Dual-Energy CT: New Horizon in Medical Imaging

PubMed Central

Goo, Jin Mo

2017-01-01

Dual-energy CT has remained underutilized over the past decade probably due to a cumbersome workflow issue and current technical limitations. Clinical radiologists should be made aware of the potential clinical benefits of dual-energy CT over single-energy CT. To accomplish this aim, the basic principle, current acquisition methods with advantages and disadvantages, and various material-specific imaging methods as clinical applications of dual-energy CT should be addressed in detail. Current dual-energy CT acquisition methods include dual tubes with or without beam filtration, rapid voltage switching, dual-layer detector, split filter technique, and sequential scanning. Dual-energy material-specific imaging methods include virtual monoenergetic or monochromatic imaging, effective atomic number map, virtual non-contrast or unenhanced imaging, virtual non-calcium imaging, iodine map, inhaled xenon map, uric acid imaging, automatic bone removal, and lung vessels analysis. In this review, we focus on dual-energy CT imaging including related issues of radiation exposure to patients, scanning and post-processing options, and potential clinical benefits mainly to improve the understanding of clinical radiologists and thus, expand the clinical use of dual-energy CT; in addition, we briefly describe the current technical limitations of dual-energy CT and the current developments of photon-counting detector. PMID:28670151

Method for non-referential defect characterization using fractal encoding and active contours

DOEpatents

Gleason, Shaun S [Knoxville, TN; Sari-Sarraf, Hamed [Lubbock, TX

2007-05-15

A method for identification of anomalous structures, such as defects, includes the steps of providing a digital image and applying fractal encoding to identify a location of at least one anomalous portion of the image. The method does not require a reference image to identify the location of the anomalous portion. The method can further include the step of initializing an active contour based on the location information obtained from the fractal encoding step and deforming an active contour to enhance the boundary delineation of the anomalous portion.

Single-Transducer, Ultrasonic Imaging Method for High-Temperature Structural Materials Eliminates the Effect of Thickness Variation in the Image

NASA Technical Reports Server (NTRS)

Roth, Don J.

1998-01-01

NASA Lewis Research Center's Life Prediction Branch, in partnership with Sonix, Inc., and Cleveland State University, recently advanced the development of, refined, and commercialized an advanced nondestructive evaluation (NDE) inspection method entitled the Single Transducer Thickness-Independent Ultrasonic Imaging Method. Selected by R&D Magazine as one of the 100 most technologically significant new products of 1996, the method uses a single transducer to eliminate the superimposing effects of thickness variation in the ultrasonic images of materials. As a result, any variation seen in the image is due solely to microstructural variation. This nondestructive method precisely and accurately characterizes material gradients (pore fraction, density, or chemical) that affect the uniformity of a material's physical performance (mechanical, thermal, or electrical). Advantages of the method over conventional ultrasonic imaging include (1) elimination of machining costs (for precision thickness control) during the quality control stages of material processing and development and (2) elimination of labor costs and subjectivity involved in further image processing and image interpretation. At NASA Lewis, the method has been used primarily for accurate inspections of high temperature structural materials including monolithic ceramics, metal matrix composites, and polymer matrix composites. Data were published this year for platelike samples, and current research is focusing on applying the method to tubular components. The initial publicity regarding the development of the method generated 150 requests for further information from a wide variety of institutions and individuals including the Federal Bureau of Investigation (FBI), Lockheed Martin Corporation, Rockwell International, Hewlett Packard Company, and Procter & Gamble Company. In addition, NASA has been solicited by the 3M Company and Allison Abrasives to use this method to inspect composite materials that are manufactured by these companies.

Remote Sensing Image Quality Assessment Experiment with Post-Processing

NASA Astrophysics Data System (ADS)

Jiang, W.; Chen, S.; Wang, X.; Huang, Q.; Shi, H.; Man, Y.

2018-04-01

This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compression with different compression ratio and image post-processing with different core. Image quality assessment method used is just noticeable difference (JND) subject assessment based on ISO20462, through subject assessment of the gathered and processing images, the influence of different imaging parameters and post-processing to image quality can be found. The six JND subject assessment experimental data can be validated each other. Main conclusions include: image post-processing can improve image quality; image post-processing can improve image quality even with lossy compression, image quality with higher compression ratio improves less than lower ratio; with our image post-processing method, image quality is better, when camera MTF being within a small range.

Fast neutron imaging device and method

DOEpatents

Popov, Vladimir; Degtiarenko, Pavel; Musatov, Igor V.

2014-02-11

A fast neutron imaging apparatus and method of constructing fast neutron radiography images, the apparatus including a neutron source and a detector that provides event-by-event acquisition of position and energy deposition, and optionally timing and pulse shape for each individual neutron event detected by the detector. The method for constructing fast neutron radiography images utilizes the apparatus of the invention.

A Comparison of Ultrasound Tomography Methods in Circular Geometry

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

Leach, R R; Azevedo, S G; Berryman, J G

2002-01-24

Extremely high quality data was acquired using an experimental ultrasound scanner developed at Lawrence Livermore National Laboratory using a 2D ring geometry with up to 720 transmitter/receiver transducer positions. This unique geometry allows reflection and transmission modes and transmission imaging and quantification of a 3D volume using 2D slice data. Standard image reconstruction methods were applied to the data including straight-ray filtered back projection, reflection tomography, and diffraction tomography. Newer approaches were also tested such as full wave, full wave adjoint method, bent-ray filtered back projection, and full-aperture tomography. A variety of data sets were collected including a formalin-fixed humanmore » breast tissue sample, a commercial ultrasound complex breast phantom, and cylindrical objects with and without inclusions. The resulting reconstruction quality of the images ranges from poor to excellent. The method and results of this study are described including like-data reconstructions produced by different algorithms with side-by-side image comparisons. Comparisons to medical B-scan and x-ray CT scan images are also shown. Reconstruction methods with respect to image quality using resolution, noise, and quantitative accuracy, and computational efficiency metrics will also be discussed.« less

Method and system for the diagnosis of disease using retinal image content and an archive of diagnosed human patient data

DOEpatents

Tobin, Kenneth W; Karnowski, Thomas P; Chaum, Edward

2013-08-06

A method for diagnosing diseases having retinal manifestations including retinal pathologies includes the steps of providing a CBIR system including an archive of stored digital retinal photography images and diagnosed patient data corresponding to the retinal photography images, the stored images each indexed in a CBIR database using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the stored images. A query image of the retina of a patient is obtained. Using image processing, regions or structures in the query image are identified. The regions or structures are then described using the plurality of feature vectors. At least one relevant stored image from the archive based on similarity to the regions or structures is retrieved, and an eye disease or a disease having retinal manifestations in the patient is diagnosed based on the diagnosed patient data associated with the relevant stored image(s).

Systems and Methods for Automated Water Detection Using Visible Sensors

NASA Technical Reports Server (NTRS)

Rankin, Arturo L. (Inventor); Matthies, Larry H. (Inventor); Bellutta, Paolo (Inventor)

2016-01-01

Systems and methods are disclosed that include automated machine vision that can utilize images of scenes captured by a 3D imaging system configured to image light within the visible light spectrum to detect water. One embodiment includes autonomously detecting water bodies within a scene including capturing at least one 3D image of a scene using a sensor system configured to detect visible light and to measure distance from points within the scene to the sensor system, and detecting water within the scene using a processor configured to detect regions within each of the at least one 3D images that possess at least one characteristic indicative of the presence of water.

Assessment methods for the evaluation of vitiligo.

PubMed

Alghamdi, K M; Kumar, A; Taïeb, A; Ezzedine, K

2012-12-01

There is no standardized method for assessing vitiligo. In this article, we review the literature from 1981 to 2011 on different vitiligo assessment methods. We aim to classify the techniques available for vitiligo assessment as subjective, semi-objective or objective; microscopic or macroscopic; and as based on morphometry or colorimetry. Macroscopic morphological measurements include visual assessment, photography in natural or ultraviolet light, photography with computerized image analysis and tristimulus colorimetry or spectrophotometry. Non-invasive micromorphological methods include confocal laser microscopy (CLM). Subjective methods include clinical evaluation by a dermatologist and a vitiligo disease activity score. Semi-objective methods include the Vitiligo Area Scoring Index (VASI) and point-counting methods. Objective methods include software-based image analysis, tristimulus colorimetry, spectrophotometry and CLM. Morphometry is the measurement of the vitiliginous surface area, whereas colorimetry quantitatively analyses skin colour changes caused by erythema or pigment. Most methods involve morphometry, except for the chromameter method, which assesses colorimetry. Some image analysis software programs can assess both morphometry and colorimetry. The details of these programs (Corel Draw, Image Pro Plus, AutoCad and Photoshop) are discussed in the review. Reflectance confocal microscopy provides real-time images and has great potential for the non-invasive assessment of pigmentary lesions. In conclusion, there is no single best method for assessing vitiligo. This review revealed that VASI, the rule of nine and Wood's lamp are likely to be the best techniques available for assessing the degree of pigmentary lesions and measuring the extent and progression of vitiligo in the clinic and in clinical trials. © 2012 The Authors. Journal of the European Academy of Dermatology and Venereology © 2012 European Academy of Dermatology and Venereology.

Imaging resolution and properties analysis of super resolution microscopy with parallel detection under different noise, detector and image restoration conditions

NASA Astrophysics Data System (ADS)

Yu, Zhongzhi; Liu, Shaocong; Sun, Shiyi; Kuang, Cuifang; Liu, Xu

2018-06-01

Parallel detection, which can use the additional information of a pinhole plane image taken at every excitation scan position, could be an efficient method to enhance the resolution of a confocal laser scanning microscope. In this paper, we discuss images obtained under different conditions and using different image restoration methods with parallel detection to quantitatively compare the imaging quality. The conditions include different noise levels and different detector array settings. The image restoration methods include linear deconvolution and pixel reassignment with Richard-Lucy deconvolution and with maximum-likelihood estimation deconvolution. The results show that the linear deconvolution share properties such as high-efficiency and the best performance under all different conditions, and is therefore expected to be of use for future biomedical routine research.

Light-leaking region segmentation of FOG fiber based on quality evaluation of infrared image

NASA Astrophysics Data System (ADS)

Liu, Haoting; Wang, Wei; Gao, Feng; Shan, Lianjie; Ma, Yuzhou; Ge, Wenqian

2014-07-01

To improve the assembly reliability of Fiber Optic Gyroscope (FOG), a light leakage detection system and method is developed. First, an agile movement control platform is designed to implement the pose control of FOG optical path component in 6 Degrees of Freedom (DOF). Second, an infrared camera is employed to capture the working state images of corresponding fibers in optical path component after the manual assembly of FOG; therefore the entire light transmission process of key sections in light-path can be recorded. Third, an image quality evaluation based region segmentation method is developed for the light leakage images. In contrast to the traditional methods, the image quality metrics, including the region contrast, the edge blur, and the image noise level, are firstly considered to distinguish the image characters of infrared image; then the robust segmentation algorithms, including graph cut and flood fill, are all developed for region segmentation according to the specific image quality. Finally, after the image segmentation of light leakage region, the typical light-leaking type, such as the point defect, the wedge defect, and the surface defect can be identified. By using the image quality based method, the applicability of our proposed system can be improved dramatically. Many experiment results have proved the validity and effectiveness of this method.

A laboratory demonstration of high-resolution hard X-ray and gamma-ray imaging using Fourier-transform techniques

NASA Technical Reports Server (NTRS)

Palmer, David; Prince, Thomas A.

1987-01-01

A laboratory imaging system has been developed to study the use of Fourier-transform techniques in high-resolution hard X-ray and gamma-ray imaging, with particular emphasis on possible applications to high-energy astronomy. Considerations for the design of a Fourier-transform imager and the instrumentation used in the laboratory studies is described. Several analysis methods for image reconstruction are discussed including the CLEAN algorithm and maximum entropy methods. Images obtained using these methods are presented.

A new approach for reducing beam hardening artifacts in polychromatic X-ray computed tomography using more accurate prior image.

PubMed

Wang, Hui; Xu, Yanan; Shi, Hongli

2018-03-15

Metal artifacts severely degrade CT image quality in clinical diagnosis, which are difficult to removed, especially for the beam hardening artifacts. The metal artifact reduction (MAR) based on prior images are the most frequently-used methods. However, there exists a lot misclassification in most prior images caused by absence of prior information such as spectrum distribution of X-ray beam source, especially when multiple or big metal are included. This work aims is to identify a more accurate prior image to improve image quality. The proposed method includes four steps. First, the metal image is segmented by thresholding an initial image, where the metal traces are identified in the initial projection data using the forward projection of the metal image. Second, the accurate absorbent model of certain metal image is calculated according to the spectrum distribution of certain X-ray beam source and energy-dependent attenuation coefficients of metal. Third, a new metal image is reconstructed by the general analytical reconstruction algorithm such as filtered back projection (FPB). The prior image is obtained by segmenting the difference image between the initial image and the new metal image into air, tissue and bone. Fourth, the initial projection data are normalized by dividing the projection data of prior image pixel to pixel. The final corrected image is obtained by interpolation, denormalization and reconstruction. Several clinical images with dental fillings and knee prostheses were used to evaluate the proposed algorithm and normalized metal artifact reduction (NMAR) and linear interpolation (LI) method. The results demonstrate the artifacts were reduced efficiently by the proposed method. The proposed method could obtain an exact prior image using the prior information about X-ray beam source and energy-dependent attenuation coefficients of metal. As a result, better performance of reducing beam hardening artifacts can be achieved. Moreover, the process of the proposed method is rather simple and little extra calculation burden is necessary. It has superiorities over other algorithms when include multiple and/or big implants.

An efficient mosaic algorithm considering seasonal variation: application to KOMPSAT-2 satellite images.

PubMed

Choi, Jaewon; Jung, Hyung-Sup; Yun, Sang-Ho

2015-03-09

As the aerospace industry grows, images obtained from Earth observation satellites have been successfully used in various fields. Specifically, the demand for a high-resolution (HR) optical images is gradually increasing, and hence the generation of a high-quality mosaic image is being magnified as an interesting issue. In this paper, we have proposed an efficient mosaic algorithm for HR optical images that are significantly different due to seasonal change. The algorithm includes main steps such as: (1) seamline extraction from gradient magnitude and seam images; (2) histogram matching; and (3) image feathering. Eleven Kompsat-2 images characterized by seasonal variations are used for the performance validation of the proposed method. The results of the performance test show that the proposed method effectively mosaics Kompsat-2 adjacent images including severe seasonal changes. Moreover, the results reveal that the proposed method is applicable to HR optic images such as GeoEye, IKONOS, QuickBird, RapidEye, SPOT, WorldView, etc.

Direct-to-digital holography reduction of reference hologram noise and fourier space smearing

DOEpatents

Voelkl, Edgar

2006-06-27

Systems and methods are described for reduction of reference hologram noise and reduction of Fourier space smearing, especially in the context of direct-to-digital holography (off-axis interferometry). A method of reducing reference hologram noise includes: recording a plurality of reference holograms; processing the plurality of reference holograms into a corresponding plurality of reference image waves; and transforming the corresponding plurality of reference image waves into a reduced noise reference image wave. A method of reducing smearing in Fourier space includes: recording a plurality of reference holograms; processing the plurality of reference holograms into a corresponding plurality of reference complex image waves; transforming the corresponding plurality of reference image waves into a reduced noise reference complex image wave; recording a hologram of an object; processing the hologram of the object into an object complex image wave; and dividing the complex image wave of the object by the reduced noise reference complex image wave to obtain a reduced smearing object complex image wave.

Simultaneous acquisition of differing image types

DOEpatents

Demos, Stavros G

2012-10-09

A system in one embodiment includes an image forming device for forming an image from an area of interest containing different image components; an illumination device for illuminating the area of interest with light containing multiple components; at least one light source coupled to the illumination device, the at least one light source providing light to the illumination device containing different components, each component having distinct spectral characteristics and relative intensity; an image analyzer coupled to the image forming device, the image analyzer decomposing the image formed by the image forming device into multiple component parts based on type of imaging; and multiple image capture devices, each image capture device receiving one of the component parts of the image. A method in one embodiment includes receiving an image from an image forming device; decomposing the image formed by the image forming device into multiple component parts based on type of imaging; receiving the component parts of the image; and outputting image information based on the component parts of the image. Additional systems and methods are presented.

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

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

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

Imaging Strategies for Tissue Engineering Applications

PubMed Central

Nam, Seung Yun; Ricles, Laura M.; Suggs, Laura J.

2015-01-01

Tissue engineering has evolved with multifaceted research being conducted using advanced technologies, and it is progressing toward clinical applications. As tissue engineering technology significantly advances, it proceeds toward increasing sophistication, including nanoscale strategies for material construction and synergetic methods for combining with cells, growth factors, or other macromolecules. Therefore, to assess advanced tissue-engineered constructs, tissue engineers need versatile imaging methods capable of monitoring not only morphological but also functional and molecular information. However, there is no single imaging modality that is suitable for all tissue-engineered constructs. Each imaging method has its own range of applications and provides information based on the specific properties of the imaging technique. Therefore, according to the requirements of the tissue engineering studies, the most appropriate tool should be selected among a variety of imaging modalities. The goal of this review article is to describe available biomedical imaging methods to assess tissue engineering applications and to provide tissue engineers with criteria and insights for determining the best imaging strategies. Commonly used biomedical imaging modalities, including X-ray and computed tomography, positron emission tomography and single photon emission computed tomography, magnetic resonance imaging, ultrasound imaging, optical imaging, and emerging techniques and multimodal imaging, will be discussed, focusing on the latest trends of their applications in recent tissue engineering studies. PMID:25012069

Passive Fully Polarimetric W-Band Millimeter-Wave Imaging

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

Bernacki, Bruce E.; Kelly, James F.; Sheen, David M.

2012-04-01

We present the theory, design, and experimental results obtained from a scanning passive W-band fully polarimetric imager. Passive millimeter-wave imaging offers persistent day/nighttime imaging and the ability to penetrate dust, clouds and other obscurants, including clothing and dry soil. The single-pixel scanning imager includes both far-field and near-field fore-optics for investigation of polarization phenomena. Using both fore-optics, a variety of scenes including natural and man-made objects was imaged and these results are presented showing the utility of polarimetric imaging for anomaly detection. Analysis includes conventional Stokes-parameter based approaches as well as multivariate image analysis methods.

Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

PubMed

Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

2015-06-01

The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

Systems and methods for detecting an image of an object by use of an X-ray beam having a polychromatic distribution

DOEpatents

Parham, Christopher; Zhong, Zhong; Pisano, Etta; Connor, Dean; Chapman, Leroy D.

2010-06-22

Systems and methods for detecting an image of an object using an X-ray beam having a polychromatic energy distribution are disclosed. According to one aspect, a method can include detecting an image of an object. The method can include generating a first X-ray beam having a polychromatic energy distribution. Further, the method can include positioning a single monochromator crystal in a predetermined position to directly intercept the first X-ray beam such that a second X-ray beam having a predetermined energy level is produced. Further, an object can be positioned in the path of the second X-ray beam for transmission of the second X-ray beam through the object and emission from the object as a transmitted X-ray beam. The transmitted X-ray beam can be directed at an angle of incidence upon a crystal analyzer. Further, an image of the object can be detected from a beam diffracted from the analyzer crystal.

System and method for controlling a combustor assembly

DOEpatents

York, William David; Ziminsky, Willy Steve; Johnson, Thomas Edward; Stevenson, Christian Xavier

2013-03-05

A system and method for controlling a combustor assembly are disclosed. The system includes a combustor assembly. The combustor assembly includes a combustor and a fuel nozzle assembly. The combustor includes a casing. The fuel nozzle assembly is positioned at least partially within the casing and includes a fuel nozzle. The fuel nozzle assembly further defines a head end. The system further includes a viewing device configured for capturing an image of at least a portion of the head end, and a processor communicatively coupled to the viewing device, the processor configured to compare the image to a standard image for the head end.

An atlas-based multimodal registration method for 2D images with discrepancy structures.

PubMed

Lv, Wenchao; Chen, Houjin; Peng, Yahui; Li, Yanfeng; Li, Jupeng

2018-06-04

An atlas-based multimodal registration method for 2-dimension images with discrepancy structures was proposed in this paper. Atlas was utilized for complementing the discrepancy structure information in multimodal medical images. The scheme includes three steps: floating image to atlas registration, atlas to reference image registration, and field-based deformation. To evaluate the performance, a frame model, a brain model, and clinical images were employed in registration experiments. We measured the registration performance by the squared sum of intensity differences. Results indicate that this method is robust and performs better than the direct registration for multimodal images with discrepancy structures. We conclude that the proposed method is suitable for multimodal images with discrepancy structures. Graphical Abstract An Atlas-based multimodal registration method schematic diagram.

Methods of Hematoxylin and Erosin Image Information Acquisition and Optimization in Confocal Microscopy

PubMed Central

Yoon, Woong Bae; Kim, Hyunjin; Kim, Kwang Gi; Choi, Yongdoo; Chang, Hee Jin

2016-01-01

Objectives We produced hematoxylin and eosin (H&E) staining-like color images by using confocal laser scanning microscopy (CLSM), which can obtain the same or more information in comparison to conventional tissue staining. Methods We improved images by using several image converting techniques, including morphological methods, color space conversion methods, and segmentation methods. Results An image obtained after image processing showed coloring very similar to that in images produced by H&E staining, and it is advantageous to conduct analysis through fluorescent dye imaging and microscopy rather than analysis based on single microscopic imaging. Conclusions The colors used in CLSM are different from those seen in H&E staining, which is the method most widely used for pathologic diagnosis and is familiar to pathologists. Computer technology can facilitate the conversion of images by CLSM to be very similar to H&E staining images. We believe that the technique used in this study has great potential for application in clinical tissue analysis. PMID:27525165

Method for indexing and retrieving manufacturing-specific digital imagery based on image content

DOEpatents

Ferrell, Regina K.; Karnowski, Thomas P.; Tobin, Jr., Kenneth W.

2004-06-15

A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image. More particularly, can include two data reductions, the first performed based upon a query vector extracted from a query image. Subsequently, a user can select relevant images resulting from the first data reduction. From the selection, a prototype vector can be calculated, from which a second-level data reduction can be performed. The second-level data reduction can result in a subset of feature vectors comparable to the prototype vector, and further comparable to the query vector. An additional fourth step can include managing the hierarchical search tree by substituting a vector average for several redundant feature vectors encapsulated by nodes in the hierarchical search tree.

Evaluation of an automatic brain segmentation method developed for neonates on adult MR brain images

NASA Astrophysics Data System (ADS)

Moeskops, Pim; Viergever, Max A.; Benders, Manon J. N. L.; Išgum, Ivana

2015-03-01

Automatic brain tissue segmentation is of clinical relevance in images acquired at all ages. The literature presents a clear distinction between methods developed for MR images of infants, and methods developed for images of adults. The aim of this work is to evaluate a method developed for neonatal images in the segmentation of adult images. The evaluated method employs supervised voxel classification in subsequent stages, exploiting spatial and intensity information. Evaluation was performed using images available within the MRBrainS13 challenge. The obtained average Dice coefficients were 85.77% for grey matter, 88.66% for white matter, 81.08% for cerebrospinal fluid, 95.65% for cerebrum, and 96.92% for intracranial cavity, currently resulting in the best overall ranking. The possibility of applying the same method to neonatal as well as adult images can be of great value in cross-sectional studies that include a wide age range.

Methods And Systems For Using Reference Images In Acoustic Image Processing

DOEpatents

Moore, Thomas L.; Barter, Robert Henry

2005-01-04

A method and system of examining tissue are provided in which a field, including at least a portion of the tissue and one or more registration fiducials, is insonified. Scattered acoustic information, including both transmitted and reflected waves, is received from the field. A representation of the field, including both the tissue and the registration fiducials, is then derived from the received acoustic radiation.

Blind image quality assessment based on aesthetic and statistical quality-aware features

NASA Astrophysics Data System (ADS)

Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

2017-07-01

The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

Robust digital image inpainting algorithm in the wireless environment

NASA Astrophysics Data System (ADS)

Karapetyan, G.; Sarukhanyan, H. G.; Agaian, S. S.

2014-05-01

Image or video inpainting is the process/art of retrieving missing portions of an image without introducing undesirable artifacts that are undetectable by an ordinary observer. An image/video can be damaged due to a variety of factors, such as deterioration due to scratches, laser dazzling effects, wear and tear, dust spots, loss of data when transmitted through a channel, etc. Applications of inpainting include image restoration (removing laser dazzling effects, dust spots, date, text, time, etc.), image synthesis (texture synthesis), completing panoramas, image coding, wireless transmission (recovery of the missing blocks), digital culture protection, image de-noising, fingerprint recognition, and film special effects and production. Most inpainting methods can be classified in two key groups: global and local methods. Global methods are used for generating large image regions from samples while local methods are used for filling in small image gaps. Each method has its own advantages and limitations. For example, the global inpainting methods perform well on textured image retrieval, whereas the classical local methods perform poorly. In addition, some of the techniques are computationally intensive; exceeding the capabilities of most currently used mobile devices. In general, the inpainting algorithms are not suitable for the wireless environment. This paper presents a new and efficient scheme that combines the advantages of both local and global methods into a single algorithm. Particularly, it introduces a blind inpainting model to solve the above problems by adaptively selecting support area for the inpainting scheme. The proposed method is applied to various challenging image restoration tasks, including recovering old photos, recovering missing data on real and synthetic images, and recovering the specular reflections in endoscopic images. A number of computer simulations demonstrate the effectiveness of our scheme and also illustrate the main properties and implementation steps of the presented algorithm. Furthermore, the simulation results show that the presented method is among the state-of-the-art and compares favorably against many available methods in the wireless environment. Robustness in the wireless environment with respect to the shape of the manually selected "marked" region is also illustrated. Currently, we are working on the expansion of this work to video and 3-D data.

Random forest regression for magnetic resonance image synthesis.

PubMed

Jog, Amod; Carass, Aaron; Roy, Snehashis; Pham, Dzung L; Prince, Jerry L

2017-01-01

By choosing different pulse sequences and their parameters, magnetic resonance imaging (MRI) can generate a large variety of tissue contrasts. This very flexibility, however, can yield inconsistencies with MRI acquisitions across datasets or scanning sessions that can in turn cause inconsistent automated image analysis. Although image synthesis of MR images has been shown to be helpful in addressing this problem, an inability to synthesize both T 2 -weighted brain images that include the skull and FLuid Attenuated Inversion Recovery (FLAIR) images has been reported. The method described herein, called REPLICA, addresses these limitations. REPLICA is a supervised random forest image synthesis approach that learns a nonlinear regression to predict intensities of alternate tissue contrasts given specific input tissue contrasts. Experimental results include direct image comparisons between synthetic and real images, results from image analysis tasks on both synthetic and real images, and comparison against other state-of-the-art image synthesis methods. REPLICA is computationally fast, and is shown to be comparable to other methods on tasks they are able to perform. Additionally REPLICA has the capability to synthesize both T 2 -weighted images of the full head and FLAIR images, and perform intensity standardization between different imaging datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

Radar studies of the atmosphere using spatial and frequency diversity

NASA Astrophysics Data System (ADS)

Yu, Tian-You

This work provides results from a thorough investigation of atmospheric radar imaging including theory, numerical simulations, observational verification, and applications. The theory is generalized to include the existing imaging techniques of coherent radar imaging (CRI) and range imaging (RIM), which are shown to be special cases of three-dimensional imaging (3D Imaging). Mathematically, the problem of atmospheric radar imaging is posed as an inverse problem. In this study, the Fourier, Capon, and maximum entropy (MaxEnt) methods are proposed to solve the inverse problem. After the introduction of the theory, numerical simulations are used to test, validate, and exercise these techniques. Statistical comparisons of the three methods of atmospheric radar imaging are presented for various signal-to-noise ratio (SNR), receiver configuration, and frequency sampling. The MaxEnt method is shown to generally possess the best performance for low SNR. The performance of the Capon method approaches the performance of the MaxEnt method for high SNR. In limited cases, the Capon method actually outperforms the MaxEnt method. The Fourier method generally tends to distort the model structure due to its limited resolution. Experimental justification of CRI and RIM is accomplished using the Middle and Upper (MU) Atmosphere Radar in Japan and the SOUnding SYstem (SOUSY) in Germany, respectively. A special application of CRI to the observation of polar mesosphere summer echoes (PMSE) is used to show direct evidence of wave steepening and possibly explain gravity wave variations associated with PMSE.

A New Pixels Flipping Method for Huge Watermarking Capacity of the Invoice Font Image

PubMed Central

Li, Li; Hou, Qingzheng; Lu, Jianfeng; Dai, Junping; Mao, Xiaoyang; Chang, Chin-Chen

2014-01-01

Invoice printing just has two-color printing, so invoice font image can be seen as binary image. To embed watermarks into invoice image, the pixels need to be flipped. The more huge the watermark is, the more the pixels need to be flipped. We proposed a new pixels flipping method in invoice image for huge watermarking capacity. The pixels flipping method includes one novel interpolation method for binary image, one flippable pixels evaluation mechanism, and one denoising method based on gravity center and chaos degree. The proposed interpolation method ensures that the invoice image keeps features well after scaling. The flippable pixels evaluation mechanism ensures that the pixels keep better connectivity and smoothness and the pattern has highest structural similarity after flipping. The proposed denoising method makes invoice font image smoother and fiter for human vision. Experiments show that the proposed flipping method not only keeps the invoice font structure well but also improves watermarking capacity. PMID:25489606

Visual perception system and method for a humanoid robot

NASA Technical Reports Server (NTRS)

Chelian, Suhas E. (Inventor); Linn, Douglas Martin (Inventor); Wampler, II, Charles W. (Inventor); Bridgwater, Lyndon (Inventor); Wells, James W. (Inventor); Mc Kay, Neil David (Inventor)

2012-01-01

A robotic system includes a humanoid robot with robotic joints each moveable using an actuator(s), and a distributed controller for controlling the movement of each of the robotic joints. The controller includes a visual perception module (VPM) for visually identifying and tracking an object in the field of view of the robot under threshold lighting conditions. The VPM includes optical devices for collecting an image of the object, a positional extraction device, and a host machine having an algorithm for processing the image and positional information. The algorithm visually identifies and tracks the object, and automatically adapts an exposure time of the optical devices to prevent feature data loss of the image under the threshold lighting conditions. A method of identifying and tracking the object includes collecting the image, extracting positional information of the object, and automatically adapting the exposure time to thereby prevent feature data loss of the image.

Availability and performance of image/video-based vital signs monitoring methods: a systematic review protocol.

PubMed

Harford, Mirae; Catherall, Jacqueline; Gerry, Stephen; Young, Duncan; Watkinson, Peter

2017-10-25

For many vital signs, monitoring methods require contact with the patient and/or are invasive in nature. There is increasing interest in developing still and video image-guided monitoring methods that are non-contact and non-invasive. We will undertake a systematic review of still and video image-based monitoring methods. We will perform searches in multiple databases which include MEDLINE, Embase, CINAHL, Cochrane library, IEEE Xplore and ACM Digital Library. We will use OpenGrey and Google searches to access unpublished or commercial data. We will not use language or publication date restrictions. The primary goal is to summarise current image-based vital signs monitoring methods, limited to heart rate, respiratory rate, oxygen saturations and blood pressure. Of particular interest will be the effectiveness of image-based methods compared to reference devices. Other outcomes of interest include the quality of the method comparison studies with respect to published reporting guidelines, any limitations of non-contact non-invasive technology and application in different populations. To the best of our knowledge, this is the first systematic review of image-based non-contact methods of vital signs monitoring. Synthesis of currently available technology will facilitate future research in this highly topical area. PROSPERO CRD42016029167.

Development of a classification method for a crack on a pavement surface images using machine learning

NASA Astrophysics Data System (ADS)

Hizukuri, Akiyoshi; Nagata, Takeshi

2017-03-01

The purpose of this study is to develop a classification method for a crack on a pavement surface image using machine learning to reduce a maintenance fee. Our database consists of 3500 pavement surface images. This includes 800 crack and 2700 normal pavement surface images. The pavement surface images first are decomposed into several sub-images using a discrete wavelet transform (DWT) decomposition. We then calculate the wavelet sub-band histogram from each several sub-images at each level. The support vector machine (SVM) with computed wavelet sub-band histogram is employed for distinguishing between a crack and normal pavement surface images. The accuracies of the proposed classification method are 85.3% for crack and 84.4% for normal pavement images. The proposed classification method achieved high performance. Therefore, the proposed method would be useful in maintenance inspection.

Magnetic imager and method

DOEpatents

Powell, J.; Reich, M.; Danby, G.

1997-07-22

A magnetic imager includes a generator for practicing a method of applying a background magnetic field over a concealed object, with the object being effective to locally perturb the background field. The imager also includes a sensor for measuring perturbations of the background field to detect the object. In one embodiment, the background field is applied quasi-statically. And, the magnitude or rate of change of the perturbations may be measured for determining location, size, and/or condition of the object. 25 figs.

High resolution resonance ionization imaging detector and method

DOEpatents

Winefordner, James D.; Matveev, Oleg I.; Smith, Benjamin W.

1999-01-01

A resonance ionization imaging device (RIID) and method for imaging objects using the RIID are provided, the RIID system including a RIID cell containing an ionizable vapor including monoisotopic atoms or molecules, the cell being positioned to intercept scattered radiation of a resonance wavelength .lambda..sub.1 from the object which is to be detected or imaged, a laser source disposed to illuminate the RIID cell with laser radiation having a wavelength .lambda..sub.2 or wavelengths .lambda..sub.2, .lambda..sub.3 selected to ionize atoms in the cell that are in an excited state by virtue of having absorbed the scattered resonance laser radiation, and a luminescent screen at the back surface of the RIID cell which presents an image of the number and position of charged particles present in the RIID cell as a result of the ionization of the excited state atoms. The method of the invention further includes the step of initially illuminating the object to be detected or imaged with a laser having a wavelength selected such that the object will scatter laser radiation having the resonance wavelength .lambda..sub.1.

Back-illuminated imager and method for making electrical and optical connections to same

NASA Technical Reports Server (NTRS)

Pain, Bedabrata (Inventor)

2010-01-01

Methods for bringing or exposing metal pads or traces to the backside of a backside-illuminated imager allow the pads or traces to reside on the illumination side for electrical connection. These methods provide a solution to a key packaging problem for backside thinned imagers. The methods also provide alignment marks for integrating color filters and microlenses to the imager pixels residing on the frontside of the wafer, enabling high performance multispectral and high sensitivity imagers, including those with extremely small pixel pitch. In addition, the methods incorporate a passivation layer for protection of devices against external contamination, and allow interface trap density reduction via thermal annealing. Backside-illuminated imagers with illumination side electrical connections are also disclosed.

Method for imaging a concealed object

DOEpatents

Davidson, James R [Idaho Falls, ID; Partin, Judy K [Idaho Falls, ID; Sawyers, Robert J [Idaho Falls, ID

2007-07-03

A method for imaging a concealed object is described and which includes a step of providing a heat radiating body, and wherein an object to be detected is concealed on the heat radiating body; imaging the heat radiating body to provide a visibly discernible infrared image of the heat radiating body; and determining if the visibly discernible infrared image of the heat radiating body is masked by the presence of the concealed object.

Beyond maximum entropy: Fractal pixon-based image reconstruction

NASA Technical Reports Server (NTRS)

Puetter, R. C.; Pina, R. K.

1994-01-01

We have developed a new Bayesian image reconstruction method that has been shown to be superior to the best implementations of other methods, including Goodness-of-Fit (e.g. Least-Squares and Lucy-Richardson) and Maximum Entropy (ME). Our new method is based on the concept of the pixon, the fundamental, indivisible unit of picture information. Use of the pixon concept provides an improved image model, resulting in an image prior which is superior to that of standard ME.

Analysis of live cell images: Methods, tools and opportunities.

PubMed

Nketia, Thomas A; Sailem, Heba; Rohde, Gustavo; Machiraju, Raghu; Rittscher, Jens

2017-02-15

Advances in optical microscopy, biosensors and cell culturing technologies have transformed live cell imaging. Thanks to these advances live cell imaging plays an increasingly important role in basic biology research as well as at all stages of drug development. Image analysis methods are needed to extract quantitative information from these vast and complex data sets. The aim of this review is to provide an overview of available image analysis methods for live cell imaging, in particular required preprocessing image segmentation, cell tracking and data visualisation methods. The potential opportunities recent advances in machine learning, especially deep learning, and computer vision provide are being discussed. This review includes overview of the different available software packages and toolkits. Copyright © 2017. Published by Elsevier Inc.

Fluorometric imaging methods for palladium and platinum and the use of palladium for imaging biomolecules.

PubMed

Tracey, Matthew P; Pham, Dianne; Koide, Kazunori

2015-07-21

Neither palladium nor platinum is an endogenous biological metal. Imaging palladium in biological samples, however, is becoming increasingly important because bioorthogonal organometallic chemistry involves palladium catalysis. In addition to being an imaging target, palladium has been used to fluorometrically image biomolecules. In these cases, palladium species are used as imaging-enabling reagents. This review article discusses these fluorometric methods. Platinum-based drugs are widely used as anticancer drugs, yet their mechanism of action remains largely unknown. We discuss fluorometric methods for imaging or quantifying platinum in cells or biofluids. These methods include the use of chemosensors to directly detect platinum, fluorescently tagging platinum-based drugs, and utilizing post-labeling to elucidate distribution and mode of action.

Computed tomography: Will the slices reveal the truth

PubMed Central

Haridas, Harish; Mohan, Abarajithan; Papisetti, Sravanthi; Ealla, Kranti K. R.

2016-01-01

With the advances in the field of imaging sciences, new methods have been developed in dental radiology. These include digital radiography, density analyzing methods, cone beam computed tomography (CBCT), magnetic resonance imaging, ultrasound, and nuclear imaging techniques, which provide high-resolution detailed images of oral structures. The current review aims to critically elaborate the use of CBCT in endodontics. PMID:27652253

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

Methods of Hematoxylin and Erosin Image Information Acquisition and Optimization in Confocal Microscopy.

PubMed

Yoon, Woong Bae; Kim, Hyunjin; Kim, Kwang Gi; Choi, Yongdoo; Chang, Hee Jin; Sohn, Dae Kyung

2016-07-01

We produced hematoxylin and eosin (H&E) staining-like color images by using confocal laser scanning microscopy (CLSM), which can obtain the same or more information in comparison to conventional tissue staining. We improved images by using several image converting techniques, including morphological methods, color space conversion methods, and segmentation methods. An image obtained after image processing showed coloring very similar to that in images produced by H&E staining, and it is advantageous to conduct analysis through fluorescent dye imaging and microscopy rather than analysis based on single microscopic imaging. The colors used in CLSM are different from those seen in H&E staining, which is the method most widely used for pathologic diagnosis and is familiar to pathologists. Computer technology can facilitate the conversion of images by CLSM to be very similar to H&E staining images. We believe that the technique used in this study has great potential for application in clinical tissue analysis.

Multiresolution generalized N dimension PCA for ultrasound image denoising

PubMed Central

2014-01-01

Background Ultrasound images are usually affected by speckle noise, which is a type of random multiplicative noise. Thus, reducing speckle and improving image visual quality are vital to obtaining better diagnosis. Method In this paper, a novel noise reduction method for medical ultrasound images, called multiresolution generalized N dimension PCA (MR-GND-PCA), is presented. In this method, the Gaussian pyramid and multiscale image stacks on each level are built first. GND-PCA as a multilinear subspace learning method is used for denoising. Each level is combined to achieve the final denoised image based on Laplacian pyramids. Results The proposed method is tested with synthetically speckled and real ultrasound images, and quality evaluation metrics, including MSE, SNR and PSNR, are used to evaluate its performance. Conclusion Experimental results show that the proposed method achieved the lowest noise interference and improved image quality by reducing noise and preserving the structure. Our method is also robust for the image with a much higher level of speckle noise. For clinical images, the results show that MR-GND-PCA can reduce speckle and preserve resolvable details. PMID:25096917

Method and apparatus for differential spectroscopic atomic-imaging using scanning tunneling microscopy

DOEpatents

Kazmerski, Lawrence L.

1990-01-01

A Method and apparatus for differential spectroscopic atomic-imaging is disclosed for spatial resolution and imaging for display not only individual atoms on a sample surface, but also bonding and the specific atomic species in such bond. The apparatus includes a scanning tunneling microscope (STM) that is modified to include photon biasing, preferably a tuneable laser, modulating electronic surface biasing for the sample, and temperature biasing, preferably a vibration-free refrigerated sample mounting stage. Computer control and data processing and visual display components are also included. The method includes modulating the electronic bias voltage with and without selected photon wavelengths and frequency biasing under a stabilizing (usually cold) bias temperature to detect bonding and specific atomic species in the bonds as the STM rasters the sample. This data is processed along with atomic spatial topography data obtained from the STM raster scan to create a real-time visual image of the atoms on the sample surface.

Rapid identification of salmonella serotypes with stereo and hyperspectral microscope imaging Methods

USDA-ARS?s Scientific Manuscript database

The hyperspectral microscope imaging (HMI) method can reduce detection time within 8 hours including incubation process. The early and rapid detection with this method in conjunction with the high throughput capabilities makes HMI method a prime candidate for implementation for the food industry. Th...

Rapid Identification of Salmonella Serotypes with Stereo and Hyperspectral Microscope Imaging Methods

USDA-ARS?s Scientific Manuscript database

The hyperspectral microscope imaging (HMI) method can reduce detection time within 8 hours including incubation process. The early and rapid detection with this method in conjunction with the high throughput capabilities makes HMI method a prime candidate for implementation for the food industry. Th...

Imaging indicator for ESD safety testing.

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

Whinnery, LeRoy L.,; Nissen, April; Keifer, Patrick N.

2013-05-01

This report describes the development of a new detection method for electrostatic discharge (ESD) testing of explosives, using a single-lens reflex (SLR) digital camera and a 200-mm macro lens. This method has demonstrated several distinct advantages to other current ESD detection methods, including the creation of a permanent record, an enlarged image for real-time viewing as well as extended periods of review, and ability to combine with most other Go/No-Go sensors. This report includes details of the method, including camera settings and position, and results with wellcharacterized explosives PETN and RDX, and two ESD-sensitive aluminum powders.

Omniview motionless camera orientation system

NASA Technical Reports Server (NTRS)

Martin, H. Lee (Inventor); Kuban, Daniel P. (Inventor); Zimmermann, Steven D. (Inventor); Busko, Nicholas (Inventor)

2010-01-01

An apparatus and method is provided for converting digital images for use in an imaging system. The apparatus includes a data memory which stores digital data representing an image having a circular or spherical field of view such as an image captured by a fish-eye lens, a control input for receiving a signal for selecting a portion of the image, and a converter responsive to the control input for converting digital data corresponding to the selected portion into digital data representing a planar image for subsequent display. Various methods include the steps of storing digital data representing an image having a circular or spherical field of view, selecting a portion of the image, and converting the stored digital data corresponding to the selected portion into digital data representing a planar image for subsequent display. In various embodiments, the data converter and data conversion step may use an orthogonal set of transformation algorithms.

Systems and methods for imaging using radiation from laser produced plasmas

DOEpatents

Renard-Le Galloudec, Nathalie; Cowan, Thomas E.; Sentoku, Yasuhiko; Rassuchine, Jennifer

2009-06-30

In particular embodiments, the present disclosure provides systems and methods for imaging a subject using radiation emitted from a laser produced plasma generating by irradiating a target with a laser. In particular examples, the target includes at least one radiation enhancing component, such as a fluor, cap, or wire. In further examples, the target has a metal layer and an internal surface defining an internal apex, the internal apex of less than about 15 .mu.m, such as less than about 1 .mu.m. The targets may take a variety of shapes, including cones, pyramids, and hemispheres. Certain aspects of the present disclosure provide improved imaging of a subject, such as improved medical images of a radiation dose than typical conventional methods and systems.

Contrast enhancing solution for use in confocal microscopy

DOEpatents

Tannous, Zeina; Torres, Abel; Gonzalez, Salvador

2006-10-31

A method of optically detecting a tumor during surgery. The method includes imaging at least one test point defined on the tumor using a first optical imaging system to provide a first tumor image. The method further includes excising a first predetermined layer of the tumor for forming an in-vivo defect area. A predetermined contrast enhancing solution is disposed on the in-vivo defect area, which is adapted to interact with at least one cell anomaly, such as basal cell carcinoma, located on the in-vivo defect area for optically enhancing the cell anomaly. Thereafter the defect area can be optically imaged to provide a clear and bright representation of the cell anomaly to aid a surgeon while surgically removing the cell anomaly.

Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images

PubMed Central

Lu, Dengsheng; Hetrick, Scott; Moran, Emilio; Li, Guiying

2011-01-01

Accurately detecting urban expansion with remote sensing techniques is a challenge due to the complexity of urban landscapes. This paper explored methods for detecting urban expansion with multitemporal QuickBird images in Lucas do Rio Verde, Mato Grosso, Brazil. Different techniques, including image differencing, principal component analysis (PCA), and comparison of classified impervious surface images with the matched filtering method, were used to examine urbanization detection. An impervious surface image classified with the hybrid method was used to modify the urbanization detection results. As a comparison, the original multispectral image and segmentation-based mean-spectral images were used during the detection of urbanization. This research indicates that the comparison of classified impervious surface images with matched filtering method provides the best change detection performance, followed by the image differencing method based on segmentation-based mean spectral images. The PCA is not a good method for urban change detection in this study. Shadows and high spectral variation within the impervious surfaces represent major challenges to the detection of urban expansion when high spatial resolution images are used. PMID:21799706

Improved image alignment method in application to X-ray images and biological images.

PubMed

Wang, Ching-Wei; Chen, Hsiang-Chou

2013-08-01

Alignment of medical images is a vital component of a large number of applications throughout the clinical track of events; not only within clinical diagnostic settings, but prominently so in the area of planning, consummation and evaluation of surgical and radiotherapeutical procedures. However, image registration of medical images is challenging because of variations on data appearance, imaging artifacts and complex data deformation problems. Hence, the aim of this study is to develop a robust image alignment method for medical images. An improved image registration method is proposed, and the method is evaluated with two types of medical data, including biological microscopic tissue images and dental X-ray images and compared with five state-of-the-art image registration techniques. The experimental results show that the presented method consistently performs well on both types of medical images, achieving 88.44 and 88.93% averaged registration accuracies for biological tissue images and X-ray images, respectively, and outperforms the benchmark methods. Based on the Tukey's honestly significant difference test and Fisher's least square difference test tests, the presented method performs significantly better than all existing methods (P ≤ 0.001) for tissue image alignment, and for the X-ray image registration, the proposed method performs significantly better than the two benchmark b-spline approaches (P < 0.001). The software implementation of the presented method and the data used in this study are made publicly available for scientific communities to use (http://www-o.ntust.edu.tw/∼cweiwang/ImprovedImageRegistration/). cweiwang@mail.ntust.edu.tw.

Magnetic imager and method

DOEpatents

Powell, James; Reich, Morris; Danby, Gordon

1997-07-22

A magnetic imager 10 includes a generator 18 for practicing a method of applying a background magnetic field over a concealed object, with the object being effective to locally perturb the background field. The imager 10 also includes a sensor 20 for measuring perturbations of the background field to detect the object. In one embodiment, the background field is applied quasi-statically. And, the magnitude or rate of change of the perturbations may be measured for determining location, size, and/or condition of the object.

Acoustic Radiation Force Elasticity Imaging in Diagnostic Ultrasound

PubMed Central

Doherty, Joshua R.; Trahey, Gregg E.; Nightingale, Kathryn R.; Palmeri, Mark L.

2013-01-01

The development of ultrasound-based elasticity imaging methods has been the focus of intense research activity since the mid-1990s. In characterizing the mechanical properties of soft tissues, these techniques image an entirely new subset of tissue properties that cannot be derived with conventional ultrasound techniques. Clinically, tissue elasticity is known to be associated with pathological condition and with the ability to image these features in vivo, elasticity imaging methods may prove to be invaluable tools for the diagnosis and/or monitoring of disease. This review focuses on ultrasound-based elasticity imaging methods that generate an acoustic radiation force to induce tissue displacements. These methods can be performed non-invasively during routine exams to provide either qualitative or quantitative metrics of tissue elasticity. A brief overview of soft tissue mechanics relevant to elasticity imaging is provided, including a derivation of acoustic radiation force, and an overview of the various acoustic radiation force elasticity imaging methods. PMID:23549529

Acoustic radiation force elasticity imaging in diagnostic ultrasound.

PubMed

Doherty, Joshua R; Trahey, Gregg E; Nightingale, Kathryn R; Palmeri, Mark L

2013-04-01

The development of ultrasound-based elasticity imaging methods has been the focus of intense research activity since the mid-1990s. In characterizing the mechanical properties of soft tissues, these techniques image an entirely new subset of tissue properties that cannot be derived with conventional ultrasound techniques. Clinically, tissue elasticity is known to be associated with pathological condition and with the ability to image these features in vivo; elasticity imaging methods may prove to be invaluable tools for the diagnosis and/or monitoring of disease. This review focuses on ultrasound-based elasticity imaging methods that generate an acoustic radiation force to induce tissue displacements. These methods can be performed noninvasively during routine exams to provide either qualitative or quantitative metrics of tissue elasticity. A brief overview of soft tissue mechanics relevant to elasticity imaging is provided, including a derivation of acoustic radiation force, and an overview of the various acoustic radiation force elasticity imaging methods.

