately 61% in the inner ROI and by 73% in the outer ROI compared to the conventional bowtie filter-based half-fan scan. The IWROI method substantially reduces the imaging radiation dose and provides reconstructed images with an acceptable level of quality for patient setup and target localization. The proposed half-fan-based IWROI imaging technique can add a valuable option to CBCT in IGRT applications.

Handheld Fluorescence Microscopy based Flow Analyzer.

PubMed

Saxena, Manish; Jayakumar, Nitin; Gorthi, Sai Siva

2016-03-01

Fluorescence microscopy has the intrinsic advantages of favourable contrast characteristics and high degree of specificity. Consequently, it has been a mainstay in modern biological inquiry and clinical diagnostics. Despite its reliable nature, fluorescence based clinical microscopy and diagnostics is a manual, labour intensive and time consuming procedure. The article outlines a cost-effective, high throughput alternative to conventional fluorescence imaging techniques. With system level integration of custom-designed microfluidics and optics, we demonstrate fluorescence microscopy based imaging flow analyzer. Using this system we have imaged more than 2900 FITC labeled fluorescent beads per minute. This demonstrates high-throughput characteristics of our flow analyzer in comparison to conventional fluorescence microscopy. The issue of motion blur at high flow rates limits the achievable throughput in image based flow analyzers. Here we address the issue by computationally deblurring the images and show that this restores the morphological features otherwise affected by motion blur. By further optimizing concentration of the sample solution and flow speeds, along with imaging multiple channels simultaneously, the system is capable of providing throughput of about 480 beads per second.

Effects of atorvastatin treatment on left ventricular diastolic function in peritoneal dialysis patients-The ALEVENT clinical trial.

PubMed

Wu, Cho-Kai; Yeh, Chih-Fan; Chiang, Jiun-Yang; Lin, Ting-Tse; Wu, Yi-Fan; Chiang, Chih-Kang; Kao, Tze-Wah; Hung, Kuan-Yu; Huang, Jenq-Wen

Left ventricular diastolic dysfunction (LVDD) is common among patients undergoing peritoneal dialysis (PD). Increased levels of inflammatory biomarkers, such as high-sensitivity C-reactive protein, predict the development of LVDD. We hypothesized that PD patients with elevated high-sensitivity C-reactive protein levels might benefit from statin treatment for LVDD and designed a randomized clinical trial to prove the hypothesis. We screened 213 PD patients and randomly assigned 32 men and women with low-density lipoprotein cholesterol levels <130 mg/dL, high-sensitivity C-reactive protein levels of ≥1.5 mg/L, and LVDD, diagnosed by conventional and tissue Doppler imaging (TDI) echocardiography, to treatment with atorvastatin, 40 mg daily, or without. The primary end points were changes in TDI diastolic parameters or global strain imaging diastolic parameters. Atorvastatin reduced low-density lipoprotein cholesterol levels by 43% and high-sensitivity C-reactive protein levels by 45% (both P < .001). Follow-up TDI showed significant improvement of early mitral flow velocities divided by early diastolic peak velocities of the mitral annulus at the medial and lateral site (Nominal change for E/E medial : -5.01 ± 6.36 vs 1.80 ± 6.59 for atorvastatin and control, respectively, P = .02). There was also a significant improvement in global strain imaging after atorvastatin treatment (global strain rate, -17.12 ± 1.42 vs -14.61 ± 1.78 for atorvastatin and control, respectively, P = .002 and E/SR IVR , 462.35 ± 110.54 vs 634.09 ± 116.81, P = .003). In this trial of PD patients without hyperlipidemia but with elevated high-sensitivity C-reactive protein levels and LVDD, atorvastatin significantly improved cardiac diastolic function (ClinicalTrials.gov number, NCT01503671). Copyright © 2017. Published by Elsevier Inc.

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.

Ultra high speed image processing techniques. [electronic packaging techniques

NASA Technical Reports Server (NTRS)

Anthony, T.; Hoeschele, D. F.; Connery, R.; Ehland, J.; Billings, J.

1981-01-01

Packaging techniques for ultra high speed image processing were developed. These techniques involve the development of a signal feedthrough technique through LSI/VLSI sapphire substrates. This allows the stacking of LSI/VLSI circuit substrates in a 3 dimensional package with greatly reduced length of interconnecting lines between the LSI/VLSI circuits. The reduced parasitic capacitances results in higher LSI/VLSI computational speeds at significantly reduced power consumption levels.

Preoperative easily misdiagnosed telangiectatic osteosarcoma: clinical-radiologic-pathologic correlations.

PubMed

Gao, Zhen-Hua; Yin, Jun-Qiang; Liu, Da-Wei; Meng, Quan-Fei; Li, Jia-Ping

2013-12-11

To describe the clinical, imaging, and pathologic characteristics and diagnostic methods of telangiectatic osteosarcoma (TOS) for improving the diagnostic level. The authors retrospectively reviewed patient demographics, serum alkaline phosphatase (AKP) levels, preoperative biopsy pathologic reports, pathologic materials, imaging findings, and treatment outcomes from 26 patients with TOS. Patient images from radiography (26 cases) and magnetic resonance (MR) imaging (22 cases) were evaluated by 3 authors in consensus for intrinsic characteristics. There were 15 male and 11 female patients in the study, with an age of 9-32 years (mean age 15.9 years). Eighteen of 26 patients died of lung metastases within 5 years of follow-up. The distal femur was affected more commonly (14 cases, 53.8%). Regarding serum AKP, normal (8 cases) or mildly elevated (18 cases) levels were found before preoperative chemotherapy. Radiographs showed geographic bone lysis without sclerotic margin (26 cases), cortical destruction (26 cases), periosteal new bone formation (24 cases), soft-tissue mass (23 cases), and matrix mineralization (4 cases). The aggressive radiographic features of TOS simulated the appearance of conventional high-grade intramedullary osteosarcoma, though different from aneurysmal bone cyst. MR images demonstrated multiple big (16 cases) or small (6 cases) cystic spaces, fluid-fluid levels (14 cases), soft-tissue mass (22 cases), and thick peripheral and septal enhancement (22 cases). Nine of 26 cases were misdiagnosed as aneurysmal bone cysts by preoperative core-needle biopsy, owing to the absence of viable high-grade sarcomatous cells in the small tissue samples. The aggressive growth pattern with occasional matrix mineralization, and multiple big or small fluid-filled cavities with thick peripheral, septal, and nodular tissue surrounding the fluid-filled cavities are characteristic imaging features of TOS, and these features are helpful in making the correct preoperative diagnosis of TOS.

High-resolution MALDI mass spectrometry imaging of gallotannins and monoterpene glucosides in the root of Paeonia lactiflora

NASA Astrophysics Data System (ADS)

Li, Bin; Bhandari, Dhaka Ram; Römpp, Andreas; Spengler, Bernhard

2016-10-01

High-resolution atmospheric-pressure scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging (AP-SMALDI MSI) at 10 μm pixel size was performed to unravel the spatio-chemical distribution of major secondary metabolites in the root of Paeonia lactiflora. The spatial distributions of two major classes of bioactive components, gallotannins and monoterpene glucosides, were investigated and visualized at the cellular level in tissue sections of P. lactiflora roots. Accordingly, other primary and secondary metabolites were imaged, including amino acids, carbohydrates, lipids and monoterpenes, indicating the capability of untargeted localization of metabolites by using high-resolution MSI platform. The employed AP-SMALDI MSI system provides significant technological advancement in the visualization of individual molecular species at the cellular level. In contrast to previous histochemical studies of tannins using unspecific staining reagents, individual gallotannin species were accurately localized and unequivocally discriminated from other phenolic components in the root tissues. High-quality ion images were obtained, providing significant clues for understanding the biosynthetic pathway of gallotannins and monoterpene glucosides and possibly helping to decipher the role of tannins in xylem cells differentiation and in the defence mechanisms of plants, as well as to investigate the interrelationship between tannins and lignins.

High-resolution MALDI mass spectrometry imaging of gallotannins and monoterpene glucosides in the root of Paeonia lactiflora.

PubMed

Li, Bin; Bhandari, Dhaka Ram; Römpp, Andreas; Spengler, Bernhard

2016-10-31

High-resolution atmospheric-pressure scanning microprobe matrix-assisted laser desorption/ionization mass spectrometry imaging (AP-SMALDI MSI) at 10 μm pixel size was performed to unravel the spatio-chemical distribution of major secondary metabolites in the root of Paeonia lactiflora. The spatial distributions of two major classes of bioactive components, gallotannins and monoterpene glucosides, were investigated and visualized at the cellular level in tissue sections of P. lactiflora roots. Accordingly, other primary and secondary metabolites were imaged, including amino acids, carbohydrates, lipids and monoterpenes, indicating the capability of untargeted localization of metabolites by using high-resolution MSI platform. The employed AP-SMALDI MSI system provides significant technological advancement in the visualization of individual molecular species at the cellular level. In contrast to previous histochemical studies of tannins using unspecific staining reagents, individual gallotannin species were accurately localized and unequivocally discriminated from other phenolic components in the root tissues. High-quality ion images were obtained, providing significant clues for understanding the biosynthetic pathway of gallotannins and monoterpene glucosides and possibly helping to decipher the role of tannins in xylem cells differentiation and in the defence mechanisms of plants, as well as to investigate the interrelationship between tannins and lignins.

Radiological image presentation requires consideration of human adaptation characteristics

NASA Astrophysics Data System (ADS)

O'Connell, N. M.; Toomey, R. J.; McEntee, M.; Ryan, J.; Stowe, J.; Adams, A.; Brennan, P. C.

2008-03-01

Visualisation of anatomical or pathological image data is highly dependent on the eye's ability to discriminate between image brightnesses and this is best achieved when these data are presented to the viewer at luminance levels to which the eye is adapted. Current ambient light recommendations are often linked to overall monitor luminance but this relies on specific regions of interest matching overall monitor brightness. The current work investigates the luminances of specific regions of interest within three image-types: postero-anterior (PA) chest; PA wrist; computerised tomography (CT) of the head. Luminance levels were measured within the hilar region and peripheral lung distal radius and supra-ventricular grey matter. For each image type average monitor luminances were calculated with a calibrated photometer at ambient light levels of 0, 100 and 400 lux. Thirty samples of each image-type were employed, resulting in a total of over 6,000 measurements. Results demonstrate that average monitor luminances varied from clinically-significant values by up to a factor of 4, 2 and 6 for chest, wrist and CT head images respectively. Values for the thoracic hilum and wrist were higher and for the peripheral lung and CT brain lower than overall monitor levels. The ambient light level had no impact on the results. The results demonstrate that clinically important radiological information for common radiological examinations is not being presented to the viewer in a way that facilitates optimised visual adaptation and subsequent interpretation. The importance of image-processing algorithms focussing on clinically-significant anatomical regions instead of radiographic projections is highlighted.

Building Change Detection in Very High Resolution Satellite Stereo Image Time Series

NASA Astrophysics Data System (ADS)

Tian, J.; Qin, R.; Cerra, D.; Reinartz, P.

2016-06-01

There is an increasing demand for robust methods on urban sprawl monitoring. The steadily increasing number of high resolution and multi-view sensors allows producing datasets with high temporal and spatial resolution; however, less effort has been dedicated to employ very high resolution (VHR) satellite image time series (SITS) to monitor the changes in buildings with higher accuracy. In addition, these VHR data are often acquired from different sensors. The objective of this research is to propose a robust time-series data analysis method for VHR stereo imagery. Firstly, the spatial-temporal information of the stereo imagery and the Digital Surface Models (DSMs) generated from them are combined, and building probability maps (BPM) are calculated for all acquisition dates. In the second step, an object-based change analysis is performed based on the derivative features of the BPM sets. The change consistence between object-level and pixel-level are checked to remove any outlier pixels. Results are assessed on six pairs of VHR satellite images acquired within a time span of 7 years. The evaluation results have proved the efficiency of the proposed method.

Deep image mining for diabetic retinopathy screening.

PubMed

Quellec, Gwenolé; Charrière, Katia; Boudi, Yassine; Cochener, Béatrice; Lamard, Mathieu

2017-07-01

Deep learning is quickly becoming the leading methodology for medical image analysis. Given a large medical archive, where each image is associated with a diagnosis, efficient pathology detectors or classifiers can be trained with virtually no expert knowledge about the target pathologies. However, deep learning algorithms, including the popular ConvNets, are black boxes: little is known about the local patterns analyzed by ConvNets to make a decision at the image level. A solution is proposed in this paper to create heatmaps showing which pixels in images play a role in the image-level predictions. In other words, a ConvNet trained for image-level classification can be used to detect lesions as well. A generalization of the backpropagation method is proposed in order to train ConvNets that produce high-quality heatmaps. The proposed solution is applied to diabetic retinopathy (DR) screening in a dataset of almost 90,000 fundus photographs from the 2015 Kaggle Diabetic Retinopathy competition and a private dataset of almost 110,000 photographs (e-ophtha). For the task of detecting referable DR, very good detection performance was achieved: A z =0.954 in Kaggle's dataset and A z =0.949 in e-ophtha. Performance was also evaluated at the image level and at the lesion level in the DiaretDB1 dataset, where four types of lesions are manually segmented: microaneurysms, hemorrhages, exudates and cotton-wool spots. For the task of detecting images containing these four lesion types, the proposed detector, which was trained to detect referable DR, outperforms recent algorithms trained to detect those lesions specifically, with pixel-level supervision. At the lesion level, the proposed detector outperforms heatmap generation algorithms for ConvNets. This detector is part of the Messidor® system for mobile eye pathology screening. Because it does not rely on expert knowledge or manual segmentation for detecting relevant patterns, the proposed solution is a promising image mining tool, which has the potential to discover new biomarkers in images. Copyright © 2017 Elsevier B.V. All rights reserved.

Cnn Based Retinal Image Upscaling Using Zero Component Analysis

NASA Astrophysics Data System (ADS)

Nasonov, A.; Chesnakov, K.; Krylov, A.

2017-05-01

The aim of the paper is to obtain high quality of image upscaling for noisy images that are typical in medical image processing. A new training scenario for convolutional neural network based image upscaling method is proposed. Its main idea is a novel dataset preparation method for deep learning. The dataset contains pairs of noisy low-resolution images and corresponding noiseless highresolution images. To achieve better results at edges and textured areas, Zero Component Analysis is applied to these images. The upscaling results are compared with other state-of-the-art methods like DCCI, SI-3 and SRCNN on noisy medical ophthalmological images. Objective evaluation of the results confirms high quality of the proposed method. Visual analysis shows that fine details and structures like blood vessels are preserved, noise level is reduced and no artifacts or non-existing details are added. These properties are essential in retinal diagnosis establishment, so the proposed algorithm is recommended to be used in real medical applications.

Architecture for a PACS primary diagnosis workstation

NASA Astrophysics Data System (ADS)

Shastri, Kaushal; Moran, Byron

1990-08-01

A major factor in determining the overall utility of a medical Picture Archiving and Communications (PACS) system is the functionality of the diagnostic workstation. Meyer-Ebrecht and Wendler [1] have proposed a modular picture computer architecture with high throughput and Perry et.al [2] have defined performance requirements for radiology workstations. In order to be clinically useful, a primary diagnosis workstation must not only provide functions of current viewing systems (e.g. mechanical alternators [3,4]) such as acceptable image quality, simultaneous viewing of multiple images, and rapid switching of image banks; but must also provide a diagnostic advantage over the current systems. This includes window-level functions on any image, simultaneous display of multi-modality images, rapid image manipulation, image processing, dynamic image display (cine), electronic image archival, hardcopy generation, image acquisition, network support, and an easy user interface. Implementation of such a workstation requires an underlying hardware architecture which provides high speed image transfer channels, local storage facilities, and image processing functions. This paper describes the hardware architecture of the Siemens Diagnostic Reporting Console (DRC) which meets these requirements.

Multi-institutional MicroCT image comparison of image-guided small animal irradiators

NASA Astrophysics Data System (ADS)

Johnstone, Chris D.; Lindsay, Patricia; E Graves, Edward; Wong, Eugene; Perez, Jessica R.; Poirier, Yannick; Ben-Bouchta, Youssef; Kanesalingam, Thilakshan; Chen, Haijian; E Rubinstein, Ashley; Sheng, Ke; Bazalova-Carter, Magdalena

2017-07-01

To recommend imaging protocols and establish tolerance levels for microCT image quality assurance (QA) performed on conformal image-guided small animal irradiators. A fully automated QA software SAPA (small animal phantom analyzer) for image analysis of the commercial Shelley micro-CT MCTP 610 phantom was developed, in which quantitative analyses of CT number linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, spatial resolution by means of modulation transfer function (MTF), and CT contrast were performed. Phantom microCT scans from eleven institutions acquired with four image-guided small animal irradiator units (including the commercial PXi X-RAD SmART and Xstrahl SARRP systems) with varying parameters used for routine small animal imaging were analyzed. Multi-institutional data sets were compared using SAPA, based on which tolerance levels for each QA test were established and imaging protocols for QA were recommended. By analyzing microCT data from 11 institutions, we established image QA tolerance levels for all image quality tests. CT number linearity set to R 2  >  0.990 was acceptable in microCT data acquired at all but three institutions. Acceptable SNR  >  36 and noise levels  <55 HU were obtained at five of the eleven institutions, where failing scans were acquired with current-exposure time of less than 120 mAs. Acceptable spatial resolution (>1.5 lp mm-1 for MTF  =  0.2) was obtained at all but four institutions due to their large image voxel size used (>0.275 mm). Ten of the eleven institutions passed the set QA tolerance for geometric accuracy (<1.5%) and nine of the eleven institutions passed the QA tolerance for contrast (>2000 HU for 30 mgI ml-1). We recommend performing imaging QA with 70 kVp, 1.5 mA, 120 s imaging time, 0.20 mm voxel size, and a frame rate of 5 fps for the PXi X-RAD SmART. For the Xstrahl SARRP, we recommend using 60 kVp, 1.0 mA, 240 s imaging time, 0.20 mm voxel size, and 6 fps. These imaging protocols should result in high quality images that pass the set tolerance levels on all systems. Average SAPA computation time for complete QA analysis for a 0.20 mm voxel, 400 slice Shelley phantom microCT data set was less than 20 s. We present image quality assurance recommendations for image-guided small animal radiotherapy systems that can aid researchers in maintaining high image quality, allowing for spatially precise conformal dose delivery to small animals.

A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

NASA Astrophysics Data System (ADS)

Rubel, Aleksey S.; Lukin, Vladimir V.; Egiazarian, Karen O.

2015-03-01

Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.

In vivo imaging through the entire thickness of human cornea by full-field optical coherence tomography

NASA Astrophysics Data System (ADS)

Mazlin, Viacheslav; Xiao, Peng; Dalimier, Eugénie; Grieve, Kate; Irsch, Kristina; Sahel, José; Fink, Mathias; Boccara, Claude

2018-02-01

Despite obvious improvements in visualization of the in vivo cornea through the faster imaging speeds and higher axial resolutions, cellular imaging stays unresolvable task for OCT, as en face viewing with a high lateral resolution is required. The latter is possible with FFOCT, a method that relies on a camera, moderate numerical aperture (NA) objectives and an incoherent light source to provide en face images with a micrometer-level resolution. Recently, we for the first time demonstrated the ability of FFOCT to capture images from the in vivo human cornea1. In the current paper we present an extensive study of appearance of healthy in vivo human corneas under FFOCT examination. En face corneal images with a micrometer-level resolution were obtained from the three healthy subjects. For each subject it was possible to acquire images through the entire corneal depth and visualize the epithelium structures, Bowman's layer, sub-basal nerve plexus (SNP) fibers, anterior, middle and posterior stroma, endothelial cells with nuclei. Dimensions and densities of the structures visible with FFOCT, are in agreement with those seen by other cornea imaging methods. Cellular-level details in the images obtained together with the relatively large field-of-view (FOV) and contactless way of imaging make this device a promising candidate for becoming a new tool in ophthalmological diagnostics.

X-Windows Widget for Image Display

NASA Technical Reports Server (NTRS)

Deen, Robert G.

2011-01-01

XvicImage is a high-performance XWindows (Motif-compliant) user interface widget for displaying images. It handles all aspects of low-level image display. The fully Motif-compliant image display widget handles the following tasks: (1) Image display, including dithering as needed (2) Zoom (3) Pan (4) Stretch (contrast enhancement, via lookup table) (5) Display of single-band or color data (6) Display of non-byte data (ints, floats) (7) Pseudocolor display (8) Full overlay support (drawing graphics on image) (9) Mouse-based panning (10) Cursor handling, shaping, and planting (disconnecting cursor from mouse) (11) Support for all user interaction events (passed to application) (12) Background loading and display of images (doesn't freeze the GUI) (13) Tiling of images.

Molecular-genetic imaging based on reporter gene expression.

PubMed

Kang, Joo Hyun; Chung, June-Key

2008-06-01

Molecular imaging includes proteomic, metabolic, cellular biologic process, and genetic imaging. In a narrow sense, molecular imaging means genetic imaging and can be called molecular-genetic imaging. Imaging reporter genes play a leading role in molecular-genetic imaging. There are 3 major methods of molecular-genetic imaging, based on optical, MRI, and nuclear medicine modalities. For each of these modalities, various reporter genes and probes have been developed, and these have resulted in successful transitions from bench to bedside applications. Each of these imaging modalities has its unique advantages and disadvantages. Fluorescent and bioluminescent optical imaging modalities are simple, less expensive, more convenient, and more user friendly than other imaging modalities. Another advantage, especially of bioluminescence imaging, is its ability to detect low levels of gene expression. MRI has the advantage of high spatial resolution, whereas nuclear medicine methods are highly sensitive and allow data from small-animal imaging studies to be translated to clinical practice. Moreover, multimodality imaging reporter genes will allow us to choose the imaging technologies that are most appropriate for the biologic problem at hand and facilitate the clinical application of reporter gene technologies. Reporter genes can be used to visualize the levels of expression of particular exogenous and endogenous genes and several intracellular biologic phenomena, including specific signal transduction pathways, nuclear receptor activities, and protein-protein interactions. This technique provides a straightforward means of monitoring tumor mass and can visualize the in vivo distributions of target cells, such as immune cells and stem cells. Molecular imaging has gradually evolved into an important tool for drug discovery and development, and transgenic mice with an imaging reporter gene can be useful during drug and stem cell therapy development. Moreover, instrumentation improvements, the identification of novel targets and genes, and imaging probe developments suggest that molecular-genetic imaging is likely to play an increasingly important role in the diagnosis and therapy of cancer.

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

A Perceptually Weighted Rank Correlation Indicator for Objective Image Quality Assessment

NASA Astrophysics Data System (ADS)

Wu, Qingbo; Li, Hongliang; Meng, Fanman; Ngan, King N.

2018-05-01

In the field of objective image quality assessment (IQA), the Spearman's $\\rho$ and Kendall's $\\tau$ are two most popular rank correlation indicators, which straightforwardly assign uniform weight to all quality levels and assume each pair of images are sortable. They are successful for measuring the average accuracy of an IQA metric in ranking multiple processed images. However, two important perceptual properties are ignored by them as well. Firstly, the sorting accuracy (SA) of high quality images are usually more important than the poor quality ones in many real world applications, where only the top-ranked images would be pushed to the users. Secondly, due to the subjective uncertainty in making judgement, two perceptually similar images are usually hardly sortable, whose ranks do not contribute to the evaluation of an IQA metric. To more accurately compare different IQA algorithms, we explore a perceptually weighted rank correlation indicator in this paper, which rewards the capability of correctly ranking high quality images, and suppresses the attention towards insensitive rank mistakes. More specifically, we focus on activating `valid' pairwise comparison towards image quality, whose difference exceeds a given sensory threshold (ST). Meanwhile, each image pair is assigned an unique weight, which is determined by both the quality level and rank deviation. By modifying the perception threshold, we can illustrate the sorting accuracy with a more sophisticated SA-ST curve, rather than a single rank correlation coefficient. The proposed indicator offers a new insight for interpreting visual perception behaviors. Furthermore, the applicability of our indicator is validated in recommending robust IQA metrics for both the degraded and enhanced image data.

Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories

PubMed Central

Groen, Iris I. A.; Ghebreab, Sennay; Lamme, Victor A. F.; Scholte, H. Steven

2012-01-01

The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs) in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis). Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task. PMID:23093921

Quiet PROPELLER MRI techniques match the quality of conventional PROPELLER brain imaging techniques.