Material appearance acquisition from a single image

NASA Astrophysics Data System (ADS)

Zhang, Xu; Cui, Shulin; Cui, Hanwen; Yang, Lin; Wu, Tao

2017-01-01

The scope of this paper is to present a method of material appearance acquisition(MAA) from a single image. In this paper, material appearance is represented by spatially varying bidirectional reflectance distribution function(SVBRDF). Therefore, MAA can be reduced to the problem of recovery of each pixel's BRDF parameters from an original input image, which include diffuse coefficient, specular coefficient, normal and glossiness based on the Blinn-Phone model. In our method, the workflow of MAA includes five main phases: highlight removal, estimation of intrinsic images, shape from shading(SFS), initialization of glossiness and refining SVBRDF parameters based on IPOPT. The results indicate that the proposed technique can effectively extract the material appearance from a single image.

Coupled dictionary learning for joint MR image restoration and segmentation

NASA Astrophysics Data System (ADS)

Yang, Xuesong; Fan, Yong

2018-03-01

To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled dictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a dictionary of low quality image patches, a dictionary of high quality image patches, and a dictionary of segmentation label patches, are learned in a unified framework so that the learned dictionaries of image restoration and segmentation can benefit each other. Our method has been evaluated for segmenting the hippocampus in MR T1 images collected with scanners of different magnetic field strengths. The experimental results have demonstrated that our method achieved better image restoration and segmentation performance than state of the art dictionary learning and sparse representation based image restoration and image segmentation methods.

Method and apparatus to image biological interactions in plants

DOEpatents

Weisenberger, Andrew; Bonito, Gregory M.; Reid, Chantal D.; Smith, Mark Frederick

2015-12-22

A method to dynamically image the actual translocation of molecular compounds of interest in a plant root, root system, and rhizosphere without disturbing the root or the soil. The technique makes use of radioactive isotopes as tracers to label molecules of interest and to image their distribution in the plant and/or soil. The method allows for the study and imaging of various biological and biochemical interactions in the rhizosphere of a plant, including, but not limited to, mycorrhizal associations in such regions.

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Skull optical clearing for assessing to cerebral hemodynamics with high contrast and resolution (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhu, Dan

2017-03-01

The tissue optical clearing technique could significantly enhance the biomedical optical imaging depth, but current investigations are mainly limited to in vitro studies. In vivo tissue optical clearing method should be enough rapid, transparent and safe, which makes it more difficult, especially, for hard tissue. During the past years, we developed skull optical clearing methods for in vivo cortical imaging. This presentation will report recent progress in skull optical clearing method, including their efficacy, safety, and applications. The skull optical clearing method is proved to be effective for adult mice ages in different month and permit various imaging techniques to monitor cortical blood flow, blood oxygen, and vascular with high resolution and contrast, not only for local cortex, but also for whole cortex. The long-term and short-term observation show that there is no obvious effect on cortical vascular function when laser speckle contrast imaging and hyperspectral imaging are used to repeatedly image the cortical blood flow, blood oxygen. Finally, we will demonstrate some applications for physiological or pathological situation, including monitoring the anoxia, drug-induced cortical response, et al.

Systems and methods for detecting an image of an object using multi-beam imaging from an X-ray beam having a polychromatic distribution

DOEpatents

Parham, Christopher A; Zhong, Zhong; Pisano, Etta; Connor, Jr., Dean M

2015-03-03

Systems and methods for detecting an image of an object using a multi-beam imaging system from an x-ray beam having a polychromatic energy distribution are disclosed. According to one aspect, a method can include generating a first X-ray beam having a polychromatic energy distribution. Further, the method can include positioning a plurality of monochromator crystals in a predetermined position to directly intercept the first X-ray beam such that a plurality of second X-ray beams having predetermined energy levels are produced. Further, an object can be positioned in the path of the second X-ray beams for transmission of the second X-ray beams through the object and emission from the object as transmitted X-ray beams. The transmitted X-ray beams can each be directed at an angle of incidence upon one or more crystal analyzers. Further, an image of the object can be detected from the beams diffracted from the analyzer crystals.

Imaging photorefractive optical vibration measurement method and device

DOEpatents

Telschow, Kenneth L.; Deason, Vance A.; Hale, Thomas C.

2000-01-01

A method and apparatus are disclosed for characterizing a vibrating image of an object of interest. The method includes providing a sensing media having a detection resolution within a limited bandwidth and providing an object of interest having a vibrating medium. Two or more wavefronts are provided, with at least one of the wavefronts being modulated by interacting the one wavefront with the vibrating medium of the object of interest. The another wavefront is modulated such that the difference frequency between the one wavefront and the another wavefront is within a response range of the sensing media. The modulated one wavefront and another wavefront are combined in association with the sensing media to interfere and produce simultaneous vibration measurements that are distributed over the object so as to provide an image of the vibrating medium. The image has an output intensity that is substantially linear with small physical variations within the vibrating medium. Furthermore, the method includes detecting the image. In one implementation, the apparatus comprises a vibration spectrum analyzer having an emitter, a modulator, sensing media and a detector configured so as to realize such method. According to another implementation, the apparatus comprises a vibration imaging device.

Recovering of images degraded by atmosphere

NASA Astrophysics Data System (ADS)

Lin, Guang; Feng, Huajun; Xu, Zhihai; Li, Qi; Chen, Yueting

2017-08-01

Remote sensing images are seriously degraded by multiple scattering and bad weather. Through the analysis of the radiative transfer procedure in atmosphere, an image atmospheric degradation model considering the influence of atmospheric absorption multiple scattering and non-uniform distribution is proposed in this paper. Based on the proposed model, a novel recovering method is presented to eliminate atmospheric degradation. Mean-shift image segmentation and block-wise deconvolution are used to reduce time cost, retaining a good result. The recovering results indicate that the proposed method can significantly remove atmospheric degradation and effectively improve contrast compared with other removal methods. The results also illustrate that our method is suitable for various degraded remote sensing, including images with large field of view (FOV), images taken in side-glance situations, image degraded by atmospheric non-uniform distribution and images with various forms of clouds.

Image Processing for Educators in Global Hands-On Universe

NASA Astrophysics Data System (ADS)

Miller, J. P.; Pennypacker, C. R.; White, G. L.

2006-08-01

A method of image processing to find time-varying objects is being developed for the National Virtual Observatory as part of Global Hands-On Universe(tm) (Lawrence Hall of Science; University of California, Berkeley). Objects that vary in space or time are of prime importance in modern astronomy and astrophysics. Such objects include active galactic nuclei, variable stars, supernovae, or moving objects across a field of view such as an asteroid, comet, or extrasolar planet transiting its parent star. The search for these objects is undertaken by acquiring an image of the region of the sky where they occur followed by a second image taken at a later time. Ideally, both images are taken with the same telescope using the same filter and charge-coupled device. The two images are aligned and subtracted with the subtracted image revealing any changes in light during the time period between the two images. We have used a method of Christophe Alard using the image processing software IDL Version 6.2 (Research Systems, Inc.) with the exception of the background correction, which is done on the two images prior to the subtraction. Testing has been extensive, using images provided by a number of National Virtual Observatory and collaborating projects. They include the Supernovae Trace Cosmic Expansion (Cerro Tololo Inter-American Observatory), Supernovae/ Acceleration Program (Lawrence Berkeley National Laboratory), Lowell Observatory Near-Earth Object Search (Lowell Observatory), and the Centre National de la Recherche Scientifique (Paris, France). Further testing has been done with students, including a May 2006 two week program at the Lawrence Berkeley National Laboratory. Students from Hardin-Simmons University (Abilene, TX) and Jackson State University (Jackson, MS) used the subtraction method to analyze images from the Cerro Tololo Inter-American Observatory (CTIO) searching for new asteroids and Kuiper Belt objects. In October 2006 students from five U.S. high schools will use the subtraction method in an asteroid search campaign using CTIO images with 7-day follow-up images to be provided by the Las Cumbres Observatory (Santa Barbara, CA). During the Spring 2006 semester, students from Cape Fear High School used the method to search for near-Earth objects and supernovae. Using images from the Astronomical Research Institute (Charleston, IL) the method contributed to the original discovery of two supernovae, SN 2006al and SN 2006bi.

ViRPET--combination of virtual reality and PET brain imaging

DOEpatents

Majewski, Stanislaw; Brefczynski-Lewis, Julie

2017-05-23

Various methods, systems and apparatus are provided for brain imaging during virtual reality stimulation. In one example, among others, a system for virtual ambulatory environment brain imaging includes a mobile brain imager configured to obtain positron emission tomography (PET) scans of a subject in motion, and a virtual reality (VR) system configured to provide one or more stimuli to the subject during the PET scans. In another example, a method for virtual ambulatory environment brain imaging includes providing stimulation to a subject through a virtual reality (VR) system; and obtaining a positron emission tomography (PET) scan of the subject while moving in response to the stimulation from the VR system. The mobile brain imager can be positioned on the subject with an array of imaging photodetector modules distributed about the head of the subject.

Single image super-resolution based on convolutional neural networks

NASA Astrophysics Data System (ADS)

Zou, Lamei; Luo, Ming; Yang, Weidong; Li, Peng; Jin, Liujia

2018-03-01

We present a deep learning method for single image super-resolution (SISR). The proposed approach learns end-to-end mapping between low-resolution (LR) images and high-resolution (HR) images. The mapping is represented as a deep convolutional neural network which inputs the LR image and outputs the HR image. Our network uses 5 convolution layers, which kernels size include 5×5, 3×3 and 1×1. In our proposed network, we use residual-learning and combine different sizes of convolution kernels at the same layer. The experiment results show that our proposed method performs better than the existing methods in reconstructing quality index and human visual effects on benchmarked images.

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spatially filtered to enforce local consensus among neighboring pixels and the spatially filtered image is output.

Method and apparatus for detecting a desired behavior in digital image data

DOEpatents

Kegelmeyer, Jr., W. Philip

1997-01-01

A method for detecting stellate lesions in digitized mammographic image data includes the steps of prestoring a plurality of reference images, calculating a plurality of features for each of the pixels of the reference images, and creating a binary decision tree from features of randomly sampled pixels from each of the reference images. Once the binary decision tree has been created, a plurality of features, preferably including an ALOE feature (analysis of local oriented edges), are calculated for each of the pixels of the digitized mammographic data. Each of these plurality of features of each pixel are input into the binary decision tree and a probability is determined, for each of the pixels, corresponding to the likelihood of the presence of a stellate lesion, to create a probability image. Finally, the probability image is spacially filtered to enforce local consensus among neighboring pixels and the spacially filtered image is output.

Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Don J.

2010-01-01

Signal- and image-processing methods are commonly needed to extract information from the waves, improve resolution of, and highlight defects in an image. Since some similarity exists for all waveform-based nondestructive evaluation (NDE) methods, it would seem that a common software platform containing multiple signal- and image-processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. NDE Wave & Image Processor Version 2.0 software provides a single, integrated signal- and image-processing and analysis environment for total NDE data processing and analysis. It brings some of the most useful algorithms developed for NDE over the past 20 years into a commercial-grade product. The software can import signal/spectroscopic data, image data, and image series data. This software offers the user hundreds of basic and advanced signal- and image-processing capabilities including esoteric 1D and 2D wavelet-based de-noising, de-trending, and filtering. Batch processing is included for signal- and image-processing capability so that an optimized sequence of processing operations can be applied to entire folders of signals, spectra, and images. Additionally, an extensive interactive model-based curve-fitting facility has been included to allow fitting of spectroscopy data such as from Raman spectroscopy. An extensive joint-time frequency module is included for analysis of non-stationary or transient data such as that from acoustic emission, vibration, or earthquake data.

An Evaluation of Feature Learning Methods for High Resolution Image Classification

NASA Astrophysics Data System (ADS)

Tokarczyk, P.; Montoya, J.; Schindler, K.

2012-07-01

Automatic image classification is one of the fundamental problems of remote sensing research. The classification problem is even more challenging in high-resolution images of urban areas, where the objects are small and heterogeneous. Two questions arise, namely which features to extract from the raw sensor data to capture the local radiometry and image structure at each pixel or segment, and which classification method to apply to the feature vectors. While classifiers are nowadays well understood, selecting the right features remains a largely empirical process. Here we concentrate on the features. Several methods are evaluated which allow one to learn suitable features from unlabelled image data by analysing the image statistics. In a comparative study, we evaluate unsupervised feature learning with different linear and non-linear learning methods, including principal component analysis (PCA) and deep belief networks (DBN). We also compare these automatically learned features with popular choices of ad-hoc features including raw intensity values, standard combinations like the NDVI, a few PCA channels, and texture filters. The comparison is done in a unified framework using the same images, the target classes, reference data and a Random Forest classifier.

Crystallization mosaic effect generation by superpixels

NASA Astrophysics Data System (ADS)

Xie, Yuqi; Bo, Pengbo; Yuan, Ye; Wang, Kuanquan

2015-03-01

Art effect generation from digital images using computational tools has been a hot research topic in recent years. We propose a new method for generating crystallization mosaic effects from color images. Two key problems in generating pleasant mosaic effect are studied: grouping pixels into mosaic tiles and arrangement of mosaic tiles adapting to image features. To give visually pleasant mosaic effect, we propose to create mosaic tiles by pixel clustering in feature space of color information, taking compactness of tiles into consideration as well. Moreover, we propose a method for processing feature boundaries in images which gives guidance for arranging mosaic tiles near image features. This method gives nearly uniform shape of mosaic tiles, adapting to feature lines in an esthetic way. The new approach considers both color distance and Euclidean distance of pixels, and thus is capable of giving mosaic tiles in a more pleasing manner. Some experiments are included to demonstrate the computational efficiency of the present method and its capability of generating visually pleasant mosaic tiles. Comparisons with existing approaches are also included to show the superiority of the new method.

Optical Brain Imaging: A Powerful Tool for Neuroscience.

PubMed

Zhu, Xinpei; Xia, Yanfang; Wang, Xuecen; Si, Ke; Gong, Wei

2017-02-01

As the control center of organisms, the brain remains little understood due to its complexity. Taking advantage of imaging methods, scientists have found an accessible approach to unraveling the mystery of neuroscience. Among these methods, optical imaging techniques are widely used due to their high molecular specificity and single-molecule sensitivity. Here, we overview several optical imaging techniques in neuroscience of recent years, including brain clearing, the micro-optical sectioning tomography system, and deep tissue imaging.

A study for watermark methods appropriate to medical images.

PubMed

Cho, Y; Ahn, B; Kim, J S; Kim, I Y; Kim, S I

2001-06-01

The network system, including the picture archiving and communication system (PACS), is essential in hospital and medical imaging fields these days. Many medical images are accessed and processed on the web, as well as in PACS. Therefore, any possible accidents caused by the illegal modification of medical images must be prevented. Digital image watermark techniques have been proposed as a method to protect against illegal copying or modification of copyrighted material. Invisible signatures made by a digital image watermarking technique can be a solution to these problems. However, medical images have some different characteristics from normal digital images in that one must not corrupt the information contained in the original medical images. In this study, we suggest modified watermark methods appropriate for medical image processing and communication system that prevent clinically important data contained in original images from being corrupted.

Multiview echocardiography fusion using an electromagnetic tracking system.

PubMed

Punithakumar, Kumaradevan; Hareendranathan, Abhilash R; Paakkanen, Riitta; Khan, Nehan; Noga, Michelle; Boulanger, Pierre; Becher, Harald

2016-08-01

Three-dimensional ultrasound is an emerging modality for the assessment of complex cardiac anatomy and function. The advantages of this modality include lack of ionizing radiation, portability, low cost, and high temporal resolution. Major limitations include limited field-of-view, reliance on frequently limited acoustic windows, and poor signal to noise ratio. This study proposes a novel approach to combine multiple views into a single image using an electromagnetic tracking system in order to improve the field-of-view. The novel method has several advantages: 1) it does not rely on image information for alignment, and therefore, the method does not require image overlap; 2) the alignment accuracy of the proposed approach is not affected by any poor image quality as in the case of image registration based approaches; 3) in contrast to previous optical tracking based system, the proposed approach does not suffer from line-of-sight limitation; and 4) it does not require any initial calibration. In this pilot project, we were able to show that using a heart phantom, our method can fuse multiple echocardiographic images and improve the field-of view. Quantitative evaluations showed that the proposed method yielded a nearly optimal alignment of image data sets in three-dimensional space. The proposed method demonstrates the electromagnetic system can be used for the fusion of multiple echocardiography images with a seamless integration of sensors to the transducer.

Method For Identifying Sedimentary Bodies From Images And Its Application To Mineral Exploration

NASA Technical Reports Server (NTRS)

Wilkinson, Murray Justin (Inventor)

2006-01-01

A method is disclosed for identifying a sediment accumulation from an image of a part of the earth's surface. The method includes identifying a topographic discontinuity from the image. A river which crosses the discontinuity is identified from the image. From the image, paleocourses of the river are identified which diverge from a point where the river crosses the discontinuity. The paleocourses are disposed on a topographically low side of the discontinuity. A smooth surface which emanates from the point is identified. The smooth surface is also disposed on the topographically low side of the point.

MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

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

Chen, G; Pan, X; Stayman, J

2014-06-15

Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within themore » reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical applications. Learning Objectives: Learn the general methodologies associated with model-based 3D image reconstruction. Learn the potential advantages in image quality and dose associated with model-based image reconstruction. Learn the challenges associated with computational load and image quality assessment for such reconstruction methods. Learn how imaging task can be incorporated as a means to drive optimal image acquisition and reconstruction techniques. Learn how model-based reconstruction methods can incorporate prior information to improve image quality, ease sampling requirements, and reduce dose.« less

Low-Income, African American and American Indian Children's Viewpoints on Body Image Assessment Tools and Body Satisfaction: A Mixed Methods Study.

PubMed

Heidelberger, Lindsay; Smith, Chery

2018-03-03

Objectives Pediatric obesity is complicated by many factors including psychological issues, such as body dissatisfaction. Body image assessment tools are used with children to measure their acceptance of their body shape or image. Limited research has been conducted with African American and American Indian children to understand their opinions on assessment tools created. This study investigated: (a) children's perception about body image and (b) differences between two body image instruments among low-income, multi-ethnic children. Methods This study uses mixed methodology including focus groups (qualitative) and body image assessment instruments (quantitative). Fifty-one children participated (25 girls, 26 boys); 53% of children identified as African American and 47% as American Indian. The average age was 10.4 years. Open coding methods were used by identify themes from focus group data. SPSS was used for quantitative analysis. Results Children preferred the Figure Rating Scale (FRS/silhouette) instrument over the Children's Body Image Scale (CBIS/photo) because their body parts and facial features were more detailed. Children formed their body image perception with influence from their parents and the media. Children verbalized that they have experienced negative consequences related to poor body image including disordered eating habits, depression, and bullying. Healthy weight children are also aware of weight-related bullying that obese and overweight children face. Conclusions for Practice Children prefer that the images on a body image assessment tool have detailed facial features and are clothed. Further research into body image assessment tools for use with African American and American Indian children is needed.

New Software Developments for Quality Mesh Generation and Optimization from Biomedical Imaging Data

PubMed Central

Yu, Zeyun; Wang, Jun; Gao, Zhanheng; Xu, Ming; Hoshijima, Masahiko

2013-01-01

In this paper we present a new software toolkit for generating and optimizing surface and volumetric meshes from three-dimensional (3D) biomedical imaging data, targeted at image-based finite element analysis of some biomedical activities in a single material domain. Our toolkit includes a series of geometric processing algorithms including surface re-meshing and quality-guaranteed tetrahedral mesh generation and optimization. All methods described have been encapsulated into a user-friendly graphical interface for easy manipulation and informative visualization of biomedical images and mesh models. Numerous examples are presented to demonstrate the effectiveness and efficiency of the described methods and toolkit. PMID:24252469

QBIC project: querying images by content, using color, texture, and shape

NASA Astrophysics Data System (ADS)

Niblack, Carlton W.; Barber, Ron; Equitz, Will; Flickner, Myron D.; Glasman, Eduardo H.; Petkovic, Dragutin; Yanker, Peter; Faloutsos, Christos; Taubin, Gabriel

1993-04-01

In the query by image content (QBIC) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include medical (`Give me other images that contain a tumor with a texture like this one'), photo-journalism (`Give me images that have blue at the top and red at the bottom'), and many others in art, fashion, cataloging, retailing, and industry. Key issues include derivation and computation of attributes of images and objects that provide useful query functionality, retrieval methods based on similarity as opposed to exact match, query by image example or user drawn image, the user interfaces, query refinement and navigation, high dimensional database indexing, and automatic and semi-automatic database population. We currently have a prototype system written in X/Motif and C running on an RS/6000 that allows a variety of queries, and a test database of over 1000 images and 1000 objects populated from commercially available photo clip art images. In this paper we present the main algorithms for color texture, shape and sketch query that we use, show example query results, and discuss future directions.

OARSI Clinical Trials Recommendations for Hip Imaging in Osteoarthritis

PubMed Central

Gold, Garry E.; Cicuttini, Flavia; Crema, Michel D.; Eckstein, Felix; Guermazi, Ali; Kijowski, Richard; Link, Thomas M.; Maheu, Emmanuel; Martel-Pelletier, Johanne; Miller, Colin G.; Pelletier, Jean-Pierre; Peterfy, Charles G.; Potter, Hollis G.; Roemer, Frank W.; Hunter, David. J

2015-01-01

Imaging of hip in osteoarthritis (OA) has seen considerable progress in the past decade, with the introduction of new techniques that may be more sensitive to structural disease changes. The purpose of this expert opinion, consensus driven recommendation is to provide detail on how to apply hip imaging in disease modifying clinical trials. It includes information on acquisition methods/ techniques (including guidance on positioning for radiography, sequence/protocol recommendations/ hardware for MRI); commonly encountered problems (including positioning, hardware and coil failures, artifacts associated with various MRI sequences); quality assurance/ control procedures; measurement methods; measurement performance (reliability, responsiveness, and validity); recommendations for trials; and research recommendations. PMID:25952344

Neutron imaging integrated circuit and method for detecting neutrons

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

Nagarkar, Vivek V.; More, Mitali J.

The present disclosure provides a neutron imaging detector and a method for detecting neutrons. In one example, a method includes providing a neutron imaging detector including plurality of memory cells and a conversion layer on the memory cells, setting one or more of the memory cells to a first charge state, positioning the neutron imaging detector in a neutron environment for a predetermined time period, and reading a state change at one of the memory cells, and measuring a charge state change at one of the plurality of memory cells from the first charge state to a second charge statemore » less than the first charge state, where the charge state change indicates detection of neutrons at said one of the memory cells.« less

Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

PubMed

Bigler, Erin D

2015-09-01

Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

Extended morphological processing: a practical method for automatic spot detection of biological markers from microscopic images.

PubMed

Kimori, Yoshitaka; Baba, Norio; Morone, Nobuhiro

2010-07-08

A reliable extraction technique for resolving multiple spots in light or electron microscopic images is essential in investigations of the spatial distribution and dynamics of specific proteins inside cells and tissues. Currently, automatic spot extraction and characterization in complex microscopic images poses many challenges to conventional image processing methods. A new method to extract closely located, small target spots from biological images is proposed. This method starts with a simple but practical operation based on the extended morphological top-hat transformation to subtract an uneven background. The core of our novel approach is the following: first, the original image is rotated in an arbitrary direction and each rotated image is opened with a single straight line-segment structuring element. Second, the opened images are unified and then subtracted from the original image. To evaluate these procedures, model images of simulated spots with closely located targets were created and the efficacy of our method was compared to that of conventional morphological filtering methods. The results showed the better performance of our method. The spots of real microscope images can be quantified to confirm that the method is applicable in a given practice. Our method achieved effective spot extraction under various image conditions, including aggregated target spots, poor signal-to-noise ratio, and large variations in the background intensity. Furthermore, it has no restrictions with respect to the shape of the extracted spots. The features of our method allow its broad application in biological and biomedical image information analysis.

Human Pose Estimation from Monocular Images: A Comprehensive Survey

PubMed Central

Gong, Wenjuan; Zhang, Xuena; Gonzàlez, Jordi; Sobral, Andrews; Bouwmans, Thierry; Tu, Changhe; Zahzah, El-hadi

2016-01-01

Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in the literature, but they focus on a certain category; for example, model-based approaches or human motion analysis, etc. As far as we know, an overall review of this problem domain has yet to be provided. Furthermore, recent advancements based on deep learning have brought novel algorithms for this problem. In this paper, a comprehensive survey of human pose estimation from monocular images is carried out including milestone works and recent advancements. Based on one standard pipeline for the solution of computer vision problems, this survey splits the problem into several modules: feature extraction and description, human body models, and modeling methods. Problem modeling methods are approached based on two means of categorization in this survey. One way to categorize includes top-down and bottom-up methods, and another way includes generative and discriminative methods. Considering the fact that one direct application of human pose estimation is to provide initialization for automatic video surveillance, there are additional sections for motion-related methods in all modules: motion features, motion models, and motion-based methods. Finally, the paper also collects 26 publicly available data sets for validation and provides error measurement methods that are frequently used. PMID:27898003

Normal and abnormal tissue identification system and method for medical images such as digital mammograms

NASA Technical Reports Server (NTRS)

Heine, John J. (Inventor); Clarke, Laurence P. (Inventor); Deans, Stanley R. (Inventor); Stauduhar, Richard Paul (Inventor); Cullers, David Kent (Inventor)

2001-01-01

A system and method for analyzing a medical image to determine whether an abnormality is present, for example, in digital mammograms, includes the application of a wavelet expansion to a raw image to obtain subspace images of varying resolution. At least one subspace image is selected that has a resolution commensurate with a desired predetermined detection resolution range. A functional form of a probability distribution function is determined for each selected subspace image, and an optimal statistical normal image region test is determined for each selected subspace image. A threshold level for the probability distribution function is established from the optimal statistical normal image region test for each selected subspace image. A region size comprising at least one sector is defined, and an output image is created that includes a combination of all regions for each selected subspace image. Each region has a first value when the region intensity level is above the threshold and a second value when the region intensity level is below the threshold. This permits the localization of a potential abnormality within the image.

Automatic registration of fused lidar/digital imagery (texel images) for three-dimensional image creation

NASA Astrophysics Data System (ADS)

Budge, Scott E.; Badamikar, Neeraj S.; Xie, Xuan

2015-03-01

Several photogrammetry-based methods have been proposed that the derive three-dimensional (3-D) information from digital images from different perspectives, and lidar-based methods have been proposed that merge lidar point clouds and texture the merged point clouds with digital imagery. Image registration alone has difficulty with smooth regions with low contrast, whereas point cloud merging alone has difficulty with outliers and a lack of proper convergence in the merging process. This paper presents a method to create 3-D images that uses the unique properties of texel images (pixel-fused lidar and digital imagery) to improve the quality and robustness of fused 3-D images. The proposed method uses both image processing and point-cloud merging to combine texel images in an iterative technique. Since the digital image pixels and the lidar 3-D points are fused at the sensor level, more accurate 3-D images are generated because registration of image data automatically improves the merging of the point clouds, and vice versa. Examples illustrate the value of this method over other methods. The proposed method also includes modifications for the situation where an estimate of position and attitude of the sensor is known, when obtained from low-cost global positioning systems and inertial measurement units sensors.

Single image super-resolution based on approximated Heaviside functions and iterative refinement

PubMed Central

Wang, Xin-Yu; Huang, Ting-Zhu; Deng, Liang-Jian

2018-01-01

One method of solving the single-image super-resolution problem is to use Heaviside functions. This has been done previously by making a binary classification of image components as “smooth” and “non-smooth”, describing these with approximated Heaviside functions (AHFs), and iteration including l1 regularization. We now introduce a new method in which the binary classification of image components is extended to different degrees of smoothness and non-smoothness, these components being represented by various classes of AHFs. Taking into account the sparsity of the non-smooth components, their coefficients are l1 regularized. In addition, to pick up more image details, the new method uses an iterative refinement for the residuals between the original low-resolution input and the downsampled resulting image. Experimental results showed that the new method is superior to the original AHF method and to four other published methods. PMID:29329298

General imaging of advanced 3D mask objects based on the fully-vectorial extended Nijboer-Zernike (ENZ) theory

NASA Astrophysics Data System (ADS)

van Haver, Sven; Janssen, Olaf T. A.; Braat, Joseph J. M.; Janssen, Augustus J. E. M.; Urbach, H. Paul; Pereira, Silvania F.

2008-03-01

In this paper we introduce a new mask imaging algorithm that is based on the source point integration method (or Abbe method). The method presented here distinguishes itself from existing methods by exploiting the through-focus imaging feature of the Extended Nijboer-Zernike (ENZ) theory of diffraction. An introduction to ENZ-theory and its application in general imaging is provided after which we describe the mask imaging scheme that can be derived from it. The remainder of the paper is devoted to illustrating the advantages of the new method over existing methods (Hopkins-based). To this extent several simulation results are included that illustrate advantages arising from: the accurate incorporation of isolated structures, the rigorous treatment of the object (mask topography) and the fully vectorial through-focus image formation of the ENZ-based algorithm.

Evaluation of double photon coincidence Compton imaging method with GEANT4 simulation

NASA Astrophysics Data System (ADS)

Yoshihara, Yuri; Shimazoe, Kenji; Mizumachi, Yuki; Takahashi, Hiroyuki

2017-11-01

Compton imaging has been used for various applications including astronomical observations, radioactive waste management, and biomedical imaging. The positions of radioisotopes are determined in the intersections of multiple cone traces through a large number of events, which reduces signal to noise ratio (SNR) of the images. We have developed an advanced Compton imaging method to localize radioisotopes with high SNR by using information of the interactions of Compton scattering caused by two gamma rays at the same time, as the double photon coincidence Compton imaging method. The targeted radioisotopes of this imaging method are specific nuclides that emit several gamma rays at the same time such as 60Co, 134Cs, and 111In, etc. Since their locations are determined in the intersections of two Compton cones, the most of cone traces would disappear in the three-dimensional space, which enhances the SNR and angular resolution. In this paper, the comparison of the double photon coincidence Compton imaging method and the single photon Compton imaging method was conducted by using GEANT4 Monte Carlo simulation.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation.

PubMed

Reeves, Anthony P; Xie, Yiting; Liu, Shuang

2017-04-01

With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset.

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

He, Liping; Zhu, Fulong, E-mail: zhufulong@hust.edu.cn; Duan, Ke

Ultrasonic waves are widely used, with applications including the medical, military, and chemical fields. However, there are currently no effective methods for ultrasonic power measurement. Previously, ultrasonic power measurement has been reliant on mechanical methods such as hydrophones and radiation force balances. This paper deals with ultrasonic power measurement based on an unconventional method: acousto-optic interaction. Compared with mechanical methods, the optical method has a greater ability to resist interference and also has reduced environmental requirements. Therefore, this paper begins with an experimental determination of the acoustic power in water contained in a glass tank using a set of opticalmore » devices. Because the light intensity of the diffraction image generated by acousto-optic interaction contains the required ultrasonic power information, specific software was written to extract the light intensity information from the image through a combination of filtering, binarization, contour extraction, and other image processing operations. The power value can then be obtained rapidly by processing the diffraction image using a computer. The results of this work show that the optical method offers advantages that include accuracy, speed, and a noncontact measurement method.« less

Ultrasonic power measurement system based on acousto-optic interaction.

PubMed

He, Liping; Zhu, Fulong; Chen, Yanming; Duan, Ke; Lin, Xinxin; Pan, Yongjun; Tao, Jiaquan

2016-05-01

Ultrasonic waves are widely used, with applications including the medical, military, and chemical fields. However, there are currently no effective methods for ultrasonic power measurement. Previously, ultrasonic power measurement has been reliant on mechanical methods such as hydrophones and radiation force balances. This paper deals with ultrasonic power measurement based on an unconventional method: acousto-optic interaction. Compared with mechanical methods, the optical method has a greater ability to resist interference and also has reduced environmental requirements. Therefore, this paper begins with an experimental determination of the acoustic power in water contained in a glass tank using a set of optical devices. Because the light intensity of the diffraction image generated by acousto-optic interaction contains the required ultrasonic power information, specific software was written to extract the light intensity information from the image through a combination of filtering, binarization, contour extraction, and other image processing operations. The power value can then be obtained rapidly by processing the diffraction image using a computer. The results of this work show that the optical method offers advantages that include accuracy, speed, and a noncontact measurement method.

Ultrasonic power measurement system based on acousto-optic interaction

NASA Astrophysics Data System (ADS)

He, Liping; Zhu, Fulong; Chen, Yanming; Duan, Ke; Lin, Xinxin; Pan, Yongjun; Tao, Jiaquan

2016-05-01

Ultrasonic waves are widely used, with applications including the medical, military, and chemical fields. However, there are currently no effective methods for ultrasonic power measurement. Previously, ultrasonic power measurement has been reliant on mechanical methods such as hydrophones and radiation force balances. This paper deals with ultrasonic power measurement based on an unconventional method: acousto-optic interaction. Compared with mechanical methods, the optical method has a greater ability to resist interference and also has reduced environmental requirements. Therefore, this paper begins with an experimental determination of the acoustic power in water contained in a glass tank using a set of optical devices. Because the light intensity of the diffraction image generated by acousto-optic interaction contains the required ultrasonic power information, specific software was written to extract the light intensity information from the image through a combination of filtering, binarization, contour extraction, and other image processing operations. The power value can then be obtained rapidly by processing the diffraction image using a computer. The results of this work show that the optical method offers advantages that include accuracy, speed, and a noncontact measurement method.

A novel method for the photographic recovery of fingermark impressions from ammunition cases using digital imaging.

PubMed

Porter, Glenn; Ebeyan, Robert; Crumlish, Charles; Renshaw, Adrian

2015-03-01

The photographic preservation of fingermark impression evidence found on ammunition cases remains problematic due to the cylindrical shape of the deposition substrate preventing complete capture of the impression in a single image. A novel method was developed for the photographic recovery of fingermarks from curved surfaces using digital imaging. The process involves the digital construction of a complete impression image made from several different images captured from multiple camera perspectives. Fingermark impressions deposited onto 9-mm and 0.22-caliber brass cartridge cases and a plastic 12-gauge shotgun shell were tested using various image parameters, including digital stitching method, number of images per 360° rotation of shell, image cropping, and overlap. The results suggest that this method may be successfully used to recover fingermark impression evidence from the surfaces of ammunition cases or other similar cylindrical surfaces. © 2014 American Academy of Forensic Sciences.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Light, sound, chemistry… action: state of the art optical methods for animal imaging.

PubMed

Ripoll, Jorge; Ntziachristos, Vasilis

2011-01-01

During recent years, macroscopic optical methods have been promoted from backstage to main actors in biological imaging. Many possible forms of energy conservation have been explored that involve light, including fluorescence emission, sound generated through absorption and bioluminescence, that is light generated through a chemical reaction. These physicochemical approaches for contrast generation have resulted in optical imaging methods that come with potent performance characteristics over simple epi-illumination optical imaging approaches of the past, and can play a central role in imaging applications in vivo as it pertains to modern biological and drug discovery, pre-clinical imaging and clinical applications. This review focuses on state of the art optical and opto-acoustic (photo-acoustic) imaging methods and discusses key performance characteristics that convert optical imaging from a qualitative modality to a powerful high-resolution and quantitative volumetric interrogation tool for operation through several millimeters of tissue depth.: © 2011 Elsevier Ltd . All rights reserved.

Vicinal light inspection of translucent materials

DOEpatents

Burns, Geroge R [Albuquerque, NM; Yang, Pin [Albuquerque, NM

2010-01-19

The present invention includes methods and apparatus for inspecting vicinally illuminated non-patterned areas of translucent materials. An initial image of the material is received. A second image is received following a relative translation between the material being inspected and a device generating the images. Each vicinally illuminated image includes a portion having optimal illumination, that can be extracted and stored in a composite image of the non-patterned area. The composite image includes aligned portions of the extracted image portions, and provides a composite having optimal illumination over a non-patterned area of the material to be inspected. The composite image can be processed by enhancement and object detection algorithms, to determine the presence of, and characterize any inhomogeneities present in the material.

Method of determining a content of a nuclear waste container

DOEpatents

Bernardi, Richard T.; Entwistle, David

2003-04-22

A method and apparatus are provided for identifying contents of a nuclear waste container. The method includes the steps of forming an image of the contents of the container using digital radiography, visually comparing contents of the image with expected contents of the container and performing computer tomography on the container when the visual inspection reveals an inconsistency between the contents of the image and the expected contents of the container.

Automatic Feature Extraction from Planetary Images

NASA Technical Reports Server (NTRS)

Troglio, Giulia; Le Moigne, Jacqueline; Benediktsson, Jon A.; Moser, Gabriele; Serpico, Sebastiano B.

2010-01-01

With the launch of several planetary missions in the last decade, a large amount of planetary images has already been acquired and much more will be available for analysis in the coming years. The image data need to be analyzed, preferably by automatic processing techniques because of the huge amount of data. Although many automatic feature extraction methods have been proposed and utilized for Earth remote sensing images, these methods are not always applicable to planetary data that often present low contrast and uneven illumination characteristics. Different methods have already been presented for crater extraction from planetary images, but the detection of other types of planetary features has not been addressed yet. Here, we propose a new unsupervised method for the extraction of different features from the surface of the analyzed planet, based on the combination of several image processing techniques, including a watershed segmentation and the generalized Hough Transform. The method has many applications, among which image registration and can be applied to arbitrary planetary images.

Malware analysis using visualized image matrices.

PubMed

Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

Guided filter-based fusion method for multiexposure images

NASA Astrophysics Data System (ADS)

Hou, Xinglin; Luo, Haibo; Qi, Feng; Zhou, Peipei

2016-11-01

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range camera. A weighted sum-based image fusion (IF) algorithm is proposed so as to express an HDR scene with a high-quality image. This method mainly includes three parts. First, two image features, i.e., gradients and well-exposedness are measured to estimate the initial weight maps. Second, the initial weight maps are refined by a guided filter, in which the source image is considered as the guidance image. This process could reduce the noise in initial weight maps and preserve more texture consistent with the original images. Finally, the fused image is constructed by a weighted sum of source images in the spatial domain. The main contributions of this method are the estimation of the initial weight maps and the appropriate use of the guided filter-based weight maps refinement. It provides accurate weight maps for IF. Compared to traditional IF methods, this algorithm avoids image segmentation, combination, and the camera response curve calibration. Furthermore, experimental results demonstrate the superiority of the proposed method in both subjective and objective evaluations.

Automatic extraction of planetary image features

NASA Technical Reports Server (NTRS)

LeMoigne-Stewart, Jacqueline J. (Inventor); Troglio, Giulia (Inventor); Benediktsson, Jon A. (Inventor); Serpico, Sebastiano B. (Inventor); Moser, Gabriele (Inventor)

2013-01-01

A method for the extraction of Lunar data and/or planetary features is provided. The feature extraction method can include one or more image processing techniques, including, but not limited to, a watershed segmentation and/or the generalized Hough Transform. According to some embodiments, the feature extraction method can include extracting features, such as, small rocks. According to some embodiments, small rocks can be extracted by applying a watershed segmentation algorithm to the Canny gradient. According to some embodiments, applying a watershed segmentation algorithm to the Canny gradient can allow regions that appear as close contours in the gradient to be segmented.

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

Object extraction method for image synthesis

NASA Astrophysics Data System (ADS)

Inoue, Seiki

1991-11-01

The extraction of component objects from images is fundamentally important for image synthesis. In TV program production, one useful method is the Video-Matte technique for specifying the necessary boundary of an object. This, however, involves some manually intricate and tedious processes. A new method proposed in this paper can reduce the needed level of operator skill and simplify object extraction. The object is automatically extracted by just a simple drawing of a thick boundary line. The basic principle involves a thinning of the thick boundary line binary image using the edge intensity of the original image. This method has many practical advantages, including the simplicity of specifying an object, the high accuracy of thinned-out boundary line, its ease of application to moving images, and the lack of any need for adjustment.

On detection of median filtering in digital images

NASA Astrophysics Data System (ADS)

Kirchner, Matthias; Fridrich, Jessica

2010-01-01

In digital image forensics, it is generally accepted that intentional manipulations of the image content are most critical and hence numerous forensic methods focus on the detection of such 'malicious' post-processing. However, it is also beneficial to know as much as possible about the general processing history of an image, including content-preserving operations, since they can affect the reliability of forensic methods in various ways. In this paper, we present a simple yet effective technique to detect median filtering in digital images-a widely used denoising and smoothing operator. As a great variety of forensic methods relies on some kind of a linearity assumption, a detection of non-linear median filtering is of particular interest. The effectiveness of our method is backed with experimental evidence on a large image database.

Research on polarization imaging information parsing method

NASA Astrophysics Data System (ADS)

Yuan, Hongwu; Zhou, Pucheng; Wang, Xiaolong

2016-11-01

Polarization information parsing plays an important role in polarization imaging detection. This paper focus on the polarization information parsing method: Firstly, the general process of polarization information parsing is given, mainly including polarization image preprocessing, multiple polarization parameters calculation, polarization image fusion and polarization image tracking, etc.; And then the research achievements of the polarization information parsing method are presented, in terms of polarization image preprocessing, the polarization image registration method based on the maximum mutual information is designed. The experiment shows that this method can improve the precision of registration and be satisfied the need of polarization information parsing; In terms of multiple polarization parameters calculation, based on the omnidirectional polarization inversion model is built, a variety of polarization parameter images are obtained and the precision of inversion is to be improve obviously; In terms of polarization image fusion , using fuzzy integral and sparse representation, the multiple polarization parameters adaptive optimal fusion method is given, and the targets detection in complex scene is completed by using the clustering image segmentation algorithm based on fractal characters; In polarization image tracking, the average displacement polarization image characteristics of auxiliary particle filtering fusion tracking algorithm is put forward to achieve the smooth tracking of moving targets. Finally, the polarization information parsing method is applied to the polarization imaging detection of typical targets such as the camouflage target, the fog and latent fingerprints.

Estimation of Noise Properties for TV-regularized Image Reconstruction in Computed Tomography

PubMed Central

Sánchez, Adrian A.

2016-01-01

A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128 × 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR. PMID:26308968

Estimation of noise properties for TV-regularized image reconstruction in computed tomography.

PubMed

Sánchez, Adrian A

2015-09-21

A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128 × 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR.

Estimation of noise properties for TV-regularized image reconstruction in computed tomography

NASA Astrophysics Data System (ADS)

Sánchez, Adrian A.

2015-09-01

A method for predicting the image covariance resulting from total-variation-penalized iterative image reconstruction (TV-penalized IIR) is presented and demonstrated in a variety of contexts. The method is validated against the sample covariance from statistical noise realizations for a small image using a variety of comparison metrics. Potential applications for the covariance approximation include investigation of image properties such as object- and signal-dependence of noise, and noise stationarity. These applications are demonstrated, along with the construction of image pixel variance maps for two-dimensional 128× 128 pixel images. Methods for extending the proposed covariance approximation to larger images and improving computational efficiency are discussed. Future work will apply the developed methodology to the construction of task-based image quality metrics such as the Hotelling observer detectability for TV-based IIR.

Infrared Ship Target Segmentation Based on Spatial Information Improved FCM.

PubMed

Bai, Xiangzhi; Chen, Zhiguo; Zhang, Yu; Liu, Zhaoying; Lu, Yi

2016-12-01

Segmentation of infrared (IR) ship images is always a challenging task, because of the intensity inhomogeneity and noise. The fuzzy C-means (FCM) clustering is a classical method widely used in image segmentation. However, it has some shortcomings, like not considering the spatial information or being sensitive to noise. In this paper, an improved FCM method based on the spatial information is proposed for IR ship target segmentation. The improvements include two parts: 1) adding the nonlocal spatial information based on the ship target and 2) using the spatial shape information of the contour of the ship target to refine the local spatial constraint by Markov random field. In addition, the results of K -means are used to initialize the improved FCM method. Experimental results show that the improved method is effective and performs better than the existing methods, including the existing FCM methods, for segmentation of the IR ship images.

Tomographic imaging using poissonian detector data

DOEpatents

Aspelmeier, Timo; Ebel, Gernot; Hoeschen, Christoph

2013-10-15

An image reconstruction method for reconstructing a tomographic image (f.sub.j) of a region of investigation within an object (1), comprises the steps of providing detector data (y.sub.i) comprising Poisson random values measured at an i-th of a plurality of different positions, e.g. i=(k,l) with pixel index k on a detector device and angular index l referring to both the angular position (.alpha..sub.l) and the rotation radius (r.sub.l) of the detector device (10) relative to the object (1), providing a predetermined system matrix A.sub.ij assigning a j-th voxel of the object (1) to the i-th detector data (y.sub.i), and reconstructing the tomographic image (f.sub.j) based on the detector data (y.sub.i), said reconstructing step including a procedure of minimizing a functional F(f) depending on the detector data (y.sub.i) and the system matrix A.sub.ij and additionally including a sparse or compressive representation of the object (1) in an orthobasis T, wherein the tomographic image (f.sub.j) represents the global minimum of the functional F(f). Furthermore, an imaging method and an imaging device using the image reconstruction method are described.

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

PubMed

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

VQone MATLAB toolbox: A graphical experiment builder for image and video quality evaluations: VQone MATLAB toolbox.

PubMed

Nuutinen, Mikko; Virtanen, Toni; Rummukainen, Olli; Häkkinen, Jukka

2016-03-01

This article presents VQone, a graphical experiment builder, written as a MATLAB toolbox, developed for image and video quality ratings. VQone contains the main elements needed for the subjective image and video quality rating process. This includes building and conducting experiments and data analysis. All functions can be controlled through graphical user interfaces. The experiment builder includes many standardized image and video quality rating methods. Moreover, it enables the creation of new methods or modified versions from standard methods. VQone is distributed free of charge under the terms of the GNU general public license and allows code modifications to be made so that the program's functions can be adjusted according to a user's requirements. VQone is available for download from the project page (http://www.helsinki.fi/psychology/groups/visualcognition/).

A Rotor Tip Vortex Tracing Algorithm for Image Post-Processing

NASA Technical Reports Server (NTRS)

Overmeyer, Austin D.

2015-01-01

A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the tip vortex location compared to other methods presented in literature.

Registration of T2-weighted and diffusion-weighted MR images of the prostate: comparison between manual and landmark-based methods

NASA Astrophysics Data System (ADS)

Peng, Yahui; Jiang, Yulei; Soylu, Fatma N.; Tomek, Mark; Sensakovic, William; Oto, Aytekin

2012-02-01

Quantitative analysis of multi-parametric magnetic resonance (MR) images of the prostate, including T2-weighted (T2w) and diffusion-weighted (DW) images, requires accurate image registration. We compared two registration methods between T2w and DW images. We collected pre-operative MR images of 124 prostate cancer patients (68 patients scanned with a GE scanner and 56 with Philips scanners). A landmark-based rigid registration was done based on six prostate landmarks in both T2w and DW images identified by a radiologist. Independently, a researcher manually registered the same images. A radiologist visually evaluated the registration results by using a 5-point ordinal scale of 1 (worst) to 5 (best). The Wilcoxon signed-rank test was used to determine whether the radiologist's ratings of the results of the two registration methods were significantly different. Results demonstrated that both methods were accurate: the average ratings were 4.2, 3.3, and 3.8 for GE, Philips, and all images, respectively, for the landmark-based method; and 4.6, 3.7, and 4.2, respectively, for the manual method. The manual registration results were more accurate than the landmark-based registration results (p < 0.0001 for GE, Philips, and all images). Therefore, the manual method produces more accurate registration between T2w and DW images than the landmark-based method.

System and method for magnetic current density imaging at ultra low magnetic fields

DOEpatents

Espy, Michelle A.; George, John Stevens; Kraus, Robert Henry; Magnelind, Per; Matlashov, Andrei Nikolaevich; Tucker, Don; Turovets, Sergei; Volegov, Petr Lvovich

2016-02-09

Preferred systems can include an electrical impedance tomography apparatus electrically connectable to an object; an ultra low field magnetic resonance imaging apparatus including a plurality of field directions and disposable about the object; a controller connected to the ultra low field magnetic resonance imaging apparatus and configured to implement a sequencing of one or more ultra low magnetic fields substantially along one or more of the plurality of field directions; and a display connected to the controller, and wherein the controller is further configured to reconstruct a displayable image of an electrical current density in the object. Preferred methods, apparatuses, and computer program products are also disclosed.

New software developments for quality mesh generation and optimization from biomedical imaging data.

PubMed

Yu, Zeyun; Wang, Jun; Gao, Zhanheng; Xu, Ming; Hoshijima, Masahiko

2014-01-01

In this paper we present a new software toolkit for generating and optimizing surface and volumetric meshes from three-dimensional (3D) biomedical imaging data, targeted at image-based finite element analysis of some biomedical activities in a single material domain. Our toolkit includes a series of geometric processing algorithms including surface re-meshing and quality-guaranteed tetrahedral mesh generation and optimization. All methods described have been encapsulated into a user-friendly graphical interface for easy manipulation and informative visualization of biomedical images and mesh models. Numerous examples are presented to demonstrate the effectiveness and efficiency of the described methods and toolkit. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A Methodology for Anatomic Ultrasound Image Diagnostic Quality Assessment.

PubMed

Hemmsen, Martin Christian; Lange, Theis; Brandt, Andreas Hjelm; Nielsen, Michael Bachmann; Jensen, Jorgen Arendt

2017-01-01

This paper discusses the methods for the assessment of ultrasound image quality based on our experiences with evaluating new methods for anatomic imaging. It presents a methodology to ensure a fair assessment between competing imaging methods using clinically relevant evaluations. The methodology is valuable in the continuing process of method optimization and guided development of new imaging methods. It includes a three phased study plan covering from initial prototype development to clinical assessment. Recommendations to the clinical assessment protocol, software, and statistical analysis are presented. Earlier uses of the methodology has shown that it ensures validity of the assessment, as it separates the influences between developer, investigator, and assessor once a research protocol has been established. This separation reduces confounding influences on the result from the developer to properly reveal the clinical value. This paper exemplifies the methodology using recent studies of synthetic aperture sequential beamforming tissue harmonic imaging.

Supervised learning based multimodal MRI brain tumour segmentation using texture features from supervoxels.

PubMed

Soltaninejad, Mohammadreza; Yang, Guang; Lambrou, Tryphon; Allinson, Nigel; Jones, Timothy L; Barrick, Thomas R; Howe, Franklyn A; Ye, Xujiong

2018-04-01

Accurate segmentation of brain tumour in magnetic resonance images (MRI) is a difficult task due to various tumour types. Using information and features from multimodal MRI including structural MRI and isotropic (p) and anisotropic (q) components derived from the diffusion tensor imaging (DTI) may result in a more accurate analysis of brain images. We propose a novel 3D supervoxel based learning method for segmentation of tumour in multimodal MRI brain images (conventional MRI and DTI). Supervoxels are generated using the information across the multimodal MRI dataset. For each supervoxel, a variety of features including histograms of texton descriptor, calculated using a set of Gabor filters with different sizes and orientations, and first order intensity statistical features are extracted. Those features are fed into a random forests (RF) classifier to classify each supervoxel into tumour core, oedema or healthy brain tissue. The method is evaluated on two datasets: 1) Our clinical dataset: 11 multimodal images of patients and 2) BRATS 2013 clinical dataset: 30 multimodal images. For our clinical dataset, the average detection sensitivity of tumour (including tumour core and oedema) using multimodal MRI is 86% with balanced error rate (BER) 7%; while the Dice score for automatic tumour segmentation against ground truth is 0.84. The corresponding results of the BRATS 2013 dataset are 96%, 2% and 0.89, respectively. The method demonstrates promising results in the segmentation of brain tumour. Adding features from multimodal MRI images can largely increase the segmentation accuracy. The method provides a close match to expert delineation across all tumour grades, leading to a faster and more reproducible method of brain tumour detection and delineation to aid patient management. Copyright © 2018 Elsevier B.V. All rights reserved.

SU-E-J-89: Deformable Registration Method Using B-TPS in Radiotherapy.

PubMed

Xie, Y

2012-06-01

A novel deformable registration method for four-dimensional computed tomography (4DCT) images is developed in radiation therapy. The proposed method combines the thin plate spline (TPS) and B-spline together to achieve high accuracy and high efficiency. The method consists of two steps. First, TPS is used as a global registration method to deform large unfit regions in the moving image to match counterpart in the reference image. Then B-spline is used for local registration, the previous deformed moving image is further deformed to match the reference image more accurately. Two clinical CT image sets, including one pair of lung and one pair of liver, are simulated using the proposed algorithm, which results in a tremendous improvement in both run-time and registration quality, compared with the conventional methods solely using either TPS or B-spline. The proposed method can combine the efficiency of TPS and the accuracy of B-spline, performing good adaptively and robust in registration of clinical 4DCT image. © 2012 American Association of Physicists in Medicine.

An Open Source Agenda for Research Linking Text and Image Content Features.

ERIC Educational Resources Information Center

Goodrum, Abby A.; Rorvig, Mark E.; Jeong, Ki-Tai; Suresh, Chitturi

2001-01-01

Proposes methods to utilize image primitives to support term assignment for image classification. Proposes to release code for image analysis in a common tool set for other researchers to use. Of particular focus is the expansion of work by researchers in image indexing to include image content-based feature extraction capabilities in their work.…

Multilinear Graph Embedding: Representation and Regularization for Images.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting

2014-02-01

Given a set of images, finding a compact and discriminative representation is still a big challenge especially when multiple latent factors are hidden in the way of data generation. To represent multifactor images, although multilinear models are widely used to parameterize the data, most methods are based on high-order singular value decomposition (HOSVD), which preserves global statistics but interprets local variations inadequately. To this end, we propose a novel method, called multilinear graph embedding (MGE), as well as its kernelization MKGE to leverage the manifold learning techniques into multilinear models. Our method theoretically links the linear, nonlinear, and multilinear dimensionality reduction. We also show that the supervised MGE encodes informative image priors for image regularization, provided that an image is represented as a high-order tensor. From our experiments on face and gait recognition, the superior performance demonstrates that MGE better represents multifactor images than classic methods, including HOSVD and its variants. In addition, the significant improvement in image (or tensor) completion validates the potential of MGE for image regularization.

Fast Acquisition and Reconstruction of Optical Coherence Tomography Images via Sparse Representation

PubMed Central

Li, Shutao; McNabb, Ryan P.; Nie, Qing; Kuo, Anthony N.; Toth, Cynthia A.; Izatt, Joseph A.; Farsiu, Sina

2014-01-01

In this paper, we present a novel technique, based on compressive sensing principles, for reconstruction and enhancement of multi-dimensional image data. Our method is a major improvement and generalization of the multi-scale sparsity based tomographic denoising (MSBTD) algorithm we recently introduced for reducing speckle noise. Our new technique exhibits several advantages over MSBTD, including its capability to simultaneously reduce noise and interpolate missing data. Unlike MSBTD, our new method does not require an a priori high-quality image from the target imaging subject and thus offers the potential to shorten clinical imaging sessions. This novel image restoration method, which we termed sparsity based simultaneous denoising and interpolation (SBSDI), utilizes sparse representation dictionaries constructed from previously collected datasets. We tested the SBSDI algorithm on retinal spectral domain optical coherence tomography images captured in the clinic. Experiments showed that the SBSDI algorithm qualitatively and quantitatively outperforms other state-of-the-art methods. PMID:23846467

High resolution three-dimensional photoacoustic imaging of human finger joints in vivo

NASA Astrophysics Data System (ADS)

Xi, Lei; Jiang, Huabei

2015-08-01

We present a method for noninvasively imaging the hand joints using a three-dimensional (3D) photoacoustic imaging (PAI) system. This 3D PAI system utilizes cylindrical scanning in data collection and virtual-detector concept in image reconstruction. The maximum lateral and axial resolutions of the PAI system are 70 μm and 240 μm. The cross-sectional photoacoustic images of a healthy joint clearly exhibited major internal structures including phalanx and tendons, which are not available from the current photoacoustic imaging methods. The in vivo PAI results obtained are comparable with the corresponding 3.0 T MRI images of the finger joint. This study suggests that the proposed method has the potential to be used in early detection of joint diseases such as osteoarthritis.

High-resolution reconstruction for terahertz imaging.

PubMed

Xu, Li-Min; Fan, Wen-Hui; Liu, Jia

2014-11-20

We present a high-resolution (HR) reconstruction model and algorithms for terahertz imaging, taking advantage of super-resolution methodology and algorithms. The algorithms used include projection onto a convex sets approach, iterative backprojection approach, Lucy-Richardson iteration, and 2D wavelet decomposition reconstruction. Using the first two HR reconstruction methods, we successfully obtain HR terahertz images with improved definition and lower noise from four low-resolution (LR) 22×24 terahertz images taken from our homemade THz-TDS system at the same experimental conditions with 1.0 mm pixel. Using the last two HR reconstruction methods, we transform one relatively LR terahertz image to a HR terahertz image with decreased noise. This indicates potential application of HR reconstruction methods in terahertz imaging with pulsed and continuous wave terahertz sources.

Hybrid statistics-simulations based method for atom-counting from ADF STEM images.

PubMed

De Wael, Annelies; De Backer, Annick; Jones, Lewys; Nellist, Peter D; Van Aert, Sandra

2017-06-01

A hybrid statistics-simulations based method for atom-counting from annular dark field scanning transmission electron microscopy (ADF STEM) images of monotype crystalline nanostructures is presented. Different atom-counting methods already exist for model-like systems. However, the increasing relevance of radiation damage in the study of nanostructures demands a method that allows atom-counting from low dose images with a low signal-to-noise ratio. Therefore, the hybrid method directly includes prior knowledge from image simulations into the existing statistics-based method for atom-counting, and accounts in this manner for possible discrepancies between actual and simulated experimental conditions. It is shown by means of simulations and experiments that this hybrid method outperforms the statistics-based method, especially for low electron doses and small nanoparticles. The analysis of a simulated low dose image of a small nanoparticle suggests that this method allows for far more reliable quantitative analysis of beam-sensitive materials. Copyright © 2017 Elsevier B.V. All rights reserved.

SU-E-J-109: Accurate Contour Transfer Between Different Image Modalities Using a Hybrid Deformable Image Registration and Fuzzy Connected Image Segmentation Method.

PubMed

Yang, C; Paulson, E; Li, X

2012-06-01

To develop and evaluate a tool that can improve the accuracy of contour transfer between different image modalities under challenging conditions of low image contrast and large image deformation, comparing to a few commonly used methods, for radiation treatment planning. The software tool includes the following steps and functionalities: (1) accepting input of images of different modalities, (2) converting existing contours on reference images (e.g., MRI) into delineated volumes and adjusting the intensity within the volumes to match target images (e.g., CT) intensity distribution for enhanced similarity metric, (3) registering reference and target images using appropriate deformable registration algorithms (e.g., B-spline, demons) and generate deformed contours, (4) mapping the deformed volumes on target images, calculating mean, variance, and center of mass as the initialization parameters for consecutive fuzzy connectedness (FC) image segmentation on target images, (5) generate affinity map from FC segmentation, (6) achieving final contours by modifying the deformed contours using the affinity map with a gradient distance weighting algorithm. The tool was tested with the CT and MR images of four pancreatic cancer patients acquired at the same respiration phase to minimize motion distortion. Dice's Coefficient was calculated against direct delineation on target image. Contours generated by various methods, including rigid transfer, auto-segmentation, deformable only transfer and proposed method, were compared. Fuzzy connected image segmentation needs careful parameter initialization and user involvement. Automatic contour transfer by multi-modality deformable registration leads up to 10% of accuracy improvement over the rigid transfer. Two extra proposed steps of adjusting intensity distribution and modifying the deformed contour with affinity map improve the transfer accuracy further to 14% averagely. Deformable image registration aided by contrast adjustment and fuzzy connectedness segmentation improves the contour transfer accuracy between multi-modality images, particularly with large deformation and low image contrast. © 2012 American Association of Physicists in Medicine.

Molecular imaging in neuroendocrine tumors: molecular uptake mechanisms and clinical results.

PubMed

Koopmans, Klaas P; Neels, Oliver N; Kema, Ido P; Elsinga, Philip H; Links, Thera P; de Vries, Elisabeth G E; Jager, Pieter L

2009-09-01

Neuroendocrine tumors can originate almost everywhere in the body and consist of a great variety of subtypes. This paper focuses on molecular imaging methods using nuclear medicine techniques in neuroendocrine tumors, coupling molecular uptake mechanisms of radiotracers with clinical results. A non-systematic review is presented on receptor based and metabolic imaging methods. Receptor-based imaging covers the molecular backgrounds of somatostatin, vaso-intestinal peptide (VIP), bombesin and cholecystokinin (CCK) receptors and their link with nuclear imaging. Imaging methods based on specific metabolic properties include meta-iodo-benzylguanide (MIBG) and dimercapto-sulphuric acid (DMSA-V) scintigraphy as well as more modern positron emission tomography (PET)-based methods using radio-labeled analogues of amino acids, glucose, dihydroxyphenylalanine (DOPA), dopamine and tryptophan. Diagnostic sensitivities are presented for each imaging method and for each neuroendocrine tumor subtype. Finally, a Forest plot analysis of diagnostic performance is presented for each tumor type in order to provide a comprehensive overview for clinical use.

Denoising Sparse Images from GRAPPA using the Nullspace Method (DESIGN)

PubMed Central

Weller, Daniel S.; Polimeni, Jonathan R.; Grady, Leo; Wald, Lawrence L.; Adalsteinsson, Elfar; Goyal, Vivek K

2011-01-01

To accelerate magnetic resonance imaging using uniformly undersampled (nonrandom) parallel imaging beyond what is achievable with GRAPPA alone, the Denoising of Sparse Images from GRAPPA using the Nullspace method (DESIGN) is developed. The trade-off between denoising and smoothing the GRAPPA solution is studied for different levels of acceleration. Several brain images reconstructed from uniformly undersampled k-space data using DESIGN are compared against reconstructions using existing methods in terms of difference images (a qualitative measure), PSNR, and noise amplification (g-factors) as measured using the pseudo-multiple replica method. Effects of smoothing, including contrast loss, are studied in synthetic phantom data. In the experiments presented, the contrast loss and spatial resolution are competitive with existing methods. Results for several brain images demonstrate significant improvements over GRAPPA at high acceleration factors in denoising performance with limited blurring or smoothing artifacts. In addition, the measured g-factors suggest that DESIGN mitigates noise amplification better than both GRAPPA and L1 SPIR-iT (the latter limited here by uniform undersampling). PMID:22213069

Multiscale infrared and visible image fusion using gradient domain guided image filtering

NASA Astrophysics Data System (ADS)

Zhu, Jin; Jin, Weiqi; Li, Li; Han, Zhenghao; Wang, Xia

2018-03-01

For better surveillance with infrared and visible imaging, a novel hybrid multiscale decomposition fusion method using gradient domain guided image filtering (HMSD-GDGF) is proposed in this study. In this method, hybrid multiscale decomposition with guided image filtering and gradient domain guided image filtering of source images are first applied before the weight maps of each scale are obtained using a saliency detection technology and filtering means with three different fusion rules at different scales. The three types of fusion rules are for small-scale detail level, large-scale detail level, and base level. Finally, the target becomes more salient and can be more easily detected in the fusion result, with the detail information of the scene being fully displayed. After analyzing the experimental comparisons with state-of-the-art fusion methods, the HMSD-GDGF method has obvious advantages in fidelity of salient information (including structural similarity, brightness, and contrast), preservation of edge features, and human visual perception. Therefore, visual effects can be improved by using the proposed HMSD-GDGF method.

Large-scale image region documentation for fully automated image biomarker algorithm development and evaluation

PubMed Central

Reeves, Anthony P.; Xie, Yiting; Liu, Shuang

2017-01-01

Abstract. With the advent of fully automated image analysis and modern machine learning methods, there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. This paper presents a method and implementation for facilitating such datasets that addresses the critical issue of size scaling for algorithm validation and evaluation; current evaluation methods that are usually used in academic studies do not scale to large datasets. This method includes protocols for the documentation of many regions in very large image datasets; the documentation may be incrementally updated by new image data and by improved algorithm outcomes. This method has been used for 5 years in the context of chest health biomarkers from low-dose chest CT images that are now being used with increasing frequency in lung cancer screening practice. The lung scans are segmented into over 100 different anatomical regions, and the method has been applied to a dataset of over 20,000 chest CT images. Using this framework, the computer algorithms have been developed to achieve over 90% acceptable image segmentation on the complete dataset. PMID:28612037

Advanced Millimeter-Wave Imaging Enhances Security Screening

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

Sheen, David M.; Bernacki, Bruce E.; McMakin, Douglas L.

2012-01-12

Millimeter-wave imaging is rapidly gaining acceptance for passenger screening at airports and other secured facilities. This paper details a number of techniques developed over the last several years including novel image reconstruction and display techniques, polarimetric imaging techniques, array switching schemes, as well as high frequency high bandwidth techniques. Implementation of some of these methods will increase the cost and complexity of the mm-wave security portal imaging systems. RF photonic methods may provide new solutions to the design and development of the sequentially switched linear mm-wave arrays that are the key element in the mm-wave portal imaging systems.

Advanced Millimeter-Wave Security Portal Imaging Techniques

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

Sheen, David M.; Bernacki, Bruce E.; McMakin, Douglas L.

2012-04-01

Millimeter-wave imaging is rapidly gaining acceptance for passenger screening at airports and other secured facilities. This paper details a number of techniques developed over the last several years including novel image reconstruction and display techniques, polarimetric imaging techniques, array switching schemes, as well as high frequency high bandwidth techniques. Implementation of some of these methods will increase the cost and complexity of the mm-wave security portal imaging systems. RF photonic methods may provide new solutions to the design and development of the sequentially switched linear mm-wave arrays that are the key element in the mm-wave portal imaging systems.

Ultrasound biomicroscopy. High-frequency ultrasound imaging of the eye at microscopic resolution.

PubMed

Pavlin, C J; Foster, F S

1998-11-01

UBM presents us with a new method of imaging the anterior segment of the eye at high resolution. Its strengths lie in its ability to produce cross-sections of the living eye at microscopic resolution without violating the integrity of the globe. UBM, although lacking the resolution of optical microscopy, gives us images in living eyes without affecting the internal relationships of the structures imaged. There are many other applications of this new imaging method. Examples of other uses include imaging adnexal pathology, assessing corneal changes with refractive surgery, the assessment of trauma, and determination of intraocular lens position.

The Study of Residential Areas Extraction Based on GF-3 Texture Image Segmentation

NASA Astrophysics Data System (ADS)

Shao, G.; Luo, H.; Tao, X.; Ling, Z.; Huang, Y.

2018-04-01

The study chooses the standard stripe and dual polarization SAR images of GF-3 as the basic data. Residential areas extraction processes and methods based upon GF-3 images texture segmentation are compared and analyzed. GF-3 images processes include radiometric calibration, complex data conversion, multi-look processing, images filtering, and then conducting suitability analysis for different images filtering methods, the filtering result show that the filtering method of Kuan is efficient for extracting residential areas, then, we calculated and analyzed the texture feature vectors using the GLCM (the Gary Level Co-occurrence Matrix), texture feature vectors include the moving window size, step size and angle, the result show that window size is 11*11, step is 1, and angle is 0°, which is effective and optimal for the residential areas extracting. And with the FNEA (Fractal Net Evolution Approach), we segmented the GLCM texture images, and extracted the residential areas by threshold setting. The result of residential areas extraction verified and assessed by confusion matrix. Overall accuracy is 0.897, kappa is 0.881, and then we extracted the residential areas by SVM classification based on GF-3 images, the overall accuracy is less 0.09 than the accuracy of extraction method based on GF-3 Texture Image Segmentation. We reached the conclusion that residential areas extraction based on GF-3 SAR texture image multi-scale segmentation is simple and highly accurate. although, it is difficult to obtain multi-spectrum remote sensing image in southern China, in cloudy and rainy weather throughout the year, this paper has certain reference significance.

Segmentation of medical images using explicit anatomical knowledge

NASA Astrophysics Data System (ADS)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

A suite of phantom-based test methods for assessing image quality of photoacoustic tomography systems

NASA Astrophysics Data System (ADS)

Vogt, William C.; Jia, Congxian; Wear, Keith A.; Garra, Brian S.; Pfefer, T. Joshua

2017-03-01

As Photoacoustic Tomography (PAT) matures and undergoes clinical translation, objective performance test methods are needed to facilitate device development, regulatory clearance and clinical quality assurance. For mature medical imaging modalities such as CT, MRI, and ultrasound, tissue-mimicking phantoms are frequently incorporated into consensus standards for performance testing. A well-validated set of phantom-based test methods is needed for evaluating performance characteristics of PAT systems. To this end, we have constructed phantoms using a custom tissue-mimicking material based on PVC plastisol with tunable, biologically-relevant optical and acoustic properties. Each phantom is designed to enable quantitative assessment of one or more image quality characteristics including 3D spatial resolution, spatial measurement accuracy, ultrasound/PAT co-registration, uniformity, penetration depth, geometric distortion, sensitivity, and linearity. Phantoms contained targets including high-intensity point source targets and dye-filled tubes. This suite of phantoms was used to measure the dependence of performance of a custom PAT system (equipped with four interchangeable linear array transducers of varying design) on design parameters (e.g., center frequency, bandwidth, element geometry). Phantoms also allowed comparison of image artifacts, including surface-generated clutter and bandlimited sensing artifacts. Results showed that transducer design parameters create strong variations in performance including a trade-off between resolution and penetration depth, which could be quantified with our method. This study demonstrates the utility of phantom-based image quality testing in device performance assessment, which may guide development of consensus standards for PAT systems.

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

PubMed Central

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease. PMID:27977767

Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

PubMed

Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

2016-01-01

Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the recognition accuracies of the training set and the testing set were 97.64% and 94.74%, respectively. Semi-supervised models for disease recognition were built based on the 45 effective features that were used for building the optimal SVM model. For the optimal semi-supervised models built with three ratios of labeled to unlabeled samples in the training set, the recognition accuracies of the training set and the testing set were both approximately 80%. The results indicated that image recognition of the four alfalfa leaf diseases can be implemented with high accuracy. This study provides a feasible solution for lesion image segmentation and image recognition of alfalfa leaf disease.

AEG-1 promoter-mediated imaging of prostate cancer

PubMed Central

Bhatnagar, Akrita; Wang, Yuchuan; Mease, Ronnie C.; Gabrielson, Matthew; Sysa, Polina; Minn, Il; Green, Gilbert; Simmons, Brian; Gabrielson, Kathleen; Sarkar, Siddik; Fisher, Paul B.; Pomper, Martin G.

2014-01-01

We describe a new imaging method for detecting prostate cancer, whether localized or disseminated and metastatic to soft tissues and bone. The method relies on the use of imaging reporter genes under the control of the promoter of AEG-1 (MTDH), which is selectively active only in malignant cells. Through systemic, nanoparticle-based delivery of the imaging construct, lesions can be identified through bioluminescence imaging and single photon emission-computed tomography in the PC3-ML murine model of prostate cancer at high sensitivity. This approach is applicable for the detection of prostate cancer metastases, including bone lesions for which there is no current reliable agent for non-invasive clinical imaging. Further, the approach compares favorably to accepted and emerging clinical standards, including positron emission tomography with [18F]fluorodeoxyglucose and [18F]sodium fluoride. Our results offer a preclinical proof of concept that rationalizes clinical evaluation in patients with advanced prostate cancer. PMID:25145668

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters – TCCF, Tθ, Tx and Ty are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images. PMID:26601045

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method.

PubMed

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters - T CCF, T θ, T x and T y are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images.

Optical Biopsy: A New Frontier in Endoscopic Detection and Diagnosis

PubMed Central

WANG, THOMAS D.; VAN DAM, JACQUES

2007-01-01

Endoscopic diagnosis currently relies on the ability of the operator to visualize abnormal patterns in the image created by light reflected from the mucosal surface of the gastrointestinal tract. Advances in fiber optics, light sources, detectors, and molecular biology have led to the development of several novel methods for tissue evaluation in situ. The term “optical biopsy” refers to methods that use the properties of light to enable the operator to make an instant diagnosis at endoscopy, previously possible only by using histological or cytological analysis. Promising imaging techniques include fluorescence endoscopy, optical coherence tomography, confocal microendoscopy, and molecular imaging. Point detection schemes under development include light scattering and Raman spectroscopy. Such advanced diagnostic methods go beyond standard endoscopic techniques by offering improved image resolution, contrast, and tissue penetration and providing biochemical and molecular information about mucosal disease. This review describes the basic biophysics of light-tissue interactions, assesses the strengths and weaknesses of each method, and examines clinical and preclinical evidence for each approach. PMID:15354274

Imaging Modalities Relevant to Intracranial Pressure Assessment in Astronauts: A Case-Based Discussion

NASA Technical Reports Server (NTRS)

Sargsyan, Ashot E.; Kramer, Larry A.; Hamilton, Douglas R.; Hamilton, Douglas R.; Fogarty, Jennifer; Polk, J. D.

2010-01-01

Introduction: Intracranial pressure (ICP) elevation has been inferred or documented in a number of space crewmembers. Recent advances in noninvasive imaging technology offer new possibilities for ICP assessment. Most International Space Station (ISS) partner agencies have adopted a battery of occupational health monitoring tests including magnetic resonance imaging (MRI) pre- and postflight, and high-resolution sonography of the orbital structures in all mission phases including during flight. We hypothesize that joint consideration of data from the two techniques has the potential to improve quality and continuity of crewmember monitoring and care. Methods: Specially designed MRI and sonographic protocols were used to image eyes and optic nerves (ON) including the meningeal sheaths. Specific crewmembers multi-modality imaging data were analyzed to identify points of mutual validation as well as unique features of complementary nature. Results and Conclusion: Magnetic resonance imaging (MRI) and high-resolution sonography are both tomographic methods, however images obtained by the two modalities are based on different physical phenomena and use different acquisition principles. Consideration of the images acquired by these two modalities allows cross-validating findings related to the volume and fluid content of the ON subarachnoid space, shape of the globe, and other anatomical features of the orbit. Each of the imaging modalities also has unique advantages, making them complementary techniques.

Flexible reduced field of view magnetic resonance imaging based on single-shot spatiotemporally encoded technique

NASA Astrophysics Data System (ADS)

Li, Jing; Cai, Cong-Bo; Chen, Lin; Chen, Ying; Qu, Xiao-Bo; Cai, Shu-Hui

2015-10-01

In many ultrafast imaging applications, the reduced field-of-view (rFOV) technique is often used to enhance the spatial resolution and field inhomogeneity immunity of the images. The stationary-phase characteristic of the spatiotemporally-encoded (SPEN) method offers an inherent applicability to rFOV imaging. In this study, a flexible rFOV imaging method is presented and the superiority of the SPEN approach in rFOV imaging is demonstrated. The proposed method is validated with phantom and in vivo rat experiments, including cardiac imaging and contrast-enhanced perfusion imaging. For comparison, the echo planar imaging (EPI) experiments with orthogonal RF excitation are also performed. The results show that the signal-to-noise ratios of the images acquired by the proposed method can be higher than those obtained with the rFOV EPI. Moreover, the proposed method shows better performance in the cardiac imaging and perfusion imaging of rat kidney, and it can scan one or more regions of interest (ROIs) with high spatial resolution in a single shot. It might be a favorable solution to ultrafast imaging applications in cases with severe susceptibility heterogeneities, such as cardiac imaging and perfusion imaging. Furthermore, it might be promising in applications with separate ROIs, such as mammary and limb imaging. Project supported by the National Natural Science Foundation of China (Grant Nos. 11474236, 81171331, and U1232212).

Container Surface Evaluation by Function Estimation

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

Wendelberger, James G.

Container images are analyzed for specific surface features, such as, pits, cracks, and corrosion. The detection of these features is confounded with complicating features. These complication features include: shape/curvature, welds, edges, scratches, foreign objects among others. A method is provided to discriminate between the various features. The method consists of estimating the image background, determining a residual image and post processing to determine the features present. The methodology is not finalized but demonstrates the feasibility of a method to determine the kind and size of the features present.

System and method for image registration of multiple video streams

DOEpatents

Dillavou, Marcus W.; Shum, Phillip Corey; Guthrie, Baron L.; Shenai, Mahesh B.; Deaton, Drew Steven; May, Matthew Benton

2018-02-06

Provided herein are methods and systems for image registration from multiple sources. A method for image registration includes rendering a common field of interest that reflects a presence of a plurality of elements, wherein at least one of the elements is a remote element located remotely from another of the elements and updating the common field of interest such that the presence of the at least one of the elements is registered relative to another of the elements.

Quantifying the quality of medical x-ray images: An evaluation based on normal anatomy for lumbar spine and chest radiography

NASA Astrophysics Data System (ADS)

Tingberg, Anders Martin

Optimisation in diagnostic radiology requires accurate methods for determination of patient absorbed dose and clinical image quality. Simple methods for evaluation of clinical image quality are at present scarce and this project aims at developing such methods. Two methods are used and further developed; fulfillment of image criteria (IC) and visual grading analysis (VGA). Clinical image quality descriptors are defined based on these two methods: image criteria score (ICS) and visual grading analysis score (VGAS), respectively. For both methods the basis is the Image Criteria of the ``European Guidelines on Quality Criteria for Diagnostic Radiographic Images''. Both methods have proved to be useful for evaluation of clinical image quality. The two methods complement each other: IC is an absolute method, which means that the quality of images of different patients and produced with different radiographic techniques can be compared with each other. The separating power of IC is, however, weaker than that of VGA. VGA is the best method for comparing images produced with different radiographic techniques and has strong separating power, but the results are relative, since the quality of an image is compared to the quality of a reference image. The usefulness of the two methods has been verified by comparing the results from both of them with results from a generally accepted method for evaluation of clinical image quality, receiver operating characteristics (ROC). The results of the comparison between the two methods based on visibility of anatomical structures and the method based on detection of pathological structures (free-response forced error) indicate that the former two methods can be used for evaluation of clinical image quality as efficiently as the method based on ROC. More studies are, however, needed for us to be able to draw a general conclusion, including studies of other organs, using other radiographic techniques, etc. The results of the experimental evaluation of clinical image quality are compared with physical quantities calculated with a theoretical model based on a voxel phantom, and correlations are found. The results demonstrate that the computer model can be a useful toot in planning further experimental studies.

Malware Analysis Using Visualized Image Matrices

PubMed Central

Im, Eul Gyu

2014-01-01

This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively. PMID:25133202

Methods for comparing 3D surface attributes

NASA Astrophysics Data System (ADS)

Pang, Alex; Freeman, Adam

1996-03-01

A common task in data analysis is to compare two or more sets of data, statistics, presentations, etc. A predominant method in use is side-by-side visual comparison of images. While straightforward, it burdens the user with the task of discerning the differences between the two images. The user if further taxed when the images are of 3D scenes. This paper presents several methods for analyzing the extent, magnitude, and manner in which surfaces in 3D differ in their attributes. The surface geometry are assumed to be identical and only the surface attributes (color, texture, etc.) are variable. As a case in point, we examine the differences obtained when a 3D scene is rendered progressively using radiosity with different form factor calculation methods. The comparison methods include extensions of simple methods such as mapping difference information to color or transparency, and more recent methods including the use of surface texture, perturbation, and adaptive placements of error glyphs.

Measuring the circular motion of small objects using laser stroboscopic images.

PubMed

Wang, Hairong; Fu, Y; Du, R

2008-01-01

Measuring the circular motion of a small object, including its displacement, speed, and acceleration, is a challenging task. This paper presents a new method for measuring repetitive and/or nonrepetitive, constant speed and/or variable speed circular motion using laser stroboscopic images. Under stroboscopic illumination, each image taken by an ordinary camera records multioutlines of an object in motion; hence, processing the stroboscopic image will be able to extract the motion information. We built an experiment apparatus consisting of a laser as the light source, a stereomicroscope to magnify the image, and a normal complementary metal oxide semiconductor camera to record the image. As the object is in motion, the stroboscopic illumination generates a speckle pattern on the object that can be recorded by the camera and analyzed by a computer. Experimental results indicate that the stroboscopic imaging is stable under various conditions. Moreover, the characteristics of the motion, including the displacement, the velocity, and the acceleration can be calculated based on the width of speckle marks, the illumination intensity, the duty cycle, and the sampling frequency. Compared with the popular high-speed camera method, the presented method may achieve the same measuring accuracy, but with much reduced cost and complexity.

Microparticle analysis system and method

NASA Technical Reports Server (NTRS)

Morrison, Dennis R. (Inventor)

2007-01-01

A device for analyzing microparticles is provided which includes a chamber with an inlet and an outlet for respectively introducing and dispensing a flowing fluid comprising microparticles, a light source for providing light through the chamber and a photometer for measuring the intensity of light transmitted through individual microparticles. The device further includes an imaging system for acquiring images of the fluid. In some cases, the device may be configured to identify and determine a quantity of the microparticles within the fluid. Consequently, a method for identifying and tracking microparticles in motion is contemplated herein. The method involves flowing a fluid comprising microparticles in laminar motion through a chamber, transmitting light through the fluid, measuring the intensities of the light transmitted through the microparticles, imaging the fluid a plurality of times and comparing at least some of the intensities of light between different images of the fluid.

Computer-implemented system and method for automated and highly accurate plaque analysis, reporting, and visualization

NASA Technical Reports Server (NTRS)

Kemp, James Herbert (Inventor); Talukder, Ashit (Inventor); Lambert, James (Inventor); Lam, Raymond (Inventor)

2008-01-01

A computer-implemented system and method of intra-oral analysis for measuring plaque removal is disclosed. The system includes hardware for real-time image acquisition and software to store the acquired images on a patient-by-patient basis. The system implements algorithms to segment teeth of interest from surrounding gum, and uses a real-time image-based morphing procedure to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The system integrates these components into a single software suite with an easy-to-use graphical user interface (GUI) that allows users to do an end-to-end run of a patient record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image.

An Improved Image Matching Method Based on Surf Algorithm

NASA Astrophysics Data System (ADS)

Chen, S. J.; Zheng, S. Z.; Xu, Z. G.; Guo, C. C.; Ma, X. L.

2018-04-01

Many state-of-the-art image matching methods, based on the feature matching, have been widely studied in the remote sensing field. These methods of feature matching which get highly operating efficiency, have a disadvantage of low accuracy and robustness. This paper proposes an improved image matching method which based on the SURF algorithm. The proposed method introduces color invariant transformation, information entropy theory and a series of constraint conditions to increase feature points detection and matching accuracy. First, the model of color invariant transformation is introduced for two matching images aiming at obtaining more color information during the matching process and information entropy theory is used to obtain the most information of two matching images. Then SURF algorithm is applied to detect and describe points from the images. Finally, constraint conditions which including Delaunay triangulation construction, similarity function and projective invariant are employed to eliminate the mismatches so as to improve matching precision. The proposed method has been validated on the remote sensing images and the result benefits from its high precision and robustness.

Research on adaptive optics image restoration algorithm based on improved joint maximum a posteriori method

NASA Astrophysics Data System (ADS)

Zhang, Lijuan; Li, Yang; Wang, Junnan; Liu, Ying

2018-03-01

In this paper, we propose a point spread function (PSF) reconstruction method and joint maximum a posteriori (JMAP) estimation method for the adaptive optics image restoration. Using the JMAP method as the basic principle, we establish the joint log likelihood function of multi-frame adaptive optics (AO) images based on the image Gaussian noise models. To begin with, combining the observed conditions and AO system characteristics, a predicted PSF model for the wavefront phase effect is developed; then, we build up iterative solution formulas of the AO image based on our proposed algorithm, addressing the implementation process of multi-frame AO images joint deconvolution method. We conduct a series of experiments on simulated and real degraded AO images to evaluate our proposed algorithm. Compared with the Wiener iterative blind deconvolution (Wiener-IBD) algorithm and Richardson-Lucy IBD algorithm, our algorithm has better restoration effects including higher peak signal-to-noise ratio ( PSNR) and Laplacian sum ( LS) value than the others. The research results have a certain application values for actual AO image restoration.

Quantitative analysis of single-molecule superresolution images

PubMed Central

Coltharp, Carla; Yang, Xinxing; Xiao, Jie

2014-01-01

This review highlights the quantitative capabilities of single-molecule localization-based superresolution imaging methods. In addition to revealing fine structural details, the molecule coordinate lists generated by these methods provide the critical ability to quantify the number, clustering, and colocalization of molecules with 10 – 50 nm resolution. Here we describe typical workflows and precautions for quantitative analysis of single-molecule superresolution images. These guidelines include potential pitfalls and essential control experiments, allowing critical assessment and interpretation of superresolution images. PMID:25179006

Design and realization of retina-like three-dimensional imaging based on a MOEMS mirror

NASA Astrophysics Data System (ADS)

Cao, Jie; Hao, Qun; Xia, Wenze; Peng, Yuxin; Cheng, Yang; Mu, Jiaxing; Wang, Peng

2016-07-01

To balance conflicts for high-resolution, large-field-of-view and real-time imaging, a retina-like imaging method based on time-of flight (TOF) is proposed. Mathematical models of 3D imaging based on MOEMS are developed. Based on this method, we perform simulations of retina-like scanning properties, including compression of redundant information and rotation and scaling invariance. To validate the theory, we develop a prototype and conduct relevant experiments. The preliminary results agree well with the simulations.

Noninvasive Techniques for Intracranial Pressure Assessment: A Review from Aerospace Medicine Perspective

NASA Technical Reports Server (NTRS)

Hamilton, Douglas R.; Sargsyan, Ashot E.; Fogarty, Jennifer; Ebert, Douglas J. W.; Polk, J. D.

2010-01-01

Microgravity-induced changes in fluid distribution and other physiological factors due to space flight have been implicated as the cause of increased intracranial pressure (ICP) in a number of space crewmembers. The modest levels of ICP elevation and absence of severe symptoms in this group do not warrant invasive diagnostic interventions. However, the long-term trends and residual or consequential changes secondary to the observed ICP elevation in this group are not yet known. Therefore, close attention is needed to evaluate the potential techniques of noninvasively assessing ICP, including those feasible for in-flight use. Of particular interest is continuity between ground and in-flight testing, whereby data from the same or different techniques allow reasonably dependable estimation of ICP trends and responses. Methods: A thorough review of current literature, analysis of NASA data, and interviews with subject matter experts were conducted to construct a presentation that reflects the state of the art for noninvasive ICP measurement and monitoring. Results: Multiple imaging and non-imaging modalities are available to assess ICP in terrestrial clinical and experimental environments. Imaging alternatives include magnetic resonance imaging (MRI) and high-resolution sonography. Non-imaging techniques include transcranial Doppler, certain audiological methods, and venous ophthalmodynamometry, among others. Special functional techniques have been proposed recently that allow the use of advanced MRI methods to calculate ICP in addition to the acquisition of high-resolution images. Our data include many of these applications, with several cases of correlation with lumbar puncture, the invasive "gold standard" measurement of ICP.

Visual Search with Image Modification in Age-Related Macular Degeneration

PubMed Central

Wiecek, Emily; Jackson, Mary Lou; Dakin, Steven C.; Bex, Peter

2012-01-01

Purpose. AMD results in loss of central vision and a dependence on low-resolution peripheral vision. While many image enhancement techniques have been proposed, there is a lack of quantitative comparison of the effectiveness of enhancement. We developed a natural visual search task that uses patients' eye movements as a quantitative and functional measure of the efficacy of image modification. Methods. Eye movements of 17 patients (mean age = 77 years) with AMD were recorded while they searched for target objects in natural images. Eight different image modification methods were implemented and included manipulations of local image or edge contrast, color, and crowding. In a subsequent task, patients ranked their preference of the image modifications. Results. Within individual participants, there was no significant difference in search duration or accuracy across eight different image manipulations. When data were collapsed across all image modifications, a multivariate model identified six significant predictors for normalized search duration including scotoma size and acuity, as well as interactions among scotoma size, age, acuity, and contrast (P < 0.05). Additionally, an analysis of image statistics showed no correlation with search performance across all image modifications. Rank ordering of enhancement methods based on participants' preference revealed a trend that participants preferred the least modified images (P < 0.05). Conclusions. There was no quantitative effect of image modification on search performance. A better understanding of low- and high-level components of visual search in natural scenes is necessary to improve future attempts at image enhancement for low vision patients. Different search tasks may require alternative image modifications to improve patient functioning and performance. PMID:22930725

Method and apparatus for animal positioning in imaging systems

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

Hadjioannou, Arion-Xenofon; Stout, David B.; Silverman, Robert W.

An apparatus for imaging an animal includes a first mounting surface, a bed sized to support the animal and releasably secured to or integral with the first mounting surface. The apparatus also includes a plurality of straps, each having a first end in a fixed position relative to the bed and a second end for tightening around a limb of the animal. A method for in-vivo imaging of an animal includes providing an animal that has limbs, providing a first mounting surface, and providing a bed removably secured to or integral with the mounting surface and sized to support themore » animal as well as being coupled to a plurality of straps. The method also includes placing the animal on the bed between the plurality of straps and tightening at least two of the plurality of straps around at least two of the limbs such that the animal is substantially secured in place relative to the bed.« less

Segmentation and feature extraction of cervical spine x-ray images

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Thoma, George R.

1999-05-01

As part of an R&D project in mixed text/image database design, the National Library of Medicine has archived a collection of 17,000 digitized x-ray images of the cervical and lumbar spine which were collected as part of the second National Health and Nutrition Examination Survey (NHANES II). To make this image data available and usable to a wide audience, we are investigating techniques for indexing the image content by automated or semi-automated means. Indexing of the images by features of interest to researchers in spine disease and structure requires effective segmentation of the vertebral anatomy. This paper describes work in progress toward this segmentation of the cervical spine images into anatomical components of interest, including anatomical landmarks for vertebral location, and segmentation and identification of individual vertebrae. Our work includes developing a reliable method for automatically fixing an anatomy-based coordinate system in the images, and work to adaptively threshold the images, using methods previously applied by researchers in cardioangiography. We describe the motivation for our work and present our current results in both areas.

Photothermal imaging of melanin

NASA Astrophysics Data System (ADS)

Kerimo, Josef; DiMarzio, Charles A.

2013-02-01

We present photothermal images of melanin using modulation with two laser beams. Strong melanin absorption followed by efficient nonradiative relaxation caused heating and an increase in temperature. This temperature effect was used as an imaging contrast to detect melanin. Melanin from several samples including Sepia officinalis, black human hair, and live zebra fish, were imaged with a high signal-to-noise ratio. For the imaging, we focused two near infrared laser beams (pump and probe) collinearly with different wavelengths and the pump was modulated in amplitude. The thermally induced variations in the refractive index, at the modulation frequency, were detected by the scattering of the probe beam. The Photothermal method brings several imaging benefits including the lack of background interference and the possibility of imaging for an extended period of time without photodamage to the melanin. The dependence of the photothermal signal on the laser power, modulation frequency, and spatial offset of the probe is discussed. The new photothermal imaging method is promising and provides background-free and label-free imaging of melanin and can be implemented with low-cost CW lasers.

Photogrammetry Applied to Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

Liu, Tian-Shu; Cattafesta, L. N., III; Radeztsky, R. H.; Burner, A. W.

2000-01-01

In image-based measurements, quantitative image data must be mapped to three-dimensional object space. Analytical photogrammetric methods, which may be used to accomplish this task, are discussed from the viewpoint of experimental fluid dynamicists. The Direct Linear Transformation (DLT) for camera calibration, used in pressure sensitive paint, is summarized. An optimization method for camera calibration is developed that can be used to determine the camera calibration parameters, including those describing lens distortion, from a single image. Combined with the DLT method, this method allows a rapid and comprehensive in-situ camera calibration and therefore is particularly useful for quantitative flow visualization and other measurements such as model attitude and deformation in production wind tunnels. The paper also includes a brief description of typical photogrammetric applications to temperature- and pressure-sensitive paint measurements and model deformation measurements in wind tunnels.

Atomic-resolution transmission electron microscopy of electron beam–sensitive crystalline materials

NASA Astrophysics Data System (ADS)

Zhang, Daliang; Zhu, Yihan; Liu, Lingmei; Ying, Xiangrong; Hsiung, Chia-En; Sougrat, Rachid; Li, Kun; Han, Yu

2018-02-01

High-resolution imaging of electron beam–sensitive materials is one of the most difficult applications of transmission electron microscopy (TEM). The challenges are manifold, including the acquisition of images with extremely low beam doses, the time-constrained search for crystal zone axes, the precise image alignment, and the accurate determination of the defocus value. We develop a suite of methods to fulfill these requirements and acquire atomic-resolution TEM images of several metal organic frameworks that are generally recognized as highly sensitive to electron beams. The high image resolution allows us to identify individual metal atomic columns, various types of surface termination, and benzene rings in the organic linkers. We also apply our methods to other electron beam–sensitive materials, including the organic-inorganic hybrid perovskite CH3NH3PbBr3.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

2018-06-01

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

Quiescent period respiratory gating for PET∕CT

PubMed Central

Liu, Chi; Alessio, Adam; Pierce, Larry; Thielemans, Kris; Wollenweber, Scott; Ganin, Alexander; Kinahan, Paul

2010-01-01

Purpose: To minimize respiratory motion artifacts, this work proposes quiescent period gating (QPG) methods that extract PET data from the end-expiration quiescent period and form a single PET frame with reduced motion and improved signal-to-noise properties. Methods: Two QPG methods are proposed and evaluated. Histogram-based quiescent period gating (H-QPG) extracts a fraction of PET data determined by a window of the respiratory displacement signal histogram. Cycle-based quiescent period gating (C-QPG) extracts data with a respiratory displacement signal below a specified threshold of the maximum amplitude of each individual respiratory cycle. Performances of both QPG methods were compared to ungated and five-bin phase-gated images across 21 FDG-PET∕CT patient data sets containing 31 thorax and abdomen lesions as well as with computer simulations driven by 1295 different patient respiratory traces. Image quality was evaluated in terms of the lesion SUVmax and the fraction of counts included in each gate as a surrogate for image noise. Results: For all the gating methods, image noise artifactually increases SUVmax when the fraction of counts included in each gate is less than 50%. While simulation data show that H-QPG is superior to C-QPG, the H-QPG and C-QPG methods lead to similar quantification-noise tradeoffs in patient data. Compared to ungated images, both QPG methods yield significantly higher lesion SUVmax. Compared to five-bin phase gating, the QPG methods yield significantly larger fraction of counts with similar SUVmax improvement. Both QPG methods result in increased lesion SUVmax for patients whose lesions have longer quiescent periods. Conclusions: Compared to ungated and phase-gated images, the QPG methods lead to images with less motion blurring and an improved compromise between SUVmax and fraction of counts. The QPG methods for respiratory motion compensation could effectively improve tumor quantification with minimal noise increase. PMID:20964223

Functional Magnetic Resonance Imaging and Spectroscopic Imaging of the Brain: Application of fMRI and fMRS to Reading Disabilities and Education.

ERIC Educational Resources Information Center

Richards, Todd L.

2001-01-01

This tutorial/review covers functional brain-imaging methods and results used to study language and reading disabilities. Although the emphasis is on magnetic resonance imaging and functional magnetic resonance spectroscopy, other imaging techniques are also discussed including positron emission tomography, electroencephalography,…

Accuracy and Precision of Radioactivity Quantification in Nuclear Medicine Images

PubMed Central

Frey, Eric C.; Humm, John L.; Ljungberg, Michael

2012-01-01

The ability to reliably quantify activity in nuclear medicine has a number of increasingly important applications. Dosimetry for targeted therapy treatment planning or for approval of new imaging agents requires accurate estimation of the activity in organs, tumors, or voxels at several imaging time points. Another important application is the use of quantitative metrics derived from images, such as the standard uptake value commonly used in positron emission tomography (PET), to diagnose and follow treatment of tumors. These measures require quantification of organ or tumor activities in nuclear medicine images. However, there are a number of physical, patient, and technical factors that limit the quantitative reliability of nuclear medicine images. There have been a large number of improvements in instrumentation, including the development of hybrid single-photon emission computed tomography/computed tomography and PET/computed tomography systems, and reconstruction methods, including the use of statistical iterative reconstruction methods, which have substantially improved the ability to obtain reliable quantitative information from planar, single-photon emission computed tomography, and PET images. PMID:22475429

Apparatus and method to achieve high-resolution microscopy with non-diffracting or refracting radiation

DOEpatents

Tobin, Jr., Kenneth W.; Bingham, Philip R.; Hawari, Ayman I.

2012-11-06

An imaging system employing a coded aperture mask having multiple pinholes is provided. The coded aperture mask is placed at a radiation source to pass the radiation through. The radiation impinges on, and passes through an object, which alters the radiation by absorption and/or scattering. Upon passing through the object, the radiation is detected at a detector plane to form an encoded image, which includes information on the absorption and/or scattering caused by the material and structural attributes of the object. The encoded image is decoded to provide a reconstructed image of the object. Because the coded aperture mask includes multiple pinholes, the radiation intensity is greater than a comparable system employing a single pinhole, thereby enabling a higher resolution. Further, the decoding of the encoded image can be performed to generate multiple images of the object at different distances from the detector plane. Methods and programs for operating the imaging system are also disclosed.

Method and system for non-linear motion estimation

NASA Technical Reports Server (NTRS)

Lu, Ligang (Inventor)

2011-01-01

A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.

Simultaneous maximum a posteriori longitudinal PET image reconstruction

NASA Astrophysics Data System (ADS)

Ellis, Sam; Reader, Andrew J.