PubMed

Corcuera-Solano, I; Doshi, A; Pawha, P S; Gui, D; Gaddipati, A; Tanenbaum, L

2015-06-01

Switching of magnetic field gradients is the primary source of acoustic noise in MR imaging. Sound pressure levels can run as high as 120 dB, capable of producing physical discomfort and at least temporary hearing loss, mandating hearing protection. New technology has made quieter techniques feasible, which range from as low as 80 dB to nearly silent. The purpose of this study was to evaluate the image quality of new commercially available quiet T2 and quiet FLAIR fast spin-echo PROPELLER acquisitions in comparison with equivalent conventional PROPELLER techniques in current day-to-day practice in imaging of the brain. Thirty-four consecutive patients were prospectively scanned with quiet T2 and quiet T2 FLAIR PROPELLER, in addition to spatial resolution-matched conventional T2 and T2 FLAIR PROPELLER imaging sequences on a clinical 1.5T MR imaging scanner. Measurement of sound pressure levels and qualitative evaluation of relative image quality was performed. Quiet T2 and quiet T2 FLAIR were comparable in image quality with conventional acquisitions, with sound levels of approximately 75 dB, a reduction in average sound pressure levels of up to 28.5 dB, with no significant trade-offs aside from longer scan times. Quiet FSE provides equivalent image quality at comfortable sound pressure levels at the cost of slightly longer scan times. The significant reduction in potentially injurious noise is particularly important in vulnerable populations such as children, the elderly, and the debilitated. Quiet techniques should be considered in these special situations for routine use in clinical practice. © 2015 by American Journal of Neuroradiology.

Image Registration Workshop Proceedings

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline (Editor)

1997-01-01

Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research.

Brain magnetic resonance imaging with contrast dependent on blood oxygenation

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

Ogawa, S.; Lee, T.M.; Kay, A.R.

1990-12-01

Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradient-echo techniques in high yields, the authors demonstrate in vivo images of brain microvasculature with image contrast reflecting the blood oxygen level. This blood oxygenation level-dependent (BOLD) contrast follows blood oxygen changes induced by anesthetics, by insulin-induced hypoglycemia, and by inhaled gas mixtures that alter metabolic demand or blood flow. The results suggest that BOLD contrast can be used to provide in vivo real-time maps of blood oxygenation in the brain under normalmore » physiological conditions. BOLD contrast adds an additional feature to magnetic resonance imaging and complement other techniques that are attempting to provide position emission tomography-like measurements related to regional neural activity.« less

Brain Magnetic Resonance Imaging with Contrast Dependent on Blood Oxygenation

NASA Astrophysics Data System (ADS)

Ogawa, S.; Lee, T. M.; Kay, A. R.; Tank, D. W.

1990-12-01

Paramagnetic deoxyhemoglobin in venous blood is a naturally occurring contrast agent for magnetic resonance imaging (MRI). By accentuating the effects of this agent through the use of gradient-echo techniques in high fields, we demonstrate in vivo images of brain microvasculature with image contrast reflecting the blood oxygen level. This blood oxygenation level-dependent (BOLD) contrast follows blood oxygen changes induced by anesthetics, by insulin-induced hypoglycemia, and by inhaled gas mixtures that alter metabolic demand or blood flow. The results suggest that BOLD contrast can be used to provide in vivo real-time maps of blood oxygenation in the brain under normal physiological conditions. BOLD contrast adds an additional feature to magnetic resonance imaging and complements other techniques that are attempting to provide positron emission tomography-like measurements related to regional neural activity.

TU-E-217BCD-06: Cone Beam Breast CT with a High Resolution Flat Panel Detector-Improvement of Calcification Visibility.

PubMed

Shen, Y; Zhong, Y; Lai, C; Wang, T; Shaw, C

2012-06-01

To investigate the advantage of a high resolution flat panel detector for improving the visibility of microcalcifications (MCs) in cone beam breast CT Methods: A paraffin cylinder was used to simulate a 100% adipose breast. Calcium carbonate grains, ranging from 125-140 μm to 224 - 250 μm in size, were used to simulate the MCs. Groups of 25 same size MCs were embedded at the phantom center. The phantom was scanned with a bench-top CBCT system at various exposure levels. A 75μm pitch flat panel detector (Dexela 2923, Perkin Elmer) with 500μm thick CsI scintillator plate was used as the high resolution detector. A 194 μm pitch detector (Paxscan 4030CB, Varian Medical Systems) was used for reference. 300 projection images were acquired over 360° and reconstructed. The images were reviewed by 6 readers. The MC visibility was quantified as the fraction of visible MCs and averaged for comparison. The visibility was plotted as a function of the estimated dose level for various MC sizes and detectors. The MTFs and DQEs were measured and compared. For imaging small (200 μm and smaller) MCs, the visibility achieved with the 75μm pitch detector was found to be significantly higher than those achieved with the 194μm pitch detector. For imaging larger MCs, there was little advantage in using the 75μm pitch detector. Using the 75μm pitch detector, MCs as small as 180 μm could be imaged to achieve a visibility of 78% with an isocenter tissue dose of ∼20 mGys versus 62% achieved with the 194 μm pitch detector at the same dose level. It was found that a high pitch flat panel detector had the advantages of extending its imaging capability to higher frequencies thus helping improve the visibility when used to image small MCs. This work was supported in part by grants CA104759, CA13852 and CA124585 from NIH-NCI, a grant EB00117 from NIH-NIBIB, and a subcontract from NIST-ATP. © 2012 American Association of Physicists in Medicine.

Scatter Correction with Combined Single-Scatter Simulation and Monte Carlo Simulation Scaling Improved the Visual Artifacts and Quantification in 3-Dimensional Brain PET/CT Imaging with 15O-Gas Inhalation.

PubMed

Magota, Keiichi; Shiga, Tohru; Asano, Yukari; Shinyama, Daiki; Ye, Jinghan; Perkins, Amy E; Maniawski, Piotr J; Toyonaga, Takuya; Kobayashi, Kentaro; Hirata, Kenji; Katoh, Chietsugu; Hattori, Naoya; Tamaki, Nagara

2017-12-01

In 3-dimensional PET/CT imaging of the brain with 15 O-gas inhalation, high radioactivity in the face mask creates cold artifacts and affects the quantitative accuracy when scatter is corrected by conventional methods (e.g., single-scatter simulation [SSS] with tail-fitting scaling [TFS-SSS]). Here we examined the validity of a newly developed scatter-correction method that combines SSS with a scaling factor calculated by Monte Carlo simulation (MCS-SSS). Methods: We performed phantom experiments and patient studies. In the phantom experiments, a plastic bottle simulating a face mask was attached to a cylindric phantom simulating the brain. The cylindric phantom was filled with 18 F-FDG solution (3.8-7.0 kBq/mL). The bottle was filled with nonradioactive air or various levels of 18 F-FDG (0-170 kBq/mL). Images were corrected either by TFS-SSS or MCS-SSS using the CT data of the bottle filled with nonradioactive air. We compared the image activity concentration in the cylindric phantom with the true activity concentration. We also performed 15 O-gas brain PET based on the steady-state method on patients with cerebrovascular disease to obtain quantitative images of cerebral blood flow and oxygen metabolism. Results: In the phantom experiments, a cold artifact was observed immediately next to the bottle on TFS-SSS images, where the image activity concentrations in the cylindric phantom were underestimated by 18%, 36%, and 70% at the bottle radioactivity levels of 2.4, 5.1, and 9.7 kBq/mL, respectively. At higher bottle radioactivity, the image activity concentrations in the cylindric phantom were greater than 98% underestimated. For the MCS-SSS, in contrast, the error was within 5% at each bottle radioactivity level, although the image generated slight high-activity artifacts around the bottle when the bottle contained significantly high radioactivity. In the patient imaging with 15 O 2 and C 15 O 2 inhalation, cold artifacts were observed on TFS-SSS images, whereas no artifacts were observed on any of the MCS-SSS images. Conclusion: MCS-SSS accurately corrected the scatters in 15 O-gas brain PET when the 3-dimensional acquisition mode was used, preventing the generation of cold artifacts, which were observed immediately next to a face mask on TFS-SSS images. The MCS-SSS method will contribute to accurate quantitative assessments. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Detectability comparison between a high energy x-ray phase sensitive and mammography systems in imaging phantoms with varying glandular-adipose ratios

NASA Astrophysics Data System (ADS)

Ghani, Muhammad U.; Wong, Molly D.; Wu, Di; Zheng, Bin; Fajardo, Laurie L.; Yan, Aimin; Fuh, Janis; Wu, Xizeng; Liu, Hong

2017-05-01

The objective of this study was to demonstrate the potential benefits of using high energy x-rays in comparison with the conventional mammography imaging systems for phase sensitive imaging of breast tissues with varying glandular-adipose ratios. This study employed two modular phantoms simulating the glandular (G) and adipose (A) breast tissue composition in 50 G-50 A and 70 G-30 A percentage densities. Each phantom had a thickness of 5 cm with a contrast detail test pattern embedded in the middle. For both phantoms, the phase contrast images were acquired using a micro-focus x-ray source operated at 120 kVp and 4.5 mAs, with a magnification factor (M) of 2.5 and a detector with a 50 µm pixel pitch. The mean glandular dose delivered to the 50 G-50 A and 70 G-30 A phantom sets were 1.33 and 1.3 mGy, respectively. A phase retrieval algorithm based on the phase attenuation duality that required only a single phase contrast image was applied. Conventional low energy mammography images were acquired using GE Senographe DS and Hologic Selenia systems utilizing their automatic exposure control (AEC) settings. In addition, the automatic contrast mode (CNT) was also used for the acquisition with the GE system. The AEC mode applied higher dose settings for the 70 G-30 A phantom set. As compared to the phase contrast images, the dose levels for the AEC mode acquired images were similar while the dose levels for the CNT mode were almost double. The observer study, contrast-to-noise ratio and figure of merit comparisons indicated a large improvement with the phase retrieved images in comparison to the AEC mode images acquired with the clinical systems for both density levels. As the glandular composition increased, the detectability of smaller discs decreased with the clinical systems, particularly with the GE system, even at higher dose settings. As compared to the CNT mode (double dose) images, the observer study also indicated that the phase retrieved images provided similar or improved detection for all disc sizes except for the disk diameters of 2 mm and 1 mm for the 50 G-50 A phantom and 3 mm and 0.5 mm for the 70 G-30 A phantom. This study demonstrated the potential of utilizing a high energy phase sensitive x-ray imaging system to improve lesion detection and reduce radiation dose when imaging breast tissues with varying glandular compositions.

Intra- and inter-rater reliability of digital image analysis for skin color measurement

PubMed Central

Sommers, Marilyn; Beacham, Barbara; Baker, Rachel; Fargo, Jamison

2013-01-01

Background We determined the intra- and inter-rater reliability of data from digital image color analysis between an expert and novice analyst. Methods Following training, the expert and novice independently analyzed 210 randomly ordered images. Both analysts used Adobe® Photoshop lasso or color sampler tools based on the type of image file. After color correction with Pictocolor® in camera software, they recorded L*a*b* (L*=light/dark; a*=red/green; b*=yellow/blue) color values for all skin sites. We computed intra-rater and inter-rater agreement within anatomical region, color value (L*, a*, b*), and technique (lasso, color sampler) using a series of one-way intra-class correlation coefficients (ICCs). Results Results of ICCs for intra-rater agreement showed high levels of internal consistency reliability within each rater for the lasso technique (ICC ≥ 0.99) and somewhat lower, yet acceptable, level of agreement for the color sampler technique (ICC = 0.91 for expert, ICC = 0.81 for novice). Skin L*, skin b*, and labia L* values reached the highest level of agreement (ICC ≥ 0.92) and skin a*, labia b*, and vaginal wall b* were the lowest (ICC ≥ 0.64). Conclusion Data from novice analysts can achieve high levels of agreement with data from expert analysts with training and the use of a detailed, standard protocol. PMID:23551208

Intra- and inter-rater reliability of digital image analysis for skin color measurement.

PubMed

Sommers, Marilyn; Beacham, Barbara; Baker, Rachel; Fargo, Jamison

2013-11-01

We determined the intra- and inter-rater reliability of data from digital image color analysis between an expert and novice analyst. Following training, the expert and novice independently analyzed 210 randomly ordered images. Both analysts used Adobe(®) Photoshop lasso or color sampler tools based on the type of image file. After color correction with Pictocolor(®) in camera software, they recorded L*a*b* (L*=light/dark; a*=red/green; b*=yellow/blue) color values for all skin sites. We computed intra-rater and inter-rater agreement within anatomical region, color value (L*, a*, b*), and technique (lasso, color sampler) using a series of one-way intra-class correlation coefficients (ICCs). Results of ICCs for intra-rater agreement showed high levels of internal consistency reliability within each rater for the lasso technique (ICC ≥ 0.99) and somewhat lower, yet acceptable, level of agreement for the color sampler technique (ICC = 0.91 for expert, ICC = 0.81 for novice). Skin L*, skin b*, and labia L* values reached the highest level of agreement (ICC ≥ 0.92) and skin a*, labia b*, and vaginal wall b* were the lowest (ICC ≥ 0.64). Data from novice analysts can achieve high levels of agreement with data from expert analysts with training and the use of a detailed, standard protocol. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The collection of images of an insulator taken outdoors in varying lighting conditions with additional laser spots.

PubMed

Tomaszewski, Michał; Ruszczak, Bogdan; Michalski, Paweł

2018-06-01

Electrical insulators are elements of power lines that require periodical diagnostics. Due to their location on the components of high-voltage power lines, their imaging can be cumbersome and time-consuming, especially under varying lighting conditions. Insulator diagnostics with the use of visual methods may require localizing insulators in the scene. Studies focused on insulator localization in the scene apply a number of methods, including: texture analysis, MRF (Markov Random Field), Gabor filters or GLCM (Gray Level Co-Occurrence Matrix) [1], [2]. Some methods, e.g. those which localize insulators based on colour analysis [3], rely on object and scene illumination, which is why the images from the dataset are taken under varying lighting conditions. The dataset may also be used to compare the effectiveness of different methods of localizing insulators in images. This article presents high-resolution images depicting a long rod electrical insulator under varying lighting conditions and against different backgrounds: crops, forest and grass. The dataset contains images with visible laser spots (generated by a device emitting light at the wavelength of 532 nm) and images without such spots, as well as complementary data concerning the illumination level and insulator position in the scene, the number of registered laser spots, and their coordinates in the image. The laser spots may be used to support object-localizing algorithms, while the images without spots may serve as a source of information for those algorithms which do not need spots to localize an insulator.

Richardson-Lucy deconvolution as a general tool for combining images with complementary strengths.

PubMed

Ingaramo, Maria; York, Andrew G; Hoogendoorn, Eelco; Postma, Marten; Shroff, Hari; Patterson, George H

2014-03-17

We use Richardson-Lucy (RL) deconvolution to combine multiple images of a simulated object into a single image in the context of modern fluorescence microscopy techniques. RL deconvolution can merge images with very different point-spread functions, such as in multiview light-sheet microscopes,1, 2 while preserving the best resolution information present in each image. We show that RL deconvolution is also easily applied to merge high-resolution, high-noise images with low-resolution, low-noise images, relevant when complementing conventional microscopy with localization microscopy. We also use RL deconvolution to merge images produced by different simulated illumination patterns, relevant to structured illumination microscopy (SIM)3, 4 and image scanning microscopy (ISM). The quality of our ISM reconstructions is at least as good as reconstructions using standard inversion algorithms for ISM data, but our method follows a simpler recipe that requires no mathematical insight. Finally, we apply RL deconvolution to merge a series of ten images with varying signal and resolution levels. This combination is relevant to gated stimulated-emission depletion (STED) microscopy, and shows that merges of high-quality images are possible even in cases for which a non-iterative inversion algorithm is unknown. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Assessing microscope image focus quality with deep learning.

PubMed

Yang, Samuel J; Berndl, Marc; Michael Ando, D; Barch, Mariya; Narayanaswamy, Arunachalam; Christiansen, Eric; Hoyer, Stephan; Roat, Chris; Hung, Jane; Rueden, Curtis T; Shankar, Asim; Finkbeiner, Steven; Nelson, Philip

2018-03-15

Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with high accuracy is important for obtaining a clean, unbiased image dataset. Complicating this task is the fact that image focus quality is only well-defined in foreground regions of images, and as a result, most previous approaches only enable a computation of the relative difference in quality between two or more images, rather than an absolute measure of quality. We present a deep neural network model capable of predicting an absolute measure of image focus on a single image in isolation, without any user-specified parameters. The model operates at the image-patch level, and also outputs a measure of prediction certainty, enabling interpretable predictions. The model was trained on only 384 in-focus Hoechst (nuclei) stain images of U2OS cells, which were synthetically defocused to one of 11 absolute defocus levels during training. The trained model can generalize on previously unseen real Hoechst stain images, identifying the absolute image focus to within one defocus level (approximately 3 pixel blur diameter difference) with 95% accuracy. On a simpler binary in/out-of-focus classification task, the trained model outperforms previous approaches on both Hoechst and Phalloidin (actin) stain images (F-scores of 0.89 and 0.86, respectively over 0.84 and 0.83), despite only having been presented Hoechst stain images during training. Lastly, we observe qualitatively that the model generalizes to two additional stains, Hoechst and Tubulin, of an unseen cell type (Human MCF-7) acquired on a different instrument. Our deep neural network enables classification of out-of-focus microscope images with both higher accuracy and greater precision than previous approaches via interpretable patch-level focus and certainty predictions. The use of synthetically defocused images precludes the need for a manually annotated training dataset. The model also generalizes to different image and cell types. The framework for model training and image prediction is available as a free software library and the pre-trained model is available for immediate use in Fiji (ImageJ) and CellProfiler.

The Association Between Body Image and Smoking Cessation Among Individuals Living with HIV/AIDS

PubMed Central

Fingeret, Michelle Cororve; Vidrine, Damon J.; Arduino, Roberto C.; Gritz, Ellen R.

2007-01-01

Lower smoking cessation rates are associated with body image concerns in the general population. This relationship is particularly important to study in individuals living with HIV/AIDS due to alarmingly high smoking rates and considerable bodily changes experienced with HIV disease progression and treatment. The association between body image and smoking cessation rates was examined among individuals living with HIV/AIDS participating in a smoking cessation intervention. Body image concerns were significantly associated with depression, anxiety, stress, and social support, all variables known to affect cessation rates. However, reduced quit rates were found among individuals reporting elevated and low levels of body image concerns at the end of treatment. These findings suggest a unique relationship between smoking and body image among individuals living with HIV/AIDS. Further research is needed to examine these effects and whether moderate levels of body image concerns in this population reflect realistic body perceptions associated with positive mental health. PMID:18089265

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

NASA Astrophysics Data System (ADS)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

Digital photography for the light microscope: results with a gated, video-rate CCD camera and NIH-image software.

PubMed

Shaw, S L; Salmon, E D; Quatrano, R S

1995-12-01

In this report, we describe a relatively inexpensive method for acquiring, storing and processing light microscope images that combines the advantages of video technology with the powerful medium now termed digital photography. Digital photography refers to the recording of images as digital files that are stored, manipulated and displayed using a computer. This report details the use of a gated video-rate charge-coupled device (CCD) camera and a frame grabber board for capturing 256 gray-level digital images from the light microscope. This camera gives high-resolution bright-field, phase contrast and differential interference contrast (DIC) images but, also, with gated on-chip integration, has the capability to record low-light level fluorescent images. The basic components of the digital photography system are described, and examples are presented of fluorescence and bright-field micrographs. Digital processing of images to remove noise, to enhance contrast and to prepare figures for printing is discussed.

Fast single image dehazing based on image fusion

NASA Astrophysics Data System (ADS)

Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

2015-01-01

Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.

Formulation of image fusion as a constrained least squares optimization problem

PubMed Central

Dwork, Nicholas; Lasry, Eric M.; Pauly, John M.; Balbás, Jorge

2017-01-01

Abstract. Fusing a lower resolution color image with a higher resolution monochrome image is a common practice in medical imaging. By incorporating spatial context and/or improving the signal-to-noise ratio, it provides clinicians with a single frame of the most complete information for diagnosis. In this paper, image fusion is formulated as a convex optimization problem that avoids image decomposition and permits operations at the pixel level. This results in a highly efficient and embarrassingly parallelizable algorithm based on widely available robust and simple numerical methods that realizes the fused image as the global minimizer of the convex optimization problem. PMID:28331885

Finger vein recognition based on the hyperinformation feature

NASA Astrophysics Data System (ADS)

Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

2014-01-01

The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

Development and Analysis of New 3D Tactile Materials for the Enhancement of STEM Education for the Blind and Visually Impaired

NASA Astrophysics Data System (ADS)

Gonzales, Ashleigh

Blind and visually impaired individuals have historically demonstrated a low participation in the fields of science, engineering, mathematics, and technology (STEM). This low participation is reflected in both their education and career choices. Despite the establishment of the Americans with Disabilities Act (ADA) and the Individuals with Disabilities Education Act (IDEA), blind and visually impaired (BVI) students continue to academically fall below the level of their sighted peers in the areas of science and math. Although this deficit is created by many factors, this study focuses on the lack of adequate accessible image based materials. Traditional methods for creating accessible image materials for the vision impaired have included detailed verbal descriptions accompanying an image or conversion into a simplified tactile graphic. It is very common that no substitute materials will be provided to students within STEM courses because they are image rich disciplines and often include a large number images, diagrams and charts. Additionally, images that are translated into text or simplified into basic line drawings are frequently inadequate because they rely on the interpretations of resource personnel who do not have expertise in STEM. Within this study, a method to create a new type of tactile 3D image was developed using High Density Polyethylene (HDPE) and Computer Numeric Control (CNC) milling. These tactile image boards preserve high levels of detail when compared to the original print image. To determine the discernibility and effectiveness of tactile images, these customizable boards were tested in various university classrooms as well as in participation studies which included BVI and sighted students. Results from these studies indicate that tactile images are discernable and were found to improve performance in lab exercises as much as 60% for those with visual impairment. Incorporating tactile HDPE 3D images into a classroom setting was shown to increase the interest, participation and performance of BVI students suggesting that this type of 3D tactile image should be incorporated into STEM classes to increase the participation of these students and improve the level of training they receive in science and math.

Analysis of Low-Light and Night-Time Stereo-Pair Images for Photogrammetric Reconstruction

NASA Astrophysics Data System (ADS)

Santise, M.; Thoeni, K.; Roncella, R.; Diotri, F.; Giacomini, A.

2018-05-01

Rockfalls and rockslides represent a significant risk to human lives and infrastructures because of the high levels of energy involved in the phenomena. Generally, these events occur in accordance to specific environmental conditions, such as temperature variations between day and night, that can contribute to the triggering of structural instabilities in the rock-wall and the detachment of blocks and debris. The monitoring and the geostructural characterization of the wall are required for reducing the potential hazard and to improve the management of the risk at the bottom of the slopes affected by such phenomena. In this context, close range photogrammetry is largely used for the monitoring of high-mountain terrains and rock walls in mine sites allowing for periodic survey of rockfalls and wall movements. This work focuses on the analysis of low-light and night-time images of a fixed-base stereo pair photogrammetry system. The aim is to study the reliability of the images acquired over the night to produce digital surface models (DSMs) for change detection. The images are captured by a high-sensitivity DLSR camera using various settings accounting for different values of ISO, aperture and time of exposure. For each acquisition, the DSM is compared to a photogrammetric reference model produced by images captured in optimal illumination conditions. Results show that, with high level of ISO and maintaining the same grade of aperture, extending the exposure time improves the quality of the point clouds in terms of completeness and accuracy of the photogrammetric models.

Probabilistic model for quick detection of dissimilar binary images

NASA Astrophysics Data System (ADS)

Mustafa, Adnan A. Y.

2015-09-01

We present a quick method to detect dissimilar binary images. The method is based on a "probabilistic matching model" for image matching. The matching model is used to predict the probability of occurrence of distinct-dissimilar image pairs (completely different images) when matching one image to another. Based on this model, distinct-dissimilar images can be detected by matching only a few points between two images with high confidence, namely 11 points for a 99.9% successful detection rate. For image pairs that are dissimilar but not distinct-dissimilar, more points need to be mapped. The number of points required to attain a certain successful detection rate or confidence depends on the amount of similarity between the compared images. As this similarity increases, more points are required. For example, images that differ by 1% can be detected by mapping fewer than 70 points on average. More importantly, the model is image size invariant; so, images of any sizes will produce high confidence levels with a limited number of matched points. As a result, this method does not suffer from the image size handicap that impedes current methods. We report on extensive tests conducted on real images of different sizes.