2017-09-01

Positron emission tomography (PET) is frequently used to monitor functional changes that occur over extended time scales, for example in longitudinal oncology PET protocols that include routine clinical follow-up scans to assess the efficacy of a course of treatment. In these contexts PET datasets are currently reconstructed into images using single-dataset reconstruction methods. Inspired by recently proposed joint PET-MR reconstruction methods, we propose to reconstruct longitudinal datasets simultaneously by using a joint penalty term in order to exploit the high degree of similarity between longitudinal images. We achieved this by penalising voxel-wise differences between pairs of longitudinal PET images in a one-step-late maximum a posteriori (MAP) fashion, resulting in the MAP simultaneous longitudinal reconstruction (SLR) method. The proposed method reduced reconstruction errors and visually improved images relative to standard maximum likelihood expectation-maximisation (ML-EM) in simulated 2D longitudinal brain tumour scans. In reconstructions of split real 3D data with inserted simulated tumours, noise across images reconstructed with MAP-SLR was reduced to levels equivalent to doubling the number of detected counts when using ML-EM. Furthermore, quantification of tumour activities was largely preserved over a variety of longitudinal tumour changes, including changes in size and activity, with larger changes inducing larger biases relative to standard ML-EM reconstructions. Similar improvements were observed for a range of counts levels, demonstrating the robustness of the method when used with a single penalty strength. The results suggest that longitudinal regularisation is a simple but effective method of improving reconstructed PET images without using resolution degrading priors.

Improvement of automatic hemorrhage detection methods using brightness correction on fundus images

NASA Astrophysics Data System (ADS)

Hatanaka, Yuji; Nakagawa, Toshiaki; Hayashi, Yoshinori; Kakogawa, Masakatsu; Sawada, Akira; Kawase, Kazuhide; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

We have been developing several automated methods for detecting abnormalities in fundus images. The purpose of this study is to improve our automated hemorrhage detection method to help diagnose diabetic retinopathy. We propose a new method for preprocessing and false positive elimination in the present study. The brightness of the fundus image was changed by the nonlinear curve with brightness values of the hue saturation value (HSV) space. In order to emphasize brown regions, gamma correction was performed on each red, green, and blue-bit image. Subsequently, the histograms of each red, blue, and blue-bit image were extended. After that, the hemorrhage candidates were detected. The brown regions indicated hemorrhages and blood vessels and their candidates were detected using density analysis. We removed the large candidates such as blood vessels. Finally, false positives were removed by using a 45-feature analysis. To evaluate the new method for the detection of hemorrhages, we examined 125 fundus images, including 35 images with hemorrhages and 90 normal images. The sensitivity and specificity for the detection of abnormal cases was were 80% and 88%, respectively. These results indicate that the new method may effectively improve the performance of our computer-aided diagnosis system for hemorrhages.

l0 regularization based on a prior image incorporated non-local means for limited-angle X-ray CT reconstruction.

PubMed

Zhang, Lingli; Zeng, Li; Guo, Yumeng

2018-01-01

Restricted by the scanning environment in some CT imaging modalities, the acquired projection data are usually incomplete, which may lead to a limited-angle reconstruction problem. Thus, image quality usually suffers from the slope artifacts. The objective of this study is to first investigate the distorted domains of the reconstructed images which encounter the slope artifacts and then present a new iterative reconstruction method to address the limited-angle X-ray CT reconstruction problem. The presented framework of new method exploits the structural similarity between the prior image and the reconstructed image aiming to compensate the distorted edges. Specifically, the new method utilizes l0 regularization and wavelet tight framelets to suppress the slope artifacts and pursue the sparsity. New method includes following 4 steps to (1) address the data fidelity using SART; (2) compensate for the slope artifacts due to the missed projection data using the prior image and modified nonlocal means (PNLM); (3) utilize l0 regularization to suppress the slope artifacts and pursue the sparsity of wavelet coefficients of the transformed image by using iterative hard thresholding (l0W); and (4) apply an inverse wavelet transform to reconstruct image. In summary, this method is referred to as "l0W-PNLM". Numerical implementations showed that the presented l0W-PNLM was superior to suppress the slope artifacts while preserving the edges of some features as compared to the commercial and other popular investigative algorithms. When the image to be reconstructed is inconsistent with the prior image, the new method can avoid or minimize the distorted edges in the reconstructed images. Quantitative assessments also showed that applying the new method obtained the highest image quality comparing to the existing algorithms. This study demonstrated that the presented l0W-PNLM yielded higher image quality due to a number of unique characteristics, which include that (1) it utilizes the structural similarity between the reconstructed image and prior image to modify the distorted edges by slope artifacts; (2) it adopts wavelet tight frames to obtain the first and high derivative in several directions and levels; and (3) it takes advantage of l0 regularization to promote the sparsity of wavelet coefficients, which is effective for the inhibition of the slope artifacts. Therefore, the new method can address the limited-angle CT reconstruction problem effectively and have practical significance.

Image reconstruction for PET/CT scanners: past achievements and future challenges

PubMed Central

Tong, Shan; Alessio, Adam M; Kinahan, Paul E

2011-01-01

PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions. PMID:21339831

Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

NASA Technical Reports Server (NTRS)

Ranson, K. J.; Sun, Guoqing

1992-01-01

Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

Beam Characterization at the Neutron Radiography Facility

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

Sarah Morgan; Jeffrey King

The quality of a neutron imaging beam directly impacts the quality of radiographic images produced using that beam. Fully characterizing a neutron beam, including determination of the beam’s effective length-to-diameter ratio, neutron flux profile, energy spectrum, image quality, and beam divergence, is vital for producing quality radiographic images. This project characterized the east neutron imaging beamline at the Idaho National Laboratory Neutron Radiography Reactor (NRAD). The experiments which measured the beam’s effective length-to-diameter ratio and image quality are based on American Society for Testing and Materials (ASTM) standards. An analysis of the image produced by a calibrated phantom measured themore » beam divergence. The energy spectrum measurements consist of a series of foil irradiations using a selection of activation foils, compared to the results produced by a Monte Carlo n-Particle (MCNP) model of the beamline. Improvement of the existing NRAD MCNP beamline model includes validation of the model’s energy spectrum and the development of enhanced image simulation methods. The image simulation methods predict the radiographic image of an object based on the foil reaction rate data obtained by placing a model of the object in front of the image plane in an MCNP beamline model.« less

Lesion Border Detection in Dermoscopy Images

PubMed Central

Celebi, M. Emre; Schaefer, Gerald; Iyatomi, Hitoshi; Stoecker, William V.

2009-01-01

Background Dermoscopy is one of the major imaging modalities used in the diagnosis of melanoma and other pigmented skin lesions. Due to the difficulty and subjectivity of human interpretation, computerized analysis of dermoscopy images has become an important research area. One of the most important steps in dermoscopy image analysis is the automated detection of lesion borders. Methods In this article, we present a systematic overview of the recent border detection methods in the literature paying particular attention to computational issues and evaluation aspects. Conclusion Common problems with the existing approaches include the acquisition, size, and diagnostic distribution of the test image set, the evaluation of the results, and the inadequate description of the employed methods. Border determination by dermatologists appears to depend upon higher-level knowledge, therefore it is likely that the incorporation of domain knowledge in automated methods will enable them to perform better, especially in sets of images with a variety of diagnoses. PMID:19121917

A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks

PubMed Central

Wang, Changjian; Liu, Xiaohui; Jin, Shiyao

2018-01-01

Wound segmentation plays an important supporting role in the wound observation and wound healing. Current methods of image segmentation include those based on traditional process of image and those based on deep neural networks. The traditional methods use the artificial image features to complete the task without large amounts of labeled data. Meanwhile, the methods based on deep neural networks can extract the image features effectively without the artificial design, but lots of training data are required. Combined with the advantages of them, this paper presents a composite model of wound segmentation. The model uses the skin with wound detection algorithm we designed in the paper to highlight image features. Then, the preprocessed images are segmented by deep neural networks. And semantic corrections are applied to the segmentation results at last. The model shows a good performance in our experiment. PMID:29955227

Automatic Centerline Extraction of Coverd Roads by Surrounding Objects from High Resolution Satellite Images

NASA Astrophysics Data System (ADS)

Kamangir, H.; Momeni, M.; Satari, M.

2017-09-01

This paper presents an automatic method to extract road centerline networks from high and very high resolution satellite images. The present paper addresses the automated extraction roads covered with multiple natural and artificial objects such as trees, vehicles and either shadows of buildings or trees. In order to have a precise road extraction, this method implements three stages including: classification of images based on maximum likelihood algorithm to categorize images into interested classes, modification process on classified images by connected component and morphological operators to extract pixels of desired objects by removing undesirable pixels of each class, and finally line extraction based on RANSAC algorithm. In order to evaluate performance of the proposed method, the generated results are compared with ground truth road map as a reference. The evaluation performance of the proposed method using representative test images show completeness values ranging between 77% and 93%.

Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model.

PubMed

Lee, Sangyeol; Reinhardt, Joseph M; Cattin, Philippe C; Abràmoff, Michael D

2010-08-01

Fundus camera imaging of the retina is widely used to diagnose and manage ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. Retinal images typically have a limited field of view, and multiple images can be joined together using an image registration technique to form a montage with a larger field of view. A variety of methods for retinal image registration have been proposed, but evaluating such methods objectively is difficult due to the lack of a reference standard for the true alignment of the individual images that make up the montage. A method of generating simulated retinal images by modeling the geometric distortions due to the eye geometry and the image acquisition process is described in this paper. We also present a validation process that can be used for any retinal image registration method by tracing through the distortion path and assessing the geometric misalignment in the coordinate system of the reference standard. The proposed method can be used to perform an accuracy evaluation over the whole image, so that distortion in the non-overlapping regions of the montage components can be easily assessed. We demonstrate the technique by generating test image sets with a variety of overlap conditions and compare the accuracy of several retinal image registration models. Copyright 2010 Elsevier B.V. All rights reserved.

Personal identification based on blood vessels of retinal fundus images

NASA Astrophysics Data System (ADS)

Fukuta, Keisuke; Nakagawa, Toshiaki; Hayashi, Yoshinori; Hatanaka, Yuji; Hara, Takeshi; Fujita, Hiroshi

2008-03-01

Biometric technique has been implemented instead of conventional identification methods such as password in computer, automatic teller machine (ATM), and entrance and exit management system. We propose a personal identification (PI) system using color retinal fundus images which are unique to each individual. The proposed procedure for identification is based on comparison of an input fundus image with reference fundus images in the database. In the first step, registration between the input image and the reference image is performed. The step includes translational and rotational movement. The PI is based on the measure of similarity between blood vessel images generated from the input and reference images. The similarity measure is defined as the cross-correlation coefficient calculated from the pixel values. When the similarity is greater than a predetermined threshold, the input image is identified. This means both the input and the reference images are associated to the same person. Four hundred sixty-two fundus images including forty-one same-person's image pairs were used for the estimation of the proposed technique. The false rejection rate and the false acceptance rate were 9.9×10 -5% and 4.3×10 -5%, respectively. The results indicate that the proposed method has a higher performance than other biometrics except for DNA. To be used for practical application in the public, the device which can take retinal fundus images easily is needed. The proposed method is applied to not only the PI but also the system which warns about misfiling of fundus images in medical facilities.

Localization microscopy of DNA in situ using Vybrant{sup ®} DyeCycle™ Violet fluorescent probe: A new approach to study nuclear nanostructure at single molecule resolution

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

Żurek-Biesiada, Dominika; Szczurek, Aleksander T.; Prakash, Kirti

Higher order chromatin structure is not only required to compact and spatially arrange long chromatids within a nucleus, but have also important functional roles, including control of gene expression and DNA processing. However, studies of chromatin nanostructures cannot be performed using conventional widefield and confocal microscopy because of the limited optical resolution. Various methods of superresolution microscopy have been described to overcome this difficulty, like structured illumination and single molecule localization microscopy. We report here that the standard DNA dye Vybrant{sup ®} DyeCycle™ Violet can be used to provide single molecule localization microscopy (SMLM) images of DNA in nuclei ofmore » fixed mammalian cells. This SMLM method enabled optical isolation and localization of large numbers of DNA-bound molecules, usually in excess of 10{sup 6} signals in one cell nucleus. The technique yielded high-quality images of nuclear DNA density, revealing subdiffraction chromatin structures of the size in the order of 100 nm; the interchromatin compartment was visualized at unprecedented optical resolution. The approach offers several advantages over previously described high resolution DNA imaging methods, including high specificity, an ability to record images using a single wavelength excitation, and a higher density of single molecule signals than reported in previous SMLM studies. The method is compatible with DNA/multicolor SMLM imaging which employs simple staining methods suited also for conventional optical microscopy. - Highlights: • Super-resolution imaging of nuclear DNA with Vybrant Violet and blue excitation. • 90nm resolution images of DNA structures in optically thick eukaryotic nuclei. • Enhanced resolution confirms the existence of DNA-free regions inside the nucleus. • Optimized imaging conditions enable multicolor super-resolution imaging.« less

A Method to Recognize Anatomical Site and Image Acquisition View in X-ray Images.

PubMed

Chang, Xiao; Mazur, Thomas; Li, H Harold; Yang, Deshan

2017-12-01

A method was developed to recognize anatomical site and image acquisition view automatically in 2D X-ray images that are used in image-guided radiation therapy. The purpose is to enable site and view dependent automation and optimization in the image processing tasks including 2D-2D image registration, 2D image contrast enhancement, and independent treatment site confirmation. The X-ray images for 180 patients of six disease sites (the brain, head-neck, breast, lung, abdomen, and pelvis) were included in this study with 30 patients each site and two images of orthogonal views each patient. A hierarchical multiclass recognition model was developed to recognize general site first and then specific site. Each node of the hierarchical model recognized the images using a feature extraction step based on principal component analysis followed by a binary classification step based on support vector machine. Given two images in known orthogonal views, the site recognition model achieved a 99% average F1 score across the six sites. If the views were unknown in the images, the average F1 score was 97%. If only one image was taken either with or without view information, the average F1 score was 94%. The accuracy of the site-specific view recognition models was 100%.

External Prior Guided Internal Prior Learning for Real-World Noisy Image Denoising

NASA Astrophysics Data System (ADS)

Xu, Jun; Zhang, Lei; Zhang, David

2018-06-01

Most of existing image denoising methods learn image priors from either external data or the noisy image itself to remove noise. However, priors learned from external data may not be adaptive to the image to be denoised, while priors learned from the given noisy image may not be accurate due to the interference of corrupted noise. Meanwhile, the noise in real-world noisy images is very complex, which is hard to be described by simple distributions such as Gaussian distribution, making real noisy image denoising a very challenging problem. We propose to exploit the information in both external data and the given noisy image, and develop an external prior guided internal prior learning method for real noisy image denoising. We first learn external priors from an independent set of clean natural images. With the aid of learned external priors, we then learn internal priors from the given noisy image to refine the prior model. The external and internal priors are formulated as a set of orthogonal dictionaries to efficiently reconstruct the desired image. Extensive experiments are performed on several real noisy image datasets. The proposed method demonstrates highly competitive denoising performance, outperforming state-of-the-art denoising methods including those designed for real noisy images.

Photogrammetric Modeling and Image-Based Rendering for Rapid Virtual Environment Creation

DTIC Science & Technology

2004-12-01

area and different methods have been proposed. Pertinent methods include: Camera Calibration , Structure from Motion, Stereo Correspondence, and Image...Based Rendering 1.1.1 Camera Calibration Determining the 3D structure of a model from multiple views becomes simpler if the intrinsic (or internal...can introduce significant nonlinearities into the image. We have found that camera calibration is a straightforward process which can simplify the

Cyclopentadienyl Rhenium (Technetium) Tricarbonyl Complexes Integrated in Estrogen Receptor Ligands for ER+ Tumor Imaging

DTIC Science & Technology

2006-10-01

determined by imaging correlate well with those determined by immunoassay methods on surgical biopsies. Because of the short half-life of fluorine -18, this...immunoassay methods on surgical biopsies. Currently, the most effective ER imaging agent is a fluorine -18 labeled estrogen. However, because of the short...substituent to the central pentacycle, including nucleophilic addition of organometallic reagents, addition of electrophiles to the cyclopentadiene

Imaging of shoulder instability

PubMed Central

Martínez Martínez, Alberto; Tomás Muñoz, Pablo; Pozo Sánchez, José; Zarza Pérez, Antonio

2017-01-01

This extended review tries to cover the imaging findings of the wide range of shoulder injuries secondary to shoulder joint instability. Usefulness of the different imaging methods is stressed, including radiography, computed tomography (CT) and magnetic resonance. The main topics to be covered include traumatic, atraumatic and minor instability syndromes. Radiography may show bone abnormalities associated to instability, including developmental and post-traumatic changes. CT is the best technique depicting and quantifying skeletal changes. MR-arthrography is the main tool in diagnosing the shoulder instability injuries. PMID:28932699

3D/3D registration of coronary CTA and biplane XA reconstructions for improved image guidance

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

Dibildox, Gerardo, E-mail: g.dibildox@erasmusmc.nl; Baka, Nora; Walsum, Theo van

2014-09-15

Purpose: The authors aim to improve image guidance during percutaneous coronary interventions of chronic total occlusions (CTO) by providing information obtained from computed tomography angiography (CTA) to the cardiac interventionist. To this end, the authors investigate a method to register a 3D CTA model to biplane reconstructions. Methods: The authors developed a method for registering preoperative coronary CTA with intraoperative biplane x-ray angiography (XA) images via 3D models of the coronary arteries. The models are extracted from the CTA and biplane XA images, and are temporally aligned based on CTA reconstruction phase and XA ECG signals. Rigid spatial alignment ismore » achieved with a robust probabilistic point set registration approach using Gaussian mixture models (GMMs). This approach is extended by including orientation in the Gaussian mixtures and by weighting bifurcation points. The method is evaluated on retrospectively acquired coronary CTA datasets of 23 CTO patients for which biplane XA images are available. Results: The Gaussian mixture model approach achieved a median registration accuracy of 1.7 mm. The extended GMM approach including orientation was not significantly different (P > 0.1) but did improve robustness with regards to the initialization of the 3D models. Conclusions: The authors demonstrated that the GMM approach can effectively be applied to register CTA to biplane XA images for the purpose of improving image guidance in percutaneous coronary interventions.« less

[Imaging assessment of bone and cartilage destruction in rheumatoid arthritis].

PubMed

Hirata, Shintaro; Tanaka, Yoshiya

2015-12-01

Rheumatoid arthritis (RA) is characterized by synovitis and subsequent joint destruction involving bone and cartilage. Recent therapeutic development have improved outcomes including disease activity and structural progression in RA, and standardized procedures of imaging assessment including modified total Sharp score (mTSS) have contributed largely for the development of therapeutic strategy. In addition, ultrasonography and MRI of joints have been recently emerging as novel imaging methods for RA. Here, we review current imaging assessments of bone and cartilage destruction in RA.

Nanoparticle-assisted laser desorption/ionization mass spectrometry: Novel sample preparation methods and nanoparticle screening for plant metabolite imaging

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

Yagnik, Gargey B.

The main goal of the presented research is development of nanoparticle based matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS). This dissertation includes the application of previously developed data acquisition methods, development of novel sample preparation methods, application and comparison of novel nanoparticle matrices, and comparison of two nanoparticle matrix application methods for MALDI-MS and MALDI-MS imaging.

Electron tomography simulator with realistic 3D phantom for evaluation of acquisition, alignment and reconstruction methods.

PubMed

Wan, Xiaohua; Katchalski, Tsvi; Churas, Christopher; Ghosh, Sreya; Phan, Sebastien; Lawrence, Albert; Hao, Yu; Zhou, Ziying; Chen, Ruijuan; Chen, Yu; Zhang, Fa; Ellisman, Mark H

2017-05-01

Because of the significance of electron microscope tomography in the investigation of biological structure at nanometer scales, ongoing improvement efforts have been continuous over recent years. This is particularly true in the case of software developments. Nevertheless, verification of improvements delivered by new algorithms and software remains difficult. Current analysis tools do not provide adaptable and consistent methods for quality assessment. This is particularly true with images of biological samples, due to image complexity, variability, low contrast and noise. We report an electron tomography (ET) simulator with accurate ray optics modeling of image formation that includes curvilinear trajectories through the sample, warping of the sample and noise. As a demonstration of the utility of our approach, we have concentrated on providing verification of the class of reconstruction methods applicable to wide field images of stained plastic-embedded samples. Accordingly, we have also constructed digital phantoms derived from serial block face scanning electron microscope images. These phantoms are also easily modified to include alignment features to test alignment algorithms. The combination of more realistic phantoms with more faithful simulations facilitates objective comparison of acquisition parameters, alignment and reconstruction algorithms and their range of applicability. With proper phantoms, this approach can also be modified to include more complex optical models, including distance-dependent blurring and phase contrast functions, such as may occur in cryotomography. Copyright © 2017 Elsevier Inc. All rights reserved.

Systems, computer-implemented methods, and tangible computer-readable storage media for wide-field interferometry

NASA Technical Reports Server (NTRS)

Lyon, Richard G. (Inventor); Leisawitz, David T. (Inventor); Rinehart, Stephen A. (Inventor); Memarsadeghi, Nargess (Inventor)

2012-01-01

Disclosed herein are systems, computer-implemented methods, and tangible computer-readable storage media for wide field imaging interferometry. The method includes for each point in a two dimensional detector array over a field of view of an image: gathering a first interferogram from a first detector and a second interferogram from a second detector, modulating a path-length for a signal from an image associated with the first interferogram in the first detector, overlaying first data from the modulated first detector and second data from the second detector, and tracking the modulating at every point in a two dimensional detector array comprising the first detector and the second detector over a field of view for the image. The method then generates a wide-field data cube based on the overlaid first data and second data for each point. The method can generate an image from the wide-field data cube.

Adaptive removal of background and white space from document images using seam categorization

NASA Astrophysics Data System (ADS)

Fillion, Claude; Fan, Zhigang; Monga, Vishal

2011-03-01

Document images are obtained regularly by rasterization of document content and as scans of printed documents. Resizing via background and white space removal is often desired for better consumption of these images, whether on displays or in print. While white space and background are easy to identify in images, existing methods such as naïve removal and content aware resizing (seam carving) each have limitations that can lead to undesirable artifacts, such as uneven spacing between lines of text or poor arrangement of content. An adaptive method based on image content is hence needed. In this paper we propose an adaptive method to intelligently remove white space and background content from document images. Document images are different from pictorial images in structure. They typically contain objects (text letters, pictures and graphics) separated by uniform background, which include both white paper space and other uniform color background. Pixels in uniform background regions are excellent candidates for deletion if resizing is required, as they introduce less change in document content and style, compared with deletion of object pixels. We propose a background deletion method that exploits both local and global context. The method aims to retain the document structural information and image quality.

Person Recognition System Based on a Combination of Body Images from Visible Light and Thermal Cameras.

PubMed

Nguyen, Dat Tien; Hong, Hyung Gil; Kim, Ki Wan; Park, Kang Ryoung

2017-03-16

The human body contains identity information that can be used for the person recognition (verification/recognition) problem. In this paper, we propose a person recognition method using the information extracted from body images. Our research is novel in the following three ways compared to previous studies. First, we use the images of human body for recognizing individuals. To overcome the limitations of previous studies on body-based person recognition that use only visible light images for recognition, we use human body images captured by two different kinds of camera, including a visible light camera and a thermal camera. The use of two different kinds of body image helps us to reduce the effects of noise, background, and variation in the appearance of a human body. Second, we apply a state-of-the art method, called convolutional neural network (CNN) among various available methods, for image features extraction in order to overcome the limitations of traditional hand-designed image feature extraction methods. Finally, with the extracted image features from body images, the recognition task is performed by measuring the distance between the input and enrolled samples. The experimental results show that the proposed method is efficient for enhancing recognition accuracy compared to systems that use only visible light or thermal images of the human body.

Overview of machine vision methods in x-ray imaging and microtomography

NASA Astrophysics Data System (ADS)

Buzmakov, Alexey; Zolotov, Denis; Chukalina, Marina; Nikolaev, Dmitry; Gladkov, Andrey; Ingacheva, Anastasia; Yakimchuk, Ivan; Asadchikov, Victor

2018-04-01

Digital X-ray imaging became widely used in science, medicine, non-destructive testing. This allows using modern digital images analysis for automatic information extraction and interpretation. We give short review of scientific applications of machine vision in scientific X-ray imaging and microtomography, including image processing, feature detection and extraction, images compression to increase camera throughput, microtomography reconstruction, visualization and setup adjustment.

New Techniques for High-contrast Imaging with ADI: The ACORNS-ADI SEEDS Data Reduction Pipeline

NASA Astrophysics Data System (ADS)

Brandt, Timothy D.; McElwain, Michael W.; Turner, Edwin L.; Abe, L.; Brandner, W.; Carson, J.; Egner, S.; Feldt, M.; Golota, T.; Goto, M.; Grady, C. A.; Guyon, O.; Hashimoto, J.; Hayano, Y.; Hayashi, M.; Hayashi, S.; Henning, T.; Hodapp, K. W.; Ishii, M.; Iye, M.; Janson, M.; Kandori, R.; Knapp, G. R.; Kudo, T.; Kusakabe, N.; Kuzuhara, M.; Kwon, J.; Matsuo, T.; Miyama, S.; Morino, J.-I.; Moro-Martín, A.; Nishimura, T.; Pyo, T.-S.; Serabyn, E.; Suto, H.; Suzuki, R.; Takami, M.; Takato, N.; Terada, H.; Thalmann, C.; Tomono, D.; Watanabe, M.; Wisniewski, J. P.; Yamada, T.; Takami, H.; Usuda, T.; Tamura, M.

2013-02-01

We describe Algorithms for Calibration, Optimized Registration, and Nulling the Star in Angular Differential Imaging (ACORNS-ADI), a new, parallelized software package to reduce high-contrast imaging data, and its application to data from the SEEDS survey. We implement several new algorithms, including a method to register saturated images, a trimmed mean for combining an image sequence that reduces noise by up to ~20%, and a robust and computationally fast method to compute the sensitivity of a high-contrast observation everywhere on the field of view without introducing artificial sources. We also include a description of image processing steps to remove electronic artifacts specific to Hawaii2-RG detectors like the one used for SEEDS, and a detailed analysis of the Locally Optimized Combination of Images (LOCI) algorithm commonly used to reduce high-contrast imaging data. ACORNS-ADI is written in python. It is efficient and open-source, and includes several optional features which may improve performance on data from other instruments. ACORNS-ADI requires minimal modification to reduce data from instruments other than HiCIAO. It is freely available for download at www.github.com/t-brandt/acorns-adi under a Berkeley Software Distribution (BSD) license. Based on data collected at Subaru Telescope, which is operated by the National Astronomical Observatory of Japan.

[Research on spatially modulated Fourier transform imaging spectrometer data processing method].

PubMed

Huang, Min; Xiangli, Bin; Lü, Qun-Bo; Zhou, Jin-Song; Jing, Juan-Juan; Cui, Yan

2010-03-01

Fourier transform imaging spectrometer is a new technic, and has been developed very rapidly in nearly ten years. The data catched by Fourier transform imaging spectrometer is indirect data, can not be used by user, and need to be processed by various approaches, including data pretreatment, apodization, phase correction, FFT, and spectral radicalization calibration. No paper so far has been found roundly to introduce this method. In the present paper, the author will give an effective method to process the interfering data to spectral data, and with this method we can obtain good result.

Automatic annotation of histopathological images using a latent topic model based on non-negative matrix factorization

PubMed Central

Cruz-Roa, Angel; Díaz, Gloria; Romero, Eduardo; González, Fabio A.

2011-01-01

Histopathological images are an important resource for clinical diagnosis and biomedical research. From an image understanding point of view, the automatic annotation of these images is a challenging problem. This paper presents a new method for automatic histopathological image annotation based on three complementary strategies, first, a part-based image representation, called the bag of features, which takes advantage of the natural redundancy of histopathological images for capturing the fundamental patterns of biological structures, second, a latent topic model, based on non-negative matrix factorization, which captures the high-level visual patterns hidden in the image, and, third, a probabilistic annotation model that links visual appearance of morphological and architectural features associated to 10 histopathological image annotations. The method was evaluated using 1,604 annotated images of skin tissues, which included normal and pathological architectural and morphological features, obtaining a recall of 74% and a precision of 50%, which improved a baseline annotation method based on support vector machines in a 64% and 24%, respectively. PMID:22811960

Mapping the different methods adopted for diagnostic imaging instruction at medical schools in Brazil

PubMed Central

Chojniak, Rubens; Carneiro, Dominique Piacenti; Moterani, Gustavo Simonetto Peres; Duarte, Ivone da Silva; Bitencourt, Almir Galvão Vieira; Muglia, Valdair Francisco; D'Ippolito, Giuseppe

2017-01-01

Objective To map the different methods for diagnostic imaging instruction at medical schools in Brazil. Materials and Methods In this cross-sectional study, a questionnaire was sent to each of the coordinators of 178 Brazilian medical schools. The following characteristics were assessed: teaching model; total course hours; infrastructure; numbers of students and professionals involved; themes addressed; diagnostic imaging modalities covered; and education policies related to diagnostic imaging. Results Of the 178 questionnaires sent, 45 (25.3%) were completed and returned. Of those 45 responses, 17 (37.8%) were from public medical schools, whereas 28 (62.2%) were from private medical schools. Among the 45 medical schools evaluated, the method of diagnostic imaging instruction was modular at 21 (46.7%), classic (independent discipline) at 13 (28.9%), hybrid (classical and modular) at 9 (20.0%), and none of the preceding at 3 (6.7%). Diagnostic imaging is part of the formal curriculum at 36 (80.0%) of the schools, an elective course at 3 (6.7%), and included within another modality at 6 (13.3%). Professors involved in diagnostic imaging teaching are radiologists at 43 (95.5%) of the institutions. Conclusion The survey showed that medical courses in Brazil tend to offer diagnostic imaging instruction in courses that include other content and at different time points during the course. Radiologists are extensively involved in undergraduate medical education, regardless of the teaching methodology employed at the institution. PMID:28298730

System and method for bullet tracking and shooter localization

DOEpatents

Roberts, Randy S [Livermore, CA; Breitfeller, Eric F [Dublin, CA

2011-06-21

A system and method of processing infrared imagery to determine projectile trajectories and the locations of shooters with a high degree of accuracy. The method includes image processing infrared image data to reduce noise and identify streak-shaped image features, using a Kalman filter to estimate optimal projectile trajectories, updating the Kalman filter with new image data, determining projectile source locations by solving a combinatorial least-squares solution for all optimal projectile trajectories, and displaying all of the projectile source locations. Such a shooter-localization system is of great interest for military and law enforcement applications to determine sniper locations, especially in urban combat scenarios.

Improved Discrete Approximation of Laplacian of Gaussian

NASA Technical Reports Server (NTRS)

Shuler, Robert L., Jr.

2004-01-01

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

Development and Validation of the Suprathreshold Stochastic Resonance-Based Image Processing Method for the Detection of Abdomino-pelvic Tumor on PET/CT Scans.

PubMed

Saroha, Kartik; Pandey, Anil Kumar; Sharma, Param Dev; Behera, Abhishek; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh

2017-01-01

The detection of abdomino-pelvic tumors embedded in or nearby radioactive urine containing 18F-FDG activity is a challenging task on PET/CT scan. In this study, we propose and validate the suprathreshold stochastic resonance-based image processing method for the detection of these tumors. The method consists of the addition of noise to the input image, and then thresholding it that creates one frame of intermediate image. One hundred such frames were generated and averaged to get the final image. The method was implemented using MATLAB R2013b on a personal computer. Noisy image was generated using random Poisson variates corresponding to each pixel of the input image. In order to verify the method, 30 sets of pre-diuretic and its corresponding post-diuretic PET/CT scan images (25 tumor images and 5 control images with no tumor) were included. For each sets of pre-diuretic image (input image), 26 images (at threshold values equal to mean counts multiplied by a constant factor ranging from 1.0 to 2.6 with increment step of 0.1) were created and visually inspected, and the image that most closely matched with the gold standard (corresponding post-diuretic image) was selected as the final output image. These images were further evaluated by two nuclear medicine physicians. In 22 out of 25 images, tumor was successfully detected. In five control images, no false positives were reported. Thus, the empirical probability of detection of abdomino-pelvic tumors evaluates to 0.88. The proposed method was able to detect abdomino-pelvic tumors on pre-diuretic PET/CT scan with a high probability of success and no false positives.

Boron-based dual imaging probes, compositions and methods for rapid aqueous F-18 labeling, and imaging methods using same

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

Li, Zibo; Gabbai, Francois P.; Conti, Peter S.

A composition useful as a PET and/or fluorescence imaging probe a compound a compound of Formula I, including salts, hydrates and solvates thereof: ##STR00001## wherein R.sub.1-R.sub.7 may be independently selected from hydrogen, halogen, hydroxy, alkoxy, nitro, substituted and unsubstituted amino, cycloalkyl, carboxy, carboxylic acids and esters thereof, cyano, haloalkyl, aryl, X is selected from the group consisting of C and N; and A is selected of hydrogen, halogen, hydroxy, alkoxy, nitro, substituted and unsubstituted amino, alkyl, cycloalkyl, carboxy, carboxylic acids and esters thereof, cyano, haloalkyl, aryl, including phenyl and aminophenyl, and heteroaryl.

Method and apparatus for implementing material thermal property measurement by flash thermal imaging

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

Sun, Jiangang

A method and apparatus are provided for implementing measurement of material thermal properties including measurement of thermal effusivity of a coating and/or film or a bulk material of uniform property. The test apparatus includes an infrared camera, a data acquisition and processing computer coupled to the infrared camera for acquiring and processing thermal image data, a flash lamp providing an input of heat onto the surface of a two-layer sample with an enhanced optical filter covering the flash lamp attenuating an entire infrared wavelength range with a series of thermal images is taken of the surface of the two-layer sample.

System and method for generating motion corrected tomographic images

DOEpatents

Gleason, Shaun S [Knoxville, TN; Goddard, Jr., James S.

2012-05-01

A method and related system for generating motion corrected tomographic images includes the steps of illuminating a region of interest (ROI) to be imaged being part of an unrestrained live subject and having at least three spaced apart optical markers thereon. Simultaneous images are acquired from a first and a second camera of the markers from different angles. Motion data comprising 3D position and orientation of the markers relative to an initial reference position is then calculated. Motion corrected tomographic data obtained from the ROI using the motion data is then obtained, where motion corrected tomographic images obtained therefrom.

Gimbaled multispectral imaging system and method

DOEpatents

Brown, Kevin H.; Crollett, Seferino; Henson, Tammy D.; Napier, Matthew; Stromberg, Peter G.

2016-01-26

A gimbaled multispectral imaging system and method is described herein. In an general embodiment, the gimbaled multispectral imaging system has a cross support that defines a first gimbal axis and a second gimbal axis, wherein the cross support is rotatable about the first gimbal axis. The gimbaled multispectral imaging system comprises a telescope that fixed to an upper end of the cross support, such that rotation of the cross support about the first gimbal axis causes the tilt of the telescope to alter. The gimbaled multispectral imaging system includes optics that facilitate on-gimbal detection of visible light and off-gimbal detection of infrared light.

Molar axis estimation from computed tomography images.

PubMed

Dongxia Zhang; Yangzhou Gan; Zeyang Xia; Xinwen Zhou; Shoubin Liu; Jing Xiong; Guanglin Li

2016-08-01

Estimation of tooth axis is needed for some clinical dental treatment. Existing methods require to segment the tooth volume from Computed Tomography (CT) images, and then estimate the axis from the tooth volume. However, they may fail during estimating molar axis due to that the tooth segmentation from CT images is challenging and current segmentation methods may get poor segmentation results especially for these molars with angle which will result in the failure of axis estimation. To resolve this problem, this paper proposes a new method for molar axis estimation from CT images. The key innovation point is that: instead of estimating the 3D axis of each molar from the segmented volume, the method estimates the 3D axis from two projection images. The method includes three steps. (1) The 3D images of each molar are projected to two 2D image planes. (2) The molar contour are segmented and the contour's 2D axis are extracted in each 2D projection image. Principal Component Analysis (PCA) and a modified symmetry axis detection algorithm are employed to extract the 2D axis from the segmented molar contour. (3) A 3D molar axis is obtained by combining the two 2D axes. Experimental results verified that the proposed method was effective to estimate the axis of molar from CT images.

An object-oriented simulator for 3D digital breast tomosynthesis imaging system.

PubMed

Seyyedi, Saeed; Cengiz, Kubra; Kamasak, Mustafa; Yildirim, Isa

2013-01-01

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values.

Implementation of an anonymisation tool for clinical trials using a clinical trial processor integrated with an existing trial patient data information system.

PubMed

Aryanto, Kadek Y E; Broekema, André; Oudkerk, Matthijs; van Ooijen, Peter M A

2012-01-01

To present an adapted Clinical Trial Processor (CTP) test set-up for receiving, anonymising and saving Digital Imaging and Communications in Medicine (DICOM) data using external input from the original database of an existing clinical study information system to guide the anonymisation process. Two methods are presented for an adapted CTP test set-up. In the first method, images are pushed from the Picture Archiving and Communication System (PACS) using the DICOM protocol through a local network. In the second method, images are transferred through the internet using the HTTPS protocol. In total 25,000 images from 50 patients were moved from the PACS, anonymised and stored within roughly 2 h using the first method. In the second method, an average of 10 images per minute were transferred and processed over a residential connection. In both methods, no duplicated images were stored when previous images were retransferred. The anonymised images are stored in appropriate directories. The CTP can transfer and process DICOM images correctly in a very easy set-up providing a fast, secure and stable environment. The adapted CTP allows easy integration into an environment in which patient data are already included in an existing information system.

An Object-Oriented Simulator for 3D Digital Breast Tomosynthesis Imaging System

PubMed Central

Cengiz, Kubra

2013-01-01

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3D image of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values. PMID:24371468

Retinal imaging and image analysis.

PubMed

Abràmoff, Michael D; Garvin, Mona K; Sonka, Milan

2010-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships.

Retinal Imaging and Image Analysis

PubMed Central

Abràmoff, Michael D.; Garvin, Mona K.; Sonka, Milan

2011-01-01

Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships. PMID:22275207

Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images.

PubMed

Ruusuvuori, Pekka; Aijö, Tarmo; Chowdhury, Sharif; Garmendia-Torres, Cecilia; Selinummi, Jyrki; Birbaumer, Mirko; Dudley, Aimée M; Pelkmans, Lucas; Yli-Harja, Olli

2010-05-13

Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method selection and thus more accurate results, relatively few studies have been performed. To better understand algorithm performance under different conditions, we have carried out a comparative study including eleven spot detection or segmentation algorithms from various application fields. We used microscope images from well plate experiments with a human osteosarcoma cell line and frames from image stacks of yeast cells in different focal planes. These experimentally derived images permit a comparison of method performance in realistic situations where the number of objects varies within image set. We also used simulated microscope images in order to compare the methods and validate them against a ground truth reference result. Our study finds major differences in the performance of different algorithms, in terms of both object counts and segmentation accuracies. These results suggest that the selection of detection algorithms for image based screens should be done carefully and take into account different conditions, such as the possibility of acquiring empty images or images with very few spots. Our inclusion of methods that have not been used before in this context broadens the set of available detection methods and compares them against the current state-of-the-art methods for subcellular particle detection.

Method for the reduction of image content redundancy in large image databases

DOEpatents

Tobin, Kenneth William; Karnowski, Thomas P.

2010-03-02

A method of increasing information content for content-based image retrieval (CBIR) systems includes the steps of providing a CBIR database, the database having an index for a plurality of stored digital images using a plurality of feature vectors, the feature vectors corresponding to distinct descriptive characteristics of the images. A visual similarity parameter value is calculated based on a degree of visual similarity between features vectors of an incoming image being considered for entry into the database and feature vectors associated with a most similar of the stored images. Based on said visual similarity parameter value it is determined whether to store or how long to store the feature vectors associated with the incoming image in the database.

TU-AB-207-01: Introduction to Tomosynthesis

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

Sechopoulos, I.

2015-06-15

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact,more » the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. To learn how to test the performance of tomosynthesis imaging systems. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.« less

TU-AB-207-03: Tomosynthesis: Clinical Applications

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

Maidment, A.

2015-06-15

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact,more » the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. To learn how to test the performance of tomosynthesis imaging systems. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.« less

TU-AB-207-00: Digital Tomosynthesis

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

NONE

2015-06-15

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact,more » the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. To learn how to test the performance of tomosynthesis imaging systems. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.« less

TU-AB-207-02: Testing of Body and Breast Tomosynthesis Sytems

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

Jones, A.

2015-06-15

Digital Tomosynthesis (DT) is becoming increasingly common in breast imaging and many other applications. DT is a form of computed tomography in which a limited set of projection images are acquired over a small angular range and reconstructed into a tomographic data set. The angular range and number of projections is determined both by the imaging task and equipment manufacturer. For example, in breast imaging between 9 and 25 projections are acquired over a range of 15° to 60°. It is equally valid to treat DT as the digital analog of classical tomography - for example, linear tomography. In fact,more » the name “tomosynthesis” is an acronym for “synthetic tomography”. DT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DT systems is a hybrid between CT and classical tomographic methods. This lecture will consist of three presentations that will provide a complete overview of DT, including a review of the fundamentals of DT, a discussion of testing methods for DT systems, and a description of the clinical applications of DT. While digital breast tomosynthesis will be emphasized, analogies will be drawn to body imaging to illustrate and compare tomosynthesis methods. Learning Objectives: To understand the fundamental principles behind tomosynthesis, including the determinants of image quality and dose. To learn how to test the performance of tomosynthesis imaging systems. To appreciate the uses of tomosynthesis in the clinic and the future applications of tomosynthesis.« less

Dynamical Modeling of NGC 6397: Simulated HST Imaging

NASA Astrophysics Data System (ADS)

Dull, J. D.; Cohn, H. N.; Lugger, P. M.; Slavin, S. D.; Murphy, B. W.

1994-12-01

The proximity of NGC 6397 (2.2 kpc) provides an ideal opportunity to test current dynamical models for globular clusters with the HST Wide-Field/Planetary Camera (WFPC2)\\@. We have used a Monte Carlo algorithm to generate ensembles of simulated Planetary Camera (PC) U-band images of NGC 6397 from evolving, multi-mass Fokker-Planck models. These images, which are based on the post-repair HST-PC point-spread function, are used to develop and test analysis methods for recovering structural information from actual HST imaging. We have considered a range of exposure times up to 2.4times 10(4) s, based on our proposed HST Cycle 5 observations. Our Fokker-Planck models include energy input from dynamically-formed binaries. We have adopted a 20-group mass spectrum extending from 0.16 to 1.4 M_sun. We use theoretical luminosity functions for red giants and main sequence stars. Horizontal branch stars, blue stragglers, white dwarfs, and cataclysmic variables are also included. Simulated images are generated for cluster models at both maximal core collapse and at a post-collapse bounce. We are carrying out stellar photometry on these images using ``DAOPHOT-assisted aperture photometry'' software that we have developed. We are testing several techniques for analyzing the resulting star counts, to determine the underlying cluster structure, including parametric model fits and the nonparametric density estimation methods. Our simulated images also allow us to investigate the accuracy and completeness of methods for carrying out stellar photometry in HST Planetary Camera images of dense cluster cores.

New Techniques for High-Contrast Imaging with ADI: The ACORNS-ADI SEEDS Data Reduction Pipeline

NASA Technical Reports Server (NTRS)

Brandt, Timothy D.; McElwain, Michael W.; Turner, Edwin L.; Abe, L.; Brandner, W.; Carson, J.; Egner, S.; Feldt, M.; Golota, T.; Grady, C. A.;

Modern Micro and Nanoparticle-Based Imaging Techniques

PubMed Central

Ryvolova, Marketa; Chomoucka, Jana; Drbohlavova, Jana; Kopel, Pavel; Babula, Petr; Hynek, David; Adam, Vojtech; Eckschlager, Tomas; Hubalek, Jaromir; Stiborova, Marie; Kaiser, Jozef; Kizek, Rene

2012-01-01

The requirements for early diagnostics as well as effective treatment of insidious diseases such as cancer constantly increase the pressure on development of efficient and reliable methods for targeted drug/gene delivery as well as imaging of the treatment success/failure. One of the most recent approaches covering both the drug delivery as well as the imaging aspects is benefitting from the unique properties of nanomaterials. Therefore a new field called nanomedicine is attracting continuously growing attention. Nanoparticles, including fluorescent semiconductor nanocrystals (quantum dots) and magnetic nanoparticles, have proven their excellent properties for in vivo imaging techniques in a number of modalities such as magnetic resonance and fluorescence imaging, respectively. In this article, we review the main properties and applications of nanoparticles in various in vitro imaging techniques, including microscopy and/or laser breakdown spectroscopy and in vivo methods such as magnetic resonance imaging and/or fluorescence-based imaging. Moreover the advantages of the drug delivery performed by nanocarriers such as iron oxides, gold, biodegradable polymers, dendrimers, lipid based carriers such as liposomes or micelles are also highlighted. PMID:23202187

Probabilistic-driven oriented Speckle reducing anisotropic diffusion with application to cardiac ultrasonic images.

PubMed

Vegas-Sanchez-Ferrero, G; Aja-Fernandez, S; Martin-Fernandez, M; Frangi, A F; Palencia, C

2010-01-01

A novel anisotropic diffusion filter is proposed in this work with application to cardiac ultrasonic images. It includes probabilistic models which describe the probability density function (PDF) of tissues and adapts the diffusion tensor to the image iteratively. For this purpose, a preliminary study is performed in order to select the probability models that best fit the stastitical behavior of each tissue class in cardiac ultrasonic images. Then, the parameters of the diffusion tensor are defined taking into account the statistical properties of the image at each voxel. When the structure tensor of the probability of belonging to each tissue is included in the diffusion tensor definition, a better boundaries estimates can be obtained instead of calculating directly the boundaries from the image. This is the main contribution of this work. Additionally, the proposed method follows the statistical properties of the image in each iteration. This is considered as a second contribution since state-of-the-art methods suppose that noise or statistical properties of the image do not change during the filter process.

Real-time hyperspectral imaging for food safety applications

USDA-ARS?s Scientific Manuscript database

Multispectral imaging systems with selected bands can commonly be used for real-time applications of food processing. Recent research has demonstrated several image processing methods including binning, noise removal filter, and appropriate morphological analysis in real-time mode can remove most fa...

Studies of superresolution range-Doppler imaging

NASA Astrophysics Data System (ADS)

Zhu, Zhaoda; Ye, Zhenru; Wu, Xiaoqing; Yin, Jun; She, Zhishun

1993-02-01

This paper presents three superresolution imaging methods, including the linear prediction data extrapolation DFT (LPDEDFT), the dynamic optimization linear least squares (DOLLS), and the Hopfield neural network nonlinear least squares (HNNNLS). Live data of a metalized scale model B-52 aircraft, mounted on a rotating platform in a microwave anechoic chamber, have in this way been processed, as has a flying Boeing-727 aircraft. The imaging results indicate that, compared to the conventional Fourier method, either higher resolution for the same effective bandwidth of transmitted signals and total rotation angle in imaging, or equal-quality images from smaller bandwidth and total rotation, angle may be obtained by these superresolution approaches. Moreover, these methods are compared in respect of their resolution capability and computational complexity.

Multiscale Medical Image Fusion in Wavelet Domain

PubMed Central

Khare, Ashish

2013-01-01

Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach. PMID:24453868

Online updating of context-aware landmark detectors for prostate localization in daily treatment CT images

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

Dai, Xiubin; Gao, Yaozong; Shen, Dinggang, E-mail: dgshen@med.unc.edu

2015-05-15

Purpose: In image guided radiation therapy, it is crucial to fast and accurately localize the prostate in the daily treatment images. To this end, the authors propose an online update scheme for landmark-guided prostate segmentation, which can fully exploit valuable patient-specific information contained in the previous treatment images and can achieve improved performance in landmark detection and prostate segmentation. Methods: To localize the prostate in the daily treatment images, the authors first automatically detect six anatomical landmarks on the prostate boundary by adopting a context-aware landmark detection method. Specifically, in this method, a two-layer regression forest is trained as amore » detector for each target landmark. Once all the newly detected landmarks from new treatment images are reviewed or adjusted (if necessary) by clinicians, they are further included into the training pool as new patient-specific information to update all the two-layer regression forests for the next treatment day. As more and more treatment images of the current patient are acquired, the two-layer regression forests can be continually updated by incorporating the patient-specific information into the training procedure. After all target landmarks are detected, a multiatlas random sample consensus (multiatlas RANSAC) method is used to segment the entire prostate by fusing multiple previously segmented prostates of the current patient after they are aligned to the current treatment image. Subsequently, the segmented prostate of the current treatment image is again reviewed (or even adjusted if needed) by clinicians before including it as a new shape example into the prostate shape dataset for helping localize the entire prostate in the next treatment image. Results: The experimental results on 330 images of 24 patients show the effectiveness of the authors’ proposed online update scheme in improving the accuracies of both landmark detection and prostate segmentation. Besides, compared to the other state-of-the-art prostate segmentation methods, the authors’ method achieves the best performance. Conclusions: By appropriate use of valuable patient-specific information contained in the previous treatment images, the authors’ proposed online update scheme can obtain satisfactory results for both landmark detection and prostate segmentation.« less

An improved arteriovenous classification method for the early diagnostics of various diseases in retinal image.