Two approximations for the geometric model of signal amplification in an electron-multiplying charge-coupled device detector

PubMed Central

Chao, Jerry; Ram, Sripad; Ward, E. Sally; Ober, Raimund J.

2014-01-01

The extraction of information from images acquired under low light conditions represents a common task in diverse disciplines. In single molecule microscopy, for example, techniques for superresolution image reconstruction depend on the accurate estimation of the locations of individual particles from generally low light images. In order to estimate a quantity of interest with high accuracy, however, an appropriate model for the image data is needed. To this end, we previously introduced a data model for an image that is acquired using the electron-multiplying charge-coupled device (EMCCD) detector, a technology of choice for low light imaging due to its ability to amplify weak signals significantly above its readout noise floor. Specifically, we proposed the use of a geometrically multiplied branching process to model the EMCCD detector’s stochastic signal amplification. Geometric multiplication, however, can be computationally expensive and challenging to work with analytically. We therefore describe here two approximations for geometric multiplication that can be used instead. The high gain approximation is appropriate when a high level of signal amplification is used, a scenario which corresponds to the typical usage of an EMCCD detector. It is an accurate approximation that is computationally more efficient, and can be used to perform maximum likelihood estimation on EMCCD image data. In contrast, the Gaussian approximation is applicable at all levels of signal amplification, but is only accurate when the initial signal to be amplified is relatively large. As we demonstrate, it can importantly facilitate the analysis of an information-theoretic quantity called the noise coefficient. PMID:25075263

Potential accuracy of translation estimation between radar and optical images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2015-10-01

This paper investigates the potential accuracy achievable for optical to radar image registration by area-based approach. The analysis is carried out mainly based on the Cramér-Rao Lower Bound (CRLB) on translation estimation accuracy previously proposed by the authors and called CRLBfBm. This bound is now modified to take into account radar image speckle noise properties: spatial correlation and signal-dependency. The newly derived theoretical bound is fed with noise and texture parameters estimated for the co-registered pair of optical Landsat 8 and radar SIR-C images. It is found that difficulty of optical to radar image registration stems more from speckle noise influence than from dissimilarity of the considered kinds of images. At finer scales (and higher speckle noise level), probability of finding control fragments (CF) suitable for registration is low (1% or less) but overall number of such fragments is high thanks to image size. Conversely, at the coarse scale, where speckle noise level is reduced, probability of finding CFs suitable for registration can be as high as 40%, but overall number of such CFs is lower. Thus, the study confirms and supports area-based multiresolution approach for optical to radar registration where coarse scales are used for fast registration "lock" and finer scales for reaching higher registration accuracy. The CRLBfBm is found inaccurate for the main scale due to intensive speckle noise influence. For other scales, the validity of the CRLBfBm bound is confirmed by calculating statistical efficiency of area-based registration method based on normalized correlation coefficient (NCC) measure that takes high values of about 25%.

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.

Object Recognition and Random Image Structure Evolution

ERIC Educational Resources Information Center

Sadr, Jvid; Sinha, Pawan

2004-01-01

We present a technique called Random Image Structure Evolution (RISE) for use in experimental investigations of high-level visual perception. Potential applications of RISE include the quantitative measurement of perceptual hysteresis and priming, the study of the neural substrates of object perception, and the assessment and detection of subtle…

Recognizing Chromospheric Objects via Markov Chain Monte Carlo

NASA Technical Reports Server (NTRS)

Mukhtar, Saleem; Turmon, Michael J.

1997-01-01

The solar chromosphere consists of three classes which contribute differentially to ultraviolet radiation reaching the earth. We describe a data set of solar images, means of segmenting the images into the constituent classes, and a novel high-level representation for compact objects based on a triangulated spatial membership function.

Smear correction of highly variable, frame-transfer CCD images with application to polarimetry.

PubMed

Iglesias, Francisco A; Feller, Alex; Nagaraju, Krishnappa

2015-07-01

Image smear, produced by the shutterless operation of frame-transfer CCD detectors, can be detrimental for many imaging applications. Existing algorithms used to numerically remove smear do not contemplate cases where intensity levels change considerably between consecutive frame exposures. In this report, we reformulate the smearing model to include specific variations of the sensor illumination. The corresponding desmearing expression and its noise properties are also presented and demonstrated in the context of fast imaging polarimetry.

Hello World Deep Learning in Medical Imaging.

PubMed

Lakhani, Paras; Gray, Daniel L; Pett, Carl R; Nagy, Paul; Shih, George

2018-05-03

There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

The Hyper Suprime-Cam software pipeline

NASA Astrophysics Data System (ADS)

Bosch, James; Armstrong, Robert; Bickerton, Steven; Furusawa, Hisanori; Ikeda, Hiroyuki; Koike, Michitaro; Lupton, Robert; Mineo, Sogo; Price, Paul; Takata, Tadafumi; Tanaka, Masayuki; Yasuda, Naoki; AlSayyad, Yusra; Becker, Andrew C.; Coulton, William; Coupon, Jean; Garmilla, Jose; Huang, Song; Krughoff, K. Simon; Lang, Dustin; Leauthaud, Alexie; Lim, Kian-Tat; Lust, Nate B.; MacArthur, Lauren A.; Mandelbaum, Rachel; Miyatake, Hironao; Miyazaki, Satoshi; Murata, Ryoma; More, Surhud; Okura, Yuki; Owen, Russell; Swinbank, John D.; Strauss, Michael A.; Yamada, Yoshihiko; Yamanoi, Hitomi

2018-01-01

In this paper, we describe the optical imaging data processing pipeline developed for the Subaru Telescope's Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope's Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high-level processing steps that generate coadded images and science-ready catalogs as well as low-level detrending and image characterizations.

Preliminary study of the reliability of imaging charge coupled devices

NASA Technical Reports Server (NTRS)

Beall, J. R.; Borenstein, M. D.; Homan, R. A.; Johnson, D. L.; Wilson, D. D.; Young, V. F.

1978-01-01

Imaging CCDs are capable of low light level response and high signal-to-noise ratios. In space applications they offer the user the ability to achieve extremely high resolution imaging with minimum circuitry in the photo sensor array. This work relates the CCD121H Fairchild device to the fundamentals of CCDs and the representative technologies. Several failure modes are described, construction is analyzed and test results are reported. In addition, the relationship of the device reliability to packaging principles is analyzed and test data presented. Finally, a test program is defined for more general reliability evaluation of CCDs.

Mapping in-vivo optic nerve head strains caused by intraocular and intracranial pressures

NASA Astrophysics Data System (ADS)

Tran, H.; Grimm, J.; Wang, B.; Smith, M. A.; Gogola, A.; Nelson, S.; Tyler-Kabara, E.; Schuman, J.; Wollstein, G.; Sigal, I. A.

2017-02-01

Although it is well documented that abnormal levels of either intraocular (IOP) or intracranial pressure (ICP) can lead to potentially blinding conditions, such as glaucoma and papilledema, little is known about how the pressures actually affect the eye. Even less is known about potential interplay between their effects, namely how the level of one pressure might alter the effects of the other. Our goal was to measure in-vivo the pressure-induced stretch and compression of the lamina cribrosa due to acute changes of IOP and ICP. The lamina cribrosa is a structure within the optic nerve head, in the back of the eye. It is important because it is in the lamina cribrosa that the pressure-induced deformations are believed to initiate damage to neural tissues leading to blindness. An eye of a rhesus macaque monkey was imaged in-vivo with optical coherence tomography while IOP and ICP were controlled through cannulas in the anterior chamber and lateral ventricle, respectively. The image volumes were analyzed with a newly developed digital image correlation technique. The effects of both pressures were highly localized, nonlinear and non-monotonic, with strong interactions. Pressure variations from the baseline normal levels caused substantial stretch and compression of the neural tissues in the posterior pole, sometimes exceeding 20%. Chronic exposure to such high levels of biomechanical insult would likely lead to neural tissue damage and loss of vision. Our results demonstrate the power of digital image correlation technique based on non-invasive imaging technologies to help understand how pressures induce biomechanical insults and lead to vision problems.

Object-Part Attention Model for Fine-Grained Image Classification

NASA Astrophysics Data System (ADS)

Peng, Yuxin; He, Xiangteng; Zhao, Junjie

2018-03-01

Fine-grained image classification is to recognize hundreds of subcategories belonging to the same basic-level category, such as 200 subcategories belonging to the bird, which is highly challenging due to large variance in the same subcategory and small variance among different subcategories. Existing methods generally first locate the objects or parts and then discriminate which subcategory the image belongs to. However, they mainly have two limitations: (1) Relying on object or part annotations which are heavily labor consuming. (2) Ignoring the spatial relationships between the object and its parts as well as among these parts, both of which are significantly helpful for finding discriminative parts. Therefore, this paper proposes the object-part attention model (OPAM) for weakly supervised fine-grained image classification, and the main novelties are: (1) Object-part attention model integrates two level attentions: object-level attention localizes objects of images, and part-level attention selects discriminative parts of object. Both are jointly employed to learn multi-view and multi-scale features to enhance their mutual promotions. (2) Object-part spatial constraint model combines two spatial constraints: object spatial constraint ensures selected parts highly representative, and part spatial constraint eliminates redundancy and enhances discrimination of selected parts. Both are jointly employed to exploit the subtle and local differences for distinguishing the subcategories. Importantly, neither object nor part annotations are used in our proposed approach, which avoids the heavy labor consumption of labeling. Comparing with more than 10 state-of-the-art methods on 4 widely-used datasets, our OPAM approach achieves the best performance.

SNR-optimized phase-sensitive dual-acquisition turbo spin echo imaging: a fast alternative to FLAIR.

PubMed

Lee, Hyunyeol; Park, Jaeseok

2013-07-01

Phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo imaging was recently introduced, producing high-resolution isotropic cerebrospinal fluid attenuated brain images without long inversion recovery preparation. Despite the advantages, the weighted-averaging-based technique suffers from noise amplification resulting from different levels of cerebrospinal fluid signal modulations over the two acquisitions. The purpose of this work is to develop a signal-to-noise ratio-optimized version of the phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo. Variable refocusing flip angles in the first acquisition are calculated using a three-step prescribed signal evolution while those in the second acquisition are calculated using a two-step pseudo-steady state signal transition with a high flip-angle pseudo-steady state at a later portion of the echo train, balancing the levels of cerebrospinal fluid signals in both the acquisitions. Low spatial frequency signals are sampled during the high flip-angle pseudo-steady state to further suppress noise. Numerical simulations of the Bloch equations were performed to evaluate signal evolutions of brain tissues along the echo train and optimize imaging parameters. In vivo studies demonstrate that compared with conventional phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo, the proposed optimization yields 74% increase in apparent signal-to-noise ratio for gray matter and 32% decrease in imaging time. The proposed method can be a potential alternative to conventional fluid-attenuated imaging. Copyright © 2012 Wiley Periodicals, Inc.

Motmot, an open-source toolkit for realtime video acquisition and analysis.

PubMed

Straw, Andrew D; Dickinson, Michael H

2009-07-22

Video cameras sense passively from a distance, offer a rich information stream, and provide intuitively meaningful raw data. Camera-based imaging has thus proven critical for many advances in neuroscience and biology, with applications ranging from cellular imaging of fluorescent dyes to tracking of whole-animal behavior at ecologically relevant spatial scales. Here we present 'Motmot': an open-source software suite for acquiring, displaying, saving, and analyzing digital video in real-time. At the highest level, Motmot is written in the Python computer language. The large amounts of data produced by digital cameras are handled by low-level, optimized functions, usually written in C. This high-level/low-level partitioning and use of select external libraries allow Motmot, with only modest complexity, to perform well as a core technology for many high-performance imaging tasks. In its current form, Motmot allows for: (1) image acquisition from a variety of camera interfaces (package motmot.cam_iface), (2) the display of these images with minimal latency and computer resources using wxPython and OpenGL (package motmot.wxglvideo), (3) saving images with no compression in a single-pass, low-CPU-use format (package motmot.FlyMovieFormat), (4) a pluggable framework for custom analysis of images in realtime and (5) firmware for an inexpensive USB device to synchronize image acquisition across multiple cameras, with analog input, or with other hardware devices (package motmot.fview_ext_trig). These capabilities are brought together in a graphical user interface, called 'FView', allowing an end user to easily view and save digital video without writing any code. One plugin for FView, 'FlyTrax', which tracks the movement of fruit flies in real-time, is included with Motmot, and is described to illustrate the capabilities of FView. Motmot enables realtime image processing and display using the Python computer language. In addition to the provided complete applications, the architecture allows the user to write relatively simple plugins, which can accomplish a variety of computer vision tasks and be integrated within larger software systems. The software is available at http://code.astraw.com/projects/motmot.

Multi-Level and Multi-Scale Feature Aggregation Using Pretrained Convolutional Neural Networks for Music Auto-Tagging

NASA Astrophysics Data System (ADS)

Lee, Jongpil; Nam, Juhan

2017-08-01

Music auto-tagging is often handled in a similar manner to image classification by regarding the 2D audio spectrogram as image data. However, music auto-tagging is distinguished from image classification in that the tags are highly diverse and have different levels of abstractions. Considering this issue, we propose a convolutional neural networks (CNN)-based architecture that embraces multi-level and multi-scaled features. The architecture is trained in three steps. First, we conduct supervised feature learning to capture local audio features using a set of CNNs with different input sizes. Second, we extract audio features from each layer of the pre-trained convolutional networks separately and aggregate them altogether given a long audio clip. Finally, we put them into fully-connected networks and make final predictions of the tags. Our experiments show that using the combination of multi-level and multi-scale features is highly effective in music auto-tagging and the proposed method outperforms previous state-of-the-arts on the MagnaTagATune dataset and the Million Song Dataset. We further show that the proposed architecture is useful in transfer learning.

A global "imaging'' view on systems approaches in immunology.

PubMed

Ludewig, Burkhard; Stein, Jens V; Sharpe, James; Cervantes-Barragan, Luisa; Thiel, Volker; Bocharov, Gennady

2012-12-01

The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A framework for medical image retrieval using machine learning and statistical similarity matching techniques with relevance feedback.

PubMed

Rahman, Md Mahmudur; Bhattacharya, Prabir; Desai, Bipin C

2007-01-01

A content-based image retrieval (CBIR) framework for diverse collection of medical images of different imaging modalities, anatomic regions with different orientations and biological systems is proposed. Organization of images in such a database (DB) is well defined with predefined semantic categories; hence, it can be useful for category-specific searching. The proposed framework consists of machine learning methods for image prefiltering, similarity matching using statistical distance measures, and a relevance feedback (RF) scheme. To narrow down the semantic gap and increase the retrieval efficiency, we investigate both supervised and unsupervised learning techniques to associate low-level global image features (e.g., color, texture, and edge) in the projected PCA-based eigenspace with their high-level semantic and visual categories. Specially, we explore the use of a probabilistic multiclass support vector machine (SVM) and fuzzy c-mean (FCM) clustering for categorization and prefiltering of images to reduce the search space. A category-specific statistical similarity matching is proposed in a finer level on the prefiltered images. To incorporate a better perception subjectivity, an RF mechanism is also added to update the query parameters dynamically and adjust the proposed matching functions. Experiments are based on a ground-truth DB consisting of 5000 diverse medical images of 20 predefined categories. Analysis of results based on cross-validation (CV) accuracy and precision-recall for image categorization and retrieval is reported. It demonstrates the improvement, effectiveness, and efficiency achieved by the proposed framework.

Public Outreach and Archiving of Data from the High Resolution Stereo Camera Onboard Mars Express: 2004 The First Year

NASA Technical Reports Server (NTRS)

Koehler, U.; Neukum, G.; Gasselt, S. v.; Jaumann, R.; Roatsch, Th.; Hoffmann, H.; Zender, J.; Acton, C.; Drigani, F.

2005-01-01

During the first year of operation, corresponding to the calendar year 2004, the HRSC imaging experiment onboard ESA's Mars Express mission recorded 23 Gigabyte of 8-bit compressed raw data. After processing, the amount of data increased to more than 344 Gigabyte of decompressed and radiometrically calibrated scientifically useable image products. Every six months these HRSC Level 2 data are fed into ESA's Planetary Science Archive (PSA) that sends all data also to the Planetary Data System (PDS) to ensure easy availability to the interested user. On their respective web portals, the European Space Agency published in cooperation with the Principal Investigator-Group at Freie Universitat Berlin and the German Space Agency (DLR) almost 40 sets of high-level image scenes and movies for PR needs that have been electronically visited many hundred thousand times.

[Digital breast tomosynthesis : technical principles, current clinical relevance and future perspectives].

PubMed

Hellerhoff, K

2010-11-01

In recent years digital full field mammography has increasingly replaced conventional film mammography. High quality imaging is guaranteed by high quantum efficiency and very good contrast resolution with optimized dosing even for women with dense glandular tissue. However, digital mammography remains a projection procedure by which overlapping tissue limits the detectability of subtle alterations. Tomosynthesis is a procedure developed from digital mammography for slice examination of breasts which eliminates the effects of overlapping tissue and allows 3D imaging of breasts. A curved movement of the X-ray tube during scanning allows the acquisition of many 2D images from different angles. Subseqently, reconstruction algorithms employing a shift and add method improve the recognition of details at a defined level and at the same time eliminate smear artefacts due to overlapping structures. The total dose corresponds to that of conventional mammography imaging. The technical procedure, including the number of levels, suitable anodes/filter combinations, angle regions of images and selection of reconstruction algorithms, is presently undergoing optimization. Previous studies on the clinical value of tomosynthesis have examined screening parameters, such as recall rate and detection rate as well as information on tumor extent for histologically proven breast tumors. More advanced techniques, such as contrast medium-enhanced tomosynthesis, are presently under development and dual-energy imaging is of particular importance.

Using novel control groups to dissect the amygdala's role in Williams syndrome.

PubMed

Thornton-Wells, Tricia A; Avery, Suzanne N; Blackford, Jennifer Urbano

2011-07-01

Williams syndrome is a neurodevelopmental disorder with an intriguing behavioral phenotype-hypersociability combined with significant non-social fears. Previous studies have demonstrated abnormalities in amygdala function in individuals with Williams syndrome compared to typically-developing controls. However, it remains unclear whether the findings are related to the atypical neurodevelopment of Williams syndrome, or are also associated with behavioral traits at the extreme end of a normal continuum. We used functional magnetic resonance imaging (fMRI) to compare amygdala blood-oxygenation-level-dependent (BOLD) responses to non-social and social images in individuals with Williams syndrome compared to either individuals with inhibited temperament (high non-social fear) or individuals with uninhibited temperament (high sociability). Individuals with Williams syndrome had larger amygdala BOLD responses when viewing the non-social fear images than the inhibited temperament control group. In contrast, when viewing both fear and neutral social images, individuals with Williams syndrome did not show smaller amygdala BOLD responses relative to the uninhibited temperament control group, but instead had amygdala responses proportionate to their sociability. These results suggest heightened amygdala response to non-social fear images is characteristic of WS, whereas, variability in amygdala response to social fear images is proportionate to, and might be explained by, levels of trait sociability.

Variable Threshold Method for Determining the Boundaries of Imaged Subvisible Particles.

PubMed

Cavicchi, Richard E; Collett, Cayla; Telikepalli, Srivalli; Hu, Zhishang; Carrier, Michael; Ripple, Dean C

2017-06-01

An accurate assessment of particle characteristics and concentrations in pharmaceutical products by flow imaging requires accurate particle sizing and morphological analysis. Analysis of images begins with the definition of particle boundaries. Commonly a single threshold defines the level for a pixel in the image to be included in the detection of particles, but depending on the threshold level, this results in either missing translucent particles or oversizing of less transparent particles due to the halos and gradients in intensity near the particle boundaries. We have developed an imaging analysis algorithm that sets the threshold for a particle based on the maximum gray value of the particle. We show that this results in tighter boundaries for particles with high contrast, while conserving the number of highly translucent particles detected. The method is implemented as a plugin for FIJI, an open-source image analysis software. The method is tested for calibration beads in water and glycerol/water solutions, a suspension of microfabricated rods, and stir-stressed aggregates made from IgG. The result is that appropriate thresholds are automatically set for solutions with a range of particle properties, and that improved boundaries will allow for more accurate sizing results and potentially improved particle classification studies. Published by Elsevier Inc.

Opportunities in Participatory Science and Citizen Science with MRO's High Resolution Imaging Science Experiment: A Virtual Science Team Experience

NASA Astrophysics Data System (ADS)

Gulick, Ginny

2009-09-01

We report on the accomplishments of the HiRISE EPO program over the last two and a half years of science operations. We have focused primarily on delivering high impact science opportunities through our various participatory science and citizen science websites. Uniquely, we have invited students from around the world to become virtual HiRISE team members by submitting target suggestions via our HiRISE Quest Image challenges using HiWeb the team's image suggestion facility web tools. When images are acquired, students analyze their returned images, write a report and work with a HiRISE team member to write a image caption for release on the HiRISE website (http://hirise.lpl.arizona.edu). Another E/PO highlight has been our citizen scientist effort, HiRISE Clickworkers (http://clickworkers.arc.nasa.gov/hirise). Clickworkers enlists volunteers to identify geologic features (e.g., dunes, craters, wind streaks, gullies, etc.) in the HiRISE images and help generate searchable image databases. In addition, the large image sizes and incredible spatial resolution of the HiRISE camera can tax the capabilities of the most capable computers, so we have also focused on enabling typical users to browse, pan and zoom the HiRISE images using our HiRISE online image viewer (http://marsoweb.nas.nasa.gov/HiRISE/hirise_images/). Our educational materials available on the HiRISE EPO web site (http://hirise.seti.org/epo) include an assortment of K through college level, standards-based activity books, a K through 3 coloring/story book, a middle school level comic book, and several interactive educational games, including Mars jigsaw puzzles, crosswords, word searches and flash cards.

Energy Efficient Image/Video Data Transmission on Commercial Multi-Core Processors

PubMed Central

Lee, Sungju; Kim, Heegon; Chung, Yongwha; Park, Daihee

2012-01-01

In transmitting image/video data over Video Sensor Networks (VSNs), energy consumption must be minimized while maintaining high image/video quality. Although image/video compression is well known for its efficiency and usefulness in VSNs, the excessive costs associated with encoding computation and complexity still hinder its adoption for practical use. However, it is anticipated that high-performance handheld multi-core devices will be used as VSN processing nodes in the near future. In this paper, we propose a way to improve the energy efficiency of image and video compression with multi-core processors while maintaining the image/video quality. We improve the compression efficiency at the algorithmic level or derive the optimal parameters for the combination of a machine and compression based on the tradeoff between the energy consumption and the image/video quality. Based on experimental results, we confirm that the proposed approach can improve the energy efficiency of the straightforward approach by a factor of 2∼5 without compromising image/video quality. PMID:23202181

High-resolution imaging using a wideband MIMO radar system with two distributed arrays.

PubMed

Wang, Dang-wei; Ma, Xiao-yan; Chen, A-Lei; Su, Yi

2010-05-01

Imaging a fast maneuvering target has been an active research area in past decades. Usually, an array antenna with multiple elements is implemented to avoid the motion compensations involved in the inverse synthetic aperture radar (ISAR) imaging. Nevertheless, there is a price dilemma due to the high level of hardware complexity compared to complex algorithm implemented in the ISAR imaging system with only one antenna. In this paper, a wideband multiple-input multiple-output (MIMO) radar system with two distributed arrays is proposed to reduce the hardware complexity of the system. Furthermore, the system model, the equivalent array production method and the imaging procedure are presented. As compared with the classical real aperture radar (RAR) imaging system, there is a very important contribution in our method that the lower hardware complexity can be involved in the imaging system since many additive virtual array elements can be obtained. Numerical simulations are provided for testing our system and imaging method.

K-edge subtraction synchrotron X-ray imaging in bio-medical research.

PubMed

Thomlinson, W; Elleaume, H; Porra, L; Suortti, P

2018-05-01

High contrast in X-ray medical imaging, while maintaining acceptable radiation dose levels to the patient, has long been a goal. One of the most promising methods is that of K-edge subtraction imaging. This technique, first advanced as long ago as 1953 by B. Jacobson, uses the large difference in the absorption coefficient of elements at energies above and below the K-edge. Two images, one taken above the edge and one below the edge, are subtracted leaving, ideally, only the image of the distribution of the target element. This paper reviews the development of the KES techniques and technology as applied to bio-medical imaging from the early low-power tube sources of X-rays to the latest high-power synchrotron sources. Applications to coronary angiography, functional lung imaging and bone growth are highlighted. A vision of possible imaging with new compact sources is presented. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis.

PubMed

Bühnemann, Claudia; Li, Simon; Yu, Haiyue; Branford White, Harriet; Schäfer, Karl L; Llombart-Bosch, Antonio; Machado, Isidro; Picci, Piero; Hogendoorn, Pancras C W; Athanasou, Nicholas A; Noble, J Alison; Hassan, A Bassim

2014-01-01

Driven by genomic somatic variation, tumour tissues are typically heterogeneous, yet unbiased quantitative methods are rarely used to analyse heterogeneity at the protein level. Motivated by this problem, we developed automated image segmentation of images of multiple biomarkers in Ewing sarcoma to generate distributions of biomarkers between and within tumour cells. We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF) machine learning. Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. Ki67, pS6, Foxo3a, EGR1, MAPK) localised relative to nuclear and cytoplasmic regions of each cell in order to generate image feature distributions. The image distribution features were analysed with RSF in relation to known overall patient survival from three separate cohorts (185 informative cases). Variation in pre-analytical processing resulted in elimination of a high number of non-informative images that had poor DAPI localisation or biomarker preservation (67 cases, 36%). The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case) were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. A prognostic classifier for Ewing sarcoma with low cross-validation error rates (0.36) was comprised of multiple features, including the Ki67 proliferative marker and a sub-population of cells with low cytoplasmic/nuclear ratio of CD99. Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour material could be achieved. Such an automated and integrated methodology has potential application in the identification of prognostic classifiers based on tumour cell heterogeneity.

Quality-control issues on high-resolution diagnostic monitors.

PubMed

Parr, L F; Anderson, A L; Glennon, B K; Fetherston, P

2001-06-01

Previous literature indicates a need for more data collection in the area of quality control of high-resolution diagnostic monitors. Throughout acceptance testing, which began in June 2000, stability of monitor calibration was analyzed. Although image quality on all monitors was found to be acceptable upon initial acceptance testing using VeriLUM software by Image Smiths, Inc (Germantown, MD), it was determined to be unacceptable during the clinical phase of acceptance testing. High-resolution monitors were evaluated for quality assurance on a weekly basis from installation through acceptance testing and beyond. During clinical utilization determination (CUD), monitor calibration was identified as a problem and the manufacturer returned and recalibrated all workstations. From that time through final acceptance testing, high-resolution monitor calibration and monitor failure rate remained a problem. The monitor vendor then returned to the site to address these areas. Monitor defocus was still noticeable and calibration checks were increased to three times per week. White and black level drift on medium-resolution monitors had been attributed to raster size settings. Measurements of white and black level at several different size settings were taken to determine the effect of size on white and black level settings. Black level remained steady with size change. White level appeared to increase by 2.0 cd/m2 for every 0.1 inches decrease in horizontal raster size. This was determined not to be the cause of the observed brightness drift. Frequency of calibration/testing is an issue in a clinical environment. The increased frequency required at our site cannot be sustained. The medical physics division cannot provide dedicated personnel to conduct the quality-assurance testing on all monitors at this interval due to other physics commitments throughout the hospital. Monitor access is also an issue due to radiologists' need to read images. Some workstations are in use 7 AM to 11 PM daily. An appropriate monitor calibration frequency must be established during acceptance testing to ensure unacceptable drift is not masked by excessive calibration frequency. Standards for acceptable black level and white level drift also need to be determined. The monitor vendor and hospital staff agree that currently, very small printed text is an acceptable method of determining monitor blur, however, a better method of determining monitor blur is being pursued. Although monitors may show acceptable quality during initial acceptance testing, they need to show sustained quality during the clinical acceptance-testing phase. Defocus, black level, and white level are image quality concerns, which need to be evaluated during the clinical phase of acceptance testing. Image quality deficiencies can have a negative impact on patient care and raise serious medical-legal concerns. The attention to quality control required of the hospital staff needs to be realistic and not have a significant impact on radiology workflow.

The effects of video compression on acceptability of images for monitoring life sciences experiments

NASA Astrophysics Data System (ADS)

Haines, Richard F.; Chuang, Sherry L.

1992-07-01

Future manned space operations for Space Station Freedom will call for a variety of carefully planned multimedia digital communications, including full-frame-rate color video, to support remote operations of scientific experiments. This paper presents the results of an investigation to determine if video compression is a viable solution to transmission bandwidth constraints. It reports on the impact of different levels of compression and associated calculational parameters on image acceptability to investigators in life-sciences research at ARC. Three nonhuman life-sciences disciplines (plant, rodent, and primate biology) were selected for this study. A total of 33 subjects viewed experimental scenes in their own scientific disciplines. Ten plant scientists viewed still images of wheat stalks at various stages of growth. Each image was compressed to four different compression levels using the Joint Photographic Expert Group (JPEG) standard algorithm, and the images were presented in random order. Twelve and eleven staffmembers viewed 30-sec videotaped segments showing small rodents and a small primate, respectively. Each segment was repeated at four different compression levels in random order using an inverse cosine transform (ICT) algorithm. Each viewer made a series of subjective image-quality ratings. There was a significant difference in image ratings according to the type of scene viewed within disciplines; thus, ratings were scene dependent. Image (still and motion) acceptability does, in fact, vary according to compression level. The JPEG still-image-compression levels, even with the large range of 5:1 to 120:1 in this study, yielded equally high levels of acceptability. In contrast, the ICT algorithm for motion compression yielded a sharp decline in acceptability below 768 kb/sec. Therefore, if video compression is to be used as a solution for overcoming transmission bandwidth constraints, the effective management of the ratio and compression parameters according to scientific discipline and experiment type is critical to the success of remote experiments.

The effects of video compression on acceptability of images for monitoring life sciences experiments

NASA Technical Reports Server (NTRS)

Haines, Richard F.; Chuang, Sherry L.

1992-01-01

Future manned space operations for Space Station Freedom will call for a variety of carefully planned multimedia digital communications, including full-frame-rate color video, to support remote operations of scientific experiments. This paper presents the results of an investigation to determine if video compression is a viable solution to transmission bandwidth constraints. It reports on the impact of different levels of compression and associated calculational parameters on image acceptability to investigators in life-sciences research at ARC. Three nonhuman life-sciences disciplines (plant, rodent, and primate biology) were selected for this study. A total of 33 subjects viewed experimental scenes in their own scientific disciplines. Ten plant scientists viewed still images of wheat stalks at various stages of growth. Each image was compressed to four different compression levels using the Joint Photographic Expert Group (JPEG) standard algorithm, and the images were presented in random order. Twelve and eleven staffmembers viewed 30-sec videotaped segments showing small rodents and a small primate, respectively. Each segment was repeated at four different compression levels in random order using an inverse cosine transform (ICT) algorithm. Each viewer made a series of subjective image-quality ratings. There was a significant difference in image ratings according to the type of scene viewed within disciplines; thus, ratings were scene dependent. Image (still and motion) acceptability does, in fact, vary according to compression level. The JPEG still-image-compression levels, even with the large range of 5:1 to 120:1 in this study, yielded equally high levels of acceptability. In contrast, the ICT algorithm for motion compression yielded a sharp decline in acceptability below 768 kb/sec. Therefore, if video compression is to be used as a solution for overcoming transmission bandwidth constraints, the effective management of the ratio and compression parameters according to scientific discipline and experiment type is critical to the success of remote experiments.

Influence of Hearing Risk Information on the Motivation and Modification of Personal Listening Device Use.

PubMed

Serpanos, Yula C; Berg, Abbey L; Renne, Brittany

2016-12-01

The purpose of this study was (a) to investigate the behaviors, knowledge, and motivators associated with personal listening device (PLD) use and (b) to determine the influence of different types of hearing health risk education information (text with or without visual images) on motivation to modify PLD listening use behaviors in young adults. College-age students (N = 523) completed a paper-and-pencil survey tapping their behaviors, knowledge, and motivation regarding listening to music or media at high volume using PLDs. Participants rated their motivation to listen to PLDs at lower volume levels following each of three information sets: text only, behind-the-ear hearing aid image with text, and inner ear hair cell damage image with text. Acoustically pleasing and emotional motives were the most frequently cited (38%-45%) reasons for listening to music or media using a PLD at high volume levels. The behind-the-ear hearing aid image with text information was significantly (p < .0001) more motivating to participants than text alone or the inner ear hair cell damage image with text. Evocative imagery using hearing aids may be an effective approach in hearing protective health campaigns for motivating safer listening practices with PLDs in young adults.

Efficacy and Clinical Utility of a High-Attenuation Object Artifact Reduction Algorithm in Flat-Detector Image Reconstruction Compared With Standard Image Reconstruction.

PubMed

Naehle, Claas P; Hechelhammer, Lukas; Richter, Heiko; Ryffel, Fabian; Wildermuth, Simon; Weber, Johannes

To evaluate the effectiveness and clinical utility of a metal artifact reduction (MAR) image reconstruction algorithm for the reduction of high-attenuation object (HAO)-related image artifacts. Images were quantitatively evaluated for image noise (noiseSD and noiserange) and qualitatively for artifact severity, gray-white-matter delineation, and diagnostic confidence with conventional reconstruction and after applying a MAR algorithm. Metal artifact reduction reduces noiseSD and noiserange (median [interquartile range]) at the level of HAO in 1-cm distance compared with conventional reconstruction (noiseSD: 60.0 [71.4] vs 12.8 [16.1] and noiserange: 262.0 [236.8] vs 72.0 [28.3]; P < 0.0001). Artifact severity (reader 1 [mean ± SD]: 1.1 ± 0.6 vs 2.4 ± 0.5, reader 2: 0.8 ± 0.6 vs 2.0 ± 0.4) at level of HAO and diagnostic confidence (reader 1: 1.6 ± 0.7 vs 2.6 ± 0.5, reader 2: 1.0 ± 0.6 vs 2.3 ± 0.7) significantly improved with MAR (P < 0.0001). Metal artifact reduction did not affect gray-white-matter delineation. Metal artifact reduction effectively reduces image artifacts caused by HAO and significantly improves diagnostic confidence without worsening gray-white-matter delineation.

Boundary identification and error analysis of shocked material images

NASA Astrophysics Data System (ADS)

Hock, Margaret; Howard, Marylesa; Cooper, Leora; Meehan, Bernard; Nelson, Keith

2017-06-01

To compute quantities such as pressure and velocity from laser-induced shock waves propagating through materials, high-speed images are captured and analyzed. Shock images typically display high noise and spatially-varying intensities, causing conventional analysis techniques to have difficulty identifying boundaries in the images without making significant assumptions about the data. We present a novel machine learning algorithm that efficiently segments, or partitions, images with high noise and spatially-varying intensities, and provides error maps that describe a level of uncertainty in the partitioning. The user trains the algorithm by providing locations of known materials within the image but no assumptions are made on the geometries in the image. The error maps are used to provide lower and upper bounds on quantities of interest, such as velocity and pressure, once boundaries have been identified and propagated through equations of state. This algorithm will be demonstrated on images of shock waves with noise and aberrations to quantify properties of the wave as it progresses. DOE/NV/25946-3126 This work was done by National Security Technologies, LLC, under Contract No. DE- AC52-06NA25946 with the U.S. Department of Energy and supported by the SDRD Program.

Relapse surveillance in AFP-positive hepatoblastoma: re-evaluating the role of imaging.

PubMed

Rojas, Yesenia; Guillerman, R Paul; Zhang, Wei; Vasudevan, Sanjeev A; Nuchtern, Jed G; Thompson, Patrick A

2014-10-01

Children with hepatoblastoma routinely undergo repetitive surveillance imaging, with CT scans for several years after therapy, increasing the risk of radiation-induced cancer. The purpose of this study was to determine the utility of surveillance CT scans compared to serum alpha-fetoprotein (AFP) levels for the detection of hepatoblastoma relapse. This was a retrospective study of all children diagnosed with AFP-positive hepatoblastoma from 2001 to 2011 at a single institution. Twenty-six children with hepatoblastoma were identified, with a mean age at diagnosis of 2 years 4 months (range 3 months to 11 years). Mean AFP level at diagnosis was 132,732 ng/ml (range 172.8-572,613 ng/ml). Five of the 26 children had hepatoblastoma relapse. A total of 105 imaging exams were performed following completion of therapy; 88 (84%) CT, 8 (8%) MRI, 5 (5%) US and 4 (4%) FDG PET/CT exams. A total of 288 alpha-fetoprotein levels were drawn, with a mean of 11 per child. The AFP level was elevated in all recurrences and no relapses were detected by imaging before AFP elevation. Two false-positive AFP levels and 15 false-positive imaging exams were detected. AFP elevation was found to be significantly more specific than PET/CT and CT imaging at detecting relapse. We recommend using serial serum AFP levels as the preferred method of surveillance in children with AFP-positive hepatoblastoma, reserving imaging for the early postoperative period, for children at high risk of relapse, and for determination of the anatomical site of clinically suspected recurrence. Given the small size of this preliminary study, validation in a larger patient population is warranted.

Detection and Interpretation of Low-Level and High-Level Surprising and Important Events in Large-Scale Data Streams

DTIC Science & Technology

2016-06-28

Likewise, we have developed a new general theory of relevance that quanti - fies how new data observations may or not affect an observer’s beliefs about how...which suggests that relevance is not an inherent attribute but rather is dependent on the knowledge or beliefs of the subject evaluating the...subjects. This allowed us to evaluate the accuracy of each person as the number of image pairs for which they selected the majority image. The average

Image splitting and remapping method for radiological image compression

NASA Astrophysics Data System (ADS)

Lo, Shih-Chung B.; Shen, Ellen L.; Mun, Seong K.

1990-07-01

A new decomposition method using image splitting and gray-level remapping has been proposed for image compression, particularly for images with high contrast resolution. The effects of this method are especially evident in our radiological image compression study. In our experiments, we tested the impact of this decomposition method on image compression by employing it with two coding techniques on a set of clinically used CT images and several laser film digitized chest radiographs. One of the compression techniques used was full-frame bit-allocation in the discrete cosine transform domain, which has been proven to be an effective technique for radiological image compression. The other compression technique used was vector quantization with pruned tree-structured encoding, which through recent research has also been found to produce a low mean-square-error and a high compression ratio. The parameters we used in this study were mean-square-error and the bit rate required for the compressed file. In addition to these parameters, the difference between the original and reconstructed images will be presented so that the specific artifacts generated by both techniques can be discerned by visual perception.

Object-based class modelling for multi-scale riparian forest habitat mapping

NASA Astrophysics Data System (ADS)

Strasser, Thomas; Lang, Stefan

2015-05-01

Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m2 were modelled from 938 forest stand patches (MPS = 6868.20 m2) and 43,742 tree stand patches (MPS = 140.79 m2). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.

Jupiter's Multi-level Clouds

NASA Technical Reports Server (NTRS)

1997-01-01

Clouds and hazes at various altitudes within the dynamic Jovian atmosphere are revealed by multi-color imaging taken by the Near-Infrared Mapping Spectrometer (NIMS) onboard the Galileo spacecraft. These images were taken during the second orbit (G2) on September 5, 1996 from an early-morning vantage point 2.1 million kilometers (1.3 million miles) above Jupiter. They show the planet's appearance as viewed at various near-infrared wavelengths, with distinct differences due primarily to variations in the altitudes and opacities of the cloud systems. The top left and right images, taken at 1.61 microns and 2.73 microns respectively, show relatively clear views of the deep atmosphere, with clouds down to a level about three times the atmospheric pressure at the Earth's surface.

By contrast, the middle image in top row, taken at 2.17 microns, shows only the highest altitude clouds and hazes. This wavelength is severely affected by the absorption of light by hydrogen gas, the main constituent of Jupiter's atmosphere. Therefore, only the Great Red Spot, the highest equatorial clouds, a small feature at mid-northern latitudes, and thin, high photochemical polar hazes can be seen. In the lower left image, at 3.01 microns, deeper clouds can be seen dimly against gaseous ammonia and methane absorption. In the lower middle image, at 4.99 microns, the light observed is the planet's own indigenous heat from the deep, warm atmosphere.

The false color image (lower right) succinctly shows various cloud and haze levels seen in the Jovian atmosphere. This image indicates the temperature and altitude at which the light being observed is produced. Thermally-rich red areas denote high temperatures from photons in the deep atmosphere leaking through minimal cloud cover; green denotes cool temperatures of the tropospheric clouds; blue denotes cold of the upper troposphere and lower stratosphere. The polar regions appear purplish, because small-particle hazes allow leakage and reflectivity, while yellowish regions at temperate latitudes may indicate tropospheric clouds with small particles which also allow leakage. A mix of high and low-altitude aerosols causes the aqua appearance of the Great Red Spot and equatorial region.

The Jet Propulsion Laboratory manages the Galileo mission for NASA's Office of Space Science, Washington, DC.

This image and other images and data received from Galileo are posted on the World Wide Web Galileo mission home page at http://galileo.jpl.nasa.gov.

eHUGS: Enhanced Hierarchical Unbiased Graph Shrinkage for Efficient Groupwise Registration

PubMed Central

Wu, Guorong; Peng, Xuewei; Ying, Shihui; Wang, Qian; Yap, Pew-Thian; Shen, Dan; Shen, Dinggang

2016-01-01

Effective and efficient spatial normalization of a large population of brain images is critical for many clinical and research studies, but it is technically very challenging. A commonly used approach is to choose a certain image as the template and then align all other images in the population to this template by applying pairwise registration. To avoid the potential bias induced by the inappropriate template selection, groupwise registration methods have been proposed to simultaneously register all images to a latent common space. However, current groupwise registration methods do not make full use of image distribution information for more accurate registration. In this paper, we present a novel groupwise registration method that harnesses the image distribution information by capturing the image distribution manifold using a hierarchical graph with its nodes representing the individual images. More specifically, a low-level graph describes the image distribution in each subgroup, and a high-level graph encodes the relationship between representative images of subgroups. Given the graph representation, we can register all images to the common space by dynamically shrinking the graph on the image manifold. The topology of the entire image distribution is always maintained during graph shrinkage. Evaluations on two datasets, one for 80 elderly individuals and one for 285 infants, indicate that our method can yield promising results. PMID:26800361

Digital fundus image grading with the non-mydriatic Visucam(PRO NM) versus the FF450(plus) camera in diabetic retinopathy.

PubMed

Neubauer, Aljoscha S; Rothschuh, Antje; Ulbig, Michael W; Blum, Marcus

2008-03-01

Grading diabetic retinopathy in clinical trials is frequently based on 7-field stereo photography of the fundus in diagnostic mydriasis. In terms of image quality, the FF450(plus) camera (Carl Zeiss Meditec AG, Jena, Germany) defines a high-quality reference. The aim of the study was to investigate if the fully digital fundus camera Visucam(PRO NM) could serve as an alternative in clinical trials requiring 7-field stereo photography. A total of 128 eyes of diabetes patients were enrolled in the randomized, controlled, prospective trial. Seven-field stereo photography was performed with the Visucam(PRO NM) and the FF450(plus) camera, in random order, both in diagnostic mydriasis. The resulting 256 image sets from the two camera systems were graded for retinopathy levels and image quality (on a scale of 1-5); both were anonymized and blinded to the image source. On FF450(plus) stereoscopic imaging, 20% of the patients had no or mild diabetic retinopathy (ETDRS level < or = 20) and 29% had no macular oedema. No patient had to be excluded as a result of image quality. Retinopathy level did not influence the quality of grading or of images. Excellent overall correspondence was obtained between the two fundus cameras regarding retinopathy levels (kappa 0.87) and macular oedema (kappa 0.80). In diagnostic mydriasis the image quality of the Visucam was graded slightly as better than that of the FF450(plus) (2.20 versus 2.41; p < 0.001), especially for pupils < 7 mm in mydriasis. The non-mydriatic Visucam(PRO NM) offers good image quality and is suitable as a more cost-efficient and easy-to-operate camera for applications and clinical trials requiring 7-field stereo photography.

Interpretation of medical imaging data with a mobile application: a mobile digital imaging processing environment.

PubMed

Lin, Meng Kuan; Nicolini, Oliver; Waxenegger, Harald; Galloway, Graham J; Ullmann, Jeremy F P; Janke, Andrew L

2013-01-01

Digital Imaging Processing (DIP) requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and DIP service, called M-DIP. The objective of the system is to (1) automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC), Neuroimaging Informatics Technology Initiative (NIFTI) to RAW formats; (2) speed up querying of imaging measurement; and (3) display high-level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle-layer database, a stand-alone DIP server, and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data at multiple zoom levels and to increase its quality to meet users' expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services.

Interpretation of Medical Imaging Data with a Mobile Application: A Mobile Digital Imaging Processing Environment

PubMed Central

Lin, Meng Kuan; Nicolini, Oliver; Waxenegger, Harald; Galloway, Graham J.; Ullmann, Jeremy F. P.; Janke, Andrew L.

2013-01-01

Digital Imaging Processing (DIP) requires data extraction and output from a visualization tool to be consistent. Data handling and transmission between the server and a user is a systematic process in service interpretation. The use of integrated medical services for management and viewing of imaging data in combination with a mobile visualization tool can be greatly facilitated by data analysis and interpretation. This paper presents an integrated mobile application and DIP service, called M-DIP. The objective of the system is to (1) automate the direct data tiling, conversion, pre-tiling of brain images from Medical Imaging NetCDF (MINC), Neuroimaging Informatics Technology Initiative (NIFTI) to RAW formats; (2) speed up querying of imaging measurement; and (3) display high-level of images with three dimensions in real world coordinates. In addition, M-DIP provides the ability to work on a mobile or tablet device without any software installation using web-based protocols. M-DIP implements three levels of architecture with a relational middle-layer database, a stand-alone DIP server, and a mobile application logic middle level realizing user interpretation for direct querying and communication. This imaging software has the ability to display biological imaging data at multiple zoom levels and to increase its quality to meet users’ expectations. Interpretation of bioimaging data is facilitated by an interface analogous to online mapping services using real world coordinate browsing. This allows mobile devices to display multiple datasets simultaneously from a remote site. M-DIP can be used as a measurement repository that can be accessed by any network environment, such as a portable mobile or tablet device. In addition, this system and combination with mobile applications are establishing a virtualization tool in the neuroinformatics field to speed interpretation services. PMID:23847587

General Approach for Rock Classification Based on Digital Image Analysis of Electrical Borehole Wall Images

NASA Astrophysics Data System (ADS)

Linek, M.; Jungmann, M.; Berlage, T.; Clauser, C.

2005-12-01

Within the Ocean Drilling Program (ODP), image logging tools have been routinely deployed such as the Formation MicroScanner (FMS) or the Resistivity-At-Bit (RAB) tools. Both logging methods are based on resistivity measurements at the borehole wall and therefore are sensitive to conductivity contrasts, which are mapped in color scale images. These images are commonly used to study the structure of the sedimentary rocks and the oceanic crust (petrologic fabric, fractures, veins, etc.). So far, mapping of lithology from electrical images is purely based on visual inspection and subjective interpretation. We apply digital image analysis on electrical borehole wall images in order to develop a method, which augments objective rock identification. We focus on supervised textural pattern recognition which studies the spatial gray level distribution with respect to certain rock types. FMS image intervals of rock classes known from core data are taken in order to train textural characteristics for each class. A so-called gray level co-occurrence matrix is computed by counting the occurrence of a pair of gray levels that are a certain distant apart. Once the matrix for an image interval is computed, we calculate the image contrast, homogeneity, energy, and entropy. We assign characteristic textural features to different rock types by reducing the image information into a small set of descriptive features. Once a discriminating set of texture features for each rock type is found, we are able to discriminate the entire FMS images regarding the trained rock type classification. A rock classification based on texture features enables quantitative lithology mapping and is characterized by a high repeatability, in contrast to a purely visual subjective image interpretation. We show examples for the rock classification between breccias, pillows, massive units, and horizontally bedded tuffs based on ODP image data.

Malpractice Liability Risk and Use of Diagnostic Imaging Services: A Systematic Review of the Literature.