PubMed

Xu, Xiayu; Ding, Wenxiang; Abràmoff, Michael D; Cao, Ruofan

2017-04-01

Retinal artery and vein classification is an important task for the automatic computer-aided diagnosis of various eye diseases and systemic diseases. This paper presents an improved supervised artery and vein classification method in retinal image. Intra-image regularization and inter-subject normalization is applied to reduce the differences in feature space. Novel features, including first-order and second-order texture features, are utilized to capture the discriminating characteristics of arteries and veins. The proposed method was tested on the DRIVE dataset and achieved an overall accuracy of 0.923. This retinal artery and vein classification algorithm serves as a potentially important tool for the early diagnosis of various diseases, including diabetic retinopathy and cardiovascular diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

Overview of Microwave and Millimeter Wave Testing Activities for the Inspection of the Space Shuttle SOH and Heat Tiles

NASA Technical Reports Server (NTRS)

Zoughi, R.

2005-01-01

Microwave and millimeter wave nondestructive testing and evaluation methods, have shown great potential for inspecting the Space Shuttle s external tank spray on foam insulation (SOFI) and acreage heat tiles. These methods are capable of producing high-resolution images of et interior of these structures. To this end, several different microwave and millimeter wave nondestructive testing methods have been investigated for this purpose. These methods have included near-field as well as focused approaches ranging in frequency from 10 GHz to beyond 100 GHz. Additionally, synthetic aperture focusing methods have also been developed in this regime for obtaining high-resolution images of the interior of these critical structures. These methods possess the potential for producing 3D images of these structures in a relatively short amount of time. This paper presents a summary of these activities in addition to providing examples of images produced using these diverse methods.

Methods and Systems for Measurement and Estimation of Normalized Contrast in Infrared Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M. (Inventor)

2017-01-01

Methods and systems for converting an image contrast evolution of an object to a temperature contrast evolution and vice versa are disclosed, including methods for assessing an emissivity of the object; calculating an afterglow heat flux evolution; calculating a measurement region of interest temperature change; calculating a reference region of interest temperature change; calculating a reflection temperature change; calculating the image contrast evolution or the temperature contrast evolution; and converting the image contrast evolution to the temperature contrast evolution or vice versa, respectively.

Methods and Systems for Measurement and Estimation of Normalized Contrast in Infrared Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M. (Inventor)

2015-01-01

Methods and systems for converting an image contrast evolution of an object to a temperature contrast evolution and vice versa are disclosed, including methods for assessing an emissivity of the object; calculating an afterglow heat flux evolution; calculating a measurement region of interest temperature change; calculating a reference region of interest temperature change; calculating a reflection temperature change; calculating the image contrast evolution or the temperature contrast evolution; and converting the image contrast evolution to the temperature contrast evolution or vice versa, respectively.

Applications of emerging imaging techniques for meat quality and safety detection and evaluation: A review.

PubMed

Xiong, Zhenjie; Sun, Da-Wen; Pu, Hongbin; Gao, Wenhong; Dai, Qiong

2017-03-04

With improvement in people's living standards, many people nowadays pay more attention to quality and safety of meat. However, traditional methods for meat quality and safety detection and evaluation, such as manual inspection, mechanical methods, and chemical methods, are tedious, time-consuming, and destructive, which cannot meet the requirements of modern meat industry. Therefore, seeking out rapid, non-destructive, and accurate inspection techniques is important for the meat industry. In recent years, a number of novel and noninvasive imaging techniques, such as optical imaging, ultrasound imaging, tomographic imaging, thermal imaging, and odor imaging, have emerged and shown great potential in quality and safety assessment. In this paper, a detailed overview of advanced applications of these emerging imaging techniques for quality and safety assessment of different types of meat (pork, beef, lamb, chicken, and fish) is presented. In addition, advantages and disadvantages of each imaging technique are also summarized. Finally, future trends for these emerging imaging techniques are discussed, including integration of multiple imaging techniques, cost reduction, and developing powerful image-processing algorithms.

Cardiac-gated parametric images from 82 Rb PET from dynamic frames and direct 4D reconstruction.

PubMed

Germino, Mary; Carson, Richard E

2018-02-01

Cardiac perfusion PET data can be reconstructed as a dynamic sequence and kinetic modeling performed to quantify myocardial blood flow, or reconstructed as static gated images to quantify function. Parametric images from dynamic PET are conventionally not gated, to allow use of all events with lower noise. An alternative method for dynamic PET is to incorporate the kinetic model into the reconstruction algorithm itself, bypassing the generation of a time series of emission images and directly producing parametric images. So-called "direct reconstruction" can produce parametric images with lower noise than the conventional method because the noise distribution is more easily modeled in projection space than in image space. In this work, we develop direct reconstruction of cardiac-gated parametric images for 82 Rb PET with an extension of the Parametric Motion compensation OSEM List mode Algorithm for Resolution-recovery reconstruction for the one tissue model (PMOLAR-1T). PMOLAR-1T was extended to accommodate model terms to account for spillover from the left and right ventricles into the myocardium. The algorithm was evaluated on a 4D simulated 82 Rb dataset, including a perfusion defect, as well as a human 82 Rb list mode acquisition. The simulated list mode was subsampled into replicates, each with counts comparable to one gate of a gated acquisition. Parametric images were produced by the indirect (separate reconstructions and modeling) and direct methods for each of eight low-count and eight normal-count replicates of the simulated data, and each of eight cardiac gates for the human data. For the direct method, two initialization schemes were tested: uniform initialization, and initialization with the filtered iteration 1 result of the indirect method. For the human dataset, event-by-event respiratory motion compensation was included. The indirect and direct methods were compared for the simulated dataset in terms of bias and coefficient of variation as a function of iteration. Convergence of direct reconstruction was slow with uniform initialization; lower bias was achieved in fewer iterations by initializing with the filtered indirect iteration 1 images. For most parameters and regions evaluated, the direct method achieved the same or lower absolute bias at matched iteration as the indirect method, with 23%-65% lower noise. Additionally, the direct method gave better contrast between the perfusion defect and surrounding normal tissue than the indirect method. Gated parametric images from the human dataset had comparable relative performance of indirect and direct, in terms of mean parameter values per iteration. Changes in myocardial wall thickness and blood pool size across gates were readily visible in the gated parametric images, with higher contrast between myocardium and left ventricle blood pool in parametric images than gated SUV images. Direct reconstruction can produce parametric images with less noise than the indirect method, opening the potential utility of gated parametric imaging for perfusion PET. © 2017 American Association of Physicists in Medicine.

Consistency of response and image recognition, pulmonary nodules

PubMed Central

Liu, M A Q; Galvan, E; Bassett, R; Murphy, W A; Matamoros, A; Marom, E M

2014-01-01

Objective: To investigate the effect of recognition of a previously encountered radiograph on consistency of response in localized pulmonary nodules. Methods: 13 radiologists interpreted 40 radiographs each to locate pulmonary nodules. A few days later, they again interpreted 40 radiographs. Half of the images in the second set were new. We asked the radiologists whether each image had been in the first set. We used Fisher's exact test and Kruskal–Wallis test to evaluate the correlation between recognition of an image and consistency in its interpretation. We evaluated the data using all possible recognition levels—definitely, probably or possibly included vs definitely, probably or possibly not included by collapsing the recognition levels into two and by eliminating the “possibly included” and “possibly not included” scores. Results: With all but one of six methods of looking at the data, there was no significant correlation between consistency in interpretation and recognition of the image. When the possibly included and possibly not included scores were eliminated, there was a borderline statistical significance (p = 0.04) with slightly greater consistency in interpretation of recognized than that of non-recognized images. Conclusion: We found no convincing evidence that radiologists' recognition of images in an observer performance study affects their interpretation on a second encounter. Advances in knowledge: Conscious recognition of chest radiographs did not result in a greater degree of consistency in the tested interpretation than that in the interpretation of images that were not recognized. PMID:24697724

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications

PubMed Central

Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

2017-01-01

Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC. PMID:29280970

Background Registration-Based Adaptive Noise Filtering of LWIR/MWIR Imaging Sensors for UAV Applications.

PubMed

Kim, Byeong Hak; Kim, Min Young; Chae, You Seong

2017-12-27

Unmanned aerial vehicles (UAVs) are equipped with optical systems including an infrared (IR) camera such as electro-optical IR (EO/IR), target acquisition and designation sights (TADS), or forward looking IR (FLIR). However, images obtained from IR cameras are subject to noise such as dead pixels, lines, and fixed pattern noise. Nonuniformity correction (NUC) is a widely employed method to reduce noise in IR images, but it has limitations in removing noise that occurs during operation. Methods have been proposed to overcome the limitations of the NUC method, such as two-point correction (TPC) and scene-based NUC (SBNUC). However, these methods still suffer from unfixed pattern noise. In this paper, a background registration-based adaptive noise filtering (BRANF) method is proposed to overcome the limitations of conventional methods. The proposed BRANF method utilizes background registration processing and robust principle component analysis (RPCA). In addition, image quality verification methods are proposed that can measure the noise filtering performance quantitatively without ground truth images. Experiments were performed for performance verification with middle wave infrared (MWIR) and long wave infrared (LWIR) images obtained from practical military optical systems. As a result, it is found that the image quality improvement rate of BRANF is 30% higher than that of conventional NUC.

[The application of X-ray imaging in forensic medicine].

PubMed

Kučerová, Stěpánka; Safr, Miroslav; Ublová, Michaela; Urbanová, Petra; Hejna, Petr

2014-07-01

X-ray is the most common, basic and essential imaging method used in forensic medicine. It serves to display and localize the foreign objects in the body and helps to detect various traumatic and pathological changes. X-ray imaging is valuable in anthropological assessment of an individual. X-ray allows non-invasive evaluation of important findings before the autopsy and thus selection of the optimal strategy for dissection. Basic indications for postmortem X-ray imaging in forensic medicine include gunshot and explosive fatalities (identification and localization of projectiles or other components of ammunition, visualization of secondary missiles), sharp force injuries (air embolism, identification of the weapon) and motor vehicle related deaths. The method is also helpful for complex injury evaluation in abused victims or in persons where abuse is suspected. Finally, X-ray imaging still remains the gold standard method for identification of unknown deceased. With time modern imaging methods, especially computed tomography and magnetic resonance imaging, are more and more applied in forensic medicine. Their application extends possibilities of the visualization the bony structures toward a more detailed imaging of soft tissues and internal organs. The application of modern imaging methods in postmortem body investigation is known as digital or virtual autopsy. At present digital postmortem imaging is considered as a bloodless alternative to the conventional autopsy.

Edge Sharpness Assessment by Parametric Modeling: Application to Magnetic Resonance Imaging.

PubMed

Ahmad, R; Ding, Y; Simonetti, O P

2015-05-01

In biomedical imaging, edge sharpness is an important yet often overlooked image quality metric. In this work, a semi-automatic method to quantify edge sharpness in the presence of significant noise is presented with application to magnetic resonance imaging (MRI). The method is based on parametric modeling of image edges. First, an edge map is automatically generated and one or more edges-of-interest (EOI) are manually selected using graphical user interface. Multiple exclusion criteria are then enforced to eliminate edge pixels that are potentially not suitable for sharpness assessment. Second, at each pixel of the EOI, an image intensity profile is read along a small line segment that runs locally normal to the EOI. Third, the profiles corresponding to all EOI pixels are individually fitted with a sigmoid function characterized by four parameters, including one that represents edge sharpness. Last, the distribution of the sharpness parameter is used to quantify edge sharpness. For validation, the method is applied to simulated data as well as MRI data from both phantom imaging and cine imaging experiments. This method allows for fast, quantitative evaluation of edge sharpness even in images with poor signal-to-noise ratio. Although the utility of this method is demonstrated for MRI, it can be adapted for other medical imaging applications.

A Method of Spatial Mapping and Reclassification for High-Spatial-Resolution Remote Sensing Image Classification

PubMed Central

Wang, Guizhou; Liu, Jianbo; He, Guojin

2013-01-01

This paper presents a new classification method for high-spatial-resolution remote sensing images based on a strategic mechanism of spatial mapping and reclassification. The proposed method includes four steps. First, the multispectral image is classified by a traditional pixel-based classification method (support vector machine). Second, the panchromatic image is subdivided by watershed segmentation. Third, the pixel-based multispectral image classification result is mapped to the panchromatic segmentation result based on a spatial mapping mechanism and the area dominant principle. During the mapping process, an area proportion threshold is set, and the regional property is defined as unclassified if the maximum area proportion does not surpass the threshold. Finally, unclassified regions are reclassified based on spectral information using the minimum distance to mean algorithm. Experimental results show that the classification method for high-spatial-resolution remote sensing images based on the spatial mapping mechanism and reclassification strategy can make use of both panchromatic and multispectral information, integrate the pixel- and object-based classification methods, and improve classification accuracy. PMID:24453808

Use of synchrotron tomography to image naturalistic anatomy in insects

NASA Astrophysics Data System (ADS)

Socha, John J.; De Carlo, Francesco

2008-08-01

Understanding the morphology of anatomical structures is a cornerstone of biology. For small animals, classical methods such as histology have provided a wealth of data, but such techniques can be problematic due to destruction of the sample. More importantly, fixation and physical slicing can cause deformation of anatomy, a critical limitation when precise three-dimensional data are required. Modern techniques such as confocal microscopy, MRI, and tabletop x-ray microCT provide effective non-invasive methods, but each of these tools each has limitations including sample size constraints, resolution limits, and difficulty visualizing soft tissue. Our research group at the Advanced Photon Source (Argonne National Laboratory) studies physiological processes in insects, focusing on the dynamics of breathing and feeding. To determine the size, shape, and relative location of internal anatomy in insects, we use synchrotron microtomography at the beamline 2-BM to image structures including tracheal tubes, muscles, and gut. Because obtaining naturalistic, undeformed anatomical information is a key component of our studies, we have developed methods to image fresh and non-fixed whole animals and tissues. Although motion artifacts remain a problem, we have successfully imaged multiple species including beetles, ants, fruit flies, and butterflies. Here we discuss advances in biological imaging and highlight key findings in insect morphology.

Methods for validating the presence of and characterizing proteins deposited onto an array

DOEpatents

Schabacker, Daniel S.

2010-09-21

A method of determining if proteins have been transferred from liquid-phase protein fractions to an array comprising staining the array with a total protein stain and imaging the array, optionally comparing the staining with a standard curve generated by staining known amounts of a known protein on the same or a similar array; a method of characterizing proteins transferred from liquid-phase protein fractions to an array including staining the array with a post-translational modification-specific (PTM-specific) stain and imaging the array and, optionally, after staining the array with a PTM-specific stain and imaging the array, washing the array, re-staining the array with a total protein stain, imaging the array, and comparing the imaging with the PTM-specific stain with the imaging with the total protein stain; stained arrays; and images of stained arrays.

Imaging for lung physiology: What do we wish we could measure?

PubMed Central

Buxton, Richard B.

2012-01-01

The role of imaging as a tool for investigating lung physiology is growing at an accelerating pace. Looking forward, we wished to identify unresolved issues in lung physiology that might realistically be addressed by imaging methods in development or imaging approaches that could be considered. The role of imaging is framed in terms of the importance of good spatial and temporal resolution and the types of questions that could be addressed as these technical capabilities improve. Recognizing that physiology is fundamentally a quantitative science, a recurring emphasis is on the need for imaging methods that provide reliable measurements of specific physiological parameters. The topics included necessarily reflect our perspective on what are interesting questions and are not meant to be a comprehensive review. Nevertheless, we hope that this essay will be a spur to physiologists to think about how imaging could usefully be applied in their research and to physical scientists developing new imaging methods to attack challenging questions imaging could potentially answer. PMID:22582217

Fuzzy difference-of-Gaussian-based iris recognition method for noisy iris images

NASA Astrophysics Data System (ADS)

Kang, Byung Jun; Park, Kang Ryoung; Yoo, Jang-Hee; Moon, Kiyoung

2010-06-01

Iris recognition is used for information security with a high confidence level because it shows outstanding recognition accuracy by using human iris patterns with high degrees of freedom. However, iris recognition accuracy can be reduced by noisy iris images with optical and motion blurring. We propose a new iris recognition method based on the fuzzy difference-of-Gaussian (DOG) for noisy iris images. This study is novel in three ways compared to previous works: (1) The proposed method extracts iris feature values using the DOG method, which is robust to local variations of illumination and shows fine texture information, including various frequency components. (2) When determining iris binary codes, image noises that cause the quantization error of the feature values are reduced with the fuzzy membership function. (3) The optimal parameters of the DOG filter and the fuzzy membership function are determined in terms of iris recognition accuracy. Experimental results showed that the performance of the proposed method was better than that of previous methods for noisy iris images.

Cyanine-based probe\\tag-peptide pair fluorescence protein imaging and fluorescence protein imaging methods

DOEpatents

Mayer-Cumblidge, M. Uljana; Cao, Haishi

2013-01-15

A molecular probe comprises two arsenic atoms and at least one cyanine based moiety. A method of producing a molecular probe includes providing a molecule having a first formula, treating the molecule with HgOAc, and subsequently transmetallizing with AsCl.sub.3. The As is liganded to ethanedithiol to produce a probe having a second formula. A method of labeling a peptide includes providing a peptide comprising a tag sequence and contacting the peptide with a biarsenical molecular probe. A complex is formed comprising the tag sequence and the molecular probe. A method of studying a peptide includes providing a mixture containing a peptide comprising a peptide tag sequence, adding a biarsenical probe to the mixture, and monitoring the fluorescence of the mixture.

Cyanine-based probe\\tag-peptide pair for fluorescence protein imaging and fluorescence protein imaging methods

DOEpatents

Mayer-Cumblidge, M Uljana [Richland, WA; Cao, Haishi [Richland, WA

2010-08-17

A molecular probe comprises two arsenic atoms and at least one cyanine based moiety. A method of producing a molecular probe includes providing a molecule having a first formula, treating the molecule with HgOAc, and subsequently transmetallizing with AsCl.sub.3. The As is liganded to ethanedithiol to produce a probe having a second formula. A method of labeling a peptide includes providing a peptide comprising a tag sequence and contacting the peptide with a biarsenical molecular probe. A complex is formed comprising the tag sequence and the molecular probe. A method of studying a peptide includes providing a mixture containing a peptide comprising a peptide tag sequence, adding a biarsenical probe to the mixture, and monitoring the fluorescence of the mixture.

Imaging Tumor Cell Movement In Vivo

PubMed Central

Entenberg, David; Kedrin, Dmitriy; Wyckoff, Jeffrey; Sahai, Erik; Condeelis, John; Segall, Jeffrey E.

2013-01-01

This unit describes the methods that we have been developing for analyzing tumor cell motility in mouse and rat models of breast cancer metastasis. Rodents are commonly used both to provide a mammalian system for studying human tumor cells (as xenografts in immunocompromised mice) as well as for following the development of tumors from a specific tissue type in transgenic lines. The Basic Protocol in this unit describes the standard methods used for generation of mammary tumors and imaging them. Additional protocols for labeling macrophages, blood vessel imaging, and image analysis are also included. PMID:23456602

Application of abstract harmonic analysis to the high-speed recognition of images

NASA Technical Reports Server (NTRS)

Usikov, D. A.

1979-01-01

Methods are constructed for rapidly computing correlation functions using the theory of abstract harmonic analysis. The theory developed includes as a particular case the familiar Fourier transform method for a correlation function which makes it possible to find images which are independent of their translation in the plane. Two examples of the application of the general theory described are the search for images, independent of their rotation and scale, and the search for images which are independent of their translations and rotations in the plane.

Probes for multidimensional nanospectroscopic imaging and methods of fabrication thereof

DOEpatents

Weber-Bargioni, Alexander; Cabrini, Stefano; Bao, Wei; Melli, Mauro; Yablonovitch, Eli; Schuck, Peter J

2015-03-17

This disclosure provides systems, methods, and apparatus related to probes for multidimensional nanospectroscopic imaging. In one aspect, a method includes providing a transparent tip comprising a dielectric material. A four-sided pyramidal-shaped structure is formed at an apex of the transparent tip using a focused ion beam. Metal layers are deposited over two opposing sides of the four-sided pyramidal-shaped structure.

A simple method for the detection of PM2.5 air pollutions using MODIS data

NASA Astrophysics Data System (ADS)

Kato, Yoshinobu

2016-05-01

In recent years, PM2.5 air pollution is a social and transboundary environmental issue with the rapid economic growth in many countries. As PM2.5 is small and includes various ingredients, the detection of PM2.5 air pollutions by using satellite data is difficult compared with the detection of dust and sandstorms. In this paper, we examine various images (i.e., single-band images, band-difference images, RGB composite color images) to find a good method for detecting PM2.5 air pollutions by using MODIS data. A good method for the detection of PM2.5 air pollution is {R, G, B = band10, band9, T11}, where T11 is the brightness temperature of band31. In this composite color image, PM2.5 air pollutions are represented by light purple or pink color. This proposed method is simpler than the method by Nagatani et al. (2013), and is useful to grasp the distribution of PM2.5 air pollutions in the wide area (e.g., from China and India to Japan). By comparing AVI image with the image by proposed method, DSS and PM2.5 air pollutions can be classified.

Image processing for hazard recognition in on-board weather radar

NASA Technical Reports Server (NTRS)

Kelly, Wallace E. (Inventor); Rand, Timothy W. (Inventor); Uckun, Serdar (Inventor); Ruokangas, Corinne C. (Inventor)

2003-01-01

A method of providing weather radar images to a user includes obtaining radar image data corresponding to a weather radar image to be displayed. The radar image data is image processed to identify a feature of the weather radar image which is potentially indicative of a hazardous weather condition. The weather radar image is displayed to the user along with a notification of the existence of the feature which is potentially indicative of the hazardous weather condition. Notification can take the form of textual information regarding the feature, including feature type and proximity information. Notification can also take the form of visually highlighting the feature, for example by forming a visual border around the feature. Other forms of notification can also be used.

Color correction with blind image restoration based on multiple images using a low-rank model

NASA Astrophysics Data System (ADS)

Li, Dong; Xie, Xudong; Lam, Kin-Man

2014-03-01

We present a method that can handle the color correction of multiple photographs with blind image restoration simultaneously and automatically. We prove that the local colors of a set of images of the same scene exhibit the low-rank property locally both before and after a color-correction operation. This property allows us to correct all kinds of errors in an image under a low-rank matrix model without particular priors or assumptions. The possible errors may be caused by changes of viewpoint, large illumination variations, gross pixel corruptions, partial occlusions, etc. Furthermore, a new iterative soft-segmentation method is proposed for local color transfer using color influence maps. Due to the fact that the correct color information and the spatial information of images can be recovered using the low-rank model, more precise color correction and many other image-restoration tasks-including image denoising, image deblurring, and gray-scale image colorizing-can be performed simultaneously. Experiments have verified that our method can achieve consistent and promising results on uncontrolled real photographs acquired from the Internet and that it outperforms current state-of-the-art methods.

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

PubMed

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

Image processing pipeline for segmentation and material classification based on multispectral high dynamic range polarimetric images.

PubMed

Martínez-Domingo, Miguel Ángel; Valero, Eva M; Hernández-Andrés, Javier; Tominaga, Shoji; Horiuchi, Takahiko; Hirai, Keita

2017-11-27

We propose a method for the capture of high dynamic range (HDR), multispectral (MS), polarimetric (Pol) images of indoor scenes using a liquid crystal tunable filter (LCTF). We have included the adaptive exposure estimation (AEE) method to fully automatize the capturing process. We also propose a pre-processing method which can be applied for the registration of HDR images after they are already built as the result of combining different low dynamic range (LDR) images. This method is applied to ensure a correct alignment of the different polarization HDR images for each spectral band. We have focused our efforts in two main applications: object segmentation and classification into metal and dielectric classes. We have simplified the segmentation using mean shift combined with cluster averaging and region merging techniques. We compare the performance of our segmentation with that of Ncut and Watershed methods. For the classification task, we propose to use information not only in the highlight regions but also in their surrounding area, extracted from the degree of linear polarization (DoLP) maps. We present experimental results which proof that the proposed image processing pipeline outperforms previous techniques developed specifically for MSHDRPol image cubes.

Use of technology in children’s dietary assessment

PubMed Central

Boushey, CJ; Kerr, DA; Wright, J; Lutes, KD; Ebert, DS; Delp, EJ

2010-01-01

Background Information on dietary intake provides some of the most valuable insights for mounting intervention programmes for the prevention of chronic diseases. With the growing concern about adolescent overweight, the need to accurately measure diet becomes imperative. Assessment among adolescents is problematic as this group has irregular eating patterns and they have less enthusiasm for recording food intake. Subjects/Methods We used qualitative and quantitative techniques among adolescents to assess their preferences for dietary assessment methods. Results Dietary assessment methods using technology, for example, a personal digital assistant (PDA) or a disposable camera, were preferred over the pen and paper food record. Conclusions There was a strong preference for using methods that incorporate technology such as capturing images of food. This suggests that for adolescents, dietary methods that incorporate technology may improve cooperation and accuracy. Current computing technology includes higher resolution images, improved memory capacity and faster processors that allow small mobile devices to process information not previously possible. Our goal is to develop, implement and evaluate a mobile device (for example, PDA, mobile phone) food record that will translate to an accurate account of daily food and nutrient intake among adolescents. This mobile computing device will include digital images, a nutrient database and image analysis for identification and quantification of food consumption. Mobile computing devices provide a unique vehicle for collecting dietary information that reduces the burden on record keepers. Images of food can be marked with a variety of input methods that link the item for image processing and analysis to estimate the amount of food. Images before and after the foods are eaten can estimate the amount of food consumed. The initial stages and potential of this project will be described. PMID:19190645

MR/PET quantification tools: Registration, segmentation, classification, and MR-based attenuation correction

PubMed Central

Fei, Baowei; Yang, Xiaofeng; Nye, Jonathon A.; Aarsvold, John N.; Raghunath, Nivedita; Cervo, Morgan; Stark, Rebecca; Meltzer, Carolyn C.; Votaw, John R.

2012-01-01

Purpose: Combined MR/PET is a relatively new, hybrid imaging modality. A human MR/PET prototype system consisting of a Siemens 3T Trio MR and brain PET insert was installed and tested at our institution. Its present design does not offer measured attenuation correction (AC) using traditional transmission imaging. This study is the development of quantification tools including MR-based AC for quantification in combined MR/PET for brain imaging. Methods: The developed quantification tools include image registration, segmentation, classification, and MR-based AC. These components were integrated into a single scheme for processing MR/PET data. The segmentation method is multiscale and based on the Radon transform of brain MR images. It was developed to segment the skull on T1-weighted MR images. A modified fuzzy C-means classification scheme was developed to classify brain tissue into gray matter, white matter, and cerebrospinal fluid. Classified tissue is assigned an attenuation coefficient so that AC factors can be generated. PET emission data are then reconstructed using a three-dimensional ordered sets expectation maximization method with the MR-based AC map. Ten subjects had separate MR and PET scans. The PET with [11C]PIB was acquired using a high-resolution research tomography (HRRT) PET. MR-based AC was compared with transmission (TX)-based AC on the HRRT. Seventeen volumes of interest were drawn manually on each subject image to compare the PET activities between the MR-based and TX-based AC methods. Results: For skull segmentation, the overlap ratio between our segmented results and the ground truth is 85.2 ± 2.6%. Attenuation correction results from the ten subjects show that the difference between the MR and TX-based methods was <6.5%. Conclusions: MR-based AC compared favorably with conventional transmission-based AC. Quantitative tools including registration, segmentation, classification, and MR-based AC have been developed for use in combined MR/PET. PMID:23039679

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

NASA Astrophysics Data System (ADS)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Method for eliminating artifacts in CCD imagers

DOEpatents

Turko, B.T.; Yates, G.J.

1992-06-09

An electronic method for eliminating artifacts in a video camera employing a charge coupled device (CCD) as an image sensor is disclosed. The method comprises the step of initializing the camera prior to normal read out and includes a first dump cycle period for transferring radiation generated charge into the horizontal register while the decaying image on the phosphor being imaged is being integrated in the photosites, and a second dump cycle period, occurring after the phosphor image has decayed, for rapidly dumping unwanted smear charge which has been generated in the vertical registers. Image charge is then transferred from the photosites and to the vertical registers and read out in conventional fashion. The inventive method allows the video camera to be used in environments having high ionizing radiation content, and to capture images of events of very short duration and occurring either within or outside the normal visual wavelength spectrum. Resultant images are free from ghost, smear and smear phenomena caused by insufficient opacity of the registers and, and are also free from random damage caused by ionization charges which exceed the charge limit capacity of the photosites. 3 figs.

An investigation on the intra-sample distribution of cotton color by using image analysis

USDA-ARS?s Scientific Manuscript database

The colorimeter principle is widely used to measure cotton color. This method provides the sample’s color grade; but the result does not include information about the color distribution and any variation within the sample. We conducted an investigation that used image analysis method to study the ...

Fusion method of SAR and optical images for urban object extraction

NASA Astrophysics Data System (ADS)

Jia, Yonghong; Blum, Rick S.; Li, Fangfang

2007-11-01

A new image fusion method of SAR, Panchromatic (Pan) and multispectral (MS) data is proposed. First of all, SAR texture is extracted by ratioing the despeckled SAR image to its low pass approximation, and is used to modulate high pass details extracted from the available Pan image by means of the á trous wavelet decomposition. Then, high pass details modulated with the texture is applied to obtain the fusion product by HPFM (High pass Filter-based Modulation) fusion method. A set of image data including co-registered Landsat TM, ENVISAT SAR and SPOT Pan is used for the experiment. The results demonstrate accurate spectral preservation on vegetated regions, bare soil, and also on textured areas (buildings and road network) where SAR texture information enhances the fusion product, and the proposed approach is effective for image interpret and classification.

Imaging voltage in neurons

PubMed Central

Peterka, Darcy S.; Takahashi, Hiroto; Yuste, Rafael

2011-01-01

In the last decades, imaging membrane potential has become a fruitful approach to study neural circuits, especially in invertebrate preparations with large, resilient neurons. At the same time, particularly in mammalian preparations, voltage imaging methods suffer from poor signal to noise and secondary side effects, and they fall short of providing single-cell resolution when imaging of the activity of neuronal populations. As an introduction to these techniques, we briefly review different voltage imaging methods (including organic fluorophores, SHG chromophores, genetic indicators, hybrid, nanoparticles and intrinsic approaches), and illustrate some of their applications to neuronal biophysics and mammalian circuit analysis. We discuss their mechanisms of voltage sensitivity, from reorientation, electrochromic or electro-optical phenomena, to interaction among chromophores or membrane scattering, and highlight their advantages and shortcomings, commenting on the outlook for development of novel voltage imaging methods. PMID:21220095

SU-E-J-142: Performance Study of Automatic Image-Segmentation Algorithms in Motion Tracking Via MR-IGRT

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

Feng, Y; Olsen, J.; Parikh, P.

2014-06-01

Purpose: Evaluate commonly used segmentation algorithms on a commercially available real-time MR image guided radiotherapy (MR-IGRT) system (ViewRay), compare the strengths and weaknesses of each method, with the purpose of improving motion tracking for more accurate radiotherapy. Methods: MR motion images of bladder, kidney, duodenum, and liver tumor were acquired for three patients using a commercial on-board MR imaging system and an imaging protocol used during MR-IGRT. A series of 40 frames were selected for each case to cover at least 3 respiratory cycles. Thresholding, Canny edge detection, fuzzy k-means (FKM), k-harmonic means (KHM), and reaction-diffusion level set evolution (RD-LSE),more » along with the ViewRay treatment planning and delivery system (TPDS) were included in the comparisons. To evaluate the segmentation results, an expert manual contouring of the organs or tumor from a physician was used as a ground-truth. Metrics value of sensitivity, specificity, Jaccard similarity, and Dice coefficient were computed for comparison. Results: In the segmentation of single image frame, all methods successfully segmented the bladder and kidney, but only FKM, KHM and TPDS were able to segment the liver tumor and the duodenum. For segmenting motion image series, the TPDS method had the highest sensitivity, Jarccard, and Dice coefficients in segmenting bladder and kidney, while FKM and KHM had a slightly higher specificity. A similar pattern was observed when segmenting the liver tumor and the duodenum. The Canny method is not suitable for consistently segmenting motion frames in an automated process, while thresholding and RD-LSE cannot consistently segment a liver tumor and the duodenum. Conclusion: The study compared six different segmentation methods and showed the effectiveness of the ViewRay TPDS algorithm in segmenting motion images during MR-IGRT. Future studies include a selection of conformal segmentation methods based on image/organ-specific information, different filtering methods and their influences on the segmentation results. Parag Parikh receives research grant from ViewRay. Sasa Mutic has consulting and research agreements with ViewRay. Yanle Hu receives travel reimbursement from ViewRay. Iwan Kawrakow and James Dempsey are ViewRay employees.« less

Geometric correction method for 3d in-line X-ray phase contrast image reconstruction

PubMed Central

2014-01-01

Background Mechanical system with imperfect or misalignment of X-ray phase contrast imaging (XPCI) components causes projection data misplaced, and thus result in the reconstructed slice images of computed tomography (CT) blurred or with edge artifacts. So the features of biological microstructures to be investigated are destroyed unexpectedly, and the spatial resolution of XPCI image is decreased. It makes data correction an essential pre-processing step for CT reconstruction of XPCI. Methods To remove unexpected blurs and edge artifacts, a mathematics model for in-line XPCI is built by considering primary geometric parameters which include a rotation angle and a shift variant in this paper. Optimal geometric parameters are achieved by finding the solution of a maximization problem. And an iterative approach is employed to solve the maximization problem by using a two-step scheme which includes performing a composite geometric transformation and then following a linear regression process. After applying the geometric transformation with optimal parameters to projection data, standard filtered back-projection algorithm is used to reconstruct CT slice images. Results Numerical experiments were carried out on both synthetic and real in-line XPCI datasets. Experimental results demonstrate that the proposed method improves CT image quality by removing both blurring and edge artifacts at the same time compared to existing correction methods. Conclusions The method proposed in this paper provides an effective projection data correction scheme and significantly improves the image quality by removing both blurring and edge artifacts at the same time for in-line XPCI. It is easy to implement and can also be extended to other XPCI techniques. PMID:25069768

Measuring past glacier fluctuations from historic photographs geolocated using Structure from Motion

NASA Astrophysics Data System (ADS)

Vargo, L.; Anderson, B.; Horgan, H. J.; Mackintosh, A.; Lorrey, A.; Thornton, M.

2017-12-01

Quantifying glacier fluctuations is important for understanding how the cryosphere responds to climate variability and change. Photographs of past ice extents have become iconic images of climate change, but until now incorporating these images into quantitative estimates of glacier change has been problematic. We present a new method to quantitatively measure past glacier fluctuations from historic images. The method uses a large set of modern geolocated photographs and Structure from Motion (SfM) to calculate the camera parameters for the historic images, including the location from which they were taken. We initially apply this method to a small maritime New Zealand glacier (Brewster Glacier, 44°S, 2 km2), and quantify annual equilibrium line altitudes (ELAs) and length changes from historic oblique aerial photographs (1981 - 2017). Results show that Brewster has retreated 364 ± 12 m since 1981 and, using independent field measurements of terminus positions (2005 - 2014), we show that this SfM-derived length record accurately captures glacier change. We calculate the uncertainties associated with this method using known coordinates of bedrock features surrounding the glacier. Mean uncertainties in the ELA and length records are 7 m and 11 m, respectively. In addition to Brewster, 49 other New Zealand glaciers have been monitored by aerial photographs since 1978. However, the length records for these glaciers only include years of relative advance or retreat, and no length changes have been quantified. We will ultimately apply this method to all 50 glaciers, expanding the database of New Zealand glacier fluctuations that until now included only a few glaciers. This method can be further applied to any glacier with historic images, and can be used to measure past changes in glacier width, area, and surface elevation in addition to ELA and length.

Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images

PubMed Central

Lin, Chih-Lung; Wang, Shih-Hung; Cheng, Hsu-Yung; Fan, Kuo-Chin; Hsu, Wei-Lieh; Lai, Chin-Rong

2015-01-01

In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) automatically aligning and cropping the same region of interest from different palm or palm-dorsum images; (2) applying the digital wavelet transform and inverse wavelet transform to fuse palmprint and vein pattern images; (3) extracting the line-like features (LLFs) from the fused image; (4) obtaining multiresolution representations of the LLFs by using a multiresolution filter; and (5) using a support vector machine to verify the multiresolution representations of the LLFs. The proposed method possesses four advantages: first, both modal images are captured in peg-free scenarios to improve the user-friendliness of the verification device. Second, palmprint and vein pattern images are captured using a low-resolution digital scanner and infrared (IR) camera. The use of low-resolution images results in a smaller database. In addition, the vein pattern images are captured through the invisible IR spectrum, which improves antispoofing. Third, since the physiological characteristics of palmprint and vein pattern images are different, a hybrid fusing rule can be introduced to fuse the decomposition coefficients of different bands. The proposed method fuses decomposition coefficients at different decomposed levels, with different image sizes, captured from different sensor devices. Finally, the proposed method operates automatically and hence no parameters need to be set manually. Three thousand palmprint images and 3000 vein pattern images were collected from 100 volunteers to verify the validity of the proposed method. The results show a false rejection rate of 1.20% and a false acceptance rate of 1.56%. It demonstrates the validity and excellent performance of our proposed method comparing to other methods. PMID:26703596

Bimodal Biometric Verification Using the Fusion of Palmprint and Infrared Palm-Dorsum Vein Images.

PubMed

Lin, Chih-Lung; Wang, Shih-Hung; Cheng, Hsu-Yung; Fan, Kuo-Chin; Hsu, Wei-Lieh; Lai, Chin-Rong

2015-12-12

In this paper, we present a reliable and robust biometric verification method based on bimodal physiological characteristics of palms, including the palmprint and palm-dorsum vein patterns. The proposed method consists of five steps: (1) automatically aligning and cropping the same region of interest from different palm or palm-dorsum images; (2) applying the digital wavelet transform and inverse wavelet transform to fuse palmprint and vein pattern images; (3) extracting the line-like features (LLFs) from the fused image; (4) obtaining multiresolution representations of the LLFs by using a multiresolution filter; and (5) using a support vector machine to verify the multiresolution representations of the LLFs. The proposed method possesses four advantages: first, both modal images are captured in peg-free scenarios to improve the user-friendliness of the verification device. Second, palmprint and vein pattern images are captured using a low-resolution digital scanner and infrared (IR) camera. The use of low-resolution images results in a smaller database. In addition, the vein pattern images are captured through the invisible IR spectrum, which improves antispoofing. Third, since the physiological characteristics of palmprint and vein pattern images are different, a hybrid fusing rule can be introduced to fuse the decomposition coefficients of different bands. The proposed method fuses decomposition coefficients at different decomposed levels, with different image sizes, captured from different sensor devices. Finally, the proposed method operates automatically and hence no parameters need to be set manually. Three thousand palmprint images and 3000 vein pattern images were collected from 100 volunteers to verify the validity of the proposed method. The results show a false rejection rate of 1.20% and a false acceptance rate of 1.56%. It demonstrates the validity and excellent performance of our proposed method comparing to other methods.

Methods for the visualization and analysis of extracellular matrix protein structure and degradation.

PubMed

Leonard, Annemarie K; Loughran, Elizabeth A; Klymenko, Yuliya; Liu, Yueying; Kim, Oleg; Asem, Marwa; McAbee, Kevin; Ravosa, Matthew J; Stack, M Sharon

2018-01-01

This chapter highlights methods for visualization and analysis of extracellular matrix (ECM) proteins, with particular emphasis on collagen type I, the most abundant protein in mammals. Protocols described range from advanced imaging of complex in vivo matrices to simple biochemical analysis of individual ECM proteins. The first section of this chapter describes common methods to image ECM components and includes protocols for second harmonic generation, scanning electron microscopy, and several histological methods of ECM localization and degradation analysis, including immunohistochemistry, Trichrome staining, and in situ zymography. The second section of this chapter details both a common transwell invasion assay and a novel live imaging method to investigate cellular behavior with respect to collagen and other ECM proteins of interest. The final section consists of common electrophoresis-based biochemical methods that are used in analysis of ECM proteins. Use of the methods described herein will enable researchers to gain a greater understanding of the role of ECM structure and degradation in development and matrix-related diseases such as cancer and connective tissue disorders. © 2018 Elsevier Inc. All rights reserved.

Segmentation of breast ultrasound images based on active contours using neutrosophic theory.

PubMed

Lotfollahi, Mahsa; Gity, Masoumeh; Ye, Jing Yong; Mahlooji Far, A

2018-04-01

Ultrasound imaging is an effective approach for diagnosing breast cancer, but it is highly operator-dependent. Recent advances in computer-aided diagnosis have suggested that it can assist physicians in diagnosis. Definition of the region of interest before computer analysis is still needed. Since manual outlining of the tumor contour is tedious and time-consuming for a physician, developing an automatic segmentation method is important for clinical application. The present paper represents a novel method to segment breast ultrasound images. It utilizes a combination of region-based active contour and neutrosophic theory to overcome the natural properties of ultrasound images including speckle noise and tissue-related textures. First, due to inherent speckle noise and low contrast of these images, we have utilized a non-local means filter and fuzzy logic method for denoising and image enhancement, respectively. This paper presents an improved weighted region-scalable active contour to segment breast ultrasound images using a new feature derived from neutrosophic theory. This method has been applied to 36 breast ultrasound images. It generates true-positive and false-positive results, and similarity of 95%, 6%, and 90%, respectively. The purposed method indicates clear advantages over other conventional methods of active contour segmentation, i.e., region-scalable fitting energy and weighted region-scalable fitting energy.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

NASA Astrophysics Data System (ADS)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

[Diagnostic imaging of changes of the canine intervertebral disc].

PubMed

Harder, Lisa K

2016-10-12

Intervertebral disc degeneration can cause intervertebral disc herniation. Diagnostic imaging, including radiography, computed tomography and magnetic resonance imaging, is the most important tool in diagnosis. Firstly, an overview of macroscopic and biochemical physiology and pathology of the intervertebral disc will be given. Subsequently, the physics of diagnostic imaging and the appearance of intervertebral disc degeneration and displacement in several imaging methods are described.

The viability of ADVANTG deterministic method for synthetic radiography generation

NASA Astrophysics Data System (ADS)

Bingham, Andrew; Lee, Hyoung K.

2018-07-01

Fast simulation techniques to generate synthetic radiographic images of high resolution are helpful when new radiation imaging systems are designed. However, the standard stochastic approach requires lengthy run time with poorer statistics at higher resolution. The investigation of the viability of a deterministic approach to synthetic radiography image generation was explored. The aim was to analyze a computational time decrease over the stochastic method. ADVANTG was compared to MCNP in multiple scenarios including a small radiography system prototype, to simulate high resolution radiography images. By using ADVANTG deterministic code to simulate radiography images the computational time was found to decrease 10 to 13 times compared to the MCNP stochastic approach while retaining image quality.

Filter methods to preserve local contrast and to avoid artifacts in gamut mapping

NASA Astrophysics Data System (ADS)

Meili, Marcel; Küpper, Dennis; Barańczuk, Zofia; Caluori, Ursina; Simon, Klaus

2010-01-01

Contrary to high dynamic range imaging, the preservation of details and the avoidance of artifacts is not explicitly considered in popular color management systems. An effective way to overcome these difficulties is image filtering. In this paper we investigate several image filter concepts for detail preservation as part of a practical gamut mapping strategy. In particular we define four concepts including various image filters and check their performance with a psycho-visual test. Additionally, we compare our performance evaluation to two image quality measures with emphasis on local contrast. Surprisingly, the most simple filter concept performs highly efficient and achieves an image quality which is comparable to the more established but slower methods.

Blind identification of image manipulation type using mixed statistical moments

NASA Astrophysics Data System (ADS)

Jeong, Bo Gyu; Moon, Yong Ho; Eom, Il Kyu

2015-01-01

We present a blind identification of image manipulation types such as blurring, scaling, sharpening, and histogram equalization. Motivated by the fact that image manipulations can change the frequency characteristics of an image, we introduce three types of feature vectors composed of statistical moments. The proposed statistical moments are generated from separated wavelet histograms, the characteristic functions of the wavelet variance, and the characteristic functions of the spatial image. Our method can solve the n-class classification problem. Through experimental simulations, we demonstrate that our proposed method can achieve high performance in manipulation type detection. The average rate of the correctly identified manipulation types is as high as 99.22%, using 10,800 test images and six manipulation types including the authentic image.

Automatic detection of retina disease: robustness to image quality and localization of anatomy structure.

PubMed

Karnowski, T P; Aykac, D; Giancardo, L; Li, Y; Nichols, T; Tobin, K W; Chaum, E

2011-01-01

The automated detection of diabetic retinopathy and other eye diseases in images of the retina has great promise as a low-cost method for broad-based screening. Many systems in the literature which perform automated detection include a quality estimation step and physiological feature detection, including the vascular tree and the optic nerve / macula location. In this work, we study the robustness of an automated disease detection method with respect to the accuracy of the optic nerve location and the quality of the images obtained as judged by a quality estimation algorithm. The detection algorithm features microaneurysm and exudate detection followed by feature extraction on the detected population to describe the overall retina image. Labeled images of retinas ground-truthed to disease states are used to train a supervised learning algorithm to identify the disease state of the retina image and exam set. Under the restrictions of high confidence optic nerve detections and good quality imagery, the system achieves a sensitivity and specificity of 94.8% and 78.7% with area-under-curve of 95.3%. Analysis of the effect of constraining quality and the distinction between mild non-proliferative diabetic retinopathy, normal retina images, and more severe disease states is included.

Photothermal imaging scanning microscopy

DOEpatents

Chinn, Diane [Pleasanton, CA; Stolz, Christopher J [Lathrop, CA; Wu, Zhouling [Pleasanton, CA; Huber, Robert [Discovery Bay, CA; Weinzapfel, Carolyn [Tracy, CA

2006-07-11

Photothermal Imaging Scanning Microscopy produces a rapid, thermal-based, non-destructive characterization apparatus. Also, a photothermal characterization method of surface and subsurface features includes micron and nanoscale spatial resolution of meter-sized optical materials.

Mapping the different methods adopted for diagnostic imaging instruction at medical schools in Brazil.

PubMed

Chojniak, Rubens; Carneiro, Dominique Piacenti; Moterani, Gustavo Simonetto Peres; Duarte, Ivone da Silva; Bitencourt, Almir Galvão Vieira; Muglia, Valdair Francisco; D'Ippolito, Giuseppe

2017-01-01

To map the different methods for diagnostic imaging instruction at medical schools in Brazil. In this cross-sectional study, a questionnaire was sent to each of the coordinators of 178 Brazilian medical schools. The following characteristics were assessed: teaching model; total course hours; infrastructure; numbers of students and professionals involved; themes addressed; diagnostic imaging modalities covered; and education policies related to diagnostic imaging. Of the 178 questionnaires sent, 45 (25.3%) were completed and returned. Of those 45 responses, 17 (37.8%) were from public medical schools, whereas 28 (62.2%) were from private medical schools. Among the 45 medical schools evaluated, the method of diagnostic imaging instruction was modular at 21 (46.7%), classic (independent discipline) at 13 (28.9%), hybrid (classical and modular) at 9 (20.0%), and none of the preceding at 3 (6.7%). Diagnostic imaging is part of the formal curriculum at 36 (80.0%) of the schools, an elective course at 3 (6.7%), and included within another modality at 6 (13.3%). Professors involved in diagnostic imaging teaching are radiologists at 43 (95.5%) of the institutions. The survey showed that medical courses in Brazil tend to offer diagnostic imaging instruction in courses that include other content and at different time points during the course. Radiologists are extensively involved in undergraduate medical education, regardless of the teaching methodology employed at the institution.

Segmentation of epidermal tissue with histopathological damage in images of haematoxylin and eosin stained human skin

PubMed Central

2014-01-01

Background Digital image analysis has the potential to address issues surrounding traditional histological techniques including a lack of objectivity and high variability, through the application of quantitative analysis. A key initial step in image analysis is the identification of regions of interest. A widely applied methodology is that of segmentation. This paper proposes the application of image analysis techniques to segment skin tissue with varying degrees of histopathological damage. The segmentation of human tissue is challenging as a consequence of the complexity of the tissue structures and inconsistencies in tissue preparation, hence there is a need for a new robust method with the capability to handle the additional challenges materialising from histopathological damage. Methods A new algorithm has been developed which combines enhanced colour information, created following a transformation to the L*a*b* colourspace, with general image intensity information. A colour normalisation step is included to enhance the algorithm’s robustness to variations in the lighting and staining of the input images. The resulting optimised image is subjected to thresholding and the segmentation is fine-tuned using a combination of morphological processing and object classification rules. The segmentation algorithm was tested on 40 digital images of haematoxylin & eosin (H&E) stained skin biopsies. Accuracy, sensitivity and specificity of the algorithmic procedure were assessed through the comparison of the proposed methodology against manual methods. Results Experimental results show the proposed fully automated methodology segments the epidermis with a mean specificity of 97.7%, a mean sensitivity of 89.4% and a mean accuracy of 96.5%. When a simple user interaction step is included, the specificity increases to 98.0%, the sensitivity to 91.0% and the accuracy to 96.8%. The algorithm segments effectively for different severities of tissue damage. Conclusions Epidermal segmentation is a crucial first step in a range of applications including melanoma detection and the assessment of histopathological damage in skin. The proposed methodology is able to segment the epidermis with different levels of histological damage. The basic method framework could be applied to segmentation of other epithelial tissues. PMID:24521154

Scaled Heavy-Ball Acceleration of the Richardson-Lucy Algorithm for 3D Microscopy Image Restoration.