PubMed

Li, Suhui; Brantley, Erin

2015-12-01

A widespread concern among physicians is that fear of medical malpractice liability may affect their decisions for diagnostic imaging orders. The purpose of this article is to synthesize evidence regarding the defensive use of imaging services. A literature search was conducted using a number of databases. The review included peer-reviewed publications that studied the link between physician orders of imaging tests and malpractice liability pressure. We identified 13 peer-reviewed studies conducted in the United States. Five of the studies reported physician assessments of the role of defensive medicine in imaging-order decisions; five assessed the association between physicians' liability risk and imaging ordering, and three assessed the impact of liability risk on imaging ordering at the state level. Although the belief that medical liability risk could influence decisions is highly prevalent among physicians, findings are mixed regarding the impact of liability risk on imaging orders at both the state and physician level. Inconclusive evidence suggests that physician ordering of imaging tests is affected by malpractice liability risk. Further research is needed to disentangle defensive medicine from other reasons for inefficient use of imaging. Copyright © 2015 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Image-Word Pairing-Congruity Effect on Affective Responses

NASA Astrophysics Data System (ADS)

Sanabria Z., Jorge C.; Cho, Youngil; Sambai, Ami; Yamanaka, Toshimasa

The present study explores the effects of familiarity on affective responses (pleasure and arousal) to Japanese ad elements, based on the schema incongruity theory. Print ads showing natural scenes (landscapes) were used to create the stimuli (images and words). An empirical study was conducted to measure subjects' affective responses to image-word combinations that varied in terms of incongruity. The level of incongruity was based on familiarity levels, and was statistically determined by a variable called ‘pairing-congruity status’. The tested hypothesis proposed that even highly familiar image-word combinations, when combined incongruously, would elicit strong affective responses. Subjects assessed the stimuli using bipolar scales. The study was effective in tracing interactions between familiarity, pleasure and arousal, although the incongruous image-word combinations did not elicit the predicted strong effects on pleasure and arousal. The results suggest a need for further research incorporating kansei (i.e., creativity) into the process of stimuli selection.

Method and system for assigning a confidence metric for automated determination of optic disc location

DOEpatents

Karnowski, Thomas P [Knoxville, TN; Tobin, Jr., Kenneth W.; Muthusamy Govindasamy, Vijaya Priya [Knoxville, TN; Chaum, Edward [Memphis, TN

2012-07-10

A method for assigning a confidence metric for automated determination of optic disc location that includes analyzing a retinal image and determining at least two sets of coordinates locating an optic disc in the retinal image. The sets of coordinates can be determined using first and second image analysis techniques that are different from one another. An accuracy parameter can be calculated and compared to a primary risk cut-off value. A high confidence level can be assigned to the retinal image if the accuracy parameter is less than the primary risk cut-off value and a low confidence level can be assigned to the retinal image if the accuracy parameter is greater than the primary risk cut-off value. The primary risk cut-off value being selected to represent an acceptable risk of misdiagnosis of a disease having retinal manifestations by the automated technique.

High resolution imaging of latent fingerprints by localized corrosion on brass surfaces.

PubMed

Goddard, Alex J; Hillman, A Robert; Bond, John W

2010-01-01

The Atomic Force Microscope (AFM) is capable of imaging fingerprint ridges on polished brass substrates at an unprecedented level of detail. While exposure to elevated humidity at ambient or slightly raised temperatures does not change the image appreciably, subsequent brief heating in a flame results in complete loss of the sweat deposit and the appearance of pits and trenches. Localized elemental analysis (using EDAX, coupled with SEM imaging) shows the presence of the constituents of salt in the initial deposits. Together with water and atmospheric oxygen--and with thermal enhancement--these are capable of driving a surface corrosion process. This process is sufficiently localized that it has the potential to generate a durable negative topographical image of the fingerprint. AFM examination of surface regions between ridges revealed small deposits (probably microscopic "spatter" of sweat components or transferred particulates) that may ultimately limit the level of ridge detail analysis.

Face sketch recognition based on edge enhancement via deep learning

NASA Astrophysics Data System (ADS)

Xie, Zhenzhu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

In this paper,we address the face sketch recognition problem. Firstly, we utilize the eigenface algorithm to convert a sketch image into a synthesized sketch face image. Subsequently, considering the low-level vision problem in synthesized face sketch image .Super resolution reconstruction algorithm based on CNN(convolutional neural network) is employed to improve the visual effect. To be specific, we uses a lightweight super-resolution structure to learn a residual mapping instead of directly mapping the feature maps from the low-level space to high-level patch representations, which making the networks are easier to optimize and have lower computational complexity. Finally, we adopt LDA(Linear Discriminant Analysis) algorithm to realize face sketch recognition on synthesized face image before super resolution and after respectively. Extensive experiments on the face sketch database(CUFS) from CUHK demonstrate that the recognition rate of SVM(Support Vector Machine) algorithm improves from 65% to 69% and the recognition rate of LDA(Linear Discriminant Analysis) algorithm improves from 69% to 75%.What'more,the synthesized face image after super resolution can not only better describer image details such as hair ,nose and mouth etc, but also improve the recognition accuracy effectively.

Self-phase modulation and two-photon absorption imaging of cells and active neurons

NASA Astrophysics Data System (ADS)

Fischer, Martin C.; Liu, Henry; Piletic, Ivan R.; Ye, Tong; Yasuda, Ryohei; Warren, Warren S.

2007-02-01

Even though multi-photon fluorescence microscopy offers higher resolution and better penetration depth than traditional fluorescence microscopy, its use is restricted to the detection of molecules that fluoresce. Two-photon absorption (TPA) imaging can provide contrast in non-fluorescent molecules while retaining the high resolution and sectioning capabilities of nonlinear imaging modalities. In the long-wavelength water window, tissue TPA is dominated by the endogenous molecules melanin and hemoglobin with an almost complete absence of endogenous two-photon fluorescence. A complementary nonlinear contrast mechanism is self-phase modulation (SPM), which can provide intrinsic signatures that can depend on local tissue anisotropy, chemical environment, or other structural properties. We have developed a spectral hole refilling measurement technique for TPA and SPM measurements using shaped ultrafast laser pulses. Here we report on a microscopy setup to simultaneously acquire 3D, high-resolution TPA and SPM images. We have acquired data in mounted B16 melanoma cells with very modest laser power levels. We will also discuss the possible application of this measurement technique to neuronal imaging. Since SPM is sensitive to material structure we can expect SPM properties of neurons to change during neuronal firing. Using our hole-refilling technique we have now demonstrated strong novel intrinsic nonlinear signatures of neuronal activation in a hippocampal brain slice. The observed changes in nonlinear signal upon collective activation were up to factors of two, unlike other intrinsic optical signal changes on the percent level. These results show that TPA and SPM imaging can provide important novel functional contrast in tissue using very modest power levels suitable for in vivo applications.

The Medical Imaging Interaction Toolkit: challenges and advances : 10 years of open-source development.

PubMed

Nolden, Marco; Zelzer, Sascha; Seitel, Alexander; Wald, Diana; Müller, Michael; Franz, Alfred M; Maleike, Daniel; Fangerau, Markus; Baumhauer, Matthias; Maier-Hein, Lena; Maier-Hein, Klaus H; Meinzer, Hans-Peter; Wolf, Ivo

2013-07-01

The Medical Imaging Interaction Toolkit (MITK) has been available as open-source software for almost 10 years now. In this period the requirements of software systems in the medical image processing domain have become increasingly complex. The aim of this paper is to show how MITK evolved into a software system that is able to cover all steps of a clinical workflow including data retrieval, image analysis, diagnosis, treatment planning, intervention support, and treatment control. MITK provides modularization and extensibility on different levels. In addition to the original toolkit, a module system, micro services for small, system-wide features, a service-oriented architecture based on the Open Services Gateway initiative (OSGi) standard, and an extensible and configurable application framework allow MITK to be used, extended and deployed as needed. A refined software process was implemented to deliver high-quality software, ease the fulfillment of regulatory requirements, and enable teamwork in mixed-competence teams. MITK has been applied by a worldwide community and integrated into a variety of solutions, either at the toolkit level or as an application framework with custom extensions. The MITK Workbench has been released as a highly extensible and customizable end-user application. Optional support for tool tracking, image-guided therapy, diffusion imaging as well as various external packages (e.g. CTK, DCMTK, OpenCV, SOFA, Python) is available. MITK has also been used in several FDA/CE-certified applications, which demonstrates the high-quality software and rigorous development process. MITK provides a versatile platform with a high degree of modularization and interoperability and is well suited to meet the challenging tasks of today's and tomorrow's clinically motivated research.

Researches on Position Detection for Vacuum Switch Electrode

NASA Astrophysics Data System (ADS)

Dong, Huajun; Guo, Yingjie; Li, Jie; Kong, Yihan

2018-03-01

Form and transformation character of vacuum arc is important influencing factor on the vacuum switch performance, and the dynamic separations of electrode is the chief effecting factor on the transformation of vacuum arcs forms. Consequently, how to detect the position of electrode to calculate the separations in the arcs image is of great significance. However, gray level distribution of vacuum arcs image isn’t even, the gray level of burning arcs is high, but the gray level of electrode is low, meanwhile, the forms of vacuum arcs changes sharply, the problems above restrict electrode position detection precisely. In this paper, algorithm of detecting electrode position base on vacuum arcs image was proposed. The digital image processing technology was used in vacuum switch arcs image analysis, the upper edge and lower edge were detected respectively, then linear fitting was done using the result of edge detection, the fitting result was the position of electrode, thus, accurate position detection of electrode was realized. From the experimental results, we can see that: algorithm described in this paper detected upper and lower edge of arcs successfully and the position of electrode was obtained through calculation.

Automatic rule generation for high-level vision

NASA Technical Reports Server (NTRS)

Rhee, Frank Chung-Hoon; Krishnapuram, Raghu

1992-01-01

Many high-level vision systems use rule-based approaches to solving problems such as autonomous navigation and image understanding. The rules are usually elaborated by experts. However, this procedure may be rather tedious. In this paper, we propose a method to generate such rules automatically from training data. The proposed method is also capable of filtering out irrelevant features and criteria from the rules.

Effect of Intensive Statin Therapy on Coronary High-Intensity Plaques Detected by Noncontrast T1-Weighted Imaging: The AQUAMARINE Pilot Study.

PubMed

Noguchi, Teruo; Tanaka, Atsushi; Kawasaki, Tomohiro; Goto, Yoichi; Morita, Yoshiaki; Asaumi, Yasuhide; Nakao, Kazuhiro; Fujiwara, Reiko; Nishimura, Kunihiro; Miyamoto, Yoshihiro; Ishihara, Masaharu; Ogawa, Hisao; Koga, Nobuhiko; Narula, Jagat; Yasuda, Satoshi

2015-07-21

Coronary high-intensity plaques detected by noncontrast T1-weighted imaging may represent plaque instability. High-intensity plaques can be quantitatively assessed by a plaque-to-myocardium signal-intensity ratio (PMR). This pilot, hypothesis-generating study sought to investigate whether intensive statin therapy would lower PMR. Prospective serial noncontrast T1-weighted magnetic resonance imaging and computed tomography angiography were performed in 48 patients with coronary artery disease at baseline and after 12 months of intensive pitavastatin treatment with a target low-density lipoprotein cholesterol level <80 mg/dl. The control group consisted of coronary artery disease patients not treated with statins that were matched by propensity scoring (n = 48). The primary endpoint was the 12-month change in PMR. Changes in computed tomography angiography parameters and high-sensitivity C-reactive protein levels were analyzed. In the statin group, 12 months of statin therapy significantly improved low-density lipoprotein cholesterol levels (125 to 70 mg/dl; p < 0.001), PMR (1.38 to 1.11, an 18.9% reduction; p < 0.001), low-attenuation plaque volume, and the percentage of total atheroma volume on computed tomography. In the control group, the PMR increased significantly (from 1.22 to 1.49, a 19.2% increase; p < 0.001). Changes in PMR were correlated with changes in low-density lipoprotein cholesterol (r = 0.533; p < 0.001), high-sensitivity C-reactive protein (r = 0.347; p < 0.001), percentage of atheroma volume (r = 0.477; p < 0.001), and percentage of low-attenuation plaque volume (r = 0.416; p < 0.001). Statin treatment significantly reduced the PMR of high-intensity plaques. Noncontrast T1-weighted magnetic resonance imaging could become a useful technique for repeated quantitative assessment of plaque composition. (Attempts at Plaque Vulnerability Quantification with Magnetic Resonance Imaging Using Noncontrast T1-weighted Technique [AQUAMARINE]; UMIN000003567). Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Diagnostic imaging learning resources evaluated by students and recent graduates.

PubMed

Alexander, Kate; Bélisle, Marilou; Dallaire, Sébastien; Fernandez, Nicolas; Doucet, Michèle

2013-01-01

Many learning resources can help students develop the problem-solving abilities and clinical skills required for diagnostic imaging. This study explored veterinary students' perceptions of the usefulness of a variety of learning resources. Perceived resource usefulness was measured for different levels of students and for academic versus clinical preparation. Third-year (n=139) and final (fifth) year (n=105) students and recent graduates (n=56) completed questionnaires on perceived usefulness of each resource. Resources were grouped for comparison: abstract/low complexity (e.g., notes, multimedia presentations), abstract/high complexity (e.g., Web-based and film case repositories), concrete/low complexity (e.g., large-group "clicker" workshops), and concrete/high complexity (e.g., small-group interpretation workshops). Lower-level students considered abstract/low-complexity resources more useful for academic preparation and concrete resources more useful for clinical preparation. Higher-level students/recent graduates also considered abstract/low-complexity resources more useful for academic preparation. For all levels, lecture notes were considered highly useful. Multimedia slideshows were an interactive complement to notes. The usefulness of a Web-based case repository was limited by accessibility problems and difficulty. Traditional abstract/low-complexity resources were considered useful for more levels and contexts than expected. Concrete/high-complexity resources need to better represent clinical practice to be considered more useful for clinical preparation.

Advanced two-layer level set with a soft distance constraint for dual surfaces segmentation in medical images

NASA Astrophysics Data System (ADS)

Ji, Yuanbo; van der Geest, Rob J.; Nazarian, Saman; Lelieveldt, Boudewijn P. F.; Tao, Qian

2018-03-01

Anatomical objects in medical images very often have dual contours or surfaces that are highly correlated. Manually segmenting both of them by following local image details is tedious and subjective. In this study, we proposed a two-layer region-based level set method with a soft distance constraint, which not only regularizes the level set evolution at two levels, but also imposes prior information on wall thickness in an effective manner. By updating the level set function and distance constraint functions alternatingly, the method simultaneously optimizes both contours while regularizing their distance. The method was applied to segment the inner and outer wall of both left atrium (LA) and left ventricle (LV) from MR images, using a rough initialization from inside the blood pool. Compared to manual annotation from experience observers, the proposed method achieved an average perpendicular distance (APD) of less than 1mm for the LA segmentation, and less than 1.5mm for the LV segmentation, at both inner and outer contours. The method can be used as a practical tool for fast and accurate dual wall annotations given proper initialization.

MO-FG-204-03: Using Edge-Preserving Algorithm for Significantly Improved Image-Domain Material Decomposition in Dual Energy CT

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

Zhao, W; Niu, T; Xing, L

2015-06-15

Purpose: To significantly improve dual energy CT (DECT) imaging by establishing a new theoretical framework of image-domain material decomposition with incorporation of edge-preserving techniques. Methods: The proposed algorithm, HYPR-NLM, combines the edge-preserving non-local mean filter (NLM) with the HYPR-LR (Local HighlY constrained backPRojection Reconstruction) framework. Image denoising using HYPR-LR framework depends on the noise level of the composite image which is the average of the different energy images. For DECT, the composite image is the average of high- and low-energy images. To further reduce noise, one may want to increase the window size of the filter of the HYPR-LR, leadingmore » resolution degradation. By incorporating the NLM filtering and the HYPR-LR framework, HYPR-NLM reduces the boost material decomposition noise using energy information redundancies as well as the non-local mean. We demonstrate the noise reduction and resolution preservation of the algorithm with both iodine concentration numerical phantom and clinical patient data by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). Results: The results show iterative material decomposition method reduces noise to the lowest level and provides improved DECT images. HYPR-NLM significantly reduces noise while preserving the accuracy of quantitative measurement and resolution. For the iodine concentration numerical phantom, the averaged noise levels are about 2.0, 0.7, 0.2 and 0.4 for direct inversion, HYPR-LR, Iter- DECT and HYPR-NLM, respectively. For the patient data, the noise levels of the water images are about 0.36, 0.16, 0.12 and 0.13 for direct inversion, HYPR-LR, Iter-DECT and HYPR-NLM, respectively. Difference images of both HYPR-LR and Iter-DECT show edge effect, while no significant edge effect is shown for HYPR-NLM, suggesting spatial resolution is well preserved for HYPR-NLM. Conclusion: HYPR-NLM provides an effective way to reduce the generic magnified image noise of dual–energy material decomposition while preserving resolution. This work is supported in part by NIH grants 7R01HL111141 and 1R01-EB016777. This work is also supported by the Natural Science Foundation of China (NSFC Grant No. 81201091), Fundamental Research Funds for the Central Universities in China, and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.« less

Imaging of Pancreatic and Duodenal Trauma.

PubMed

Melamud, Kira; LeBedis, Christina A; Soto, Jorge A

2015-07-01

Pancreatic and duodenal injuries are rare but life-threatening occurrences, often occurring in association with other solid organ injuries. Findings of pancreatic and duodenal trauma on computed tomography and MR imaging are often nonspecific, and high levels of clinical suspicion and understanding of mechanism of injury are imperative. Familiarity with the grading schemes of pancreatic and duodenal injury is important because they help in assessing for key imaging findings that directly influence management. This article presents an overview of imaging of blunt and penetrating pancreatic and duodenal injuries, including pathophysiology, available imaging techniques, and variety of imaging features. Copyright © 2015 Elsevier Inc. All rights reserved.

Detector and readout performance goals for quantum well and strained layer superlattice focal plane arrays imaging under tactical and strategic backgrounds

NASA Astrophysics Data System (ADS)

Bandara, Sumith V.

2009-11-01

Advancements in III-V semiconductor based, Quantum-well infrared photodetector (QWIP) and Type-II Strained-Layer Superlattice detector (T2SLS) technologies have yielded highly uniform, large-format long-wavelength infrared (LWIR) QWIP FPAs and high quantum efficiency (QE), small format, LWIR T2SLS FPAs. In this article, we have analyzed the QWIP and T2SLS detector level performance requirements and readout integrated circuit (ROIC) noise levels for several staring array long-wavelength infrared (LWIR) imaging applications at various background levels. As a result of lower absorption QE and less than unity photoconductive gain, QWIP FPAs are appropriate for high background tactical applications. However, if the application restricts the integration time, QWIP FPA performance may be limited by the read noise of the ROIC. Rapid progress in T2SLS detector material has already demonstrated LWIR detectors with sufficient performance for tactical applications and potential for strategic applications. However, significant research is needed to suppress surface leakage currents in order to reproduce performances at pixel levels of T2SLS FPAs.

A novel snapshot polarimetric imager

NASA Astrophysics Data System (ADS)

Wong, Gerald; McMaster, Ciaran; Struthers, Robert; Gorman, Alistair; Sinclair, Peter; Lamb, Robert; Harvey, Andrew R.

2012-10-01

Polarimetric imaging (PI) is of increasing importance in determining additional scene information beyond that of conventional images. For very long-range surveillance, image quality is degraded due to turbulence. Furthermore, the high magnification required to create images with sufficient spatial resolution suitable for object recognition and identification require long focal length optical systems. These are incompatible with the size and weight restrictions for aircraft. Techniques which allow detection and recognition of an object at the single pixel level are therefore likely to provide advance warning of approaching threats or long-range object cueing. PI is a technique that has the potential to detect object signatures at the pixel level. Early attempts to develop PI used rotating polarisers (and spectral filters) which recorded sequential polarized images from which the complete Stokes matrix could be derived. This approach has built-in latency between frames and requires accurate registration of consecutive frames to analyze real-time video of moving objects. Alternatively, multiple optical systems and cameras have been demonstrated to remove latency, but this approach increases cost and bulk of the imaging system. In our investigation we present a simplified imaging system that divides an image into two orthogonal polarimetric components which are then simultaneously projected onto a single detector array. Thus polarimetric data is recorded without latency on a single snapshot. We further show that, for pixel-level objects, the data derived from only two orthogonal states (H and V) is sufficient to increase the probability of detection whilst reducing false alarms compared to conventional unpolarised imaging.

a New Object-Based Framework to Detect Shodows in High-Resolution Satellite Imagery Over Urban Areas

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.; Hadavand, A.

2015-12-01

In this paper a new object-based framework to detect shadow areas in high resolution satellite images is proposed. To produce shadow map in pixel level state of the art supervised machine learning algorithms are employed. Automatic ground truth generation based on Otsu thresholding on shadow and non-shadow indices is used to train the classifiers. It is followed by segmenting the image scene and create image objects. To detect shadow objects, a majority voting on pixel-based shadow detection result is designed. GeoEye-1 multi-spectral image over an urban area in Qom city of Iran is used in the experiments. Results shows the superiority of our proposed method over traditional pixel-based, visually and quantitatively.

Novel bright-emission small-molecule NIR-II fluorophores for in vivo tumor imaging and image-guided surgery† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc00251c Click here for additional data file.

PubMed Central

Sun, Yao; Ding, Mingmin; Zeng, Xiaodong; Xiao, Yuling; Wu, Huaping; Zhou, Hui; Ding, Bingbing; Qu, Chunrong; Hou, Wei; Er-bu, AGA; Zhang, Yejun; Cheng, Zhen

2017-01-01

Though high brightness and biocompatible small NIR-II dyes are highly desirable in clinical or translational cancer research, their fluorescent cores are relatively limited and their synthetic processes are somewhat complicated. Herein, we have explored the design and synthesis of novel NIR-II fluorescent materials (H1) without tedious chromatographic isolation with improved fluorescence performance (QY ≈ 2%) by introducing 2-amino 9,9-dialkyl-substituted fluorene as a donor into the backbone. Several types of water-soluble and biocompatible NIR-II probes: SXH, SDH, and H1 NPs were constructed via different chemical strategies based on H1, and then their potential to be used in in vivo tumor imaging and image-guided surgery in the NIR-II region was explored. High levels of uptake were obtained for both passive and active tumor targeting probes SXH and SDH. Furthermore, high resolution imaging of blood vessels on tumors and the whole body of living mice using H1 NPs for the first time has demonstrated precise NIR-II image-guided sentinel lymph node (SLN) surgery. PMID:28507722

Photoacoustic and Colorimetric Visualization of Latent Fingerprints.

PubMed

Song, Kai; Huang, Peng; Yi, Chenglin; Ning, Bo; Hu, Song; Nie, Liming; Chen, Xiaoyuan; Nie, Zhihong

2015-12-22

There is a high demand on a simple, rapid, accurate, user-friendly, cost-effective, and nondestructive universal method for latent fingerprint (LFP) detection. Herein, we describe a combination imaging strategy for LFP visualization with high resolution using poly(styrene-alt-maleic anhydride)-b-polystyrene (PSMA-b-PS) functionalized gold nanoparticles (GNPs). This general approach integrates the merits of both colorimetric imaging and photoacoustic imaging. In comparison with the previous methods, our strategy is single-step and does not require the signal amplification by silver staining. The PSMA-b-PS functionalized GNPs have good stability, tunable color, and high affinity for universal secretions (proteins/polypeptides/amino acids), which makes our approach general and flexible for visualizing LFPs on different substrates (presumably with different colors) and from different people. Moreover, the unique optical property of GNPs enables the photoacoustic imaging of GNPs-deposited LFPs with high resolution. This allows observation of level 3 hyperfine features of LFPs such as the pores and ridge contours by photoacoustic imaging. This technique can potentially be used to identify chemicals within LFP residues. We believe that this dual-modality imaging of LFPs will find widespread use in forensic investigations and medical diagnostics.

Image Feature Types and Their Predictions of Aesthetic Preference and Naturalness

PubMed Central

Ibarra, Frank F.; Kardan, Omid; Hunter, MaryCarol R.; Kotabe, Hiroki P.; Meyer, Francisco A. C.; Berman, Marc G.

2017-01-01

Previous research has investigated ways to quantify visual information of a scene in terms of a visual processing hierarchy, i.e., making sense of visual environment by segmentation and integration of elementary sensory input. Guided by this research, studies have developed categories for low-level visual features (e.g., edges, colors), high-level visual features (scene-level entities that convey semantic information such as objects), and how models of those features predict aesthetic preference and naturalness. For example, in Kardan et al. (2015a), 52 participants provided aesthetic preference and naturalness ratings, which are used in the current study, for 307 images of mixed natural and urban content. Kardan et al. (2015a) then developed a model using low-level features to predict aesthetic preference and naturalness and could do so with high accuracy. What has yet to be explored is the ability of higher-level visual features (e.g., horizon line position relative to viewer, geometry of building distribution relative to visual access) to predict aesthetic preference and naturalness of scenes, and whether higher-level features mediate some of the association between the low-level features and aesthetic preference or naturalness. In this study we investigated these relationships and found that low- and high- level features explain 68.4% of the variance in aesthetic preference ratings and 88.7% of the variance in naturalness ratings. Additionally, several high-level features mediated the relationship between the low-level visual features and aaesthetic preference. In a multiple mediation analysis, the high-level feature mediators accounted for over 50% of the variance in predicting aesthetic preference. These results show that high-level visual features play a prominent role predicting aesthetic preference, but do not completely eliminate the predictive power of the low-level visual features. These strong predictors provide powerful insights for future research relating to landscape and urban design with the aim of maximizing subjective well-being, which could lead to improved health outcomes on a larger scale. PMID:28503158

Multiple Point Statistics algorithm based on direct sampling and multi-resolution images

NASA Astrophysics Data System (ADS)

Julien, S.; Renard, P.; Chugunova, T.

2017-12-01

Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.

Scanner as a Fine Art

ERIC Educational Resources Information Center

Fontes, Kris

2008-01-01

Not every art department is fortunate enough to have access to digital cameras and image-editing software, but if a scanner, computer, and printer are available, students can create some imaginative and surreal work. This high-school level lesson begins with a discussion of self-portraits, and then moves to students creating images by scanning…

Imaging in Central Nervous System Drug Discovery.

PubMed

Gunn, Roger N; Rabiner, Eugenii A

2017-01-01

The discovery and development of central nervous system (CNS) drugs is an extremely challenging process requiring large resources, timelines, and associated costs. The high risk of failure leads to high levels of risk. Over the past couple of decades PET imaging has become a central component of the CNS drug-development process, enabling decision-making in phase I studies, where early discharge of risk provides increased confidence to progress a candidate to more costly later phase testing at the right dose level or alternatively to kill a compound through failure to meet key criteria. The so called "3 pillars" of drug survival, namely; tissue exposure, target engagement, and pharmacologic activity, are particularly well suited for evaluation by PET imaging. This review introduces the process of CNS drug development before considering how PET imaging of the "3 pillars" has advanced to provide valuable tools for decision-making on the critical path of CNS drug development. Finally, we review the advances in PET science of biomarker development and analysis that enable sophisticated drug-development studies in man. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

High-throughput dual-colour precision imaging for brain-wide connectome with cytoarchitectonic landmarks at the cellular level

PubMed Central

Gong, Hui; Xu, Dongli; Yuan, Jing; Li, Xiangning; Guo, Congdi; Peng, Jie; Li, Yuxin; Schwarz, Lindsay A.; Li, Anan; Hu, Bihe; Xiong, Benyi; Sun, Qingtao; Zhang, Yalun; Liu, Jiepeng; Zhong, Qiuyuan; Xu, Tonghui; Zeng, Shaoqun; Luo, Qingming

2016-01-01

The precise annotation and accurate identification of neural structures are prerequisites for studying mammalian brain function. The orientation of neurons and neural circuits is usually determined by mapping brain images to coarse axial-sampling planar reference atlases. However, individual differences at the cellular level likely lead to position errors and an inability to orient neural projections at single-cell resolution. Here, we present a high-throughput precision imaging method that can acquire a co-localized brain-wide data set of both fluorescent-labelled neurons and counterstained cell bodies at a voxel size of 0.32 × 0.32 × 2.0 μm in 3 days for a single mouse brain. We acquire mouse whole-brain imaging data sets of multiple types of neurons and projections with anatomical annotation at single-neuron resolution. The results show that the simultaneous acquisition of labelled neural structures and cytoarchitecture reference in the same brain greatly facilitates precise tracing of long-range projections and accurate locating of nuclei. PMID:27374071

Modes of Visual Recognition and Perceptually Relevant Sketch-based Coding for Images

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1991-01-01

A review of visual recognition studies is used to define two levels of information requirements. These two levels are related to two primary subdivisions of the spatial frequency domain of images and reflect two distinct different physical properties of arbitrary scenes. In particular, pathologies in recognition due to cerebral dysfunction point to a more complete split into two major types of processing: high spatial frequency edge based recognition vs. low spatial frequency lightness (and color) based recognition. The former is more central and general while the latter is more specific and is necessary for certain special tasks. The two modes of recognition can also be distinguished on the basis of physical scene properties: the highly localized edges associated with reflectance and sharp topographic transitions vs. smooth topographic undulation. The extreme case of heavily abstracted images is pursued to gain an understanding of the minimal information required to support both modes of recognition. Here the intention is to define the semantic core of transmission. This central core of processing can then be fleshed out with additional image information and coding and rendering techniques.

Superpixel Cut for Figure-Ground Image Segmentation

NASA Astrophysics Data System (ADS)

Yang, Michael Ying; Rosenhahn, Bodo

2016-06-01

Figure-ground image segmentation has been a challenging problem in computer vision. Apart from the difficulties in establishing an effective framework to divide the image pixels into meaningful groups, the notions of figure and ground often need to be properly defined by providing either user inputs or object models. In this paper, we propose a novel graph-based segmentation framework, called superpixel cut. The key idea is to formulate foreground segmentation as finding a subset of superpixels that partitions a graph over superpixels. The problem is formulated as Min-Cut. Therefore, we propose a novel cost function that simultaneously minimizes the inter-class similarity while maximizing the intra-class similarity. This cost function is optimized using parametric programming. After a small learning step, our approach is fully automatic and fully bottom-up, which requires no high-level knowledge such as shape priors and scene content. It recovers coherent components of images, providing a set of multiscale hypotheses for high-level reasoning. We evaluate our proposed framework by comparing it to other generic figure-ground segmentation approaches. Our method achieves improved performance on state-of-the-art benchmark databases.

Ultrafast Harmonic Coherent Compound (UHCC) imaging for high frame rate echocardiography and Shear Wave Elastography

PubMed Central

Correia, Mafalda; Provost, Jean; Chatelin, Simon; Villemain, Olivier; Tanter, Mickael; Pernot, Mathieu

2016-01-01

Transthoracic shear wave elastography of the myocardium remains very challenging due to the poor quality of transthoracic ultrafast imaging and the presence of clutter noise, jitter, phase aberration, and ultrasound reverberation. Several approaches, such as, e.g., diverging-wave coherent compounding or focused harmonic imaging have been proposed to improve the imaging quality. In this study, we introduce ultrafast harmonic coherent compounding (UHCC), in which pulse-inverted diverging-waves are emitted and coherently compounded, and show that such an approach can be used to enhance both Shear Wave Elastography (SWE) and high frame rate B-mode Imaging. UHCC SWE was first tested in phantoms containing an aberrating layer and was compared against pulse-inversion harmonic imaging and against ultrafast coherent compounding (UCC) imaging at the fundamental frequency. In-vivo feasibility of the technique was then evaluated in six healthy volunteers by measuring myocardial stiffness during diastole in transthoracic imaging. We also demonstrated that improvements in imaging quality could be achieved using UHCC B-mode imaging in healthy volunteers. The quality of transthoracic images of the heart was found to be improved with the number of pulse-inverted diverging waves with reduction of the imaging mean clutter level up to 13.8-dB when compared against UCC at the fundamental frequency. These results demonstrated that UHCC B-mode imaging is promising for imaging deep tissues exposed to aberration sources with a high frame-rate. PMID:26890730

Quantitative Study for the Surface Dehydration of Vocal Folds Based on High-Speed Imaging.

PubMed

Li, Lin; Zhang, Yu; Maytag, Allison L; Jiang, Jack J

2015-07-01

From the perspective of the glottal area and mucosal wave, quantitatively estimate the differences of vocal fold on laryngeal activity during phonation at three different dehydration levels. Controlled three sets of tests. A dehydration experiment for 10 excised canine larynges was conducted at 16 cm H2O. According to the dehydration cycle time (H), dehydration levels were divided into three degrees (0% H, 50% H, 75% H). The glottal area and mucosal wave under three dehydration levels were extracted from high-speed images and digital videokymography (DKG) image sequences. Direct and non-direct amplitude components were derived from glottal areas. The amplitude and frequency of mucosal wave were calculated from DKG image sequences. These parameters in condition of three dehydration levels were compared for statistical analysis. The results showed a significant difference in direct (P = 0.001; P = 0.005) and non-direct (P = 0.005; P = 0.016) components of glottal areas between every two different dehydration levels. Considering the right-upper, right-lower, left-upper, and left-lower of vocal fold, the amplitudes of mucosal waves consistently decreased with increasing of dehydration levels. But, there was no significant difference in frequency. Surface dehydration could give rise to complex variation of vocal fold on tissues and vibratory mechanism, which should need analyzing from multiple perspectives. The results suggested that the combination of glottal area and mucosal wave could be better to research the change of vocal fold at different dehydrations. It would become a better crucial research tool for the clinical treatment of dehydration-induced laryngeal pathologies. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Combining endoscopic ultrasound with Time-Of-Flight PET: The EndoTOFPET-US Project

NASA Astrophysics Data System (ADS)

Frisch, Benjamin

2013-12-01

The EndoTOFPET-US collaboration develops a multimodal imaging technique for endoscopic exams of the pancreas or the prostate. It combines the benefits of high resolution metabolic imaging with Time-Of-Flight Positron Emission Tomography (TOF PET) and anatomical imaging with ultrasound (US). EndoTOFPET-US consists of a PET head extension for a commercial US endoscope and a PET plate outside the body in coincidence with the head. The high level of miniaturization and integration creates challenges in fields such as scintillating crystals, ultra-fast photo-detection, highly integrated electronics, system integration and image reconstruction. Amongst the developments, fast scintillators as well as fast and compact digital SiPMs with single SPAD readout are used to obtain the best coincidence time resolution (CTR). Highly integrated ASICs and DAQ electronics contribute to the timing performances of EndoTOFPET. In view of the targeted resolution of around 1 mm in the reconstructed image, we present a prototype detector system with a CTR better than 240 ps FWHM. We discuss the challenges in simulating such a system and introduce reconstruction algorithms based on graphics processing units (GPU).

Fusion of infrared and visible images based on BEMD and NSDFB

NASA Astrophysics Data System (ADS)

Zhu, Pan; Huang, Zhanhua; Lei, Hai

2016-07-01

This paper presents a new fusion method based on the adaptive multi-scale decomposition of bidimensional empirical mode decomposition (BEMD) and the flexible directional expansion of nonsubsampled directional filter banks (NSDFB) for visible-infrared images. Compared with conventional multi-scale fusion methods, BEMD is non-parametric and completely data-driven, which is relatively more suitable for non-linear signals decomposition and fusion. NSDFB can provide direction filtering on the decomposition levels to capture more geometrical structure of the source images effectively. In our fusion framework, the entropies of the two patterns of source images are firstly calculated and the residue of the image whose entropy is larger is extracted to make it highly relevant with the other source image. Then, the residue and the other source image are decomposed into low-frequency sub-bands and a sequence of high-frequency directional sub-bands in different scales by using BEMD and NSDFB. In this fusion scheme, two relevant fusion rules are used in low-frequency sub-bands and high-frequency directional sub-bands, respectively. Finally, the fused image is obtained by applying corresponding inverse transform. Experimental results indicate that the proposed fusion algorithm can obtain state-of-the-art performance for visible-infrared images fusion in both aspects of objective assessment and subjective visual quality even for the source images obtained in different conditions. Furthermore, the fused results have high contrast, remarkable target information and rich details information that are more suitable for human visual characteristics or machine perception.

Reconstruction of pulse noisy images via stochastic resonance

PubMed Central

Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan

2015-01-01

We investigate a practical technology for reconstructing nanosecond pulse noisy images via stochastic resonance, which is based on the modulation instability. A theoretical model of this method for optical pulse signal is built to effectively recover the pulse image. The nanosecond noise-hidden images grow at the expense of noise during the stochastic resonance process in a photorefractive medium. The properties of output images are mainly determined by the input signal-to-noise intensity ratio, the applied voltage across the medium, and the correlation length of noise background. A high cross-correlation gain is obtained by optimizing these parameters. This provides a potential method for detecting low-level or hidden pulse images in various imaging applications. PMID:26067911

Interferometric Imaging Directly with Closure Phases and Closure Amplitudes

NASA Astrophysics Data System (ADS)

Chael, Andrew A.; Johnson, Michael D.; Bouman, Katherine L.; Blackburn, Lindy L.; Akiyama, Kazunori; Narayan, Ramesh

2018-04-01

Interferometric imaging now achieves angular resolutions as fine as ∼10 μas, probing scales that are inaccessible to single telescopes. Traditional synthesis imaging methods require calibrated visibilities; however, interferometric calibration is challenging, especially at high frequencies. Nevertheless, most studies present only a single image of their data after a process of “self-calibration,” an iterative procedure where the initial image and calibration assumptions can significantly influence the final image. We present a method for efficient interferometric imaging directly using only closure amplitudes and closure phases, which are immune to station-based calibration errors. Closure-only imaging provides results that are as noncommittal as possible and allows for reconstructing an image independently from separate amplitude and phase self-calibration. While closure-only imaging eliminates some image information (e.g., the total image flux density and the image centroid), this information can be recovered through a small number of additional constraints. We demonstrate that closure-only imaging can produce high-fidelity results, even for sparse arrays such as the Event Horizon Telescope, and that the resulting images are independent of the level of systematic amplitude error. We apply closure imaging to VLBA and ALMA data and show that it is capable of matching or exceeding the performance of traditional self-calibration and CLEAN for these data sets.

Imaging deep skeletal muscle structure using a high-sensitivity ultrathin side-viewing optical coherence tomography needle probe

PubMed Central

Yang, Xiaojie; Lorenser, Dirk; McLaughlin, Robert A.; Kirk, Rodney W.; Edmond, Matthew; Simpson, M. Cather; Grounds, Miranda D.; Sampson, David D.

2013-01-01

We have developed an extremely miniaturized optical coherence tomography (OCT) needle probe (outer diameter 310 µm) with high sensitivity (108 dB) to enable minimally invasive imaging of cellular structure deep within skeletal muscle. Three-dimensional volumetric images were acquired from ex vivo mouse tissue, examining both healthy and pathological dystrophic muscle. Individual myofibers were visualized as striations in the images. Degradation of cellular structure in necrotic regions was seen as a loss of these striations. Tendon and connective tissue were also visualized. The observed structures were validated against co-registered hematoxylin and eosin (H&E) histology sections. These images of internal cellular structure of skeletal muscle acquired with an OCT needle probe demonstrate the potential of this technique to visualize structure at the microscopic level deep in biological tissue in situ. PMID:24466482

A perspective on high-frequency ultrasound for medical applications

NASA Astrophysics Data System (ADS)

Mamou, Jonathan; Aristizába, Orlando; Silverman, Ronald H.; Ketterling, Jeffrey A.

2010-01-01

High-frequency ultrasound (HFU, >15 MHz) is a rapidly developing field. HFU is currently used and investigated for ophthalmologic, dermatologic, intravascular, and small-animal imaging. HFU offers a non-invasive means to investigate tissue at the microscopic level with resolutions often better than 100 μm. However, fine resolution is only obtained over the limited depth-of-field (˜1 mm) of single-element spherically-focused transducers typically used for HFU applications. Another limitation is penetration depth because most biological tissues have large attenuation at high frequencies. In this study, two 5-element annular arrays with center frequencies of 17 and 34 MHz were fabricated and methods were developed to obtain images with increased penetration depth and depth-of-field. These methods were used in ophthalmologic and small-animal imaging studies. Improved blood sensitivity was obtained when a phantom mimicking a vitreous hemorrhage was imaged. Central-nervous systems of 12.5-day-old mouse embryos were imaged in utero and in three dimensions for the first time.

The Application of Virtex-II Pro FPGA in High-Speed Image Processing Technology of Robot Vision Sensor

NASA Astrophysics Data System (ADS)

Ren, Y. J.; Zhu, J. G.; Yang, X. Y.; Ye, S. H.

2006-10-01

The Virtex-II Pro FPGA is applied to the vision sensor tracking system of IRB2400 robot. The hardware platform, which undertakes the task of improving SNR and compressing data, is constructed by using the high-speed image processing of FPGA. The lower level image-processing algorithm is realized by combining the FPGA frame and the embedded CPU. The velocity of image processing is accelerated due to the introduction of FPGA and CPU. The usage of the embedded CPU makes it easily to realize the logic design of interface. Some key techniques are presented in the text, such as read-write process, template matching, convolution, and some modules are simulated too. In the end, the compare among the modules using this design, using the PC computer and using the DSP, is carried out. Because the high-speed image processing system core is a chip of FPGA, the function of which can renew conveniently, therefore, to a degree, the measure system is intelligent.

The interrelationship between self-image disparity and social competence, defensive style, and adjustment status.

PubMed

Mylet, M; Styfco, S J; Zigler, E

1979-09-01

Groups of 40 psychiatric and 40 nonpsychiatric male patients were subdivided into equal groups of high and low social competence. Each patient completed a task battery which included three measures of self-image disparity and the Byrne repression-sensitization scale. High competence patients of both types were found to have higher self-image disparities than low competence patients. Psychiatric patients were found to have higher disparity scores than nonpsychiatric patients, although some evidence indicated that this was true only for the low competence groups. Higher scores on the Byrne scale (indicating sensitization) were found for high as compared to low competence patients, and for the psychiatric as compared to nonpsychiatric groups. Defensive style correlated significantly with each of the self-image measures. The results were discussed in the context of both developmental and Rogerian formulations. It was concluded that an individual's maturational level influences both self-image and defensive style, even when the individual is judged psychologically maladjusted.

Image processing based detection of lung cancer on CT scan images

NASA Astrophysics Data System (ADS)

Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.

A homeostatic, chip-based platform for zebrafish larvae immobilization and long-term imaging

NASA Astrophysics Data System (ADS)

Friedrich, Timo; Zhu, Feng; Wlodkowic, Donald; Kaslin, Jan

2015-12-01

Zebrafish larvae are ideal for toxicology and drug screens due to their transparency, small size and similarity to humans on the genetic level. Using modern imaging techniques, cells and tissues can be dynamically visualised and followed over days in multiple zebrafish. Yet continued imaging experiments require specialized conditions such as: moisture and heat control to maintain specimen homeostasis. Chambers that control the environment are generally very expensive and are not always available for all imaging platforms. A highly customizable mounting configuration with built-in means of controlling temperature and media flow would therefore be a valuable tool for long term imaging experiments. Rapid prototyping using 3D printing is particularly suitable as a production method as it offers high flexibility in design, is widely available and allows a high degree of customizing. We study neural regeneration in zebrafish. Regeneration is limited in humans, but zebrafish recover from neural damage within days. Yet, the underlying regenerative mechanisms remain unclear. We developed an agarose based mounting system that holds the embryos in defined positions along removable strips. Homeostasis and temperature control is ensured by channels circulating buffer and heated water. This allows to image up to 120 larvae simultaneously for more than two days. Its flexibility and the low-volume, high larvae ratio will allow screening of small compound libraries. Taken together, we offer a low cost, highly adaptable solution for long term in-vivo imaging.

High Scalability Video ISR Exploitation

DTIC Science & Technology

2012-10-01

Surveillance, ARGUS) on the National Image Interpretability Rating Scale (NIIRS) at level 6. Ultra-high quality cameras like the Digital Cinema 4K (DC-4K...Scale (NIIRS) at level 6. Ultra-high quality cameras like the Digital Cinema 4K (DC-4K), which recognizes objects smaller than people, will be available...purchase ultra-high quality cameras like the Digital Cinema 4K (DC-4K) for use in the field. However, even if such a UAV sensor with a DC-4K was flown

New procedures to evaluate visually lossless compression for display systems

NASA Astrophysics Data System (ADS)

Stolitzka, Dale F.; Schelkens, Peter; Bruylants, Tim

2017-09-01

Visually lossless image coding in isochronous display streaming or plesiochronous networks reduces link complexity and power consumption and increases available link bandwidth. A new set of codecs developed within the last four years promise a new level of coding quality, but require new techniques that are sufficiently sensitive to the small artifacts or color variations induced by this new breed of codecs. This paper begins with a summary of the new ISO/IEC 29170-2, a procedure for evaluation of lossless coding and reports the new work by JPEG to extend the procedure in two important ways, for HDR content and for evaluating the differences between still images, panning images and image sequences. ISO/IEC 29170-2 relies on processing test images through a well-defined process chain for subjective, forced-choice psychophysical experiments. The procedure sets an acceptable quality level equal to one just noticeable difference. Traditional image and video coding evaluation techniques, such as, those used for television evaluation have not proven sufficiently sensitive to the small artifacts that may be induced by this breed of codecs. In 2015, JPEG received new requirements to expand evaluation of visually lossless coding for high dynamic range images, slowly moving images, i.e., panning, and image sequences. These requirements are the basis for new amendments of the ISO/IEC 29170-2 procedures described in this paper. These amendments promise to be highly useful for the new content in television and cinema mezzanine networks. The amendments passed the final ballot in April 2017 and are on track to be published in 2018.

Differential roles of low and high spatial frequency content in abnormal facial emotion perception in schizophrenia.

PubMed

McBain, Ryan; Norton, Daniel; Chen, Yue

2010-09-01

While schizophrenia patients are impaired at facial emotion perception, the role of basic visual processing in this deficit remains relatively unclear. We examined emotion perception when spatial frequency content of facial images was manipulated via high-pass and low-pass filtering. Unlike controls (n=29), patients (n=30) perceived images with low spatial frequencies as more fearful than those without this information, across emotional salience levels. Patients also perceived images with high spatial frequencies as happier. In controls, this effect was found only at low emotional salience. These results indicate that basic visual processing has an amplified modulatory effect on emotion perception in schizophrenia. (c) 2010 Elsevier B.V. All rights reserved.

Reduction of radiation exposure while maintaining high-quality fluoroscopic images during interventional cardiology using novel x-ray tube technology with extra beam filtering.

PubMed

den Boer, A; de Feyter, P J; Hummel, W A; Keane, D; Roelandt, J R

1994-06-01

Radiographic technology plays an integral role in interventional cardiology. The number of interventions continues to increase, and the associated radiation exposure to patients and personnel is of major concern. This study was undertaken to determine whether a newly developed x-ray tube deploying grid-switched pulsed fluoroscopy and extra beam filtering can achieve a reduction in radiation exposure while maintaining fluoroscopic images of high quality. Three fluoroscopic techniques were compared: continuous fluoroscopy, pulsed fluoroscopy, and a newly developed high-output pulsed fluoroscopy with extra filtering. To ascertain differences in the quality of images and to determine differences in patient entrance and investigator radiation exposure, the radiated volume curve was measured to determine the required high voltage levels (kVpeak) for different object sizes for each fluoroscopic mode. The fluoroscopic data of 124 patient procedures were combined. The data were analyzed for radiographic projections, image intensifier field size, and x-ray tube kilovoltage levels (kVpeak). On the basis of this analysis, a reference procedure was constructed. The reference procedure was tested on a phantom or dummy patient by all three fluoroscopic modes. The phantom was so designed that the kilovoltage requirements for each projection were comparable to those needed for the average patient. Radiation exposure of the operator and patient was measured during each mode. The patient entrance dose was measured in air, and the operator dose was measured by 18 dosimeters on a dummy operator. Pulsed compared with continuous fluoroscopy could be performed with improved image quality at lower kilovoltages. The patient entrance dose was reduced by 21% and the operator dose by 54%. High-output pulsed fluoroscopy with extra beam filtering compared with continuous fluoroscopy improved the image quality, lowered the kilovoltage requirements, and reduced the patient entrance dose by 55% and the operator dose by 69%. High-output pulsed fluoroscopy with a grid-switched tube and extra filtering improves the image quality and significantly reduces both the operator dose and patient dose.