PubMed

Wang, Hongbin; Miller, Paul C

2014-02-01

The Richardson-Lucy algorithm is one of the most important in image deconvolution. However, a drawback is its slow convergence. A significant acceleration was obtained using the technique proposed by Biggs and Andrews (BA), which is implemented in the deconvlucy function of the image processing MATLAB toolbox. The BA method was developed heuristically with no proof of convergence. In this paper, we introduce the heavy-ball (H-B) method for Poisson data optimization and extend it to a scaled H-B method, which includes the BA method as a special case. The method has a proof of the convergence rate of O(K(-2)), where k is the number of iterations. We demonstrate the superior convergence performance, by a speedup factor of five, of the scaled H-B method on both synthetic and real 3D images.

Person Recognition System Based on a Combination of Body Images from Visible Light and Thermal Cameras

PubMed Central

Nguyen, Dat Tien; Hong, Hyung Gil; Kim, Ki Wan; Park, Kang Ryoung

2017-01-01

The human body contains identity information that can be used for the person recognition (verification/recognition) problem. In this paper, we propose a person recognition method using the information extracted from body images. Our research is novel in the following three ways compared to previous studies. First, we use the images of human body for recognizing individuals. To overcome the limitations of previous studies on body-based person recognition that use only visible light images for recognition, we use human body images captured by two different kinds of camera, including a visible light camera and a thermal camera. The use of two different kinds of body image helps us to reduce the effects of noise, background, and variation in the appearance of a human body. Second, we apply a state-of-the art method, called convolutional neural network (CNN) among various available methods, for image features extraction in order to overcome the limitations of traditional hand-designed image feature extraction methods. Finally, with the extracted image features from body images, the recognition task is performed by measuring the distance between the input and enrolled samples. The experimental results show that the proposed method is efficient for enhancing recognition accuracy compared to systems that use only visible light or thermal images of the human body. PMID:28300783

3D temporal subtraction on multislice CT images using nonlinear warping technique

NASA Astrophysics Data System (ADS)

Ishida, Takayuki; Katsuragawa, Shigehiko; Kawashita, Ikuo; Kim, Hyounseop; Itai, Yoshinori; Awai, Kazuo; Li, Qiang; Doi, Kunio

2007-03-01

The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval changes between previous and current multislice CT images based on a nonlinear image warping technique. Our method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our computerized method includes global and local image matching techniques for accurate registration of current and previous CT images. For global image matching, we selected the corresponding previous section image for each current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred previous CT image. For local image matching, we applied the 3D template matching technique with translation and rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT images.

A method based on IHS cylindrical transform model for quality assessment of image fusion

NASA Astrophysics Data System (ADS)

Zhu, Xiaokun; Jia, Yonghong

2005-10-01

Image fusion technique has been widely applied to remote sensing image analysis and processing, and methods for quality assessment of image fusion in remote sensing have also become the research issues at home and abroad. Traditional assessment methods combine calculation of quantitative indexes and visual interpretation to compare fused images quantificationally and qualitatively. However, in the existing assessment methods, there are two defects: on one hand, most imdexes lack the theoretic support to compare different fusion methods. On the hand, there is not a uniform preference for most of the quantitative assessment indexes when they are applied to estimate the fusion effects. That is, the spatial resolution and spectral feature could not be analyzed synchronously by these indexes and there is not a general method to unify the spatial and spectral feature assessment. So in this paper, on the basis of the approximate general model of four traditional fusion methods, including Intensity Hue Saturation(IHS) triangle transform fusion, High Pass Filter(HPF) fusion, Principal Component Analysis(PCA) fusion, Wavelet Transform(WT) fusion, a correlation coefficient assessment method based on IHS cylindrical transform is proposed. By experiments, this method can not only get the evaluation results of spatial and spectral features on the basis of uniform preference, but also can acquire the comparison between fusion image sources and fused images, and acquire differences among fusion methods. Compared with the traditional assessment methods, the new methods is more intuitionistic, and in accord with subjective estimation.

A Toolbox for Imaging Stellar Surfaces

NASA Astrophysics Data System (ADS)

Young, John

2018-04-01

In this talk I will review the available algorithms for synthesis imaging at visible and infrared wavelengths, including both gray and polychromatic methods. I will explain state-of-the-art approaches to constraining the ill-posed image reconstruction problem, and selecting an appropriate regularisation function and strength of regularisation. The reconstruction biases that can follow from non-optimal choices will be discussed, including their potential impact on the physical interpretation of the results. This discussion will be illustrated with example stellar surface imaging results from real VLTI and COAST datasets.

Method and apparatus for atomic imaging

DOEpatents

Saldin, Dilano K.; de Andres Rodriquez, Pedro L.

1993-01-01

A method and apparatus for three dimensional imaging of the atomic environment of disordered adsorbate atoms are disclosed. The method includes detecting and measuring the intensity of a diffuse low energy electron diffraction pattern formed by directing a beam of low energy electrons against the surface of a crystal. Data corresponding to reconstructed amplitudes of a wave form is generated by operating on the intensity data. The data corresponding to the reconstructed amplitudes is capable of being displayed as a three dimensional image of an adsorbate atom. The apparatus includes a source of a beam of low energy electrons and a detector for detecting the intensity distribution of a DLEED pattern formed at the detector when the beam of low energy electrons is directed onto the surface of a crystal. A device responsive to the intensity distribution generates a signal corresponding to the distribution which represents a reconstructed amplitude of a wave form and is capable of being converted into a three dimensional image of the atomic environment of an adsorbate atom on the crystal surface.

Neurient: An Algorithm for Automatic Tracing of Confluent Neuronal Images to Determine Alignment

PubMed Central

Mitchel, J.A.; Martin, I.S.

2013-01-01

A goal of neural tissue engineering is the development and evaluation of materials that guide neuronal growth and alignment. However, the methods available to quantitatively evaluate the response of neurons to guidance materials are limited and/or expensive, and may require manual tracing to be performed by the researcher. We have developed an open source, automated Matlab-based algorithm, building on previously published methods, to trace and quantify alignment of fluorescent images of neurons in culture. The algorithm is divided into three phases, including computation of a lookup table which contains directional information for each image, location of a set of seed points which may lie along neurite centerlines, and tracing neurites starting with each seed point and indexing into the lookup table. This method was used to obtain quantitative alignment data for complex images of densely cultured neurons. Complete automation of tracing allows for unsupervised processing of large numbers of images. Following image processing with our algorithm, available metrics to quantify neurite alignment include angular histograms, percent of neurite segments in a given direction, and mean neurite angle. The alignment information obtained from traced images can be used to compare the response of neurons to a range of conditions. This tracing algorithm is freely available to the scientific community under the name Neurient, and its implementation in Matlab allows a wide range of researchers to use a standardized, open source method to quantitatively evaluate the alignment of dense neuronal cultures. PMID:23384629

Methods, compositions and kits for imaging cells and tissues using nanoparticles and spatial frequency heterodyne imaging

DOEpatents

Rose-Petruck, Christoph; Wands, Jack R.; Rand, Danielle; Derdak, Zoltan; Ortiz, Vivian

2016-04-19

Methods, compositions, systems, devices and kits are provided herein for preparing and using a nanoparticle composition and spatial frequency heterodyne imaging for visualizing cells or tissues. In various embodiments, the nanoparticle composition includes at least one of: a nanoparticle, a polymer layer, and a binding agent, such that the polymer layer coats the nanoparticle and is for example a polyethylene glycol, a polyelectrolyte, an anionic polymer, or a cationic polymer, and such that the binding agent that specifically binds the cells or the tissue. Methods, compositions, systems, devices and kits are provided for identifying potential therapeutic agents in a model using the nanoparticle composition and spatial frequency heterodyne imaging.

[Three-dimensional reconstruction of functional brain images].

PubMed

Inoue, M; Shoji, K; Kojima, H; Hirano, S; Naito, Y; Honjo, I

1999-08-01

We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: 1) routine images by SPM, 2) three-dimensional static images, and 3) three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface model is the most common method of three-dimensional display. However, the volume rendering method may be more effective for imaging regions such as the brain.

Neuroimaging of the Injured Pediatric Brain: Methods and New Lessons.

PubMed

Dennis, Emily L; Babikian, Talin; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-02-01

Traumatic brain injury (TBI) is a significant public health problem in the United States, especially for children and adolescents. Current epidemiological data estimate over 600,000 patients younger than 20 years are treated for TBI in emergency rooms annually. While many patients experience a full recovery, for others there can be long-lasting cognitive, neurological, psychological, and behavioral disruptions. TBI in youth can disrupt ongoing brain development and create added family stress during a formative period. The neuroimaging methods used to assess brain injury improve each year, providing researchers a more detailed characterization of the injury and recovery process. In this review, we cover current imaging methods used to quantify brain disruption post-injury, including structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, resting state fMRI, and magnetic resonance spectroscopy (MRS), with brief coverage of other methods, including electroencephalography (EEG), single-photon emission computed tomography (SPECT), and positron emission tomography (PET). We include studies focusing on pediatric moderate-severe TBI from 2 months post-injury and beyond. While the morbidity of pediatric TBI is considerable, continuing advances in imaging methods have the potential to identify new treatment targets that can lead to significant improvements in outcome.

Variance based joint sparsity reconstruction of synthetic aperture radar data for speckle reduction

NASA Astrophysics Data System (ADS)

Scarnati, Theresa; Gelb, Anne

2018-04-01

In observing multiple synthetic aperture radar (SAR) images of the same scene, it is apparent that the brightness distributions of the images are not smooth, but rather composed of complicated granular patterns of bright and dark spots. Further, these brightness distributions vary from image to image. This salt and pepper like feature of SAR images, called speckle, reduces the contrast in the images and negatively affects texture based image analysis. This investigation uses the variance based joint sparsity reconstruction method for forming SAR images from the multiple SAR images. In addition to reducing speckle, the method has the advantage of being non-parametric, and can therefore be used in a variety of autonomous applications. Numerical examples include reconstructions of both simulated phase history data that result in speckled images as well as the images from the MSTAR T-72 database.

Deep learning for low-dose CT

NASA Astrophysics Data System (ADS)

Chen, Hu; Zhang, Yi; Zhou, Jiliu; Wang, Ge

2017-09-01

Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main stream low-dose CT methods include vendor-specific sinogram domain filtration and iterative reconstruction algorithms, but they need to access raw data whose formats are not transparent to most users. Due to the difficulty of modeling the statistical characteristics in the image domain, the existing methods for directly processing reconstructed images cannot eliminate image noise very well while keeping structural details. Inspired by the idea of deep learning, here we combine the autoencoder, deconvolution network, and shortcut connections into the residual encoder-decoder convolutional neural network (RED-CNN) for low-dose CT imaging. After patch-based training, the proposed RED-CNN achieves a competitive performance relative to the-state-of-art methods. Especially, our method has been favorably evaluated in terms of noise suppression and structural preservation.

Counter sniper: a localization system based on dual thermal imager

NASA Astrophysics Data System (ADS)

He, Yuqing; Liu, Feihu; Wu, Zheng; Jin, Weiqi; Du, Benfang

2010-11-01

Sniper tactics is widely used in modern warfare, which puts forward the urgent requirement of counter sniper detection devices. This paper proposed the anti-sniper detection system based on a dual-thermal imaging system. Combining the infrared characteristics of the muzzle flash and bullet trajectory of binocular infrared images obtained by the dual-infrared imaging system, the exact location of the sniper was analyzed and calculated. This paper mainly focuses on the system design method, which includes the structure and parameter selection. It also analyzes the exact location calculation method based on the binocular stereo vision and image analysis, and give the fusion result as the sniper's position.

System and method for object localization

NASA Technical Reports Server (NTRS)

Kelly, Alonzo J. (Inventor); Zhong, Yu (Inventor)

2005-01-01

A computer-assisted method for localizing a rack, including sensing an image of the rack, detecting line segments in the sensed image, recognizing a candidate arrangement of line segments in the sensed image indicative of a predetermined feature of the rack, generating a matrix of correspondence between the candidate arrangement of line segments and an expected position and orientation of the predetermined feature of the rack, and estimating a position and orientation of the rack based on the matrix of correspondence.

ARL Summer Student Research Symposium. Volume 1: Select Papers

DTIC Science & Technology

2012-08-01

deploying Android smart phones and tablets on the battlefield, which may be a target for malware. In our research, we attempt to improve static...network. (a) The T1 and MRI images are (b) segmented into different material components. The segmented geometry is then used to create (c) a finite element...towards finding a method to detect mTBI non-invasively. One method in particular includes the use of a magnetic resonance image ( MRI )-based imaging

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN.

PubMed

Guo, Hao; Wu, Danni; An, Jubai

2017-08-09

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features.

Discrimination of Oil Slicks and Lookalikes in Polarimetric SAR Images Using CNN

PubMed Central

An, Jubai

2017-01-01

Oil slicks and lookalikes (e.g., plant oil and oil emulsion) all appear as dark areas in polarimetric Synthetic Aperture Radar (SAR) images and are highly heterogeneous, so it is very difficult to use a single feature that can allow classification of dark objects in polarimetric SAR images as oil slicks or lookalikes. We established multi-feature fusion to support the discrimination of oil slicks and lookalikes. In the paper, simple discrimination analysis is used to rationalize a preferred features subset. The features analyzed include entropy, alpha, and Single-bounce Eigenvalue Relative Difference (SERD) in the C-band polarimetric mode. We also propose a novel SAR image discrimination method for oil slicks and lookalikes based on Convolutional Neural Network (CNN). The regions of interest are selected as the training and testing samples for CNN on the three kinds of polarimetric feature images. The proposed method is applied to a training data set of 5400 samples, including 1800 crude oil, 1800 plant oil, and 1800 oil emulsion samples. In the end, the effectiveness of the method is demonstrated through the analysis of some experimental results. The classification accuracy obtained using 900 samples of test data is 91.33%. It is here observed that the proposed method not only can accurately identify the dark spots on SAR images but also verify the ability of the proposed algorithm to classify unstructured features. PMID:28792477

Three Dimensional Optical Coherence Tomography Imaging: Advantages and Advances

PubMed Central

Gabriele, Michelle L; Wollstein, Gadi; Ishikawa, Hiroshi; Xu, Juan; Kim, Jongsick; Kagemann, Larry; Folio, Lindsey S; Schuman, Joel S.

2010-01-01

Three dimensional (3D) ophthalmic imaging using optical coherence tomography (OCT) has revolutionized assessment of the eye, the retina in particular. Recent technological improvements have made the acquisition of 3D-OCT datasets feasible. However, while volumetric data can improve disease diagnosis and follow-up, novel image analysis techniques are now necessary in order to process the dense 3D-OCT dataset. Fundamental software improvements include methods for correcting subject eye motion, segmenting structures or volumes of interest, extracting relevant data post hoc and signal averaging to improve delineation of retinal layers. In addition, innovative methods for image display, such as C-mode sectioning, provide a unique viewing perspective and may improve interpretation of OCT images of pathologic structures. While all of these methods are being developed, most remain in an immature state. This review describes the current status of 3D-OCT scanning and interpretation, and discusses the need for standardization of clinical protocols as well as the potential benefits of 3D-OCT scanning that could come when software methods for fully exploiting these rich data sets are available clinically. The implications of new image analysis approaches include improved reproducibility of measurements garnered from 3D-OCT, which may then help improve disease discrimination and progression detection. In addition, 3D-OCT offers the potential for preoperative surgical planning and intraoperative surgical guidance. PMID:20542136

A review of biomechanically informed breast image registration

NASA Astrophysics Data System (ADS)

Hipwell, John H.; Vavourakis, Vasileios; Han, Lianghao; Mertzanidou, Thomy; Eiben, Björn; Hawkes, David J.

2016-01-01

Breast radiology encompasses the full range of imaging modalities from routine imaging via x-ray mammography, magnetic resonance imaging and ultrasound (both two- and three-dimensional), to more recent technologies such as digital breast tomosynthesis, and dedicated breast imaging systems for positron emission mammography and ultrasound tomography. In addition new and experimental modalities, such as Photoacoustics, Near Infrared Spectroscopy and Electrical Impedance Tomography etc, are emerging. The breast is a highly deformable structure however, and this greatly complicates visual comparison of imaging modalities for the purposes of breast screening, cancer diagnosis (including image guided biopsy), tumour staging, treatment monitoring, surgical planning and simulation of the effects of surgery and wound healing etc. Due primarily to the challenges posed by these gross, non-rigid deformations, development of automated methods which enable registration, and hence fusion, of information within and across breast imaging modalities, and between the images and the physical space of the breast during interventions, remains an active research field which has yet to translate suitable methods into clinical practice. This review describes current research in the field of breast biomechanical modelling and identifies relevant publications where the resulting models have been incorporated into breast image registration and simulation algorithms. Despite these developments there remain a number of issues that limit clinical application of biomechanical modelling. These include the accuracy of constitutive modelling, implementation of representative boundary conditions, failure to meet clinically acceptable levels of computational cost, challenges associated with automating patient-specific model generation (i.e. robust image segmentation and mesh generation) and the complexity of applying biomechanical modelling methods in routine clinical practice.

An image-based method to measure all-terrain vehicle dimensions for engineering safety purposes.

PubMed

Jennissen, Charles A; Miller, Nathan S; Tang, Kaiyang; Denning, Gerene M

2014-04-01

All-terrain vehicle (ATV) crashes are a serious public health and safety concern. Engineering approaches that address ATV injury prevention are critically needed. Avenues to pursue include evidence-based seat design that decreases risky behaviours, such as carrying passengers and operation of adult-size vehicles by children. The goal of this study was to create and validate an image-based method to measure ATV seat length and placement. Publicly available ATV images were downloaded. Adobe Photoshop was then used to generate a vertical grid through the centre of the vehicle, to define the grid scale using the manufacturer's reported wheelbase, and to determine seat length and placement relative to the front and rear axles using this scale. Images that yielded a difference greater than 5% between the calculated and the manufacturer's reported ATV lengths were excluded from further analysis. For the 77 images that met inclusion criteria, the mean±SD for the difference in calculated versus reported vehicle length was 1.8%±1.2%. The Pearson correlation coefficient for comparing image-based seat lengths determined by two independent measurers (20 models) and image-based lengths versus lengths measured at dealerships (12 models) were 0.95 and 0.96, respectively. The image-based method provides accurate and reproducible results for determining ATV measurements, including seat length and placement. This method greatly expands the number of ATV models that can be studied, and may be generalisable to other motor vehicle types. These measurements can be used to guide engineering approaches that improve ATV safety design.

MATHEMATICAL METHODS IN MEDICAL IMAGE PROCESSING

PubMed Central

ANGENENT, SIGURD; PICHON, ERIC; TANNENBAUM, ALLEN

2013-01-01

In this paper, we describe some central mathematical problems in medical imaging. The subject has been undergoing rapid changes driven by better hardware and software. Much of the software is based on novel methods utilizing geometric partial differential equations in conjunction with standard signal/image processing techniques as well as computer graphics facilitating man/machine interactions. As part of this enterprise, researchers have been trying to base biomedical engineering principles on rigorous mathematical foundations for the development of software methods to be integrated into complete therapy delivery systems. These systems support the more effective delivery of many image-guided procedures such as radiation therapy, biopsy, and minimally invasive surgery. We will show how mathematics may impact some of the main problems in this area, including image enhancement, registration, and segmentation. PMID:23645963

A concept for holistic whole body MRI data analysis, Imiomics

PubMed Central

Malmberg, Filip; Johansson, Lars; Lind, Lars; Sundbom, Magnus; Ahlström, Håkan; Kullberg, Joel

2017-01-01

Purpose To present and evaluate a whole-body image analysis concept, Imiomics (imaging–omics) and an image registration method that enables Imiomics analyses by deforming all image data to a common coordinate system, so that the information in each voxel can be compared between persons or within a person over time and integrated with non-imaging data. Methods The presented image registration method utilizes relative elasticity constraints of different tissue obtained from whole-body water-fat MRI. The registration method is evaluated by inverse consistency and Dice coefficients and the Imiomics concept is evaluated by example analyses of importance for metabolic research using non-imaging parameters where we know what to expect. The example analyses include whole body imaging atlas creation, anomaly detection, and cross-sectional and longitudinal analysis. Results The image registration method evaluation on 128 subjects shows low inverse consistency errors and high Dice coefficients. Also, the statistical atlas with fat content intensity values shows low standard deviation values, indicating successful deformations to the common coordinate system. The example analyses show expected associations and correlations which agree with explicit measurements, and thereby illustrate the usefulness of the proposed Imiomics concept. Conclusions The registration method is well-suited for Imiomics analyses, which enable analyses of relationships to non-imaging data, e.g. clinical data, in new types of holistic targeted and untargeted big-data analysis. PMID:28241015

Automatic patient-adaptive bleeding detection in a capsule endoscopy

NASA Astrophysics Data System (ADS)

Jung, Yun Sub; Kim, Yong Ho; Lee, Dong Ha; Lee, Sang Ho; Song, Jeong Joo; Kim, Jong Hyo

2009-02-01

We present a method for patient-adaptive detection of bleeding region for a Capsule Endoscopy (CE) images. The CE system has 320x320 resolution and transmits 3 images per second to receiver during around 10-hour. We have developed a technique to detect the bleeding automatically utilizing color spectrum transformation (CST) method. However, because of irregular conditions like organ difference, patient difference and illumination condition, detection performance is not uniform. To solve this problem, the detection method in this paper include parameter compensation step which compensate irregular image condition using color balance index (CBI). We have investigated color balance through sequential 2 millions images. Based on this pre-experimental result, we defined ΔCBI to represent deviate of color balance compared with standard small bowel color balance. The ΔCBI feature value is extracted from each image and used in CST method as parameter compensation constant. After candidate pixels were detected using CST method, they were labeled and examined with a bleeding character. We tested our method with 4,800 images in 12 patient data set (9 abnormal, 3 normal). Our experimental results show the proposed method achieves (before patient adaptive method : 80.87% and 74.25%, after patient adaptive method : 94.87% and 96.12%) of sensitivity and specificity.

High quality image-pair-based deblurring method using edge mask and improved residual deconvolution

NASA Astrophysics Data System (ADS)

Cui, Guangmang; Zhao, Jufeng; Gao, Xiumin; Feng, Huajun; Chen, Yueting

2017-04-01

Image deconvolution problem is a challenging task in the field of image process. Using image pairs could be helpful to provide a better restored image compared with the deblurring method from a single blurred image. In this paper, a high quality image-pair-based deblurring method is presented using the improved RL algorithm and the gain-controlled residual deconvolution technique. The input image pair includes a non-blurred noisy image and a blurred image captured for the same scene. With the estimated blur kernel, an improved RL deblurring method based on edge mask is introduced to obtain the preliminary deblurring result with effective ringing suppression and detail preservation. Then the preliminary deblurring result is served as the basic latent image and the gain-controlled residual deconvolution is utilized to recover the residual image. A saliency weight map is computed as the gain map to further control the ringing effects around the edge areas in the residual deconvolution process. The final deblurring result is obtained by adding the preliminary deblurring result with the recovered residual image. An optical experimental vibration platform is set up to verify the applicability and performance of the proposed algorithm. Experimental results demonstrate that the proposed deblurring framework obtains a superior performance in both subjective and objective assessments and has a wide application in many image deblurring fields.

The feasibility of using microwave-induced thermoacoustic tomography for detection and evaluation of renal calculi.

PubMed

Cao, Caijun; Nie, Liming; Lou, Cunguang; Xing, Da

2010-09-07

Imaging of renal calculi is important for patients who suffered a urinary calculus prior to treatment. The available imaging techniques include plain x-ray, ultrasound scan, intravenous urogram, computed tomography, etc. However, the visualization of a uric acid calculus (radiolucent calculi) is difficult and often impossible by the above imaging methods. In this paper, a new detection method based on microwave-induced thermoacoustic tomography was developed to detect the renal calculi. Thermoacoustic images of calcium oxalate and uric acid calculus were compared with their x-ray images. The microwave absorption differences among the calcium oxalate calculus, uric acid calculus and normal kidney tissue could be evaluated by the amplitude of the thermoacoustic signals. The calculi hidden in the swine kidney were clearly imaged with excellent contrast and resolution in the three orthogonal thermoacoustic images. The results indicate that thermoacoustic imaging may be developed as a complementary method for detecting renal calculi, and its low cost and effective feature shows high potential for clinical applications.

Speckle noise attenuation in optical coherence tomography by compounding images acquired at different positions of the sample

NASA Astrophysics Data System (ADS)

Popescu, Dan P.; Hewko, Mark D.; Sowa, Michael G.

2007-01-01

This study demonstrates a simple method for attenuating the speckle noise generated by coherent multiple-scattered photons in optical-coherence tomography images. The method could be included among the space-diversity techniques used for speckle reduction. It relies on displacing the sample along a weakly focused beam in the sample arm of the interferometer, acquiring a coherent image for each sample position and adding the individual images to form a compounded image. It is proven that the compounded image displays a reduction in the speckle noise generated by multiple scattered photons and an enhancement in the intensity signal caused by single-backscattered photons. To evaluate its potential biomedical applications, the method is used to investigate in vitro a caries lesion affecting the enamel layer of a wisdom tooth. Because of the uncorrelated nature of the speckle noise the compounded image provides a better mapping of the lesion compared to a single (coherent) image.

Online advertising by three commercial breast imaging services: message takeout and effectiveness.

PubMed

Johnson, Rebecca; Jalleh, Geoffrey; Pratt, Iain S; Donovan, Robert J; Lin, Chad; Saunders, Christobel; Slevin, Terry

2013-10-01

Mammography is widely acknowledged to be the most cost-effective technique for population screening for breast cancer. Recently in Australia, imaging modalities other than mammography, including thermography, electrical impedance, and computerised breast imaging, have been increasingly promoted as alternative methods of breast cancer screening. This study assessed the impact of three commercial breast imaging companies' promotional material upon consumers' beliefs about the effectiveness of the companies' technology in detecting breast cancer, and consumers' intentions to seek more information or consider having their breasts imaged by these modalities. Results showed 90% of respondents agreed that the companies' promotional material promoted the message that the advertised breast imaging method was effective in detecting breast cancer, and 80% agreed that the material promoted the message that the imaging method was equally or more effective than a mammogram. These findings have implications for women's preference for and uptake of alternative breast imaging services over mammography. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2001-01-01

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

Design and performance evaluation of the imaging payload for a remote sensing satellite

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Abbasi-Moghadam, Dariush

2012-11-01

In this paper an analysis method and corresponding analytical tools for design of the experimental imaging payload (IMPL) of a remote sensing satellite (SINA-1) are presented. We begin with top-level customer system performance requirements and constraints and derive the critical system and component parameters, then analyze imaging payload performance until a preliminary design that meets customer requirements. We consider system parameters and components composing the image chain for imaging payload system which includes aperture, focal length, field of view, image plane dimensions, pixel dimensions, detection quantum efficiency, and optical filter requirements. The performance analysis is accomplished by calculating the imaging payload's SNR (signal-to-noise ratio), and imaging resolution. The noise components include photon noise due to signal scene and atmospheric background, cold shield, out-of-band optical filter leakage and electronic noise. System resolution is simulated through cascaded modulation transfer functions (MTFs) and includes effects due to optics, image sampling, and system motion. Calculations results for the SINA-1 satellite are also presented.

Monitoring the distribution of prompt gamma rays in boron neutron capture therapy using a multiple-scattering Compton camera: A Monte Carlo simulation study

NASA Astrophysics Data System (ADS)

Lee, Taewoong; Lee, Hyounggun; Lee, Wonho

2015-10-01

This study evaluated the use of Compton imaging technology to monitor prompt gamma rays emitted by 10B in boron neutron capture therapy (BNCT) applied to a computerized human phantom. The Monte Carlo method, including particle-tracking techniques, was used for simulation. The distribution of prompt gamma rays emitted by the phantom during irradiation with neutron beams is closely associated with the distribution of the boron in the phantom. Maximum likelihood expectation maximization (MLEM) method was applied to the information obtained from the detected prompt gamma rays to reconstruct the distribution of the tumor including the boron uptake regions (BURs). The reconstructed Compton images of the prompt gamma rays were combined with the cross-sectional images of the human phantom. Quantitative analysis of the intensity curves showed that all combined images matched the predetermined conditions of the simulation. The tumors including the BURs were distinguishable if they were more than 2 cm apart.

Normalized Temperature Contrast Processing in Infrared Flash Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2016-01-01

The paper presents further development in normalized contrast processing used in flash infrared thermography method. Method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided. Methods of converting image contrast to temperature contrast and vice versa are provided. Normalized contrast processing in flash thermography is useful in quantitative analysis of flash thermography data including flaw characterization and comparison of experimental results with simulation. Computation of normalized temperature contrast involves use of flash thermography data acquisition set-up with high reflectivity foil and high emissivity tape such that the foil, tape and test object are imaged simultaneously. Methods of assessing other quantitative parameters such as emissivity of object, afterglow heat flux, reflection temperature change and surface temperature during flash thermography are also provided. Temperature imaging and normalized temperature contrast processing provide certain advantages over normalized image contrast processing by reducing effect of reflected energy in images and measurements, therefore providing better quantitative data. Examples of incorporating afterglow heat-flux and reflection temperature evolution in flash thermography simulation are also discussed.

Adaptive sigmoid function bihistogram equalization for image contrast enhancement

NASA Astrophysics Data System (ADS)

Arriaga-Garcia, Edgar F.; Sanchez-Yanez, Raul E.; Ruiz-Pinales, Jose; Garcia-Hernandez, Ma. de Guadalupe

2015-09-01

Contrast enhancement plays a key role in a wide range of applications including consumer electronic applications, such as video surveillance, digital cameras, and televisions. The main goal of contrast enhancement is to increase the quality of images. However, most state-of-the-art methods induce different types of distortion such as intensity shift, wash-out, noise, intensity burn-out, and intensity saturation. In addition, in consumer electronics, simple and fast methods are required in order to be implemented in real time. A bihistogram equalization method based on adaptive sigmoid functions is proposed. It consists of splitting the image histogram into two parts that are equalized independently by using adaptive sigmoid functions. In order to preserve the mean brightness of the input image, the parameter of the sigmoid functions is chosen to minimize the absolute mean brightness metric. Experiments on the Berkeley database have shown that the proposed method improves the quality of images and preserves their mean brightness. An application to improve the colorfulness of images is also presented.

Brain perfusion imaging using a Reconstruction-of-Difference (RoD) approach for cone-beam computed tomography

NASA Astrophysics Data System (ADS)

Mow, M.; Zbijewski, W.; Sisniega, A.; Xu, J.; Dang, H.; Stayman, J. W.; Wang, X.; Foos, D. H.; Koliatsos, V.; Aygun, N.; Siewerdsen, J. H.

2017-03-01

Purpose: To improve the timely detection and treatment of intracranial hemorrhage or ischemic stroke, recent efforts include the development of cone-beam CT (CBCT) systems for perfusion imaging and new approaches to estimate perfusion parameters despite slow rotation speeds compared to multi-detector CT (MDCT) systems. This work describes development of a brain perfusion CBCT method using a reconstruction of difference (RoD) approach to enable perfusion imaging on a newly developed CBCT head scanner prototype. Methods: A new reconstruction approach using RoD with a penalized-likelihood framework was developed to image the temporal dynamics of vascular enhancement. A digital perfusion simulation was developed to give a realistic representation of brain anatomy, artifacts, noise, scanner characteristics, and hemo-dynamic properties. This simulation includes a digital brain phantom, time-attenuation curves and noise parameters, a novel forward projection method for improved computational efficiency, and perfusion parameter calculation. Results: Our results show the feasibility of estimating perfusion parameters from a set of images reconstructed from slow scans, sparse data sets, and arc length scans as short as 60 degrees. The RoD framework significantly reduces noise and time-varying artifacts from inconsistent projections. Proper regularization and the use of overlapping reconstructed arcs can potentially further decrease bias and increase temporal resolution, respectively. Conclusions: A digital brain perfusion simulation with RoD imaging approach has been developed and supports the feasibility of using a CBCT head scanner for perfusion imaging. Future work will include testing with data acquired using a 3D-printed perfusion phantom currently and translation to preclinical and clinical studies.

Percutaneous Vertebroplasty: Preliminary Experiences with Rotational Acquisitions and 3D Reconstructions for Therapy Control

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

Hodek-Wuerz, Roman; Martin, Jean-Baptiste; Wilhelm, Kai

Percutaneous vertebroplasty (PVP) is carried out under fluoroscopic control in most centers. The exclusion of implant leakage and the assessment of implant distribution might be difficult to assess based on two-dimensional radiographic projection images only. We evaluated the feasibility of performing a follow-up examination after PVP with rotational acquisitions and volumetric reconstructions in the angio suite. Twenty consecutive patients underwent standard PVP procedures under fluoroscopic control. Immediate postprocedure evaluation of the implant distribution in the angio suite (BV 3000; Philips, The Netherlands) was performed using rotational acquisitions (typical parameters for the image acquisition included a 17-cm field-of-view, 200 acquired imagesmore » for a total angular range of 180{sup o}). Postprocessing of acquired volumetric datasets included multiplanar reconstruction (MPR), maximum intensity projection (MIP), and volume rendering technique (VRT) images that were displayed as two-dimensional slabs or as entire three-dimensional volumes. Image evaluation included lesion and implant assessment with special attention given to implant leakage. Findings from rotational acquisitions were compared to findings from postinterventional CT. The time to perform and to postprocess the rotational acquisitions was in all cases less then 10 min. Assessment of implant distribution after PVP using rotational image acquisition methods and volumetric reconstructions was possible in all patients. Cement distribution and potential leakage sites were visualized best on MIP images presented as slabs. From a total of 33 detected leakages with CT, 30 could be correctly detected by rotational image acquisition. Rotational image acquisitions and volumetric reconstruction methods provided a fast method to control radiographically the result of PVP in our cases.« less

Normalized Temperature Contrast Processing in Flash Infrared Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2016-01-01

The paper presents further development in normalized contrast processing of flash infrared thermography method by the author given in US 8,577,120 B1. The method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided, including converting one from the other. Methods of assessing emissivity of the object, afterglow heat flux, reflection temperature change and temperature video imaging during flash thermography are provided. Temperature imaging and normalized temperature contrast imaging provide certain advantages over pixel intensity normalized contrast processing by reducing effect of reflected energy in images and measurements, providing better quantitative data. The subject matter for this paper mostly comes from US 9,066,028 B1 by the author. Examples of normalized image processing video images and normalized temperature processing video images are provided. Examples of surface temperature video images, surface temperature rise video images and simple contrast video images area also provided. Temperature video imaging in flash infrared thermography allows better comparison with flash thermography simulation using commercial software which provides temperature video as the output. Temperature imaging also allows easy comparison of surface temperature change to camera temperature sensitivity or noise equivalent temperature difference (NETD) to assess probability of detecting (POD) anomalies.

Matching shapes with self-intersections: application to leaf classification.

PubMed

Mokhtarian, Farzin; Abbasi, Sadegh

2004-05-01

We address the problem of two-dimensional (2-D) shape representation and matching in presence of self-intersection for large image databases. This may occur when part of an object is hidden behind another part and results in a darker section in the gray level image of the object. The boundary contour of the object must include the boundary of this part which is entirely inside the outline of the object. The Curvature Scale Space (CSS) image of a shape is a multiscale organization of its inflection points as it is smoothed. The CSS-based shape representation method has been selected for MPEG-7 standardization. We study the effects of contour self-intersection on the Curvature Scale Space image. When there is no self-intersection, the CSS image contains several arch shape contours, each related to a concavity or a convexity of the shape. Self intersections create contours with minima as well as maxima in the CSS image. An efficient shape representation method has been introduced in this paper which describes a shape using the maxima as well as the minima of its CSS contours. This is a natural generalization of the conventional method which only includes the maxima of the CSS image contours. The conventional matching algorithm has also been modified to accommodate the new information about the minima. The method has been successfully used in a real world application to find, for an unknown leaf, similar classes from a database of classified leaf images representing different varieties of chrysanthemum. For many classes of leaves, self-intersection is inevitable during the scanning of the image. Therefore the original contributions of this paper is the generalization of the Curvature Scale Space representation to the class of 2-D contours with self-intersection, and its application to the classification of Chrysanthemum leaves.

Ultra High-Resolution In vivo Computed Tomography Imaging of Mouse Cerebrovasculature Using a Long Circulating Blood Pool Contrast Agent

PubMed Central

Starosolski, Zbigniew; Villamizar, Carlos A.; Rendon, David; Paldino, Michael J.; Milewicz, Dianna M.; Ghaghada, Ketan B.; Annapragada, Ananth V.

2015-01-01

Abnormalities in the cerebrovascular system play a central role in many neurologic diseases. The on-going expansion of rodent models of human cerebrovascular diseases and the need to use these models to understand disease progression and treatment has amplified the need for reproducible non-invasive imaging methods for high-resolution visualization of the complete cerebral vasculature. In this study, we present methods for in vivo high-resolution (19 μm isotropic) computed tomography imaging of complete mouse brain vasculature. This technique enabled 3D visualization of large cerebrovascular networks, including the Circle of Willis. Blood vessels as small as 40 μm were clearly delineated. ACTA2 mutations in humans cause cerebrovascular defects, including abnormally straightened arteries and a moyamoya-like arteriopathy characterized by bilateral narrowing of the internal carotid artery and stenosis of many large arteries. In vivo imaging studies performed in a mouse model of Acta2 mutations demonstrated the utility of this method for studying vascular morphometric changes that are practically impossible to identify using current histological methods. Specifically, the technique demonstrated changes in the width of the Circle of Willis, straightening of cerebral arteries and arterial stenoses. We believe the use of imaging methods described here will contribute substantially to the study of rodent cerebrovasculature. PMID:25985192

Parallel image logical operations using cross correlation

NASA Technical Reports Server (NTRS)

Strong, J. P., III

1972-01-01

Methods are presented for counting areas in an image in a parallel manner using noncoherent optical techniques. The techniques presented include the Levialdi algorithm for counting, optical techniques for binary operations, and cross-correlation.

Applying a 2D based CAD scheme for detecting micro-calcification clusters using digital breast tomosynthesis images: an assessment

NASA Astrophysics Data System (ADS)

Park, Sang Cheol; Zheng, Bin; Wang, Xiao-Hui; Gur, David

2008-03-01

Digital breast tomosynthesis (DBT) has emerged as a promising imaging modality for screening mammography. However, visually detecting micro-calcification clusters depicted on DBT images is a difficult task. Computer-aided detection (CAD) schemes for detecting micro-calcification clusters depicted on mammograms can achieve high performance and the use of CAD results can assist radiologists in detecting subtle micro-calcification clusters. In this study, we compared the performance of an available 2D based CAD scheme with one that includes a new grouping and scoring method when applied to both projection and reconstructed DBT images. We selected a dataset involving 96 DBT examinations acquired on 45 women. Each DBT image set included 11 low dose projection images and a varying number of reconstructed image slices ranging from 18 to 87. In this dataset 20 true-positive micro-calcification clusters were visually detected on the projection images and 40 were visually detected on the reconstructed images, respectively. We first applied the CAD scheme that was previously developed in our laboratory to the DBT dataset. We then tested a new grouping method that defines an independent cluster by grouping the same cluster detected on different projection or reconstructed images. We then compared four scoring methods to assess the CAD performance. The maximum sensitivity level observed for the different grouping and scoring methods were 70% and 88% for the projection and reconstructed images with a maximum false-positive rate of 4.0 and 15.9 per examination, respectively. This preliminary study demonstrates that (1) among the maximum, the minimum or the average CAD generated scores, using the maximum score of the grouped cluster regions achieved the highest performance level, (2) the histogram based scoring method is reasonably effective in reducing false-positive detections on the projection images but the overall CAD sensitivity is lower due to lower signal-to-noise ratio, and (3) CAD achieved higher sensitivity and higher false-positive rate (per examination) on the reconstructed images. We concluded that without changing the detection threshold or performing pre-filtering to possibly increase detection sensitivity, current CAD schemes developed and optimized for 2D mammograms perform relatively poorly and need to be re-optimized using DBT datasets and new grouping and scoring methods need to be incorporated into the schemes if these are to be used on the DBT examinations.

Holographic radar imaging privacy techniques utilizing dual-frequency implementation

NASA Astrophysics Data System (ADS)

McMakin, Douglas L.; Hall, Thomas E.; Sheen, David M.

2008-04-01

Over the last 15 years, the Pacific Northwest National Laboratory has performed significant research and development activities to enhance the state of the art of holographic radar imaging systems to be used at security checkpoints for screening people for concealed threats hidden under their garments. These enhancement activities included improvements to privacy techniques to remove human features and providing automatic detection of body-worn concealed threats. The enhanced privacy and detection methods used both physical and software imaging techniques. The physical imaging techniques included polarization-diversity illumination and reception, dual-frequency implementation, and high-frequency imaging at 60 GHz. Software imaging techniques to enhance the privacy of the person under surveillance included extracting concealed threat artifacts from the imagery to automatically detect the threat. This paper will focus on physical privacy techniques using dual-frequency implementation.

Holographic Radar Imaging Privacy Techniques Utilizing Dual-Frequency Implementation

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

McMakin, Douglas L.; Hall, Thomas E.; Sheen, David M.

2008-04-18

Over the last 15 years, the Pacific Northwest National Laboratory has performed significant research and development activities to enhance the state of the art of holographic radar imaging systems to be used at security checkpoints for screening people for concealed threats hidden under their garments. These enhancement activities included improvements to privacy techniques to remove human features and providing automatic detection of body-worn concealed threats. The enhanced privacy and detection methods used both physical and software imaging techniques. The physical imaging techniques included polarization-diversity illumination and reception, dual-frequency implementation, and high-frequency imaging at 60 GHz. Software imaging techniques to enhancemore » the privacy of the person under surveillance included extracting concealed threat artifacts from the imagery to automatically detect the threat. This paper will focus on physical privacy techniques using dual-frequency implementation.« less

A Method to Measure and Estimate Normalized Contrast in Infrared Flash Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2016-01-01

The paper presents further development in normalized contrast processing used in flash infrared thermography method. Method of computing normalized image or pixel intensity contrast, and normalized temperature contrast are provided. Methods of converting image contrast to temperature contrast and vice versa are provided. Normalized contrast processing in flash thermography is useful in quantitative analysis of flash thermography data including flaw characterization and comparison of experimental results with simulation. Computation of normalized temperature contrast involves use of flash thermography data acquisition set-up with high reflectivity foil and high emissivity tape such that the foil, tape and test object are imaged simultaneously. Methods of assessing other quantitative parameters such as emissivity of object, afterglow heat flux, reflection temperature change and surface temperature during flash thermography are also provided. Temperature imaging and normalized temperature contrast processing provide certain advantages over normalized image contrast processing by reducing effect of reflected energy in images and measurements, therefore providing better quantitative data. Examples of incorporating afterglow heat-flux and reflection temperature evolution in flash thermography simulation are also discussed.

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

Dong, X; Petrongolo, M; Wang, T

Purpose: A general problem of dual-energy CT (DECT) is that the decomposition is sensitive to noise in the two sets of dual-energy projection data, resulting in severely degraded qualities of decomposed images. We have previously proposed an iterative denoising method for DECT. Using a linear decomposition function, the method does not gain the full benefits of DECT on beam-hardening correction. In this work, we expand the framework of our iterative method to include non-linear decomposition models for noise suppression in DECT. Methods: We first obtain decomposed projections, which are free of beam-hardening artifacts, using a lookup table pre-measured on amore » calibration phantom. First-pass material images with high noise are reconstructed from the decomposed projections using standard filter-backprojection reconstruction. Noise on the decomposed images is then suppressed by an iterative method, which is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, we include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Analytical formulae are derived to compute the variance-covariance matrix from the measured decomposition lookup table. Results: We have evaluated the proposed method via phantom studies. Using non-linear decomposition, our method effectively suppresses the streaking artifacts of beam-hardening and obtains more uniform images than our previous approach based on a linear model. The proposed method reduces the average noise standard deviation of two basis materials by one order of magnitude without sacrificing the spatial resolution. Conclusion: We propose a general framework of iterative denoising for material decomposition of DECT. Preliminary phantom studies have shown the proposed method improves the image uniformity and reduces noise level without resolution loss. In the future, we will perform more phantom studies to further validate the performance of the purposed method. This work is supported by a Varian MRA grant.« less

A manual for inexpensive methods of analyzing and utilizing remote sensor data

NASA Technical Reports Server (NTRS)

Elifrits, C. D.; Barr, D. J.

1978-01-01

Instructions are provided for inexpensive methods of using remote sensor data to assist in the completion of the need to observe the earth's surface. When possible, relative costs were included. Equipment need for analysis of remote sensor data is described, and methods of use of these equipment items are included, as well as advantages and disadvantages of the use of individual items. Interpretation and analysis of stereo photos and the interpretation of typical patterns such as tone and texture, landcover, drainage, and erosional form are described. Similar treatment is given to monoscopic image interpretation, including LANDSAT MSS data. Enhancement techniques are detailed with respect to their application and simple techniques of creating an enhanced data item. Techniques described include additive and subtractive (Diazo processes) color techniques and enlargement of photos or images. Applications of these processes, including mappings of land resources, engineering soils, geology, water resources, environmental conditions, and crops and/or vegetation, are outlined.

Infrared thermal imaging in medicine.

PubMed

Ring, E F J; Ammer, K

2012-03-01

This review describes the features of modern infrared imaging technology and the standardization protocols for thermal imaging in medicine. The technique essentially uses naturally emitted infrared radiation from the skin surface. Recent studies have investigated the influence of equipment and the methods of image recording. The credibility and acceptance of thermal imaging in medicine is subject to critical use of the technology and proper understanding of thermal physiology. Finally, we review established and evolving medical applications for thermal imaging, including inflammatory diseases, complex regional pain syndrome and Raynaud's phenomenon. Recent interest in the potential applications for fever screening is described, and some other areas of medicine where some research papers have included thermal imaging as an assessment modality. In certain applications thermal imaging is shown to provide objective measurement of temperature changes that are clinically significant.

Applying high resolution remote sensing image and DEM to falling boulder hazard assessment

NASA Astrophysics Data System (ADS)

Huang, Changqing; Shi, Wenzhong; Ng, K. C.

2005-10-01

Boulder fall hazard assessing generally requires gaining the boulder information. The extensive mapping and surveying fieldwork is a time-consuming, laborious and dangerous conventional method. So this paper proposes an applying image processing technology to extract boulder and assess boulder fall hazard from high resolution remote sensing image. The method can replace the conventional method and extract the boulder information in high accuracy, include boulder size, shape, height and the slope and aspect of its position. With above boulder information, it can be satisfied for assessing, prevention and cure boulder fall hazard.

Spread spectrum image steganography.

PubMed

Marvel, L M; Boncelet, C R; Retter, C T

1999-01-01

In this paper, we present a new method of digital steganography, entitled spread spectrum image steganography (SSIS). Steganography, which means "covered writing" in Greek, is the science of communicating in a hidden manner. Following a discussion of steganographic communication theory and review of existing techniques, the new method, SSIS, is introduced. This system hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range. The hidden message can be recovered using appropriate keys without any knowledge of the original image. Image restoration, error-control coding, and techniques similar to spread spectrum are described, and the performance of the system is illustrated. A message embedded by this method can be in the form of text, imagery, or any other digital signal. Applications for such a data-hiding scheme include in-band captioning, covert communication, image tamperproofing, authentication, embedded control, and revision tracking.

Performance evaluation of infrared imaging system in field test

NASA Astrophysics Data System (ADS)

Wang, Chensheng; Guo, Xiaodong; Ren, Tingting; Zhang, Zhi-jie

2014-11-01

Infrared imaging system has been applied widely in both military and civilian fields. Since the infrared imager has various types and different parameters, for system manufacturers and customers, there is great demand for evaluating the performance of IR imaging systems with a standard tool or platform. Since the first generation IR imager was developed, the standard method to assess the performance has been the MRTD or related improved methods which are not perfect adaptable for current linear scanning imager or 2D staring imager based on FPA detector. For this problem, this paper describes an evaluation method based on the triangular orientation discrimination metric which is considered as the effective and emerging method to evaluate the synthesis performance of EO system. To realize the evaluation in field test, an experiment instrument is developed. And considering the importance of operational environment, the field test is carried in practical atmospheric environment. The test imagers include panoramic imaging system and staring imaging systems with different optics and detectors parameters (both cooled and uncooled). After showing the instrument and experiment setup, the experiment results are shown. The target range performance is analyzed and discussed. In data analysis part, the article gives the range prediction values obtained from TOD method, MRTD method and practical experiment, and shows the analysis and results discussion. The experimental results prove the effectiveness of this evaluation tool, and it can be taken as a platform to give the uniform performance prediction reference.