PHOG analysis of self-similarity in aesthetic images

NASA Astrophysics Data System (ADS)

Amirshahi, Seyed Ali; Koch, Michael; Denzler, Joachim; Redies, Christoph

2012-03-01

In recent years, there have been efforts in defining the statistical properties of aesthetic photographs and artworks using computer vision techniques. However, it is still an open question how to distinguish aesthetic from non-aesthetic images with a high recognition rate. This is possibly because aesthetic perception is influenced also by a large number of cultural variables. Nevertheless, the search for statistical properties of aesthetic images has not been futile. For example, we have shown that the radially averaged power spectrum of monochrome artworks of Western and Eastern provenance falls off according to a power law with increasing spatial frequency (1/f2 characteristics). This finding implies that this particular subset of artworks possesses a Fourier power spectrum that is self-similar across different scales of spatial resolution. Other types of aesthetic images, such as cartoons, comics and mangas also display this type of self-similarity, as do photographs of complex natural scenes. Since the human visual system is adapted to encode images of natural scenes in a particular efficient way, we have argued that artists imitate these statistics in their artworks. In support of this notion, we presented results that artists portrait human faces with the self-similar Fourier statistics of complex natural scenes although real-world photographs of faces are not self-similar. In view of these previous findings, we investigated other statistical measures of self-similarity to characterize aesthetic and non-aesthetic images. In the present work, we propose a novel measure of self-similarity that is based on the Pyramid Histogram of Oriented Gradients (PHOG). For every image, we first calculate PHOG up to pyramid level 3. The similarity between the histograms of each section at a particular level is then calculated to the parent section at the previous level (or to the histogram at the ground level). The proposed approach is tested on datasets of aesthetic and non-aesthetic categories of monochrome images. The aesthetic image datasets comprise a large variety of artworks of Western provenance. Other man-made aesthetically pleasing images, such as comics, cartoons and mangas, were also studied. For comparison, a database of natural scene photographs is used, as well as datasets of photographs of plants, simple objects and faces that are in general of low aesthetic value. As expected, natural scenes exhibit the highest degree of PHOG self-similarity. Images of artworks also show high selfsimilarity values, followed by cartoons, comics and mangas. On average, other (non-aesthetic) image categories are less self-similar in the PHOG analysis. A measure of scale-invariant self-similarity (PHOG) allows a good separation of the different aesthetic and non-aesthetic image categories. Our results provide further support for the notion that, like complex natural scenes, images of artworks display a higher degree of self-similarity across different scales of resolution than other image categories. Whether the high degree of self-similarity is the basis for the perception of beauty in both complex natural scenery and artworks remains to be investigated.

TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

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

Oliver, J; Budzevich, M; Moros, E

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images),more » image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.« less

Whole-heart magnetic resonance coronary angiography with multiple breath-holds and automatic breathing-level tracking

NASA Astrophysics Data System (ADS)

Kuhara, Shigehide; Ninomiya, Ayako; Okada, Tomohisa; Kanao, Shotaro; Kamae, Toshikazu; Togashi, Kaori

2010-05-01

Whole-heart (WH) magnetic resonance coronary angiography (MRCA) studies are usually performed during free breathing while monitoring the position of the diaphragm with real-time motion correction. However, this results in a long scan time and the patient's breathing pattern may change, causing the study to be aborted. Alternatively, WH MRCA can be performed with multiple breath-holds (mBH). However, one problem in the mBH method is that patients cannot hold their breath at the same position every time, leading to image degradation. We have developed a new WH MRCA imaging method that employs both the mBH method and automatic breathing-level tracking to permit automatic tracking of the changes in breathing or breath-hold levels. Evaluation of its effects on WH MRCA image quality showed that this method can provide high-quality images within a shorter scan time. This proposed method is expected to be very useful in clinical WH MRCA studies.

Imaging performance of annular apertures. IV - Apodization and point spread functions. V - Total and partial energy integral functions

NASA Technical Reports Server (NTRS)

Tschunko, H. F. A.

1983-01-01

Reference is made to a study by Tschunko (1979) in which it was discussed how apodization modifies the modulation transfer function for various central obstruction ratios. It is shown here how apodization, together with the central obstruction ratio, modifies the point spread function, which is the basic element for the comparison of imaging performance and for the derivation of energy integrals and other functions. At high apodization levels and lower central obstruction (less than 0.1), new extended radial zones are formed in the outer part of the central ring groups. These transmutation of the image functions are of more than theoretical interest, especially if the irradiance levels in the outer ring zones are to be compared to the background irradiance levels. Attention is then given to the energy distribution in point images generated by annular apertures apodized by various transmission functions. The total energy functions are derived; partial energy integrals are determined; and background irradiance functions are discussed.

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.

Design of small confocal endo-microscopic probe working under multiwavelength environment

NASA Astrophysics Data System (ADS)

Kim, Young-Duk; Ahn, MyoungKi; Gweon, Dae-Gab

2010-02-01

Recently, optical imaging system is widely used in medical purpose. By using optical imaging system specific diseases can be easily diagnosed at early stage because optical imaging system has high resolution performance and various imaging method. These methods are used to get high resolution image of human body and can be used to verify whether the cell is infected by virus. Confocal microscope is one of the famous imaging systems which is used for in-vivo imaging. Because most of diseases are accompanied with cellular level changes, doctors can diagnosis at early stage by observing the cellular image of human organ. Current research is focused in the development of endo-microscope that has great advantage in accessibility to human body. In this research, I designed small probe that is connected to confocal microscope through optical fiber bundle and work as endo-microscope. And this small probe is mainly designed to correct chromatic aberration to use various laser sources for both fluorescence type and reflection type confocal images. By using two kinds of laser sources at the same time we demonstrated multi-modality confocal endo-microscope.

Visual Estimation of Bacterial Growth Level in Microfluidic Culture Systems.

PubMed

Kim, Kyukwang; Kim, Seunggyu; Jeon, Jessie S

2018-02-03

Microfluidic devices are an emerging platform for a variety of experiments involving bacterial cell culture, and has advantages including cost and convenience. One inevitable step during bacterial cell culture is the measurement of cell concentration in the channel. The optical density measurement technique is generally used for bacterial growth estimation, but it is not applicable to microfluidic devices due to the small sample volumes in microfluidics. Alternately, cell counting or colony-forming unit methods may be applied, but these do not work in situ; nor do these methods show measurement results immediately. To this end, we present a new vision-based method to estimate the growth level of the bacteria in microfluidic channels. We use Fast Fourier transform (FFT) to detect the frequency level change of the microscopic image, focusing on the fact that the microscopic image becomes rough as the number of cells in the field of view increases, adding high frequencies to the spectrum of the image. Two types of microfluidic devices are used to culture bacteria in liquid and agar gel medium, and time-lapsed images are captured. The images obtained are analyzed using FFT, resulting in an increase in high-frequency noise proportional to the time passed. Furthermore, we apply the developed method in the microfluidic antibiotics susceptibility test by recognizing the regional concentration change of the bacteria that are cultured in the antibiotics gradient. Finally, a deep learning-based data regression is performed on the data obtained by the proposed vision-based method for robust reporting of data.

Argentina from MODIS

NASA Technical Reports Server (NTRS)

2002-01-01

This Moderate-resolution Imaging Spectroradiometer (MODIS) image over Argentina was acquired on April 24, 2000, and was produced using a combination of the sensor's 250-m and 500-m resolution 'true color' bands. This image was presented on June 13, 2000 as a GIFt to Argentinian President Fernando de la Rua by NASA Administrator Dan Goldin. Note the Parana River which runs due south from the top of the image before turning east to empty into the Atlantic Ocean. Note the yellowish sediment from the Parana River mixing with the redish sediment from the Uruguay River as it empties into the Rio de la Plata. The water level of the Parana seems high, which could explain the high sediment discharge. A variety of land surface features are visible in this image. To the north, the greenish pixels show forest regions, as well as characteristic clusters of rectangular patterns of agricultural fields. In the lower left of the image, the lighter green pixels show arable regions where there is grazing and farming. (Image courtesy Jacques Descloitres, MODIS Land Group, NASA GSFC)

Spatiotemporal dynamics of similarity-based neural representations of facial identity.

PubMed

Vida, Mark D; Nestor, Adrian; Plaut, David C; Behrmann, Marlene

2017-01-10

Humans' remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level "image-based" and higher level "identity-based" model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise.

Breast MRI at 7 Tesla with a bilateral coil and robust fat suppression.

PubMed

Brown, Ryan; Storey, Pippa; Geppert, Christian; McGorty, KellyAnne; Klautau Leite, Ana Paula; Babb, James; Sodickson, Daniel K; Wiggins, Graham C; Moy, Linda

2014-03-01

To develop a bilateral coil and fat suppressed T1-weighted sequence for 7 Tesla (T) breast MRI. A dual-solenoid coil and three-dimensional (3D) T1w gradient echo sequence with B1+ insensitive fat suppression (FS) were developed. T1w FS image quality was characterized through image uniformity and fat-water contrast measurements in 11 subjects. Signal-to-noise ratio (SNR) and flip angle maps were acquired to assess the coil performance. Bilateral contrast-enhanced and unilateral high resolution (0.6 mm isotropic, 6.5 min acquisition time) imaging highlighted the 7T SNR advantage. Reliable and effective FS and high image quality was observed in all subjects at 7T, indicating that the custom coil and pulse sequence were insensitive to high-field obstacles such as variable tissue loading. 7T and 3T image uniformity was similar (P=0.24), indicating adequate 7T B1+ uniformity. High 7T SNR and fat-water contrast enabled 0.6 mm isotropic imaging and visualization of a high level of fibroglandular tissue detail. 7T T1w FS bilateral breast imaging is feasible with a custom radiofrequency (RF) coil and pulse sequence. Similar image uniformity was achieved at 7T and 3T, despite different RF field behavior and variable coil-tissue interaction due to anatomic differences that might be expected to alter magnetic field patterns. Copyright © 2013 Wiley Periodicals, Inc.

Breast MRI at 7 Tesla with a Bilateral Coil and Robust Fat Suppression

PubMed Central

Brown, Ryan; Storey, Pippa; Geppert, Christian; McGorty, KellyAnne; Leite, Ana Paula Klautau; Babb, James; Sodickson, Daniel K.; Wiggins, Graham C.; Moy, Linda

2013-01-01

Purpose To develop a bilateral coil and optimized fat suppressed T1-weighted sequence for 7T breast MRI. Materials and Methods A dual-solenoid coil and 3D T1w gradient echo sequence with B1+ insensitive fat suppression (FS) were developed for 7T. T1w FS image quality was characterized through image uniformity and fat/water contrast measurements in 11 subjects. Signal-to-noise ratio (SNR) and flip angle maps were acquired to assess the coil performance. Bilateral contrast-enhanced and unilateral high resolution (0.6 mm isotropic, 6.5 min acquisition time) imaging highlighted the 7 T SNR advantage. Results Reliable and effective FS and high image quality was observed in all subjects at 7T, indicating that the custom coil and pulse sequence were insensitive to high-field obstacles such as variable tissue loading. 7T and 3T T1w FS image uniformity was similar (P=0.24), indicating adequate 7T B1+ uniformity. High 7T SNR and fat/water contrast enabled 0.6 mm isotropic imaging and visualization of a high level of fibroglandular tissue detail. Conclusion 7T T1w FS bilateral breast imaging is feasible with a custom RF coil and pulse sequence. Similar image uniformity was achieved at 7T and 3T, despite different RF field behavior and variable coil-tissue interaction due to anatomic differences that might be expected to alter magnetic field patterns. PMID:24123517

Effects of contour enhancement on low-vision preference and visual search.

PubMed

Satgunam, Premnandhini; Woods, Russell L; Luo, Gang; Bronstad, P Matthew; Reynolds, Zachary; Ramachandra, Chaithanya; Mel, Bartlett W; Peli, Eli

2012-09-01

To determine whether image enhancement improves visual search performance and whether enhanced images were also preferred by subjects with vision impairment. Subjects (n = 24) with vision impairment (vision: 20/52 to 20/240) completed visual search and preference tasks for 150 static images that were enhanced to increase object contours' visual saliency. Subjects were divided into two groups and were shown three enhancement levels. Original and medium enhancements were shown to both groups. High enhancement was shown to group 1, and low enhancement was shown to group 2. For search, subjects pointed to an object that matched a search target displayed at the top left of the screen. An "integrated search performance" measure (area under the curve of cumulative correct response rate over search time) quantified performance. For preference, subjects indicated the preferred side when viewing the same image with different enhancement levels on side-by-side high-definition televisions. Contour enhancement did not improve performance in the visual search task. Group 1 subjects significantly (p < 0.001) rejected the High enhancement, and showed no preference for medium enhancement over the original images. Group 2 subjects significantly preferred (p < 0.001) both the medium and the low enhancement levels over original. Contrast sensitivity was correlated with both preference and performance; subjects with worse contrast sensitivity performed worse in the search task (ρ = 0.77, p < 0.001) and preferred more enhancement (ρ = -0.47, p = 0.02). No correlation between visual search performance and enhancement preference was found. However, a small group of subjects (n = 6) in a narrow range of mid-contrast sensitivity performed better with the enhancement, and most (n = 5) also preferred the enhancement. Preferences for image enhancement can be dissociated from search performance in people with vision impairment. Further investigations are needed to study the relationships between preference and performance for a narrow range of mid-contrast sensitivity where a beneficial effect of enhancement may exist.

Tongue Images Classification Based on Constrained High Dispersal Network.

PubMed

Meng, Dan; Cao, Guitao; Duan, Ye; Zhu, Minghua; Tu, Liping; Xu, Dong; Xu, Jiatuo

2017-01-01

Computer aided tongue diagnosis has a great potential to play important roles in traditional Chinese medicine (TCM). However, the majority of the existing tongue image analyses and classification methods are based on the low-level features, which may not provide a holistic view of the tongue. Inspired by deep convolutional neural network (CNN), we propose a novel feature extraction framework called constrained high dispersal neural networks (CHDNet) to extract unbiased features and reduce human labor for tongue diagnosis in TCM. Previous CNN models have mostly focused on learning convolutional filters and adapting weights between them, but these models have two major issues: redundancy and insufficient capability in handling unbalanced sample distribution. We introduce high dispersal and local response normalization operation to address the issue of redundancy. We also add multiscale feature analysis to avoid the problem of sensitivity to deformation. Our proposed CHDNet learns high-level features and provides more classification information during training time, which may result in higher accuracy when predicting testing samples. We tested the proposed method on a set of 267 gastritis patients and a control group of 48 healthy volunteers. Test results show that CHDNet is a promising method in tongue image classification for the TCM study.

Nano-imaging of single cells using STIM

NASA Astrophysics Data System (ADS)

Minqin, Ren; van Kan, J. A.; Bettiol, A. A.; Daina, Lim; Gek, Chan Yee; Huat, Bay Boon; Whitlow, H. J.; Osipowicz, T.; Watt, F.

2007-07-01

Scanning transmission ion microscopy (STIM) is a technique which utilizes the energy loss of high energy (MeV) ions passing through a sample to provide structural images. In this paper, we have successfully demonstrated STIM imaging of single cells at the nano-level using the high resolution capability of the proton beam writing facility at the Centre for Ion Beam Applications, National University of Singapore. MCF-7 breast cancer cells (American Type Culture Collection [ATCC]) were seeded on to silicon nitride windows, backed by a Hamamatsu pin diode acting as a particle detector. A reasonable contrast was obtained using 1 MeV protons and excellent contrast obtained using 1 MeV alpha particles. In a further experiment, nano-STIM was also demonstrated using cells seeded on to the pin diode directly, and high quality nano-STIM images showing the nucleus and multiple nucleoli were extracted before the detector was significantly damaged.

Fabrication of coronagraph masks and laboratory scale star-shade masks: characteristics, defects, and performance

NASA Astrophysics Data System (ADS)

Balasubramanian, Kunjithapatham; Riggs, A. J. Eldorado; Cady, Eric; White, Victor; Yee, Karl; Wilson, Daniel; Echternach, Pierre; Muller, Richard; Mejia Prada, Camilo; Seo, Byoung-Joon; Shi, Fang; Ryan, Daniel; Fregoso, Santos; Metzman, Jacob; Wilson, Robert Casey

2017-09-01

NASA WFIRST mission has planned to include a coronagraph instrument to find and characterize exoplanets. Masks are needed to suppress the host star light to better than 10-8 - 10-9 level contrast over a broad bandwidth to enable the coronagraph mission objectives. Such masks for high contrast coronagraphic imaging require various fabrication technologies to meet a wide range of specifications, including precise shapes, micron scale island features, ultra-low reflectivity regions, uniformity, wave front quality, etc. We present the technologies employed at JPL to produce these pupil plane and image plane coronagraph masks, and lab-scale external occulter masks, highlighting accomplishments from the high contrast imaging testbed (HCIT) at JPL and from the high contrast imaging lab (HCIL) at Princeton University. Inherent systematic and random errors in fabrication and their impact on coronagraph performance are discussed with model predictions and measurements.

Real-time and quantitative isotropic spatial resolution susceptibility imaging for magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Pi, Shiqiang; Liu, Wenzhong; Jiang, Tao

2018-03-01

The magnetic transparency of biological tissue allows the magnetic nanoparticle (MNP) to be a promising functional sensor and contrast agent. The complex susceptibility of MNPs, strongly influenced by particle concentration, excitation magnetic field and their surrounding microenvironment, provides significant implications for biomedical applications. Therefore, magnetic susceptibility imaging of high spatial resolution will give more detailed information during the process of MNP-aided diagnosis and therapy. In this study, we present a novel spatial magnetic susceptibility extraction method for MNPs under a gradient magnetic field, a low-frequency drive magnetic field, and a weak strength high-frequency magnetic field. Based on this novel method, a magnetic particle susceptibility imaging (MPSI) of millimeter-level spatial resolution (<3 mm) was achieved using our homemade imaging system. Corroborated by the experimental results, the MPSI shows real-time (1 s per frame acquisition) and quantitative abilities, and isotropic high resolution.

The Hyper Suprime-Cam software pipeline

DOE PAGES

Bosch, James; Armstrong, Robert; Bickerton, Steven; ...

2017-10-12

Here in this article, we describe the optical imaging data processing pipeline developed for the Subaru Telescope’s Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope’s Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high-level processing steps that generate coadded images and science-ready catalogs as well as low-level detrendingmore » and image characterizations.« less

The Hyper Suprime-Cam software pipeline

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

Bosch, James; Armstrong, Robert; Bickerton, Steven

Here in this article, we describe the optical imaging data processing pipeline developed for the Subaru Telescope’s Hyper Suprime-Cam (HSC) instrument. The HSC Pipeline builds on the prototype pipeline being developed by the Large Synoptic Survey Telescope’s Data Management system, adding customizations for HSC, large-scale processing capabilities, and novel algorithms that have since been reincorporated into the LSST codebase. While designed primarily to reduce HSC Subaru Strategic Program (SSP) data, it is also the recommended pipeline for reducing general-observer HSC data. The HSC pipeline includes high-level processing steps that generate coadded images and science-ready catalogs as well as low-level detrendingmore » and image characterizations.« less

MODIS Views Variations in Cloud Types

NASA Technical Reports Server (NTRS)

2002-01-01

This MODIS image, centered over the Great Lakes region in North America, shows a variety of cloud types. The clouds at the top of the image, colored pink, are cold, high-level snow and ice clouds, while the neon green clouds are lower-level water clouds. Because different cloud types reflect and emit radiant energy differently, scientists can use MODIS' unique data set to measure the sizes of cloud particles and distinguish between water, snow, and ice clouds. This scene was acquired on Feb. 24, 2000, and is a red, green, blue composite of bands 1, 6, and 31 (0.66, 1.6, and 11.0 microns, respectively). Image by Liam Gumley, Space Science and Engineering Center, University of Wisconsin-Madison

Single-cell resolution fluorescence imaging of circadian rhythms detected with a Nipkow spinning disk confocal system.

PubMed

Enoki, Ryosuke; Ono, Daisuke; Hasan, Mazahir T; Honma, Sato; Honma, Ken-Ichi

2012-05-30

Single-point laser scanning confocal imaging produces signals with high spatial resolution in living organisms. However, photo-induced toxicity, bleaching, and focus drift remain challenges, especially when recording over several days for monitoring circadian rhythms. Bioluminescence imaging is a tool widely used for this purpose, and does not cause photo-induced difficulties. However, bioluminescence signals are dimmer than fluorescence signals, and are potentially affected by levels of cofactors, including ATP, O(2), and the substrate, luciferin. Here we describe a novel time-lapse confocal imaging technique to monitor circadian rhythms in living tissues. The imaging system comprises a multipoint scanning Nipkow spinning disk confocal unit and a high-sensitivity EM-CCD camera mounted on an inverted microscope with auto-focusing function. Brain slices of the suprachiasmatic nucleus (SCN), the central circadian clock, were prepared from transgenic mice expressing a clock gene, Period 1 (Per1), and fluorescence reporter protein (Per1::d2EGFP). The SCN slices were cut out together with membrane, flipped over, and transferred to the collagen-coated glass dishes to obtain signals with a high signal-to-noise ratio and to minimize focus drift. The imaging technique and improved culture method enabled us to monitor the circadian rhythm of Per1::d2EGFP from optically confirmed single SCN neurons without noticeable photo-induced effects or focus drift. Using recombinant adeno-associated virus carrying a genetically encoded calcium indicator, we also monitored calcium circadian rhythms at a single-cell level in a large population of SCN neurons. Thus, the Nipkow spinning disk confocal imaging system developed here facilitates long-term visualization of circadian rhythms in living cells. Copyright © 2012 Elsevier B.V. All rights reserved.

Advances in photographic X-ray imaging for solar astronomy

NASA Technical Reports Server (NTRS)

Moses, J. Daniel; Schueller, R.; Waljeski, K.; Davis, John M.

1989-01-01

The technique of obtaining quantitative data from high resolution soft X-ray photographic images produced by grazing incidence optics was successfully developed to a high degree during the Solar Research Sounding Rocket Program and the S-054 X-Ray Spectrographic Telescope Experiment Program on Skylab. Continued use of soft X-ray photographic imaging in sounding rocket flights of the High Resolution Solar Soft X-Ray Imaging Payload has provided opportunities to further develop these techniques. The developments discussed include: (1) The calibration and use of an inexpensive, commercially available microprocessor controlled drum type film processor for photometric film development; (2) The use of Kodak Technical Pan 2415 film and Kodak SO-253 High Speed Holographic film for improved resolution; and (3) The application of a technique described by Cook, Ewing, and Sutton for determining the film characteristics curves from density histograms of the flight film. Although the superior sensitivity, noise level, and linearity of microchannel plate and CCD detectors attracts the development efforts of many groups working in soft X-ray imaging, the high spatial resolution and dynamic range as well as the reliability and ease of application of photographic media assures the continued use of these techniques in solar X-ray astronomy observations.

Characterization study of an intensified complementary metal-oxide-semiconductor active pixel sensor.

PubMed

Griffiths, J A; Chen, D; Turchetta, R; Royle, G J

2011-03-01

An intensified CMOS active pixel sensor (APS) has been constructed for operation in low-light-level applications: a high-gain, fast-light decay image intensifier has been coupled via a fiber optic stud to a prototype "VANILLA" APS, developed by the UK based MI3 consortium. The sensor is capable of high frame rates and sparse readout. This paper presents a study of the performance parameters of the intensified VANILLA APS system over a range of image intensifier gain levels when uniformly illuminated with 520 nm green light. Mean-variance analysis shows the APS saturating around 3050 Digital Units (DU), with the maximum variance increasing with increasing image intensifier gain. The system's quantum efficiency varies in an exponential manner from 260 at an intensifier gain of 7.45 × 10(3) to 1.6 at a gain of 3.93 × 10(1). The usable dynamic range of the system is 60 dB for intensifier gains below 1.8 × 10(3), dropping to around 40 dB at high gains. The conclusion is that the system shows suitability for the desired application.

Characterization study of an intensified complementary metal-oxide-semiconductor active pixel sensor

NASA Astrophysics Data System (ADS)

Griffiths, J. A.; Chen, D.; Turchetta, R.; Royle, G. J.

2011-03-01

An intensified CMOS active pixel sensor (APS) has been constructed for operation in low-light-level applications: a high-gain, fast-light decay image intensifier has been coupled via a fiber optic stud to a prototype "VANILLA" APS, developed by the UK based MI3 consortium. The sensor is capable of high frame rates and sparse readout. This paper presents a study of the performance parameters of the intensified VANILLA APS system over a range of image intensifier gain levels when uniformly illuminated with 520 nm green light. Mean-variance analysis shows the APS saturating around 3050 Digital Units (DU), with the maximum variance increasing with increasing image intensifier gain. The system's quantum efficiency varies in an exponential manner from 260 at an intensifier gain of 7.45 × 103 to 1.6 at a gain of 3.93 × 101. The usable dynamic range of the system is 60 dB for intensifier gains below 1.8 × 103, dropping to around 40 dB at high gains. The conclusion is that the system shows suitability for the desired application.

Interferometric scattering (iSCAT) microscopy: studies of biological membrane dynamics

NASA Astrophysics Data System (ADS)

Reina, Francesco; Galiani, Silvia; Shrestha, Dilip; Sezgin, Erdinc; Lagerholm, B. Christoffer; Cole, Daniel; Kukura, Philipp; Eggeling, Christian

2018-02-01

The study of the organization and dynamics of molecules in model and cellular membranes is an important topic in contemporary biophysics. Imaging and single particle tracking in this particular field, however, proves particularly demanding, as it requires simultaneously high spatio-temporal resolution and high signal-to-noise ratios. A remedy to this challenge might be Interferometric Scattering (iSCAT) microscopy, due to its fast sampling rates, label-free imaging capabilities and, most importantly, tuneable signal level output. Here we report our recent advances in the imaging and molecular tracking on phase-separated model membrane systems and live-cell membranes using this technique.

Molecular Imaging of Conscious, Unrestrained Mice with AwakeSPECT

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

Baba, Justin S; Endres, Christopher; Foss, Catherine

2013-01-01

We have developed a SPECT imaging system, AwakeSPECT, to enable molecular brain imaging of untrained mice that are conscious, unanesthetized, and unrestrained. We accomplished this with head tracking and motion correction techniques. Methods: The capability of the system for motion-corrected imaging was demonstrated with a 99mTc-pertechnetate phantom, 99mTcmethylene diphosphonate bone imaging, and measurement of the binding potential of the dopamine transporter radioligand 123I-ioflupane in mouse brain in the awake and anesthetized (isoflurane) states. Stress induced by imaging in the awake state was assessed through measurement of plasma corticosterone levels. Results: AwakeSPECT provided high-resolution bone images reminiscent of those obtained frommore » CT. The binding potential of 123I-ioflupane in the awake state was on the order of 50% of that obtained with the animal under anesthesia, consistent with previous studies in nonhuman primates. Levels of stress induced were on the order of those seen in other behavioral tasks and imaging studies of awake animals. Conclusion: These results demonstrate the feasibility of SPECT molecular brain imaging of mice in the conscious, unrestrained state and demonstrate the effects of isoflurane anesthesia on radiotracer uptake.« less

Molecular Imaging of Conscious, Unrestrained Mice with AwakeSPECT

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

Baba, Justin S.; Endres, Christopher J.; Foss, Catherine A.

2013-06-01

We have developed a SPECT imaging system, AwakeSPECT, to enable molecular brain imaging of untrained mice that are conscious, unanesthetized, and unrestrained. We accomplished this with head tracking and motion correction techniques. Methods: The capability of the system for motion-corrected imaging was demonstrated with a ^99mTc-pertechnetate phantom, ^99mTc-methylene diphosphonate bone imaging, and measurement of the binding potential of the dopamine transporter radioligand ^123I-ioflupane in mouse brain in the awake and anesthetized (isoflurane) states. Stress induced by imaging in the awake state was assessed through measurement of plasma corticosterone levels. Results: AwakeSPECT provided high-resolution bone images reminiscent of those obtained frommore » CT. The binding potential of ^123I-ioflupane in the awake state was on the order of 50% of that obtained with the animal under anesthesia, consistent with previous studies in nonhuman primates. Levels of stress induced were on the order of those seen in other behavioral tasks and imaging studies of awake animals. Conclusion: These results demonstrate the feasibility of SPECT molecular brain imaging of mice in the conscious, unrestrained state and demonstrate the effects of isoflurane anesthesia on radiotracer uptake.« less

Tendon and ligament imaging

PubMed Central

Hodgson, R J; O'Connor, P J; Grainger, A J

2012-01-01

MRI and ultrasound are now widely used for the assessment of tendon and ligament abnormalities. Healthy tendons and ligaments contain high levels of collagen with a structured orientation, which gives rise to their characteristic normal imaging appearances as well as causing particular imaging artefacts. Changes to ligaments and tendons as a result of disease and injury can be demonstrated using both ultrasound and MRI. These have been validated against surgical and histological findings. Novel imaging techniques are being developed that may improve the ability of MRI and ultrasound to assess tendon and ligament disease. PMID:22553301

Color image processing and vision system for an automated laser paint-stripping system

NASA Astrophysics Data System (ADS)

Hickey, John M., III; Hise, Lawson

1994-10-01

Color image processing in machine vision systems has not gained general acceptance. Most machine vision systems use images that are shades of gray. The Laser Automated Decoating System (LADS) required a vision system which could discriminate between substrates of various colors and textures and paints ranging from semi-gloss grays to high gloss red, white and blue (Air Force Thunderbirds). The changing lighting levels produced by the pulsed CO2 laser mandated a vision system that did not require a constant color temperature lighting for reliable image analysis.

Development of Prior Image-Based, High-Quality, Low-Dose Kilovoltage Cone Beam CT for Use in Adaptive Radiotherapy of Prostate Cancer

DTIC Science & Technology

2011-05-01

for the research in the next year. The aims in the next year include further develop- ment of the prior image- based , narrowly collimated CBCT imaging...further investigation planned for the next year. 5 BODY 1 Research Accomplishments 1.1 Implement narrow beam collimation for CBCT ROI imaging I have...noise level to mimic different mAs used in clinical and research modes of the CBCT system. Based upon experiences with the numerical phantom, I designed

Research on Remote Sensing Image Classification Based on Feature Level Fusion

NASA Astrophysics Data System (ADS)

Yuan, L.; Zhu, G.

2018-04-01

Remote sensing image classification, as an important direction of remote sensing image processing and application, has been widely studied. However, in the process of existing classification algorithms, there still exists the phenomenon of misclassification and missing points, which leads to the final classification accuracy is not high. In this paper, we selected Sentinel-1A and Landsat8 OLI images as data sources, and propose a classification method based on feature level fusion. Compare three kind of feature level fusion algorithms (i.e., Gram-Schmidt spectral sharpening, Principal Component Analysis transform and Brovey transform), and then select the best fused image for the classification experimental. In the classification process, we choose four kinds of image classification algorithms (i.e. Minimum distance, Mahalanobis distance, Support Vector Machine and ISODATA) to do contrast experiment. We use overall classification precision and Kappa coefficient as the classification accuracy evaluation criteria, and the four classification results of fused image are analysed. The experimental results show that the fusion effect of Gram-Schmidt spectral sharpening is better than other methods. In four kinds of classification algorithms, the fused image has the best applicability to Support Vector Machine classification, the overall classification precision is 94.01 % and the Kappa coefficients is 0.91. The fused image with Sentinel-1A and Landsat8 OLI is not only have more spatial information and spectral texture characteristics, but also enhances the distinguishing features of the images. The proposed method is beneficial to improve the accuracy and stability of remote sensing image classification.

The Effect of Shadow Area on Sgm Algorithm and Disparity Map Refinement from High Resolution Satellite Stereo Images

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.

2017-09-01

Semi Global Matching (SGM) algorithm is known as a high performance and reliable stereo matching algorithm in photogrammetry community. However, there are some challenges using this algorithm especially for high resolution satellite stereo images over urban areas and images with shadow areas. As it can be seen, unfortunately the SGM algorithm computes highly noisy disparity values for shadow areas around the tall neighborhood buildings due to mismatching in these lower entropy areas. In this paper, a new method is developed to refine the disparity map in shadow areas. The method is based on the integration of potential of panchromatic and multispectral image data to detect shadow areas in object level. In addition, a RANSAC plane fitting and morphological filtering are employed to refine the disparity map. The results on a stereo pair of GeoEye-1 captured over Qom city in Iran, shows a significant increase in the rate of matched pixels compared to standard SGM algorithm.

Mis-segmentation in voxel-based morphometry due to a signal intensity change in the putamen.

PubMed

Goto, Masami; Abe, Osamu; Miyati, Tosiaki; Aoki, Shigeki; Gomi, Tsutomu; Takeda, Tohoru

2017-12-01

The aims of this study were to demonstrate an association between changes in the signal intensity of the putamen on three-dimensional T1-weighted magnetic resonance images (3D-T1WI) and mis-segmentation, using the voxel-based morphometry (VBM) 8 toolbox. The sagittal 3D-T1WIs of 22 healthy volunteers were obtained for VBM analysis using the 1.5-T MR scanner. We prepared five levels of 3D-T1WI signal intensity (baseline, same level, background level, low level, and high level) in regions of interest containing the putamen. Groups of smoothed, spatially normalized tissue images were compared to the baseline group using a paired t test. The baseline was compared to the other four levels. In all comparisons, significant volume changes were observed around and outside the area that included the signal intensity change. The present study demonstrated an association between a change in the signal intensity of the putamen on 3D-T1WI and changed volume in segmented tissue images.

Values of (99m)Tc-methoxyisobutylisonitrile imaging after first-time large-dose (131)I therapy in treating differentiated thyroid cancer.

PubMed

Pan, Xiaomei; Duan, Dong; Zhu, Yuquan; Pang, Hua; Guan, Lili; Lv, Zhixiang

2016-01-01

The aim of this study is to investigate the use of (99m)Tc-methoxyisobutylisonitrile (MIBI) imaging for evaluating the treatment response of differentiated thyroid cancer (DTC) after the first administration of a high dose of (131)I. Patients with DTC who received (131)I therapy underwent (99m)Tc-MIBI imaging after successive increases in the therapeutic dose of (131)I, and the serum levels of thyroglobulin (Tg) were measured. A total of 191 patients were enrolled in the final analysis, including 65 metastases and/or thyroid remnant-positive patients (22 patients with metastases and 43 patients with thyroid remnants). The sensitivity of (99m)Tc-MIBI imaging for detecting positive cases and thyroid remnants was 56.9% and 39.5%, respectively, which was significantly lower than that of (131)I imaging (92.3% and 100%, respectively, P<0.01 for both). The sensitivity of (99m)Tc-MIBI imaging for detecting metastases was 90.9%, which was slightly higher than that of (131)I imaging (77.3%, P>0.05). The Tg levels in the positive group were significantly higher than that in the negative group (P<0.01). In addition, the Tg levels in the (99m)Tc-MIBI(+)/(131)I(-) group were significantly higher than that in the (131)I(+)/(99m)Tc-MIBI group (P<0.05). After the first (131)I therapy, although (99m)Tc-MIBI imaging was able to detect the existence of metastatic lesions in patients with DTC better, its assessment for the removal efficiency of thyroid remnants was unsatisfactory. The results of (99m)Tc-MIBI imaging showed good correlations with the Tg level.

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.

High-speed laser photoacoustic imaging system combined with a digital ultrasonic imaging platform

NASA Astrophysics Data System (ADS)

Zeng, Lvming; Liu, Guodong; Ji, Xuanrong; Ren, Zhong; Huang, Zhen

2009-07-01

As a new field of combined ultrasound/photoacoustic imaging in biomedical photonics research, we present and demonstrate a high-speed laser photoacoustic imaging system combined with digital ultrasound imaging platform. In the prototype system, a new B-mode digital ultrasonic imaging system is modified as the hardware platform with 384 vertical transducer elements. The centre resonance frequency of the piezoelectric transducer is 5.0 MHz with greater than 70% pulse-echo -6dB fractional bandwidth. The modular instrument of PCI-6541 is used as the hardware control centre of the testing system, which features 32 high-speed channels to build low-skew and multi-channel system. The digital photoacoustic data is transported into computer for subsequent reconstruction at 25 MHz clock frequency. Meantime, the software system for controlling and analyzing is correspondingly explored with LabVIEW language on virtual instrument platform. In the breast tissue experiment, the reconstructed image agrees well with the original sample, and the spatial resolution of the system can reach 0.2 mm with multi-element synthetic aperture focusing technique. Therefore, the system and method may have a significant value in improving early detecting level of cancer in the breast and other organs.

In-vivo and in-situ detection of atherosclerotic plaques using full-range complex-conjugate-free spectral domain optical coherence tomography in the murine carotid

NASA Astrophysics Data System (ADS)

Huang, Yong; Wicks, Robert; Zhang, Kang; Zhao, Mingtao; Tyler, Betty M.; Hwang, Lee; Pradilla, Gustavo; Kang, Jin U.

2013-03-01

Carotid endarterectomy is a common vascular surgical procedure which may help prevent patients' risk of having a stroke. A high resolution real-time imaging technique that can detect the position and size of vascular plaques would provide great value to reduce the risk level and increase the surgical outcome. Optical coherence tomography (OCT), as a high resolution high speed noninvasive imaging technique, was evaluated in this study. Twenty-four 24-week old apolipoprotein E-deficient (ApoE-/-) mice were divided into three groups with 8 in each. One served as the control group fed with normal diet. One served as the study group fed with high-fat diet to induce atherosclerosis. The last served as the treatment group fed with both high-fat diet and medicine to treat atherosclerosis. Full-range, complex-conjugate-free spectral-domain OCT was used to image the mouse aorta near the neck area in-vivo with aorta exposed to the imaging head through surgical procedure. 2D and 3D images of the area of interest were presented real-time through graphics processing unit accelerated algorithm. In-situ imaging of all the mice after perfusion were performed again to validate the invivo detection result and to show potential capability of OCT if combined with surgical saline flush. Later all the imaged arteries were stained with H and E to perform histology analysis. Preliminary results confirmed the accuracy and fast imaging speed of OCT imaging technique in determining atherosclerosis.

Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

PubMed

Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

2018-01-01

The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

Imaging the Parasinus Region with a Third-Generation Dual-Source CT and the Effect of Tin Filtration on Image Quality and Radiation Dose.

PubMed

Lell, M M; May, M S; Brand, M; Eller, A; Buder, T; Hofmann, E; Uder, M; Wuest, W

2015-07-01

CT is the imaging technique of choice in the evaluation of midface trauma or inflammatory disease. We performed a systematic evaluation of scan protocols to optimize image quality and radiation exposure on third-generation dual-source CT. CT protocols with different tube voltage (70-150 kV), current (25-300 reference mAs), prefiltration, pitch value, and rotation time were systematically evaluated. All images were reconstructed with iterative reconstruction (Advanced Modeled Iterative Reconstruction, level 2). To individually compare results with otherwise identical factors, we obtained all scans on a frozen human head. Conebeam CT was performed for image quality and dose comparison with multidetector row CT. Delineation of important anatomic structures and incidental pathologic conditions in the cadaver head was evaluated. One hundred kilovolts with tin prefiltration demonstrated the best compromise between dose and image quality. The most dose-effective combination for trauma imaging was Sn100 kV/250 mAs (volume CT dose index, 2.02 mGy), and for preoperative sinus surgery planning, Sn100 kV/150 mAs (volume CT dose index, 1.22 mGy). "Sn" indicates an additional prefiltration of the x-ray beam with a tin filter to constrict the energy spectrum. Exclusion of sinonasal disease was possible with even a lower dose by using Sn100 kV/25 mAs (volume CT dose index, 0.2 mGy). High image quality at very low dose levels can be achieved by using a Sn100-kV protocol with iterative reconstruction. The effective dose is comparable with that of conventional radiography, and the high image quality at even lower radiation exposure favors multidetector row CT over conebeam CT. © 2015 by American Journal of Neuroradiology.

Effective low-level processing for interferometric image enhancement

NASA Astrophysics Data System (ADS)

Joo, Wonjong; Cha, Soyoung S.

1995-09-01

The hybrid operation of digital image processing and a knowledge-based AI system has been recognized as a desirable approach of the automated evaluation of noise-ridden interferogram. Early noise/data reduction before phase is extracted is essential for the success of the knowledge- based processing. In this paper, new concepts of effective, interactive low-level processing operators: that is, a background-matched filter and a directional-smoothing filter, are developed and tested with transonic aerodynamic interferograms. The results indicate that these new operators have promising advantages in noise/data reduction over the conventional ones, leading success of the high-level, intelligent phase extraction.

Metallic artefact reduction with monoenergetic dual-energy CT: systematic ex vivo evaluation of posterior spinal fusion implants from various vendors and different spine levels.

PubMed

Guggenberger, R; Winklhofer, S; Osterhoff, G; Wanner, G A; Fortunati, M; Andreisek, G; Alkadhi, H; Stolzmann, P

2012-11-01

To evaluate optimal monoenergetic dual-energy computed tomography (DECT) settings for artefact reduction of posterior spinal fusion implants of various vendors and spine levels. Posterior spinal fusion implants of five vendors for cervical, thoracic and lumbar spine were examined ex vivo with single-energy (SE) CT (120 kVp) and DECT (140/100 kVp). Extrapolated monoenergetic DECT images at 64, 69, 88, 105 keV and individually adjusted monoenergy for optimised image quality (OPTkeV) were generated. Two independent radiologists assessed quantitative and qualitative image parameters for each device and spine level. Inter-reader agreements of quantitative and qualitative parameters were high (ICC = 0.81-1.00, κ = 0.54-0.77). HU values of spinal fusion implants were significantly different among vendors (P < 0.001), spine levels (P < 0.01) and among SECT, monoenergetic DECT of 64, 69, 88, 105 keV and OPTkeV (P < 0.01). Image quality was significantly (P < 0.001) different between datasets and improved with higher monoenergies of DECT compared with SECT (V = 0.58, P < 0.001). Artefacts decreased significantly (V = 0.51, P < 0.001) at higher monoenergies. OPTkeV values ranged from 123-141 keV. OPTkeV according to vendor and spine level are presented herein. Monoenergetic DECT provides significantly better image quality and less metallic artefacts from implants than SECT. Use of individual keV values for vendor and spine level is recommended. • Artefacts pose problems for CT following posterior spinal fusion implants. • CT images are interpreted better with monoenergetic extrapolation using dual-energy (DE) CT. • DECT extrapolation improves image quality and reduces metallic artefacts over SECT. • There were considerable differences in monoenergy values among vendors and spine levels. • Use of individualised monoenergy values is indicated for different metallic hardware devices.

An Off-Axis Four-Quadrant Phase Mask (FQPM) Coronagraph for Palomar: High-Contrast Near Bright Stars Imager

NASA Technical Reports Server (NTRS)

Haguenauer, Pierre; Serabyn, Eugene; Bloemhof, Eric E.; Troy, Mitchell; Wallace, James K.; Koresko, Chris D.; Mennesson, Bertrand

2005-01-01

Direct detection of planets around nearby stars requires the development of high-contrast imaging techniques because of the high difference between their respective fluxes. This led us to test a new coronagraphic approach based on the use of phase mask instead of dark occulting ones. Combined with high-level wavefront correction on an unobscured off-axis section of a large telescope, this method allows imaging very close to the star. Calculations indicate that for a given ground-based on-axis telescope, use of such an off-axis coronagraph provides a near-neighbor detection capability superior to that of a traditional coronagraph utilizing the full telescope aperture. Setting up a laboratory experiment working in near infrared allowed us to demonstrate the principle of the method, and a rejection of 2000:1 has already been achieved.

Imaging of idle breast implants with ultrasound-strain elastography- A first experimental study to establish criteria for accurate imaging of idle implants via ultrasound-strain elastography.

PubMed

Kuehlmann, Britta; Prantl, Lukas; Michael Jung, Ernst

2016-01-01

To investigate whether there are fundamental sonographic and elastographic criteria to precisely assess different surfaces and fillings of idle breast implants and to determine their most distinctive parameters. This was a comparative study of different unused breast implant materials, neighter in animals nor in humans. This knowledge should be transferred in vivo to develop an objective measurement tool. Nine idle breast implants-silicone and polyurethane (PU)-were examined in an experimental study by using ultrasound B-mode with tissue harmonic imaging (THI), speckle reduction imaging (SRI, level 0-4), cross-beam (CB, low, medium, high), photopic and the colour coded ultrasound-strain elastography with a multifrequency probe (9-15 MHz).Using a standardised protocol the implants' centre as well as the edge were analysed by one experienced examiner. Two independent readers performed analysis and evaluation. For image interpretation a score was created (score 0:inadequate image, score 5:best image quality). The highest score result for the centre was achieved by using ultrasound with B-mode in addition with CB level medium, SRI level 2, THI and photopic (mean:3.22±SD:1.56), but without any statistic significant difference (t-value = 0.71). With elastography the implants' edge in general was represented without disruptive artefacts (3.89±0.60) with statistic significant difference (t-value = 5.29). Implants filled with inner cohesive silicone gel II° showed best imaging conditions for their centre via ultrasound (5±0) as well as for their edge via elastography (4.50±0.71). Ultrasound-strain elastography and high resolution ultrasound represent a valuable measurement tool to evaluate different properties of idle breast implants. These modified ultrasound examinations could be an additional help for clinical investigations and be correlated with Baker's Classification.

Digital readout for image converter cameras

NASA Astrophysics Data System (ADS)

Honour, Joseph

1991-04-01

There is an increasing need for fast and reliable analysis of recorded sequences from image converter cameras so that experimental information can be readily evaluated without recourse to more time consuming photographic procedures. A digital readout system has been developed using a randomly triggerable high resolution CCD camera, the output of which is suitable for use with IBM AT compatible PC. Within half a second from receipt of trigger pulse, the frame reformatter displays the image and transfer to storage media can be readily achieved via the PC and dedicated software. Two software programmes offer different levels of image manipulation which includes enhancement routines and parameter calculations with accuracy down to pixel levels. Hard copy prints can be acquired using a specially adapted Polaroid printer, outputs for laser and video printer extend the overall versatility of the system.

Multi-Sensor Fusion of Infrared and Electro-Optic Signals for High Resolution Night Images

PubMed Central

Huang, Xiaopeng; Netravali, Ravi; Man, Hong; Lawrence, Victor

2012-01-01

Electro-optic (EO) image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR) image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge) from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF) proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1) inverse filter-based IR image transformation; (2) EO image edge detection; (3) registration; and (4) blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available. PMID:23112602

Multi-sensor fusion of infrared and electro-optic signals for high resolution night images.

PubMed

Huang, Xiaopeng; Netravali, Ravi; Man, Hong; Lawrence, Victor

2012-01-01

Electro-optic (EO) image sensors exhibit the properties of high resolution and low noise level at daytime, but they do not work in dark environments. Infrared (IR) image sensors exhibit poor resolution and cannot separate objects with similar temperature. Therefore, we propose a novel framework of IR image enhancement based on the information (e.g., edge) from EO images, which improves the resolution of IR images and helps us distinguish objects at night. Our framework superimposing/blending the edges of the EO image onto the corresponding transformed IR image improves their resolution. In this framework, we adopt the theoretical point spread function (PSF) proposed by Hardie et al. for the IR image, which has the modulation transfer function (MTF) of a uniform detector array and the incoherent optical transfer function (OTF) of diffraction-limited optics. In addition, we design an inverse filter for the proposed PSF and use it for the IR image transformation. The framework requires four main steps: (1) inverse filter-based IR image transformation; (2) EO image edge detection; (3) registration; and (4) blending/superimposing of the obtained image pair. Simulation results show both blended and superimposed IR images, and demonstrate that blended IR images have better quality over the superimposed images. Additionally, based on the same steps, simulation result shows a blended IR image of better quality when only the original IR image is available.

GPU accelerated edge-region based level set evolution constrained by 2D gray-scale histogram.

PubMed

Balla-Arabé, Souleymane; Gao, Xinbo; Wang, Bin

2013-07-01

Due to its intrinsic nature which allows to easily handle complex shapes and topological changes, the level set method (LSM) has been widely used in image segmentation. Nevertheless, LSM is computationally expensive, which limits its applications in real-time systems. For this purpose, we propose a new level set algorithm, which uses simultaneously edge, region, and 2D histogram information in order to efficiently segment objects of interest in a given scene. The computational complexity of the proposed LSM is greatly reduced by using the highly parallelizable lattice Boltzmann method (LBM) with a body force to solve the level set equation (LSE). The body force is the link with image data and is defined from the proposed LSE. The proposed LSM is then implemented using an NVIDIA graphics processing units to fully take advantage of the LBM local nature. The new algorithm is effective, robust against noise, independent to the initial contour, fast, and highly parallelizable. The edge and region information enable to detect objects with and without edges, and the 2D histogram information enable the effectiveness of the method in a noisy environment. Experimental results on synthetic and real images demonstrate subjectively and objectively the performance of the proposed method.