TU-F-BRF-06: 3D Pancreas MRI Segmentation Using Dictionary Learning and Manifold Clustering

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

Gou, S; Rapacchi, S; Hu, P

2014-06-15

Purpose: The recent advent of MRI guided radiotherapy machines has lent an exciting platform for soft tissue target localization during treatment. However, tools to efficiently utilize MRI images for such purpose have not been developed. Specifically, to efficiently quantify the organ motion, we develop an automated segmentation method using dictionary learning and manifold clustering (DLMC). Methods: Fast 3D HASTE and VIBE MR images of 2 healthy volunteers and 3 patients were acquired. A bounding box was defined to include pancreas and surrounding normal organs including the liver, duodenum and stomach. The first slice of the MRI was used for dictionarymore » learning based on mean-shift clustering and K-SVD sparse representation. Subsequent images were iteratively reconstructed until the error is less than a preset threshold. The preliminarily segmentation was subject to the constraints of manifold clustering. The segmentation results were compared with the mean shift merging (MSM), level set (LS) and manual segmentation methods. Results: DLMC resulted in consistently higher accuracy and robustness than comparing methods. Using manual contours as the ground truth, the mean Dices indices for all subjects are 0.54, 0.56 and 0.67 for MSM, LS and DLMC, respectively based on the HASTE image. The mean Dices indices are 0.70, 0.77 and 0.79 for the three methods based on VIBE images. DLMC is clearly more robust on the patients with the diseased pancreas while LS and MSM tend to over-segment the pancreas. DLMC also achieved higher sensitivity (0.80) and specificity (0.99) combining both imaging techniques. LS achieved equivalent sensitivity on VIBE images but was more computationally inefficient. Conclusion: We showed that pancreas and surrounding normal organs can be reliably segmented based on fast MRI using DLMC. This method will facilitate both planning volume definition and imaging guidance during treatment.« less

Emerging From Water: Underwater Image Color Correction Based on Weakly Supervised Color Transfer

NASA Astrophysics Data System (ADS)

Li, Chongyi; Guo, Jichang; Guo, Chunle

2018-03-01

Underwater vision suffers from severe effects due to selective attenuation and scattering when light propagates through water. Such degradation not only affects the quality of underwater images but limits the ability of vision tasks. Different from existing methods which either ignore the wavelength dependency of the attenuation or assume a specific spectral profile, we tackle color distortion problem of underwater image from a new view. In this letter, we propose a weakly supervised color transfer method to correct color distortion, which relaxes the need of paired underwater images for training and allows for the underwater images unknown where were taken. Inspired by Cycle-Consistent Adversarial Networks, we design a multi-term loss function including adversarial loss, cycle consistency loss, and SSIM (Structural Similarity Index Measure) loss, which allows the content and structure of the corrected result the same as the input, but the color as if the image was taken without the water. Experiments on underwater images captured under diverse scenes show that our method produces visually pleasing results, even outperforms the art-of-the-state methods. Besides, our method can improve the performance of vision tasks.

A spatially-variant deconvolution method based on total variation for optical coherence tomography images

NASA Astrophysics Data System (ADS)

Almasganj, Mohammad; Adabi, Saba; Fatemizadeh, Emad; Xu, Qiuyun; Sadeghi, Hamid; Daveluy, Steven; Nasiriavanaki, Mohammadreza

2017-03-01

Optical Coherence Tomography (OCT) has a great potential to elicit clinically useful information from tissues due to its high axial and transversal resolution. In practice, an OCT setup cannot reach to its theoretical resolution due to imperfections of its components, which make its images blurry. The blurriness is different alongside regions of image; thus, they cannot be modeled by a unique point spread function (PSF). In this paper, we investigate the use of solid phantoms to estimate the PSF of each sub-region of imaging system. We then utilize Lucy-Richardson, Hybr and total variation (TV) based iterative deconvolution methods for mitigating occurred spatially variant blurriness. It is shown that the TV based method will suppress the so-called speckle noise in OCT images better than the two other approaches. The performance of proposed algorithm is tested on various samples, including several skin tissues besides the test image blurred with synthetic PSF-map, demonstrating qualitatively and quantitatively the advantage of TV based deconvolution method using spatially-variant PSF for enhancing image quality.

Estimation of color modification in digital images by CFA pattern change.

PubMed

Choi, Chang-Hee; Lee, Hae-Yeoun; Lee, Heung-Kyu

2013-03-10

Extensive studies have been carried out for detecting image forgery such as copy-move, re-sampling, blurring, and contrast enhancement. Although color modification is a common forgery technique, there is no reported forensic method for detecting this type of manipulation. In this paper, we propose a novel algorithm for estimating color modification in images acquired from digital cameras when the images are modified. Most commercial digital cameras are equipped with a color filter array (CFA) for acquiring the color information of each pixel. As a result, the images acquired from such digital cameras include a trace from the CFA pattern. This pattern is composed of the basic red green blue (RGB) colors, and it is changed when color modification is carried out on the image. We designed an advanced intermediate value counting method for measuring the change in the CFA pattern and estimating the extent of color modification. The proposed method is verified experimentally by using 10,366 test images. The results confirmed the ability of the proposed method to estimate color modification with high accuracy. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Comparison of three-dimensional particle tracking and sizing using plenoptic imaging and digital in-line holography.

PubMed

Hall, Elise M; Thurow, Brian S; Guildenbecher, Daniel R

2016-08-10

Digital in-line holography (DIH) and plenoptic photography are two techniques for single-shot, volumetric measurement of 3D particle fields. Here we present a comparison of the two methods by applying plenoptic imaging to experimental configurations that have been previously investigated with DIH. These experiments include the tracking of secondary droplets from the impact of a water drop on a thin film of water and tracking of pellets from a shotgun. Both plenoptic imaging and DIH successfully quantify the 3D nature of these particle fields. This includes measurement of the 3D particle position, individual particle sizes, and three-component velocity vectors. For the initial processing methods presented here, both techniques give out-of-plane positional accuracy of approximately 1-2 particle diameters. For a fixed image sensor, digital holography achieves higher effective in-plane spatial resolutions. However, collimated and coherent illumination makes holography susceptible to image distortion through index of refraction gradients, as demonstrated in the shotgun experiments. In contrast, plenoptic imaging allows for a simpler experimental configuration and, due to the use of diffuse, white-light illumination, plenoptic imaging is less susceptible to image distortion in the shotgun experiments.

Novel image processing method study for a label-free optical biosensor

NASA Astrophysics Data System (ADS)

Yang, Chenhao; Wei, Li'an; Yang, Rusong; Feng, Ying

2015-10-01

Optical biosensor is generally divided into labeled type and label-free type, the former mainly contains fluorescence labeled method and radioactive-labeled method, while fluorescence-labeled method is more mature in the application. The mainly image processing methods of fluorescent-labeled biosensor includes smooth filtering, artificial gridding and constant thresholding. Since some fluorescent molecules may influence the biological reaction, label-free methods have been the main developing direction of optical biosensors nowadays. The using of wider field of view and larger angle of incidence light path which could effectively improve the sensitivity of the label-free biosensor also brought more difficulties in image processing, comparing with the fluorescent-labeled biosensor. Otsu's method is widely applied in machine vision, etc, which choose the threshold to minimize the intraclass variance of the thresholded black and white pixels. It's capacity-constrained with the asymmetrical distribution of images as a global threshold segmentation. In order to solve the irregularity of light intensity on the transducer, we improved the algorithm. In this paper, we present a new image processing algorithm based on a reflectance modulation biosensor platform, which mainly comprises the design of sliding normalization algorithm for image rectification and utilizing the improved otsu's method for image segmentation, in order to implement automatic recognition of target areas. Finally we used adaptive gridding method extracting the target parameters for analysis. Those methods could improve the efficiency of image processing, reduce human intervention, enhance the reliability of experiments and laid the foundation for the realization of high throughput of label-free optical biosensors.

Beyond maximum entropy: Fractal Pixon-based image reconstruction

NASA Technical Reports Server (NTRS)

Puetter, Richard C.; Pina, R. K.

1994-01-01

We have developed a new Bayesian image reconstruction method that has been shown to be superior to the best implementations of other competing methods, including Goodness-of-Fit methods such as Least-Squares fitting and Lucy-Richardson reconstruction, as well as Maximum Entropy (ME) methods such as those embodied in the MEMSYS algorithms. Our new method is based on the concept of the pixon, the fundamental, indivisible unit of picture information. Use of the pixon concept provides an improved image model, resulting in an image prior which is superior to that of standard ME. Our past work has shown how uniform information content pixons can be used to develop a 'Super-ME' method in which entropy is maximized exactly. Recently, however, we have developed a superior pixon basis for the image, the Fractal Pixon Basis (FPB). Unlike the Uniform Pixon Basis (UPB) of our 'Super-ME' method, the FPB basis is selected by employing fractal dimensional concepts to assess the inherent structure in the image. The Fractal Pixon Basis results in the best image reconstructions to date, superior to both UPB and the best ME reconstructions. In this paper, we review the theory of the UPB and FPB pixon and apply our methodology to the reconstruction of far-infrared imaging of the galaxy M51. The results of our reconstruction are compared to published reconstructions of the same data using the Lucy-Richardson algorithm, the Maximum Correlation Method developed at IPAC, and the MEMSYS ME algorithms. The results show that our reconstructed image has a spatial resolution a factor of two better than best previous methods (and a factor of 20 finer than the width of the point response function), and detects sources two orders of magnitude fainter than other methods.

Generation of synthetic image sequences for the verification of matching and tracking algorithms for deformation analysis

NASA Astrophysics Data System (ADS)

Bethmann, F.; Jepping, C.; Luhmann, T.

2013-04-01

This paper reports on a method for the generation of synthetic image data for almost arbitrary static or dynamic 3D scenarios. Image data generation is based on pre-defined 3D objects, object textures, camera orientation data and their imaging properties. The procedure does not focus on the creation of photo-realistic images under consideration of complex imaging and reflection models as they are used by common computer graphics programs. In contrast, the method is designed with main emphasis on geometrically correct synthetic images without radiometric impact. The calculation process includes photogrammetric distortion models, hence cameras with arbitrary geometric imaging characteristics can be applied. Consequently, image sets can be created that are consistent to mathematical photogrammetric models to be used as sup-pixel accurate data for the assessment of high-precision photogrammetric processing methods. In the first instance the paper describes the process of image simulation under consideration of colour value interpolation, MTF/PSF and so on. Subsequently the geometric quality of the synthetic images is evaluated with ellipse operators. Finally, simulated image sets are used to investigate matching and tracking algorithms as they have been developed at IAPG for deformation measurement in car safety testing.

Apparatus and method for a light direction sensor

NASA Technical Reports Server (NTRS)

Leviton, Douglas B. (Inventor)

2011-01-01

The present invention provides a light direction sensor for determining the direction of a light source. The system includes an image sensor; a spacer attached to the image sensor, and a pattern mask attached to said spacer. The pattern mask has a slit pattern that as light passes through the slit pattern it casts a diffraction pattern onto the image sensor. The method operates by receiving a beam of light onto a patterned mask, wherein the patterned mask as a plurality of a slit segments. Then, diffusing the beam of light onto an image sensor and determining the direction of the light source.

System and method for disrupting suspect objects

DOEpatents

Gladwell, T. Scott; Garretson, Justin R; Hobart, Clinton G; Monda, Mark J

2013-07-09

A system and method for disrupting at least one component of a suspect object is provided. The system includes a source for passing radiation through the suspect object, a screen for receiving the radiation passing through the suspect object and generating at least one image therefrom, a weapon having a discharge deployable therefrom, and a targeting unit. The targeting unit displays the image(s) of the suspect object and aims the weapon at a disruption point on the displayed image such that the weapon may be positioned to deploy the discharge at the disruption point whereby the suspect object is disabled.

A quantitative experimental phantom study on MRI image uniformity.

PubMed

Felemban, Doaa; Verdonschot, Rinus G; Iwamoto, Yuri; Uchiyama, Yuka; Kakimoto, Naoya; Kreiborg, Sven; Murakami, Shumei

2018-05-23

Our goal was to assess MR image uniformity by investigating aspects influencing said uniformity via a method laid out by the National Electrical Manufacturers Association (NEMA). Six metallic materials embedded in a glass phantom were scanned (i.e. Au, Ag, Al, Au-Ag-Pd alloy, Ti and Co-Cr alloy) as well as a reference image. Sequences included spin echo (SE) and gradient echo (GRE) scanned in three planes (i.e. axial, coronal, and sagittal). Moreover, three surface coil types (i.e. head and neck, Brain, and temporomandibular joint coils) and two image correction methods (i.e. surface coil intensity correction or SCIC, phased array uniformity enhancement or PURE) were employed to evaluate their effectiveness on image uniformity. Image uniformity was assessed using the National Electrical Manufacturers Association peak-deviation non-uniformity method. Results showed that temporomandibular joint coils elicited the least uniform image and brain coils outperformed head and neck coils when metallic materials were present. Additionally, when metallic materials were present, spin echo outperformed gradient echo especially for Co-Cr (particularly in the axial plane). Furthermore, both SCIC and PURE improved image uniformity compared to uncorrected images, and SCIC slightly surpassed PURE when metallic metals were present. Lastly, Co-Cr elicited the least uniform image while other metallic materials generally showed similar patterns (i.e. no significant deviation from images without metallic metals). Overall, a quantitative understanding of the factors influencing MR image uniformity (e.g. coil type, imaging method, metal susceptibility, and post-hoc correction method) is advantageous to optimize image quality, assists clinical interpretation, and may result in improved medical and dental care.

Methods and apparatuses for detection of radiation with semiconductor image sensors

DOEpatents

Cogliati, Joshua Joseph

2018-04-10

A semiconductor image sensor is repeatedly exposed to high-energy photons while a visible light obstructer is in place to block visible light from impinging on the sensor to generate a set of images from the exposures. A composite image is generated from the set of images with common noise substantially removed so the composite image includes image information corresponding to radiated pixels that absorbed at least some energy from the high-energy photons. The composite image is processed to determine a set of bright points in the composite image, each bright point being above a first threshold. The set of bright points is processed to identify lines with two or more bright points that include pixels therebetween that are above a second threshold and identify a presence of the high-energy particles responsive to a number of lines.

SU-E-J-76: CBCT Reconstruction of a Full Couch Using Rigid Registration and Pre-Scanned Couch Image and Its Clinical Application

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

Hu, E; Lasio, G; Lee, M

Purpose: Only a part of a treatment couch is reconstructed in CBCT due to the limited field of view (FOV). This often generates inaccurate results in the delivered dose evaluation with CBCT and more noise in the CBCT reconstruction. Full reconstruction of the couch at treatment setup can be used for more accurate exit beam dosimetry. The goal of this study is to develop a method to reconstruct a full treatment couch using a pre-scanned couch image and rigid registration. Methods: A full couch (Exact Couch, Varian) model image was reconstructed by rigidly registering and combining two sets of partialmore » CBCT images. The full couch model includes three parts: two side rails and a couch top. A patient CBCT was reconstructed with reconstruction grid size larger than the physical field of view to include the full couch. The image quality of the couch is not good due to data truncation, but good enough to allow rigid registration of the couch. A composite CBCT image of the patient plus couch has been generated from the original reconstruction by replacing couch portion with the pre-acquired model couch, rigidly registered to the original scan. We evaluated the clinical usefulness of this method by comparing treatment plans generated on the original and on the modified scans. Results: The full couch model could be attached to a patient CBCT image set via rigid image registration. Plan DVHs showed 1∼2% difference between plans with and without full couch modeling. Conclusion: The proposed method generated a full treatment couch CBCT model, which can be successfully registered to the original patient image. This method was also shown to be useful in generating more accurate dose distributions, by lowering 1∼2% dose in PTV and a few other critical organs. Part of this study is supported by NIH R01CA133539.« less

Characterization of coronary plaque regions in intravascular ultrasound images using a hybrid ensemble classifier.

PubMed

Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Shin, Eun Seok; Kim, Sung Min

2018-01-01

The purpose of this study was to propose a hybrid ensemble classifier to characterize coronary plaque regions in intravascular ultrasound (IVUS) images. Pixels were allocated to one of four tissues (fibrous tissue (FT), fibro-fatty tissue (FFT), necrotic core (NC), and dense calcium (DC)) through processes of border segmentation, feature extraction, feature selection, and classification. Grayscale IVUS images and their corresponding virtual histology images were acquired from 11 patients with known or suspected coronary artery disease using 20 MHz catheter. A total of 102 hybrid textural features including first order statistics (FOS), gray level co-occurrence matrix (GLCM), extended gray level run-length matrix (GLRLM), Laws, local binary pattern (LBP), intensity, and discrete wavelet features (DWF) were extracted from IVUS images. To select optimal feature sets, genetic algorithm was implemented. A hybrid ensemble classifier based on histogram and texture information was then used for plaque characterization in this study. The optimal feature set was used as input of this ensemble classifier. After tissue characterization, parameters including sensitivity, specificity, and accuracy were calculated to validate the proposed approach. A ten-fold cross validation approach was used to determine the statistical significance of the proposed method. Our experimental results showed that the proposed method had reliable performance for tissue characterization in IVUS images. The hybrid ensemble classification method outperformed other existing methods by achieving characterization accuracy of 81% for FFT and 75% for NC. In addition, this study showed that Laws features (SSV and SAV) were key indicators for coronary tissue characterization. The proposed method had high clinical applicability for image-based tissue characterization. Copyright © 2017 Elsevier B.V. All rights reserved.

Three-Dimensional Localization of Single Molecules for Super-Resolution Imaging and Single-Particle Tracking

PubMed Central

von Diezmann, Alex; Shechtman, Yoav; Moerner, W. E.

2017-01-01

Single-molecule super-resolution fluorescence microscopy and single-particle tracking are two imaging modalities that illuminate the properties of cells and materials on spatial scales down to tens of nanometers, or with dynamical information about nanoscale particle motion in the millisecond range, respectively. These methods generally use wide-field microscopes and two-dimensional camera detectors to localize molecules to much higher precision than the diffraction limit. Given the limited total photons available from each single-molecule label, both modalities require careful mathematical analysis and image processing. Much more information can be obtained about the system under study by extending to three-dimensional (3D) single-molecule localization: without this capability, visualization of structures or motions extending in the axial direction can easily be missed or confused, compromising scientific understanding. A variety of methods for obtaining both 3D super-resolution images and 3D tracking information have been devised, each with their own strengths and weaknesses. These include imaging of multiple focal planes, point-spread-function engineering, and interferometric detection. These methods may be compared based on their ability to provide accurate and precise position information of single-molecule emitters with limited photons. To successfully apply and further develop these methods, it is essential to consider many practical concerns, including the effects of optical aberrations, field-dependence in the imaging system, fluorophore labeling density, and registration between different color channels. Selected examples of 3D super-resolution imaging and tracking are described for illustration from a variety of biological contexts and with a variety of methods, demonstrating the power of 3D localization for understanding complex systems. PMID:28151646

Use of technology in children's dietary assessment.

PubMed

Boushey, C J; Kerr, D A; Wright, J; Lutes, K D; Ebert, D S; Delp, E J

2009-02-01

Information on dietary intake provides some of the most valuable insights for mounting intervention programmes for the prevention of chronic diseases. With the growing concern about adolescent overweight, the need to accurately measure diet becomes imperative. Assessment among adolescents is problematic as this group has irregular eating patterns and they have less enthusiasm for recording food intake. We used qualitative and quantitative techniques among adolescents to assess their preferences for dietary assessment methods. Dietary assessment methods using technology, for example, a personal digital assistant (PDA) or a disposable camera, were preferred over the pen and paper food record. There was a strong preference for using methods that incorporate technology such as capturing images of food. This suggests that for adolescents, dietary methods that incorporate technology may improve cooperation and accuracy. Current computing technology includes higher resolution images, improved memory capacity and faster processors that allow small mobile devices to process information not previously possible. Our goal is to develop, implement and evaluate a mobile device (for example, PDA, mobile phone) food record that will translate to an accurate account of daily food and nutrient intake among adolescents. This mobile computing device will include digital images, a nutrient database and image analysis for identification and quantification of food consumption. Mobile computing devices provide a unique vehicle for collecting dietary information that reduces the burden on record keepers. Images of food can be marked with a variety of input methods that link the item for image processing and analysis to estimate the amount of food. Images before and after the foods are eaten can estimate the amount of food consumed. The initial stages and potential of this project will be described.

Imaging of surface spin textures on bulk crystals by scanning electron microscopy

NASA Astrophysics Data System (ADS)

Akamine, Hiroshi; Okumura, So; Farjami, Sahar; Murakami, Yasukazu; Nishida, Minoru

2016-11-01

Direct observation of magnetic microstructures is vital for advancing spintronics and other technologies. Here we report a method for imaging surface domain structures on bulk samples by scanning electron microscopy (SEM). Complex magnetic domains, referred to as the maze state in CoPt/FePt alloys, were observed at a spatial resolution of less than 100 nm by using an in-lens annular detector. The method allows for imaging almost all the domain walls in the mazy structure, whereas the visualisation of the domain walls with the classical SEM method was limited. Our method provides a simple way to analyse surface domain structures in the bulk state that can be used in combination with SEM functions such as orientation or composition analysis. Thus, the method extends applications of SEM-based magnetic imaging, and is promising for resolving various problems at the forefront of fields including physics, magnetics, materials science, engineering, and chemistry.

Iterative deep convolutional encoder-decoder network for medical image segmentation.

PubMed

Jung Uk Kim; Hak Gu Kim; Yong Man Ro

2017-07-01

In this paper, we propose a novel medical image segmentation using iterative deep learning framework. We have combined an iterative learning approach and an encoder-decoder network to improve segmentation results, which enables to precisely localize the regions of interest (ROIs) including complex shapes or detailed textures of medical images in an iterative manner. The proposed iterative deep convolutional encoder-decoder network consists of two main paths: convolutional encoder path and convolutional decoder path with iterative learning. Experimental results show that the proposed iterative deep learning framework is able to yield excellent medical image segmentation performances for various medical images. The effectiveness of the proposed method has been proved by comparing with other state-of-the-art medical image segmentation methods.

Recovery of Background Structures in Nanoscale Helium Ion Microscope Imaging.

PubMed

Carasso, Alfred S; Vladár, András E

2014-01-01

This paper discusses a two step enhancement technique applicable to noisy Helium Ion Microscope images in which background structures are not easily discernible due to a weak signal. The method is based on a preliminary adaptive histogram equalization, followed by 'slow motion' low-exponent Lévy fractional diffusion smoothing. This combined approach is unexpectedly effective, resulting in a companion enhanced image in which background structures are rendered much more visible, and noise is significantly reduced, all with minimal loss of image sharpness. The method also provides useful enhancements of scanning charged-particle microscopy images obtained by composing multiple drift-corrected 'fast scan' frames. The paper includes software routines, written in Interactive Data Language (IDL),(1) that can perform the above image processing tasks.

How Do Health Care Providers Diagnose Pheochromocytoma?

MedlinePlus

... NICHD Research Information Find a Study More Information Pharmacology Condition Information NICHD Research Information Find a Study ... several imaging methods, including computed tomography (CT) and magnetic resonance imaging (MRI). CT scans use X-rays to produce ...

Surface defect detection in tiling Industries using digital image processing methods: analysis and evaluation.

PubMed

Karimi, Mohammad H; Asemani, Davud

2014-05-01

Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

An Aggregated Method for Determining Railway Defects and Obstacle Parameters

NASA Astrophysics Data System (ADS)

Loktev, Daniil; Loktev, Alexey; Stepanov, Roman; Pevzner, Viktor; Alenov, Kanat

2018-03-01

The method of combining algorithms of image blur analysis and stereo vision to determine the distance to objects (including external defects of railway tracks) and the speed of moving objects-obstacles is proposed. To estimate the deviation of the distance depending on the blur a statistical approach, logarithmic, exponential and linear standard functions are used. The statistical approach includes a method of estimating least squares and the method of least modules. The accuracy of determining the distance to the object, its speed and direction of movement is obtained. The paper develops a method of determining distances to objects by analyzing a series of images and assessment of depth using defocusing using its aggregation with stereoscopic vision. This method is based on a physical effect of dependence on the determined distance to the object on the obtained image from the focal length or aperture of the lens. In the calculation of the blur spot diameter it is assumed that blur occurs at the point equally in all directions. According to the proposed approach, it is possible to determine the distance to the studied object and its blur by analyzing a series of images obtained using the video detector with different settings. The article proposes and scientifically substantiates new and improved existing methods for detecting the parameters of static and moving objects of control, and also compares the results of the use of various methods and the results of experiments. It is shown that the aggregate method gives the best approximation to the real distances.

[Evaluation study on a new method of dietary assessment with instant photography applied in urban pregnant women in Nanjing city].

PubMed

Jiang, Tingting; Dai, Yongmei; Miao, Miao; Zhang, Yue; Song, Chenglin; Wang, Zhixu

2015-07-01

To evaluate the usefulness and efficiency of a novel dietary method among urban pregnant women. Sixty one pregnant women were recruited from the ward and provided with a meal accurately weighed before cooking. The meal was photographed from three different angles before and after eating. The subjects were also interviewed for 24 h dietary recall by the investigators. Food weighting, image quantification and 24 h dietary recall were conducted by investigators from three different groups, and the messages were isolated from each other. Food consumption was analyzed on bases of classification and total summation. Nutrient intake from the meal was calculated for each subject. The data obtained from the dietary recall and the image quantification were compared with the actual values. Correlation and regression analyses were carried out on values between weight method and image quantification as well as dietary recall. Total twenty three kinds of food including rice, vegetables, fish, meats and soy bean curd were included in the experimental meal for the study. Compared with data from 24 h dietary recall (r = 0.413, P < 0.05), food weight estimated by image quantification (r = 0.778, P < 0.05, n = 308) were more correlated with weighed data, and show more concentrated linear distribution. Absolute difference distribution between image quantification and weight method of all food was 77.23 ± 56.02 (P < 0.05, n = 61), which was much small than the difference (172.77 ± 115.18) between 24 h recall and weight method. Values of almost all nutrients, including energy, protein, fat, carbohydrate, vitamin A, vitamin C, calcium, iron and zine calculated based on food weight from image quantification were more close to those of weighed data compared with 24 h dietary recall (P < 0.01). The results found by the Bland Altman analysis showed that the majority of the measurements for nutrient intake, were scattered along the mean difference line and close to the equality line (difference = 0). The plots show fairly good agreement between estimated and actual food consumption. It indicate that the differences (including the outliers) were random and did not exhibit any systematic bias, being consistent over different levels of mean food amount. On the other hand, the questionnaire showed that fifty six pregnant women considered the image quantification was less time-consuming and burdened than 24 h recall. Fifty eight of them would like to use image quantification to know their dietary status. The novel method which called instant photography (image quantification) for dietary assessment is more effective than conventional 24 h dietary recall and it also can obtain food intake values close to weighed data.

Calibration, reconstruction, and rendering of cylindrical millimeter-wave image data

NASA Astrophysics Data System (ADS)

Sheen, David M.; Hall, Thomas E.

2011-05-01

Cylindrical millimeter-wave imaging systems and technology have been under development at the Pacific Northwest National Laboratory (PNNL) for several years. This technology has been commercialized, and systems are currently being deployed widely across the United States and internationally. These systems are effective at screening for concealed items of all types; however, new sensor designs, image reconstruction techniques, and image rendering algorithms could potentially improve performance. At PNNL, a number of specific techniques have been developed recently to improve cylindrical imaging methods including wideband techniques, combining data from full 360-degree scans, polarimetric imaging techniques, calibration methods, and 3-D data visualization techniques. Many of these techniques exploit the three-dimensionality of the cylindrical imaging technique by optimizing the depth resolution of the system and using this information to enhance detection. Other techniques, such as polarimetric methods, exploit scattering physics of the millimeter-wave interaction with concealed targets on the body. In this paper, calibration, reconstruction, and three-dimensional rendering techniques will be described that optimize the depth information in these images and the display of the images to the operator.

A novel automated method for doing registration and 3D reconstruction from multi-modal RGB/IR image sequences

NASA Astrophysics Data System (ADS)

Kirby, Richard; Whitaker, Ross

2016-09-01

In recent years, the use of multi-modal camera rigs consisting of an RGB sensor and an infrared (IR) sensor have become increasingly popular for use in surveillance and robotics applications. The advantages of using multi-modal camera rigs include improved foreground/background segmentation, wider range of lighting conditions under which the system works, and richer information (e.g. visible light and heat signature) for target identification. However, the traditional computer vision method of mapping pairs of images using pixel intensities or image features is often not possible with an RGB/IR image pair. We introduce a novel method to overcome the lack of common features in RGB/IR image pairs by using a variational methods optimization algorithm to map the optical flow fields computed from different wavelength images. This results in the alignment of the flow fields, which in turn produce correspondences similar to those found in a stereo RGB/RGB camera rig using pixel intensities or image features. In addition to aligning the different wavelength images, these correspondences are used to generate dense disparity and depth maps. We obtain accuracies similar to other multi-modal image alignment methodologies as long as the scene contains sufficient depth variations, although a direct comparison is not possible because of the lack of standard image sets from moving multi-modal camera rigs. We test our method on synthetic optical flow fields and on real image sequences that we created with a multi-modal binocular stereo RGB/IR camera rig. We determine our method's accuracy by comparing against a ground truth.

Dual-Tree Complex Wavelet Transform and Image Block Residual-Based Multi-Focus Image Fusion in Visual Sensor Networks

PubMed Central

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-01-01

This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs. PMID:25587878

Dual-tree complex wavelet transform and image block residual-based multi-focus image fusion in visual sensor networks.

PubMed

Yang, Yong; Tong, Song; Huang, Shuying; Lin, Pan

2014-11-26

This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs.

Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

USGS Publications Warehouse

Shermeyer, Jacob S.; Haack, Barry N.

2015-01-01

Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

A new integrated dual time-point amyloid PET/MRI data analysis method.

PubMed

Cecchin, Diego; Barthel, Henryk; Poggiali, Davide; Cagnin, Annachiara; Tiepolt, Solveig; Zucchetta, Pietro; Turco, Paolo; Gallo, Paolo; Frigo, Anna Chiara; Sabri, Osama; Bui, Franco

2017-11-01

In the initial evaluation of patients with suspected dementia and Alzheimer's disease, there is no consensus on how to perform semiquantification of amyloid in such a way that it: (1) facilitates visual qualitative interpretation, (2) takes the kinetic behaviour of the tracer into consideration particularly with regard to at least partially correcting for blood flow dependence, (3) analyses the amyloid load based on accurate parcellation of cortical and subcortical areas, (4) includes partial volume effect correction (PVEC), (5) includes MRI-derived topographical indexes, (6) enables application to PET/MRI images and PET/CT images with separately acquired MR images, and (7) allows automation. A method with all of these characteristics was retrospectively tested in 86 subjects who underwent amyloid ( 18 F-florbetaben) PET/MRI in a clinical setting (using images acquired 90-110 min after injection, 53 were classified visually as amyloid-negative and 33 as amyloid-positive). Early images after tracer administration were acquired between 0 and 10 min after injection, and later images were acquired between 90 and 110 min after injection. PVEC of the PET data was carried out using the geometric transfer matrix method. Parametric images and some regional output parameters, including two innovative "dual time-point" indexes, were obtained. Subjects classified visually as amyloid-positive showed a sparse tracer uptake in the primary sensory, motor and visual areas in accordance with the isocortical stage of the topographic distribution of the amyloid plaque (Braak stages V/VI). In patients classified visually as amyloid-negative, the method revealed detectable levels of tracer uptake in the basal portions of the frontal and temporal lobes, areas that are known to be sites of early deposition of amyloid plaques that probably represented early accumulation (Braak stage A) that is typical of normal ageing. There was a strong correlation between age and the indexes of the new dual time-point amyloid imaging method in amyloid-negative patients. The method can be considered a valuable tool in both routine clinical practice and in the research setting as it will standardize data regarding amyloid deposition. It could potentially also be used to identify early amyloid plaque deposition in younger subjects in whom treatment could theoretically be more effective.

Improved GO/PO method and its application to wideband SAR image of conducting objects over rough surface

NASA Astrophysics Data System (ADS)

Jiang, Wang-Qiang; Zhang, Min; Nie, Ding; Jiao, Yong-Chang

2018-04-01

To simulate the multiple scattering effect of target in synthetic aperture radar (SAR) image, the hybrid method GO/PO method, which combines the geometrical optics (GO) and physical optics (PO), is employed to simulate the scattering field of target. For ray tracing is time-consuming, the Open Graphics Library (OpenGL) is usually employed to accelerate the process of ray tracing. Furthermore, the GO/PO method is improved for the simulation in low pixel situation. For the improved GO/PO method, the pixels are arranged corresponding to the rectangular wave beams one by one, and the GO/PO result is the sum of the contribution values of all the rectangular wave beams. To get high-resolution SAR image, the wideband echo signal is simulated which includes information of many electromagnetic (EM) waves with different frequencies. Finally, the improved GO/PO method is used to simulate the SAR image of targets above rough surface. And the effects of reflected rays and the size of pixel matrix on the SAR image are also discussed.

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

Niu, T; Dong, X; Petrongolo, M

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its material decomposition capability. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical value. Existing de-noising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. We propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimationmore » with smoothness regularization. It includes the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Performance is evaluated using an evaluation phantom (Catphan 600) and an anthropomorphic head phantom. Results are compared to those generated using direct matrix inversion with no noise suppression, a de-noising method applied on the decomposed images, and an existing algorithm with similar formulation but with an edge-preserving regularization term. Results: On the Catphan phantom, our method retains the same spatial resolution as the CT images before decomposition while reducing the noise standard deviation of decomposed images by over 98%. The other methods either degrade spatial resolution or achieve less low-contrast detectability. Also, our method yields lower electron density measurement error than direct matrix inversion and reduces error variation by over 97%. On the head phantom, it reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusion: We propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. The proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability. This work is supported by a Varian MRA grant.« less

Stochastic simulation by image quilting of process-based geological models

NASA Astrophysics Data System (ADS)

Hoffimann, Júlio; Scheidt, Céline; Barfod, Adrian; Caers, Jef

2017-09-01

Process-based modeling offers a way to represent realistic geological heterogeneity in subsurface models. The main limitation lies in conditioning such models to data. Multiple-point geostatistics can use these process-based models as training images and address the data conditioning problem. In this work, we further develop image quilting as a method for 3D stochastic simulation capable of mimicking the realism of process-based geological models with minimal modeling effort (i.e. parameter tuning) and at the same time condition them to a variety of data. In particular, we develop a new probabilistic data aggregation method for image quilting that bypasses traditional ad-hoc weighting of auxiliary variables. In addition, we propose a novel criterion for template design in image quilting that generalizes the entropy plot for continuous training images. The criterion is based on the new concept of voxel reuse-a stochastic and quilting-aware function of the training image. We compare our proposed method with other established simulation methods on a set of process-based training images of varying complexity, including a real-case example of stochastic simulation of the buried-valley groundwater system in Denmark.

Content-based cell pathology image retrieval by combining different features

NASA Astrophysics Data System (ADS)

Zhou, Guangquan; Jiang, Lu; Luo, Limin; Bao, Xudong; Shu, Huazhong

2004-04-01

Content Based Color Cell Pathology Image Retrieval is one of the newest computer image processing applications in medicine. Recently, some algorithms have been developed to achieve this goal. Because of the particularity of cell pathology images, the result of the image retrieval based on single characteristic is not satisfactory. A new method for pathology image retrieval by combining color, texture and morphologic features to search cell images is proposed. Firstly, nucleus regions of leukocytes in images are automatically segmented by K-mean clustering method. Then single leukocyte region is detected by utilizing thresholding algorithm segmentation and mathematics morphology. The features that include color, texture and morphologic features are extracted from single leukocyte to represent main attribute in the search query. The features are then normalized because the numerical value range and physical meaning of extracted features are different. Finally, the relevance feedback system is introduced. So that the system can automatically adjust the weights of different features and improve the results of retrieval system according to the feedback information. Retrieval results using the proposed method fit closely with human perception and are better than those obtained with the methods based on single feature.

Method for eliminating artifacts in CCD imagers

DOEpatents

Turko, Bojan T.; Yates, George J.

1992-01-01

An electronic method for eliminating artifacts in a video camera (10) employing a charge coupled device (CCD) (12) as an image sensor. The method comprises the step of initializing the camera (10) prior to normal read out and includes a first dump cycle period (76) for transferring radiation generated charge into the horizontal register (28) while the decaying image on the phosphor (39) being imaged is being integrated in the photosites, and a second dump cycle period (78), occurring after the phosphor (39) image has decayed, for rapidly dumping unwanted smear charge which has been generated in the vertical registers (32). Image charge is then transferred from the photosites (36) and (38) to the vertical registers (32) and read out in conventional fashion. The inventive method allows the video camera (10) to be used in environments having high ionizing radiation content, and to capture images of events of very short duration and occurring either within or outside the normal visual wavelength spectrum. Resultant images are free from ghost, smear and smear phenomena caused by insufficient opacity of the registers (28) and (32), and are also free from random damage caused by ionization charges which exceed the charge limit capacity of the photosites (36) and (37).

Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer

NASA Astrophysics Data System (ADS)

Luiza Bondar, M.; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

2013-08-01

For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

Intra-patient semi-automated segmentation of the cervix-uterus in CT-images for adaptive radiotherapy of cervical cancer.

PubMed

Bondar, M Luiza; Hoogeman, Mischa; Schillemans, Wilco; Heijmen, Ben

2013-08-07

For online adaptive radiotherapy of cervical cancer, fast and accurate image segmentation is required to facilitate daily treatment adaptation. Our aim was twofold: (1) to test and compare three intra-patient automated segmentation methods for the cervix-uterus structure in CT-images and (2) to improve the segmentation accuracy by including prior knowledge on the daily bladder volume or on the daily coordinates of implanted fiducial markers. The tested methods were: shape deformation (SD) and atlas-based segmentation (ABAS) using two non-rigid registration methods: demons and a hierarchical algorithm. Tests on 102 CT-scans of 13 patients demonstrated that the segmentation accuracy significantly increased by including the bladder volume predicted with a simple 1D model based on a manually defined bladder top. Moreover, manually identified implanted fiducial markers significantly improved the accuracy of the SD method. For patients with large cervix-uterus volume regression, the use of CT-data acquired toward the end of the treatment was required to improve segmentation accuracy. Including prior knowledge, the segmentation results of SD (Dice similarity coefficient 85 ± 6%, error margin 2.2 ± 2.3 mm, average time around 1 min) and of ABAS using hierarchical non-rigid registration (Dice 82 ± 10%, error margin 3.1 ± 2.3 mm, average time around 30 s) support their use for image guided online adaptive radiotherapy of cervical cancer.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

A comparative study on methods of improving SCR for ship detection in SAR image

NASA Astrophysics Data System (ADS)

Lang, Haitao; Shi, Hongji; Tao, Yunhong; Ma, Li

2017-10-01

Knowledge about ship positions plays a critical role in a wide range of maritime applications. To improve the performance of ship detector in SAR image, an effective strategy is improving the signal-to-clutter ratio (SCR) before conducting detection. In this paper, we present a comparative study on methods of improving SCR, including power-law scaling (PLS), max-mean and max-median filter (MMF1 and MMF2), method of wavelet transform (TWT), traditional SPAN detector, reflection symmetric metric (RSM), scattering mechanism metric (SMM). The ability of SCR improvement to SAR image and ship detection performance associated with cell- averaging CFAR (CA-CFAR) of different methods are evaluated on two real SAR data.

Patch Based Synthesis of Whole Head MR Images: Application to EPI Distortion Correction.

PubMed

Roy, Snehashis; Chou, Yi-Yu; Jog, Amod; Butman, John A; Pham, Dzung L

2016-10-01

Different magnetic resonance imaging pulse sequences are used to generate image contrasts based on physical properties of tissues, which provide different and often complementary information about them. Therefore multiple image contrasts are useful for multimodal analysis of medical images. Often, medical image processing algorithms are optimized for particular image contrasts. If a desirable contrast is unavailable, contrast synthesis (or modality synthesis) methods try to "synthesize" the unavailable constrasts from the available ones. Most of the recent image synthesis methods generate synthetic brain images, while whole head magnetic resonance (MR) images can also be useful for many applications. We propose an atlas based patch matching algorithm to synthesize T 2 -w whole head (including brain, skull, eyes etc) images from T 1 -w images for the purpose of distortion correction of diffusion weighted MR images. The geometric distortion in diffusion MR images due to in-homogeneous B 0 magnetic field are often corrected by non-linearly registering the corresponding b = 0 image with zero diffusion gradient to an undistorted T 2 -w image. We show that our synthetic T 2 -w images can be used as a template in absence of a real T 2 -w image. Our patch based method requires multiple atlases with T 1 and T 2 to be registeLowRes to a given target T 1 . Then for every patch on the target, multiple similar looking matching patches are found on the atlas T 1 images and corresponding patches on the atlas T 2 images are combined to generate a synthetic T 2 of the target. We experimented on image data obtained from 44 patients with traumatic brain injury (TBI), and showed that our synthesized T 2 images produce more accurate distortion correction than a state-of-the-art registration based image synthesis method.

Rapid water and lipid imaging with T2 mapping using a radial IDEAL-GRASE technique.

PubMed

Li, Zhiqiang; Graff, Christian; Gmitro, Arthur F; Squire, Scott W; Bilgin, Ali; Outwater, Eric K; Altbach, Maria I

2009-06-01

Three-point Dixon methods have been investigated as a means to generate water and fat images without the effects of field inhomogeneities. Recently, an iterative algorithm (IDEAL, iterative decomposition of water and fat with echo asymmetry and least squares estimation) was combined with a gradient and spin-echo acquisition strategy (IDEAL-GRASE) to provide a time-efficient method for lipid-water imaging with correction for the effects of field inhomogeneities. The method presented in this work combines IDEAL-GRASE with radial data acquisition. Radial data sampling offers robustness to motion over Cartesian trajectories as well as the possibility of generating high-resolution T(2) maps in addition to the water and fat images. The radial IDEAL-GRASE technique is demonstrated in phantoms and in vivo for various applications including abdominal, pelvic, and cardiac imaging.

Influence of environmental tobacco smoke on morphology and functions of cardiovascular system assessed using diagnostic imaging.

PubMed

Gać, Paweł; Poręba, Małgorzata; Pawlas, Krystyna; Sobieszczańska, Małgorzata; Poręba, Rafał

Exposure to tobacco smoke is a significant problem of environmental medicine. Tobacco smoke contains over one thousand identified chemicals including numerous toxicants. Cardiovascular system diseases are the major cause of general mortality. The recent development of diagnostic imaging provided methods which enable faster and more precise diagnosis of numerous diseases, also those of cardiovascular system. This paper reviews the most significant scientific research concerning relationship between environmental exposure to tobacco smoke and the morphology and function of cardiovascular system carried out using diagnostic imaging methods, i.e. ultrasonography, angiography, computed tomography and magnetic resonance imaging. In the forthcoming future, the studies using current diagnostic imaging methods should contribute to the reliable documentation, followed by the wide-spreading knowledge of the harmful impact of the environmental tobacco smoke exposure on the cardiovascular system.

Mueller matrix imaging study to detect the dental demineralization

NASA Astrophysics Data System (ADS)

Chen, Qingguang; Shen, Huanbo; Wang, Binqiang

2018-01-01

Mueller matrix is an optical parameter invasively to reveal the structure information of anisotropic material. Dental tissue has the ordered structure including dental enamel prism and dentinal tubule. The ordered structure of teeth surface will be destroyed by demineralization. The structure information has the possibility to reflect the dental demineralization. In the paper, the experiment setup was built to obtain the Mueller matrix images based on the dual- wave plate rotation method. Two linear polarizer and two quarter-wave plate were rotated by electric control revolving stage respectively to capture 16 images at different group of polarization states. Therefore, Mueller matrix image can be calculated from the 16 images. On this basis, depolarization index, the diattenuation index and retardance index of the Mueller matrix were analyzed by Lu-Chipman polarization decomposition method. Mueller matrix images of artificial demineralized enamels at different stages were analyzed and the results show the possibility to detect the dental demineralization using Mueller matrix imaging method.

Binary image encryption in a joint transform correlator scheme by aid of run-length encoding and QR code

NASA Astrophysics Data System (ADS)

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

2018-07-01

We propose a binary image encryption method in joint transform correlator (JTC) by aid of the run-length encoding (RLE) and Quick Response (QR) code, which enables lossless retrieval of the primary image. The binary image is encoded with RLE to obtain the highly compressed data, and then the compressed binary image is further scrambled using a chaos-based method. The compressed and scrambled binary image is then transformed into one QR code that will be finally encrypted in JTC. The proposed method successfully, for the first time to our best knowledge, encodes a binary image into a QR code with the identical size of it, and therefore may probe a new way for extending the application of QR code in optical security. Moreover, the preprocessing operations, including RLE, chaos scrambling and the QR code translation, append an additional security level on JTC. We present digital results that confirm our approach.

A quality quantitative method of silicon direct bonding based on wavelet image analysis

NASA Astrophysics Data System (ADS)

Tan, Xiao; Tao, Zhi; Li, Haiwang; Xu, Tiantong; Yu, Mingxing

2018-04-01

The rapid development of MEMS (micro-electro-mechanical systems) has received significant attention from researchers in various fields and subjects. In particular, the MEMS fabrication process is elaborate and, as such, has been the focus of extensive research inquiries. However, in MEMS fabrication, component bonding is difficult to achieve and requires a complex approach. Thus, improvements in bonding quality are relatively important objectives. A higher quality bond can only be achieved with improved measurement and testing capabilities. In particular, the traditional testing methods mainly include infrared testing, tensile testing, and strength testing, despite the fact that using these methods to measure bond quality often results in low efficiency or destructive analysis. Therefore, this paper focuses on the development of a precise, nondestructive visual testing method based on wavelet image analysis that is shown to be highly effective in practice. The process of wavelet image analysis includes wavelet image denoising, wavelet image enhancement, and contrast enhancement, and as an end result, can display an image with low background noise. In addition, because the wavelet analysis software was developed with MATLAB, it can reveal the bonding boundaries and bonding rates to precisely indicate the bond quality at all locations on the wafer. This work also presents a set of orthogonal experiments that consist of three prebonding factors, the prebonding temperature, the positive pressure value and the prebonding time, which are used to analyze the prebonding quality. This method was used to quantify the quality of silicon-to-silicon wafer bonding, yielding standard treatment quantities that could be practical for large-scale use.

A marker-based watershed method for X-ray image segmentation.

PubMed

Zhang, Xiaodong; Jia, Fucang; Luo, Suhuai; Liu, Guiying; Hu, Qingmao

2014-03-01

Digital X-ray images are the most frequent modality for both screening and diagnosis in hospitals. To facilitate subsequent analysis such as quantification and computer aided diagnosis (CAD), it is desirable to exclude image background. A marker-based watershed segmentation method was proposed to segment background of X-ray images. The method consisted of six modules: image preprocessing, gradient computation, marker extraction, watershed segmentation from markers, region merging and background extraction. One hundred clinical direct radiograph X-ray images were used to validate the method. Manual thresholding and multiscale gradient based watershed method were implemented for comparison. The proposed method yielded a dice coefficient of 0.964±0.069, which was better than that of the manual thresholding (0.937±0.119) and that of multiscale gradient based watershed method (0.942±0.098). Special means were adopted to decrease the computational cost, including getting rid of few pixels with highest grayscale via percentile, calculation of gradient magnitude through simple operations, decreasing the number of markers by appropriate thresholding, and merging regions based on simple grayscale statistics. As a result, the processing time was at most 6s even for a 3072×3072 image on a Pentium 4 PC with 2.4GHz CPU (4 cores) and 2G RAM, which was more than one time faster than that of the multiscale gradient based watershed method. The proposed method could be a potential tool for diagnosis and quantification of X-ray images. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Live-cell confocal microscopy and quantitative 4D image analysis of anchor cell invasion through the basement membrane in C. elegans

PubMed Central

Kelley, Laura C.; Wang, Zheng; Hagedorn, Elliott J.; Wang, Lin; Shen, Wanqing; Lei, Shijun; Johnson, Sam A.; Sherwood, David R.

2018-01-01

Cell invasion through basement membrane (BM) barriers is crucial during development, leukocyte trafficking, and for the spread of cancer. Despite its importance in normal and diseased states, the mechanisms that direct invasion are poorly understood, in large part because of the inability to visualize dynamic cell-basement membrane interactions in vivo. This protocol describes multi-channel time-lapse confocal imaging of anchor cell invasion in live C. elegans. Methods presented include outline slide preparation and worm growth synchronization (15 min), mounting (20 min), image acquisition (20-180 min), image processing (20 min), and quantitative analysis (variable timing). Images acquired enable direct measurement of invasive dynamics including invadopodia formation, cell membrane protrusions, and BM removal. This protocol can be combined with genetic analysis, molecular activity probes, and optogenetic approaches to uncover molecular mechanisms underlying cell invasion. These methods can also be readily adapted for real-time analysis of cell migration, basement membrane turnover, and cell membrane dynamics by any worm laboratory. PMID:28880279

Computer-aided diagnosis based on enhancement of degraded fundus photographs.

PubMed

Jin, Kai; Zhou, Mei; Wang, Shaoze; Lou, Lixia; Xu, Yufeng; Ye, Juan; Qian, Dahong

2018-05-01

Retinal imaging is an important and effective tool for detecting retinal diseases. However, degraded images caused by the aberrations of the eye can disguise lesions, so that a diseased eye can be mistakenly diagnosed as normal. In this work, we propose a new image enhancement method to improve the quality of degraded images. A new method is used to enhance degraded-quality fundus images. In this method, the image is converted from the input RGB colour space to LAB colour space and then each normalized component is enhanced using contrast-limited adaptive histogram equalization. Human visual system (HVS)-based fundus image quality assessment, combined with diagnosis by experts, is used to evaluate the enhancement. The study included 191 degraded-quality fundus photographs of 143 subjects with optic media opacity. Objective quality assessment of image enhancement (range: 0-1) indicated that our method improved colour retinal image quality from an average of 0.0773 (variance 0.0801) to an average of 0.3973 (variance 0.0756). Following enhancement, area under curves (AUC) were 0.996 for the glaucoma classifier, 0.989 for the diabetic retinopathy (DR) classifier, 0.975 for the age-related macular degeneration (AMD) classifier and 0.979 for the other retinal diseases classifier. The relatively simple method for enhancing degraded-quality fundus images achieves superior image enhancement, as demonstrated in a qualitative HVS-based image quality assessment. This retinal image enhancement may, therefore, be employed to assist ophthalmologists in more efficient screening of retinal diseases and the development of computer-aided diagnosis. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

Evaluation of magnetic nanoparticle samples made from biocompatible ferucarbotran by time-correlation magnetic particle imaging reconstruction method

PubMed Central

2013-01-01

Background Molecular imaging using magnetic nanoparticles (MNPs)—magnetic particle imaging (MPI)—has attracted interest for the early diagnosis of cancer and cardiovascular disease. However, because a steep local magnetic field distribution is required to obtain a defined image, sophisticated hardware is required. Therefore, it is desirable to realize excellent image quality even with low-performance hardware. In this study, the spatial resolution of MPI was evaluated using an image reconstruction method based on the correlation information of the magnetization signal in a time domain and by applying MNP samples made from biocompatible ferucarbotran that have adjusted particle diameters. Methods The magnetization characteristics and particle diameters of four types of MNP samples made from ferucarbotran were evaluated. A numerical analysis based on our proposed method that calculates the image intensity from correlation information between the magnetization signal generated from MNPs and the system function was attempted, and the obtained image quality was compared with that using the prototype in terms of image resolution and image artifacts. Results MNP samples obtained by adjusting ferucarbotran showed superior properties to conventional ferucarbotran samples, and numerical analysis showed that the same image quality could be obtained using a gradient magnetic field generator with 0.6 times the performance. However, because image blurring was included theoretically by the proposed method, an algorithm will be required to improve performance. Conclusions MNP samples obtained by adjusting ferucarbotran showed magnetizing properties superior to conventional ferucarbotran samples, and by using such samples, comparable image quality (spatial resolution) could be obtained with a lower gradient magnetic field intensity. PMID:23734917

Image enhancement by holography.

NASA Technical Reports Server (NTRS)

Stroke, G. W.

1973-01-01

The speed of the holographic image deblurring method has recently been further enhanced by a new speed in the realization of the powerful holographic image-deblurring filter. The filter makes it possible to carry out the deblurring, in the optical computer used, in times of the order of one second. The experimental achievements using the holographic image-enhancement method are illustrated with examples ranging from out-of-focus or motion-blurred photographs, including 'amateur' photos recorded on Polaroid film, to the sharpening of the best available electron micrographs of viruses. Images recorded with X-rays, notably from rocket-borne photos of the sun, and out-of-focus photographs from cameras in NASA satellites have been similarly deblurred.

Beam imaging sensor and method for using same

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

McAninch, Michael D.; Root, Jeffrey J.

The present invention relates generally to the field of sensors for beam imaging and, in particular, to a new and useful beam imaging sensor for use in determining, for example, the power density distribution of a beam including, but not limited to, an electron beam or an ion beam. In one embodiment, the beam imaging sensor of the present invention comprises, among other items, a circumferential slit that is either circular, elliptical or polygonal in nature. In another embodiment, the beam imaging sensor of the present invention comprises, among other things, a discontinuous partially circumferential slit. Also disclosed is amore » method for using the various beams sensor embodiments of the present invention.« less

Incoherent Diffractive Imaging via Intensity Correlations of Hard X Rays

NASA Astrophysics Data System (ADS)

Classen, Anton; Ayyer, Kartik; Chapman, Henry N.; Röhlsberger, Ralf; von Zanthier, Joachim

2017-08-01

Established x-ray diffraction methods allow for high-resolution structure determination of crystals, crystallized protein structures, or even single molecules. While these techniques rely on coherent scattering, incoherent processes like fluorescence emission—often the predominant scattering mechanism—are generally considered detrimental for imaging applications. Here, we show that intensity correlations of incoherently scattered x-ray radiation can be used to image the full 3D arrangement of the scattering atoms with significantly higher resolution compared to conventional coherent diffraction imaging and crystallography, including additional three-dimensional information in Fourier space for a single sample orientation. We present a number of properties of incoherent diffractive imaging that are conceptually superior to those of coherent methods.

A review of optimization and quantification techniques for chemical exchange saturation transfer (CEST) MRI toward sensitive in vivo imaging

PubMed Central

Guo, Yingkun; Zheng, Hairong; Sun, Phillip Zhe

2015-01-01

Chemical exchange saturation transfer (CEST) MRI is a versatile imaging method that probes the chemical exchange between bulk water and exchangeable protons. CEST imaging indirectly detects dilute labile protons via bulk water signal changes following selective saturation of exchangeable protons, which offers substantial sensitivity enhancement and has sparked numerous biomedical applications. Over the past decade, CEST imaging techniques have rapidly evolved due to contributions from multiple domains, including the development of CEST mathematical models, innovative contrast agent designs, sensitive data acquisition schemes, efficient field inhomogeneity correction algorithms, and quantitative CEST (qCEST) analysis. The CEST system that underlies the apparent CEST-weighted effect, however, is complex. The experimentally measurable CEST effect depends not only on parameters such as CEST agent concentration, pH and temperature, but also on relaxation rate, magnetic field strength and more importantly, experimental parameters including repetition time, RF irradiation amplitude and scheme, and image readout. Thorough understanding of the underlying CEST system using qCEST analysis may augment the diagnostic capability of conventional imaging. In this review, we provide a concise explanation of CEST acquisition methods and processing algorithms, including their advantages and limitations, for optimization and quantification of CEST MRI experiments. PMID:25641791

Advances in interpretation of subsurface processes with time-lapse electrical imaging

USGS Publications Warehouse

Singha, Kaminit; Day-Lewis, Frederick D.; Johnson, Tim B.; Slater, Lee D.

2015-01-01

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

Advances in interpretation of subsurface processes with time-lapse electrical imaging

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

Singha, Kamini; Day-Lewis, Frederick D.; Johnson, Timothy C.

2015-03-15

Electrical geophysical methods, including electrical resistivity, time-domain induced polarization, and complex resistivity, have become commonly used to image the near subsurface. Here, we outline their utility for time-lapse imaging of hydrological, geochemical, and biogeochemical processes, focusing on new instrumentation, processing, and analysis techniques specific to monitoring. We review data collection procedures, parameters measured, and petrophysical relationships and then outline the state of the science with respect to inversion methodologies, including coupled inversion. We conclude by highlighting recent research focused on innovative applications of time-lapse imaging in hydrology, biology, ecology, and geochemistry, among other areas of interest.

Device and Method of Scintillating Quantum Dots for Radiation Imaging

NASA Technical Reports Server (NTRS)

Burke, Eric R. (Inventor); DeHaven, Stanton L. (Inventor); Williams, Phillip A. (Inventor)

2017-01-01

A radiation imaging device includes a radiation source and a micro structured detector comprising a material defining a surface that faces the radiation source. The material includes a plurality of discreet cavities having openings in the surface. The detector also includes a plurality of quantum dots disclosed in the cavities. The quantum dots are configured to interact with radiation from the radiation source, and to emit visible photons that indicate the presence of radiation. A digital camera and optics may be used to capture images formed by the detector in response to exposure to radiation.

Motion estimation of subcellular structures from fluorescence microscopy images.

PubMed

Vallmitjana, A; Civera-Tregon, A; Hoenicka, J; Palau, F; Benitez, R

2017-07-01

We present an automatic image processing framework to study moving intracellular structures from live cell fluorescence microscopy. The system includes the identification of static and dynamic structures from time-lapse images using data clustering as well as the identification of the trajectory of moving objects with a probabilistic tracking algorithm. The method has been successfully applied to study mitochondrial movement in neurons. The approach provides excellent performance under different experimental conditions and is robust to common sources of noise including experimental, molecular and biological fluctuations.

Whole surface image reconstruction for machine vision inspection of fruit

NASA Astrophysics Data System (ADS)

Reese, D. Y.; Lefcourt, A. M.; Kim, M. S.; Lo, Y. M.

2007-09-01

Automated imaging systems offer the potential to inspect the quality and safety of fruits and vegetables consumed by the public. Current automated inspection systems allow fruit such as apples to be sorted for quality issues including color and size by looking at a portion of the surface of each fruit. However, to inspect for defects and contamination, the whole surface of each fruit must be imaged. The goal of this project was to develop an effective and economical method for whole surface imaging of apples using mirrors and a single camera. Challenges include mapping the concave stem and calyx regions. To allow the entire surface of an apple to be imaged, apples were suspended or rolled above the mirrors using two parallel music wires. A camera above the apples captured 90 images per sec (640 by 480 pixels). Single or multiple flat or concave mirrors were mounted around the apple in various configurations to maximize surface imaging. Data suggest that the use of two flat mirrors provides inadequate coverage of a fruit but using two parabolic concave mirrors allows the entire surface to be mapped. Parabolic concave mirrors magnify images, which results in greater pixel resolution and reduced distortion. This result suggests that a single camera with two parabolic concave mirrors can be a cost-effective method for whole surface imaging.

Image compression system and method having optimized quantization tables

NASA Technical Reports Server (NTRS)

Ratnakar, Viresh (Inventor); Livny, Miron (Inventor)

1998-01-01

A digital image compression preprocessor for use in a discrete cosine transform-based digital image compression device is provided. The preprocessor includes a gathering mechanism for determining discrete cosine transform statistics from input digital image data. A computing mechanism is operatively coupled to the gathering mechanism to calculate a image distortion array and a rate of image compression array based upon the discrete cosine transform statistics for each possible quantization value. A dynamic programming mechanism is operatively coupled to the computing mechanism to optimize the rate of image compression array against the image distortion array such that a rate-distortion-optimal quantization table is derived. In addition, a discrete cosine transform-based digital image compression device and a discrete cosine transform-based digital image compression and decompression system are provided. Also, a method for generating a rate-distortion-optimal quantization table, using discrete cosine transform-based digital image compression, and operating a discrete cosine transform-based digital image compression and decompression system are provided.

A Review on Medical Image Registration as an Optimization Problem

PubMed Central

Song, Guoli; Han, Jianda; Zhao, Yiwen; Wang, Zheng; Du, Huibin

2017-01-01

Objective: In the course of clinical treatment, several medical media are required by a phy-sician in order to provide accurate and complete information about a patient. Medical image registra-tion techniques can provide a richer diagnosis and treatment information to doctors and to provide a comprehensive reference source for the researchers involved in image registration as an optimization problem. Methods: The essence of image registration is associating two or more different images spatial asso-ciation, and getting the translation of their spatial relationship. For medical image registration, its pro-cess is not absolute. Its core purpose is finding the conversion relationship between different images. Result: The major step of image registration includes the change of geometrical dimensions, and change of the image of the combination, image similarity measure, iterative optimization and interpo-lation process. Conclusion: The contribution of this review is sort of related image registration research methods, can provide a brief reference for researchers about image registration. PMID:28845149

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

PubMed Central

Ashman, Amy M.; Collins, Clare E.; Brown, Leanne J.; Rae, Kym M.; Rollo, Megan E.

2017-01-01

Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application) of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete), median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber (r = 0.58–0.84, all p < 0.05), and for micronutrients both including (r = 0.47–0.94, all p < 0.05) and excluding (r = 0.40–0.85, all p < 0.05) supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women. PMID:28106758

Segmentation of humeral head from axial proton density weighted shoulder MR images

NASA Astrophysics Data System (ADS)

Sezer, Aysun; Sezer, Hasan Basri; Albayrak, Songul

2015-01-01

The purpose of this study is to determine the effectiveness of segmentation of axial MR proton density (PD) images of bony humeral head. PD sequence images which are included in standard shoulder MRI protocol are used instead of T1 MR images. Bony structures were reported to be successfully segmented in the literature from T1 MR images. T1 MR images give more sharp determination of bone and soft tissue border but cannot address the pathological process which takes place in the bone. In the clinical settings PD images of shoulder are used to investigate soft tissue alterations which can cause shoulder instability and are better in demonstrating edema and the pathology but have a higher noise ratio than other modalities. Moreover the alteration of humeral head intensity in patients and soft tissues in contact with the humeral head which have the very similar intensities with bone makes the humeral head segmentation a challenging problem in PD images. However segmentation of the bony humeral head is required initially to facilitate the segmentation of the soft tissues of shoulder. In this study shoulder MRI of 33 randomly selected patients were included. Speckle reducing anisotropic diffusion (SRAD) method was used to decrease noise and then Active Contour Without Edge (ACWE) and Signed Pressure Force (SPF) models were applied on our data set. Success of these methods is determined by comparing our results with manually segmented images by an expert. Applications of these methods on PD images provide highly successful results for segmentation of bony humeral head. This is the first study to determine bone contours in PD images in literature.

Social image quality

NASA Astrophysics Data System (ADS)

Qiu, Guoping; Kheiri, Ahmed

2011-01-01

Current subjective image quality assessments have been developed in the laboratory environments, under controlledconditions, and are dependent on the participation of limited numbers of observers. In this research, with the help of Web 2.0 and social media technology, a new method for building a subjective image quality metric has been developed where the observers are the Internet users. A website with a simple user interface that enables Internet users from anywhere at any time to vote for a better quality version of a pair of the same image has been constructed. Users' votes are recorded and used to rank the images according to their perceived visual qualities. We have developed three rank aggregation algorithms to process the recorded pair comparison data, the first uses a naive approach, the second employs a Condorcet method, and the third uses the Dykstra's extension of Bradley-Terry method. The website has been collecting data for about three months and has accumulated over 10,000 votes at the time of writing this paper. Results show that the Internet and its allied technologies such as crowdsourcing offer a promising new paradigm for image and video quality assessment where hundreds of thousands of Internet users can contribute to building more robust image quality metrics. We have made Internet user generated social image quality (SIQ) data of a public image database available online (http://www.hdri.cs.nott.ac.uk/siq/) to provide the image quality research community with a new source of ground truth data. The website continues to collect votes and will include more public image databases and will also be extended to include videos to collect social video quality (SVQ) data. All data will be public available on the website in due course.

Quantitative Image Recovery From Measured Blind Backscattered Data Using a Globally Convergent Inverse Method

DTIC Science & Technology

2012-01-01

research interests include in- 794 verse problems related to superresolution imaging and metamaterial design. 795 Dr. Fiddy is a Fellow of the Optical...verse problems related to superresolution imaging and metamaterial design. 795 Dr. Fiddy is a Fellow of the Optical Society of America, the IOP, and The

Solid-state NMR imaging system

DOEpatents

Gopalsami, Nachappa; Dieckman, Stephen L.; Ellingson, William A.

1992-01-01

An apparatus for use with a solid-state NMR spectrometer includes a special imaging probe with linear, high-field strength gradient fields and high-power broadband RF coils using a back projection method for data acquisition and image reconstruction, and a real-time pulse programmer adaptable for use by a conventional computer for complex high speed pulse sequences.

Digital holographic 3D imaging spectrometry (a review)

NASA Astrophysics Data System (ADS)

Yoshimori, Kyu

2017-09-01

This paper reviews recent progress in the digital holographic 3D imaging spectrometry. The principle of this method is a marriage of incoherent holography and Fourier transform spectroscopy. Review includes principle, procedure of signal processing and experimental results to obtain a multispectral set of 3D images for spatially incoherent, polychromatic objects.

Quantitative cardiac SPECT reconstruction with reduced image degradation due to patient anatomy

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

Tsui, B.M.W.; Zhao, X.D.; Gregoriou, G.K.

1994-12-01

Patient anatomy has complicated effects on cardiac SPECT images. The authors investigated reconstruction methods which substantially reduced these effects for improved image quality. A 3D mathematical cardiac-torso (MCAT) phantom which models the anatomical structures in the thorax region were used in the study. The phantom was modified to simulate variations in patient anatomy including regions of natural thinning along the myocardium, body size, diaphragmatic shape, gender, and size and shape of breasts for female patients. Distributions of attenuation coefficients and Tl-201 uptake in different organs in a normal patient were also simulated. Emission projection data were generated from the phantomsmore » including effects of attenuation and detector response. The authors have observed the attenuation-induced artifacts caused by patient anatomy in the conventional FBP reconstructed images. Accurate attenuation compensation using iterative reconstruction algorithms and attenuation maps substantially reduced the image artifacts and improved quantitative accuracy. They conclude that reconstruction methods which accurately compensate for non-uniform attenuation can substantially reduce image degradation caused by variations in patient anatomy in cardiac SPECT.« less

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.

Review of optical breast imaging and spectroscopy

NASA Astrophysics Data System (ADS)

Grosenick, Dirk; Rinneberg, Herbert; Cubeddu, Rinaldo; Taroni, Paola

2016-09-01

Diffuse optical imaging and spectroscopy of the female breast is an area of active research. We review the present status of this field and discuss the broad range of methodologies and applications. Starting with a brief overview on breast physiology, the remodeling of vasculature and extracellular matrix caused by solid tumors is highlighted that is relevant for contrast in optical imaging. Then, the various instrumental techniques and the related methods of data analysis and image generation are described and compared including multimodality instrumentation, fluorescence mammography, broadband spectroscopy, and diffuse correlation spectroscopy. We review the clinical results on functional properties of malignant and benign breast lesions compared to host tissue and discuss the various methods to improve contrast between healthy and diseased tissue, such as enhanced spectroscopic information, dynamic variations of functional properties, pharmacokinetics of extrinsic contrast agents, including the enhanced permeability and retention effect. We discuss research on monitoring neoadjuvant chemotherapy and on breast cancer risk assessment as potential clinical applications of optical breast imaging and spectroscopy. Moreover, we consider new experimental approaches, such as photoacoustic imaging and long-wavelength tissue spectroscopy.

Particle Morphology Analysis of Biomass Material Based on Improved Image Processing Method

PubMed Central

Lu, Zhaolin

2017-01-01

Particle morphology, including size and shape, is an important factor that significantly influences the physical and chemical properties of biomass material. Based on image processing technology, a method was developed to process sample images, measure particle dimensions, and analyse the particle size and shape distributions of knife-milled wheat straw, which had been preclassified into five nominal size groups using mechanical sieving approach. Considering the great variation of particle size from micrometer to millimeter, the powders greater than 250 μm were photographed by a flatbed scanner without zoom function, and the others were photographed using a scanning electron microscopy (SEM) with high-image resolution. Actual imaging tests confirmed the excellent effect of backscattered electron (BSE) imaging mode of SEM. Particle aggregation is an important factor that affects the recognition accuracy of the image processing method. In sample preparation, the singulated arrangement and ultrasonic dispersion methods were used to separate powders into particles that were larger and smaller than the nominal size of 250 μm. In addition, an image segmentation algorithm based on particle geometrical information was proposed to recognise the finer clustered powders. Experimental results demonstrated that the improved image processing method was suitable to analyse the particle size and shape distributions of ground biomass materials and solve the size inconsistencies in sieving analysis. PMID:28298925

Skin cancer texture analysis of OCT images based on Haralick, fractal dimension and the complex directional field features

NASA Astrophysics Data System (ADS)

Raupov, Dmitry S.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Kornilin, Dmitry V.; Zakharov, Valery P.; Khramov, Alexander G.

2016-04-01

Optical coherence tomography (OCT) is usually employed for the measurement of tumor topology, which reflects structural changes of a tissue. We investigated the possibility of OCT in detecting changes using a computer texture analysis method based on Haralick texture features, fractal dimension and the complex directional field method from different tissues. These features were used to identify special spatial characteristics, which differ healthy tissue from various skin cancers in cross-section OCT images (B-scans). Speckle reduction is an important pre-processing stage for OCT image processing. In this paper, an interval type-II fuzzy anisotropic diffusion algorithm for speckle noise reduction in OCT images was used. The Haralick texture feature set includes contrast, correlation, energy, and homogeneity evaluated in different directions. A box-counting method is applied to compute fractal dimension of investigated tissues. Additionally, we used the complex directional field calculated by the local gradient methodology to increase of the assessment quality of the diagnosis method. The complex directional field (as well as the "classical" directional field) can help describe an image as set of directions. Considering to a fact that malignant tissue grows anisotropically, some principal grooves may be observed on dermoscopic images, which mean possible existence of principal directions on OCT images. Our results suggest that described texture features may provide useful information to differentiate pathological from healthy patients. The problem of recognition melanoma from nevi is decided in this work due to the big quantity of experimental data (143 OCT-images include tumors as Basal Cell Carcinoma (BCC), Malignant Melanoma (MM) and Nevi). We have sensitivity about 90% and specificity about 85%. Further research is warranted to determine how this approach may be used to select the regions of interest automatically.

A phantom design for assessment of detectability in PET imaging

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

Wollenweber, Scott D., E-mail: scott.wollenweber@g

2016-09-15

Purpose: The primary clinical role of positron emission tomography (PET) imaging is the detection of anomalous regions of {sup 18}F-FDG uptake, which are often indicative of malignant lesions. The goal of this work was to create a task-configurable fillable phantom for realistic measurements of detectability in PET imaging. Design goals included simplicity, adjustable feature size, realistic size and contrast levels, and inclusion of a lumpy (i.e., heterogeneous) background. Methods: The detection targets were hollow 3D-printed dodecahedral nylon features. The exostructure sphere-like features created voids in a background of small, solid non-porous plastic (acrylic) spheres inside a fillable tank. The featuresmore » filled at full concentration while the background concentration was reduced due to filling only between the solid spheres. Results: Multiple iterations of feature size and phantom construction were used to determine a configuration at the limit of detectability for a PET/CT system. A full-scale design used a 20 cm uniform cylinder (head-size) filled with a fixed pattern of features at a contrast of approximately 3:1. Known signal-present and signal-absent PET sub-images were extracted from multiple scans of the same phantom and with detectability in a challenging (i.e., useful) range. These images enabled calculation and comparison of the quantitative observer detectability metrics between scanner designs and image reconstruction methods. The phantom design has several advantages including filling simplicity, wall-less contrast features, the control of the detectability range via feature size, and a clinically realistic lumpy background. Conclusions: This phantom provides a practical method for testing and comparison of lesion detectability as a function of imaging system, acquisition parameters, and image reconstruction methods and parameters.« less

Design and Implementation of a Self-Directed Stereochemistry Lesson Using Embedded Virtual Three-Dimensional Images in a Portable Document Format

ERIC Educational Resources Information Center

Cody, Jeremy A.; Craig, Paul A.; Loudermilk, Adam D.; Yacci, Paul M.; Frisco, Sarah L.; Milillo, Jennifer R.

2012-01-01

A novel stereochemistry lesson was prepared that incorporated both handheld molecular models and embedded virtual three-dimensional (3D) images. The images are fully interactive and eye-catching for the students; methods for preparing 3D molecular images in Adobe Acrobat are included. The lesson was designed and implemented to showcase the 3D…

Method and apparatus for providing a seamless tiled display

NASA Technical Reports Server (NTRS)

Dubin, Matthew B. (Inventor); Johnson, Michael J. (Inventor)

2002-01-01

A display for producing a seamless composite image from at least two discrete images. The display includes one or more projectors for projecting each of the discrete images separately onto a screen such that at least one of the discrete images overlaps at least one other of the discrete images by more than 25 percent. The amount of overlap that is required to reduce the seams of the composite image to an acceptable level over a predetermined viewing angle depends on a number of factors including the field-of-view and aperture size of the projectors, the screen gain profile, etc. For rear-projection screens and some front projection screens, an overlap of more than 25 percent is acceptable.

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

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

Transformations based on continuous piecewise-affine velocity fields

DOE PAGES

Freifeld, Oren; Hauberg, Soren; Batmanghelich, Kayhan; ...

2017-01-11

Here, we propose novel finite-dimensional spaces of well-behaved Rn → Rn transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volume preservation and/or boundary conditions), and supports convenient modeling choices such as smoothing priors and coarse-to-fine analysis. Importantly, the proposed approach, partly due to its rapid likelihood evaluations and partly due to its other properties, facilitates tractable inference over rich transformation spaces, including using Markov-Chain Monte-Carlo methods. Its applications include, but are not limited to: monotonic regression (more generally, optimization overmore » monotonic functions); modeling cumulative distribution functions or histograms; time-warping; image warping; image registration; real-time diffeomorphic image editing; data augmentation for image classifiers. Our GPU-based code is publicly available.« less

Transformations Based on Continuous Piecewise-Affine Velocity Fields

PubMed Central

Freifeld, Oren; Hauberg, Søren; Batmanghelich, Kayhan; Fisher, Jonn W.

2018-01-01

We propose novel finite-dimensional spaces of well-behaved ℝn → ℝn transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volume preservation and/or boundary conditions), and supports convenient modeling choices such as smoothing priors and coarse-to-fine analysis. Importantly, the proposed approach, partly due to its rapid likelihood evaluations and partly due to its other properties, facilitates tractable inference over rich transformation spaces, including using Markov-Chain Monte-Carlo methods. Its applications include, but are not limited to: monotonic regression (more generally, optimization over monotonic functions); modeling cumulative distribution functions or histograms; time-warping; image warping; image registration; real-time diffeomorphic image editing; data augmentation for image classifiers. Our GPU-based code is publicly available. PMID:28092517

Extraction of latent images from printed media

NASA Astrophysics Data System (ADS)

Sergeyev, Vladislav; Fedoseev, Victor

2015-12-01

In this paper we propose an automatic technology for extraction of latent images from printed media such as documents, banknotes, financial securities, etc. This technology includes image processing by adaptively constructed Gabor filter bank for obtaining feature images, as well as subsequent stages of feature selection, grouping and multicomponent segmentation. The main advantage of the proposed technique is versatility: it allows to extract latent images made by different texture variations. Experimental results showing performance of the method over another known system for latent image extraction are given.

[Fundus Autofluorescence Imaging].

PubMed

Schmitz-Valckenberg, S

2015-09-01

Fundus autofluorescence (FAF) imaging allows for non-invasive mapping of changes at the level of the retinal pigment epithelium/photoreceptor complex and of alterations of macular pigment distribution. This imaging method is based on the visualisation of intrinsic fluorophores and may be easily and rapidly used in routine patient care. Main applications include degenerative disorders of the outer retina such as age-related macular degeneration, hereditary and acquired retinal diseases. FAF imaging is particularly helpful for differential diagnosis, detection and extent of involved retinal areas, structural-functional correlations and monitoring of changes over time. Recent developments include - in addition to the original application of short wavelength light for excitation ("blue" FAF imaging) - the use of other wavelength ranges ("green" or "near-infrared" FAF imaging), widefield imaging for visualisation of peripheral retinal areas and quantitative FAF imaging. Georg Thieme Verlag KG Stuttgart · New York.

The detective quantum efficiency of photon-counting x-ray detectors using cascaded-systems analyses

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

Tanguay, Jesse; Yun, Seungman; School of Mechanical Engineering, Pusan National University, Jangjeon-dong, Geumjeong-gu, Busan 609-735

Purpose: Single-photon counting (SPC) x-ray imaging has the potential to improve image quality and enable new advanced energy-dependent methods. The purpose of this study is to extend cascaded-systems analyses (CSA) to the description of image quality and the detective quantum efficiency (DQE) of SPC systems. Methods: Point-process theory is used to develop a method of propagating the mean signal and Wiener noise-power spectrum through a thresholding stage (required to identify x-ray interaction events). The new transfer relationships are used to describe the zero-frequency DQE of a hypothetical SPC detector including the effects of stochastic conversion of incident photons to secondarymore » quanta, secondary quantum sinks, additive noise, and threshold level. Theoretical results are compared with Monte Carlo calculations assuming the same detector model. Results: Under certain conditions, the CSA approach can be applied to SPC systems with the additional requirement of propagating the probability density function describing the total number of image-forming quanta through each stage of a cascaded model. Theoretical results including DQE show excellent agreement with Monte Carlo calculations under all conditions considered. Conclusions: Application of the CSA method shows that false counts due to additive electronic noise results in both a nonlinear image signal and increased image noise. There is a window of allowable threshold values to achieve a high DQE that depends on conversion gain, secondary quantum sinks, and additive noise.« less

A comparative study on preprocessing techniques in diabetic retinopathy retinal images: illumination correction and contrast enhancement.

PubMed

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation.

A method for mandibular dental arch superimposition using 3D cone beam CT and orthodontic 3D digital model

PubMed Central

Park, Tae-Joon; Lee, Sang-Hyun

2012-01-01

Objective The purpose of this study was to develop superimposition method on the lower arch using 3-dimensional (3D) cone beam computed tomography (CBCT) images and orthodontic 3D digital modeling. Methods Integrated 3D CBCT images were acquired by substituting the dental portion of 3D CBCT images with precise dental images of an orthodontic 3D digital model. Images were acquired before and after treatment. For the superimposition, 2 superimposition methods were designed. Surface superimposition was based on the basal bone structure of the mandible by surface-to-surface matching (best-fit method). Plane superimposition was based on anatomical structures (mental and lingual foramen). For the evaluation, 10 landmarks including teeth and anatomic structures were assigned, and 30 times of superimpositions and measurements were performed to determine the more reproducible and reliable method. Results All landmarks demonstrated that the surface superimposition method produced relatively more consistent coordinate values. The mean distances of measured landmarks values from the means were statistically significantly lower with the surface superimpositions method. Conclusions Between the 2 superimposition methods designed for the evaluation of 3D changes in the lower arch, surface superimposition was the simpler, more reproducible, reliable method. PMID:23112948

Methods for magnetic resonance analysis using magic angle technique

DOEpatents

Hu, Jian Zhi [Richland, WA; Wind, Robert A [Kennewick, WA; Minard, Kevin R [Kennewick, WA; Majors, Paul D [Kennewick, WA

2011-11-22

Methods of performing a magnetic resonance analysis of a biological object are disclosed that include placing the object in a main magnetic field (that has a static field direction) and in a radio frequency field; rotating the object at a frequency of less than about 100 Hz around an axis positioned at an angle of about 54.degree.44' relative to the main magnetic static field direction; pulsing the radio frequency to provide a sequence that includes a phase-corrected magic angle turning pulse segment; and collecting data generated by the pulsed radio frequency. In particular embodiments the method includes pulsing the radio frequency to provide at least two of a spatially selective read pulse, a spatially selective phase pulse, and a spatially selective storage pulse. Further disclosed methods provide pulse sequences that provide extended imaging capabilities, such as chemical shift imaging or multiple-voxel data acquisition.

System and method for investigating sub-surface features and 3D imaging of non-linear property, compressional velocity VP, shear velocity VS and velocity ratio VP/VS of a rock formation

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

Vu, Cung Khac; Skelt, Christopher; Nihei, Kurt

A system and a method for generating a three-dimensional image of a rock formation, compressional velocity VP, shear velocity VS and velocity ratio VP/VS of a rock formation are provided. A first acoustic signal includes a first plurality of pulses. A second acoustic signal from a second source includes a second plurality of pulses. A detected signal returning to the borehole includes a signal generated by a non-linear mixing process from the first and second acoustic signals in a non-linear mixing zone within an intersection volume. The received signal is processed to extract the signal over noise and/or signals resultingmore » from linear interaction and the three dimensional image of is generated.« less

"Tools For Analysis and Visualization of Large Time- Varying CFD Data Sets"

NASA Technical Reports Server (NTRS)

Wilhelms, Jane; vanGelder, Allen

1999-01-01

During the four years of this grant (including the one year extension), we have explored many aspects of the visualization of large CFD (Computational Fluid Dynamics) datasets. These have included new direct volume rendering approaches, hierarchical methods, volume decimation, error metrics, parallelization, hardware texture mapping, and methods for analyzing and comparing images. First, we implemented an extremely general direct volume rendering approach that can be used to render rectilinear, curvilinear, or tetrahedral grids, including overlapping multiple zone grids, and time-varying grids. Next, we developed techniques for associating the sample data with a k-d tree, a simple hierarchial data model to approximate samples in the regions covered by each node of the tree, and an error metric for the accuracy of the model. We also explored a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH (Association for Computing Machinery Special Interest Group on Computer Graphics) '96. In our initial implementation, we automatically image the volume from 32 approximately evenly distributed positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation.

Calcium-based biomaterials for diagnosis, treatment, and theranostics.

PubMed

Qi, Chao; Lin, Jing; Fu, Lian-Hua; Huang, Peng

2018-01-22

Calcium-based (CaXs) biomaterials including calcium phosphates, calcium carbonates, calcium silicate and calcium fluoride have been widely utilized in the biomedical field owing to their excellent biocompatibility and biodegradability. In recent years, CaXs biomaterials have been strategically integrated with imaging contrast agents and therapeutic agents for various molecular imaging modalities including fluorescence imaging, magnetic resonance imaging, ultrasound imaging or multimodal imaging, as well as for various therapeutic approaches including chemotherapy, gene therapy, hyperthermia therapy, photodynamic therapy, radiation therapy, or combination therapy, even imaging-guided therapy. Compared with other inorganic biomaterials such as silica-, carbon-, and gold-based biomaterials, CaXs biomaterials can dissolve into nontoxic ions and participate in the normal metabolism of organisms. Thus, they offer safer clinical solutions for disease theranostics. This review focuses on the state-of-the-art progress in CaXs biomaterials, which covers from their categories, characteristics and preparation methods to their bioapplications including diagnosis, treatment, and theranostics. Moreover, the current trends and key problems as well as the future prospects and challenges of CaXs biomaterials are also discussed at the end.

Automatic and hierarchical segmentation of the human skeleton in CT images.

PubMed

Fu, Yabo; Liu, Shi; Li, Harold; Yang, Deshan

2017-04-07

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.

Automatic and hierarchical segmentation of the human skeleton in CT images

NASA Astrophysics Data System (ADS)

Fu, Yabo; Liu, Shi; Li, H. Harold; Yang, Deshan

2017-04-01

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic vertebrae, and 1.45 mm for pelvis bones.

Modeling 4D Pathological Changes by Leveraging Normative Models

PubMed Central

Wang, Bo; Prastawa, Marcel; Irimia, Andrei; Saha, Avishek; Liu, Wei; Goh, S.Y. Matthew; Vespa, Paul M.; Van Horn, John D.; Gerig, Guido

2016-01-01

With the increasing use of efficient multimodal 3D imaging, clinicians are able to access longitudinal imaging to stage pathological diseases, to monitor the efficacy of therapeutic interventions, or to assess and quantify rehabilitation efforts. Analysis of such four-dimensional (4D) image data presenting pathologies, including disappearing and newly appearing lesions, represents a significant challenge due to the presence of complex spatio-temporal changes. Image analysis methods for such 4D image data have to include not only a concept for joint segmentation of 3D datasets to account for inherent correlations of subject-specific repeated scans but also a mechanism to account for large deformations and the destruction and formation of lesions (e.g., edema, bleeding) due to underlying physiological processes associated with damage, intervention, and recovery. In this paper, we propose a novel framework that provides a joint segmentation-registration framework to tackle the inherent problem of image registration in the presence of objects not present in all images of the time series. Our methodology models 4D changes in pathological anatomy across time and and also provides an explicit mapping of a healthy normative template to a subject’s image data with pathologies. Since atlas-moderated segmentation methods cannot explain appearance and locality pathological structures that are not represented in the template atlas, the new framework provides different options for initialization via a supervised learning approach, iterative semisupervised active learning, and also transfer learning, which results in a fully automatic 4D segmentation method. We demonstrate the effectiveness of our novel approach with synthetic experiments and a 4D multimodal MRI dataset of severe traumatic brain injury (TBI), including validation via comparison to expert segmentations. However, the proposed methodology is generic in regard to different clinical applications requiring quantitative analysis of 4D imaging representing spatio-temporal changes of pathologies. PMID:27818606

Thermal Physical Property-Based Fusion of Geostationary Meteorological Satellite Visible and Infrared Channel Images

PubMed Central

Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei

2014-01-01

Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties. PMID:24919017

Thermal physical property-based fusion of geostationary meteorological satellite visible and infrared channel images.

PubMed

Han, Lei; Shi, Lu; Yang, Yiling; Song, Dalei

2014-06-10

Geostationary meteorological satellite infrared (IR) channel data contain important spectral information for meteorological research and applications, but their spatial resolution is relatively low. The objective of this study is to obtain higher-resolution IR images. One common method of increasing resolution fuses the IR data with high-resolution visible (VIS) channel data. However, most existing image fusion methods focus only on visual performance, and often fail to take into account the thermal physical properties of the IR images. As a result, spectral distortion occurs frequently. To tackle this problem, we propose a thermal physical properties-based correction method for fusing geostationary meteorological satellite IR and VIS images. In our two-step process, the high-resolution structural features of the VIS image are first extracted and incorporated into the IR image using regular multi-resolution fusion approach, such as the multiwavelet analysis. This step significantly increases the visual details in the IR image, but fake thermal information may be included. Next, the Stefan-Boltzmann Law is applied to correct the distortion, to retain or recover the thermal infrared nature of the fused image. The results of both the qualitative and quantitative evaluation demonstrate that the proposed physical correction method both improves the spatial resolution and preserves the infrared thermal properties.

Three-dimensional registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation.

PubMed

Prabhu, David; Mehanna, Emile; Gargesha, Madhusudhana; Brandt, Eric; Wen, Di; van Ditzhuijzen, Nienke S; Chamie, Daniel; Yamamoto, Hirosada; Fujino, Yusuke; Alian, Ali; Patel, Jaymin; Costa, Marco; Bezerra, Hiram G; Wilson, David L

2016-04-01

Evidence suggests high-resolution, high-contrast, [Formula: see text] intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and three-dimensional (3-D) registration methods to provide validation of IVOCT pullback volumes using microscopic, color, and fluorescent cryo-image volumes with optional registered cryo-histology. A specialized registration method matched IVOCT pullback images acquired in the catheter reference frame to a true 3-D cryo-image volume. Briefly, an 11-parameter registration model including a polynomial virtual catheter was initialized within the cryo-image volume, and perpendicular images were extracted, mimicking IVOCT image acquisition. Virtual catheter parameters were optimized to maximize cryo and IVOCT lumen overlap. Multiple assessments suggested that the registration error was better than the [Formula: see text] spacing between IVOCT image frames. Tests on a digital synthetic phantom gave a registration error of only [Formula: see text] (signed distance). Visual assessment of randomly presented nearby frames suggested registration accuracy within 1 IVOCT frame interval ([Formula: see text]). This would eliminate potential misinterpretations confronted by the typical histological approaches to validation, with estimated 1-mm errors. The method can be used to create annotated datasets and automated plaque classification methods and can be extended to other intravascular imaging modalities.

Prosthetic component segmentation with blur compensation: a fast method for 3D fluoroscopy.

PubMed

Tarroni, Giacomo; Tersi, Luca; Corsi, Cristiana; Stagni, Rita

2012-06-01

A new method for prosthetic component segmentation from fluoroscopic images is presented. The hybrid approach we propose combines diffusion filtering, region growing and level-set techniques without exploiting any a priori knowledge of the analyzed geometry. The method was evaluated on a synthetic dataset including 270 images of knee and hip prosthesis merged to real fluoroscopic data simulating different conditions of blurring and illumination gradient. The performance of the method was assessed by comparing estimated contours to references using different metrics. Results showed that the segmentation procedure is fast, accurate, independent on the operator as well as on the specific geometrical characteristics of the prosthetic component, and able to compensate for amount of blurring and illumination gradient. Importantly, the method allows a strong reduction of required user interaction time when compared to traditional segmentation techniques. Its effectiveness and robustness in different image conditions, together with simplicity and fast implementation, make this prosthetic component segmentation procedure promising and suitable for multiple clinical applications including assessment of in vivo joint kinematics in a variety of cases.

Microscopic neural image registration based on the structure of mitochondria

NASA Astrophysics Data System (ADS)

Cao, Huiwen; Han, Hua; Rao, Qiang; Xiao, Chi; Chen, Xi

2017-02-01

Microscopic image registration is a key component of the neural structure reconstruction with serial sections of neural tissue. The goal of microscopic neural image registration is to recover the 3D continuity and geometrical properties of specimen. During image registration, various distortions need to be corrected, including image rotation, translation, tissue deformation et.al, which come from the procedure of sample cutting, staining and imaging. Furthermore, there is only certain similarity between adjacent sections, and the degree of similarity depends on local structure of the tissue and the thickness of the sections. These factors make the microscopic neural image registration a challenging problem. To tackle the difficulty of corresponding landmarks extraction, we introduce a novel image registration method for Scanning Electron Microscopy (SEM) images of serial neural tissue sections based on the structure of mitochondria. The ellipsoidal shape of mitochondria ensures that the same mitochondria has similar shape between adjacent sections, and its characteristic of broad distribution in the neural tissue guarantees that landmarks based on the mitochondria distributed widely in the image. The proposed image registration method contains three parts: landmarks extraction between adjacent sections, corresponding landmarks matching and image deformation based on the correspondences. We demonstrate the performance of our method with SEM images of drosophila brain.

Light field creating and imaging with different order intensity derivatives

NASA Astrophysics Data System (ADS)

Wang, Yu; Jiang, Huan

2014-10-01

Microscopic image restoration and reconstruction is a challenging topic in the image processing and computer vision, which can be widely applied to life science, biology and medicine etc. A microscopic light field creating and three dimensional (3D) reconstruction method is proposed for transparent or partially transparent microscopic samples, which is based on the Taylor expansion theorem and polynomial fitting. Firstly the image stack of the specimen is divided into several groups in an overlapping or non-overlapping way along the optical axis, and the first image of every group is regarded as reference image. Then different order intensity derivatives are calculated using all the images of every group and polynomial fitting method based on the assumption that the structure of the specimen contained by the image stack in a small range along the optical axis are possessed of smooth and linear property. Subsequently, new images located any position from which to reference image the distance is Δz along the optical axis can be generated by means of Taylor expansion theorem and the calculated different order intensity derivatives. Finally, the microscopic specimen can be reconstructed in 3D form using deconvolution technology and all the images including both the observed images and the generated images. The experimental results show the effectiveness and feasibility of our method.

Nanophotonic Image Sensors

PubMed Central

Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R. S.

2016-01-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial‐based THz image sensors, filter‐free nanowire image sensors and nanostructured‐based multispectral image sensors. This novel combination of cutting edge photonics research and well‐developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. PMID:27239941

Empirical gradient threshold technique for automated segmentation across image modalities and cell lines.

PubMed

Chalfoun, J; Majurski, M; Peskin, A; Breen, C; Bajcsy, P; Brady, M

2015-10-01

New microscopy technologies are enabling image acquisition of terabyte-sized data sets consisting of hundreds of thousands of images. In order to retrieve and analyze the biological information in these large data sets, segmentation is needed to detect the regions containing cells or cell colonies. Our work with hundreds of large images (each 21,000×21,000 pixels) requires a segmentation method that: (1) yields high segmentation accuracy, (2) is applicable to multiple cell lines with various densities of cells and cell colonies, and several imaging modalities, (3) can process large data sets in a timely manner, (4) has a low memory footprint and (5) has a small number of user-set parameters that do not require adjustment during the segmentation of large image sets. None of the currently available segmentation methods meet all these requirements. Segmentation based on image gradient thresholding is fast and has a low memory footprint. However, existing techniques that automate the selection of the gradient image threshold do not work across image modalities, multiple cell lines, and a wide range of foreground/background densities (requirement 2) and all failed the requirement for robust parameters that do not require re-adjustment with time (requirement 5). We present a novel and empirically derived image gradient threshold selection method for separating foreground and background pixels in an image that meets all the requirements listed above. We quantify the difference between our approach and existing ones in terms of accuracy, execution speed, memory usage and number of adjustable parameters on a reference data set. This reference data set consists of 501 validation images with manually determined segmentations and image sizes ranging from 0.36 Megapixels to 850 Megapixels. It includes four different cell lines and two image modalities: phase contrast and fluorescent. Our new technique, called Empirical Gradient Threshold (EGT), is derived from this reference data set with a 10-fold cross-validation method. EGT segments cells or colonies with resulting Dice accuracy index measurements above 0.92 for all cross-validation data sets. EGT results has also been visually verified on a much larger data set that includes bright field and Differential Interference Contrast (DIC) images, 16 cell lines and 61 time-sequence data sets, for a total of 17,479 images. This method is implemented as an open-source plugin to ImageJ as well as a standalone executable that can be downloaded from the following link: https://isg.nist.gov/. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Ensemble Sparse Classification of Alzheimer’s Disease

PubMed Central

Liu, Manhua; Zhang, Daoqiang; Shen, Dinggang

2012-01-01

The high-dimensional pattern classification methods, e.g., support vector machines (SVM), have been widely investigated for analysis of structural and functional brain images (such as magnetic resonance imaging (MRI)) to assist the diagnosis of Alzheimer’s disease (AD) including its prodromal stage, i.e., mild cognitive impairment (MCI). Most existing classification methods extract features from neuroimaging data and then construct a single classifier to perform classification. However, due to noise and small sample size of neuroimaging data, it is challenging to train only a global classifier that can be robust enough to achieve good classification performance. In this paper, instead of building a single global classifier, we propose a local patch-based subspace ensemble method which builds multiple individual classifiers based on different subsets of local patches and then combines them for more accurate and robust classification. Specifically, to capture the local spatial consistency, each brain image is partitioned into a number of local patches and a subset of patches is randomly selected from the patch pool to build a weak classifier. Here, the sparse representation-based classification (SRC) method, which has shown effective for classification of image data (e.g., face), is used to construct each weak classifier. Then, multiple weak classifiers are combined to make the final decision. We evaluate our method on 652 subjects (including 198 AD patients, 225 MCI and 229 normal controls) from Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using MR images. The experimental results show that our method achieves an accuracy of 90.8% and an area under the ROC curve (AUC) of 94.86% for AD classification and an accuracy of 87.85% and an AUC of 92.90% for MCI classification, respectively, demonstrating a very promising performance of our method compared with the state-of-the-art methods for AD/MCI classification using MR images. PMID:22270352

Intensity-based dual model method for generation of synthetic CT images from standard T2-weighted MR images - Generalized technique for four different MR scanners.

PubMed

Koivula, Lauri; Kapanen, Mika; Seppälä, Tiina; Collan, Juhani; Dowling, Jason A; Greer, Peter B; Gustafsson, Christian; Gunnlaugsson, Adalsteinn; Olsson, Lars E; Wee, Leonard; Korhonen, Juha

2017-12-01

Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2 w ) MR images of the pelvis. This study developed a generalized dual model HU conversion method to convert standard T2 w MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancer patients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors. For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16 ± 6 HUs (34 HUs) and -46 ± 56 HUs (181 HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6 ± 0.4% (-1.3%). The study provides a generalized method for sCT creation from standard T2 w images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences. Copyright © 2017 Elsevier B.V. All rights reserved.

Microscopy imaging device with advanced imaging properties

DOEpatents

Ghosh, Kunal; Burns, Laurie; El Gamal, Abbas; Schnitzer, Mark J.; Cocker, Eric; Ho, Tatt Wei

2015-11-24

Systems, methods and devices are implemented for microscope imaging solutions. One embodiment of the present disclosure is directed toward an epifluorescence microscope. The microscope includes an image capture circuit including an array of optical sensor. An optical arrangement is configured to direct excitation light of less than about 1 mW to a target object in a field of view of that is at least 0.5 mm.sup.2 and to direct epi-fluorescence emission caused by the excitation light to the array of optical sensors. The optical arrangement and array of optical sensors are each sufficiently close to the target object to provide at least 2.5 .mu.m resolution for an image of the field of view.

Microscopy imaging device with advanced imaging properties

DOEpatents

Ghosh, Kunal; Burns, Laurie; El Gamal, Abbas; Schnitzer, Mark J.; Cocker, Eric; Ho, Tatt Wei

2016-10-25

Systems, methods and devices are implemented for microscope imaging solutions. One embodiment of the present disclosure is directed toward an epifluorescence microscope. The microscope includes an image capture circuit including an array of optical sensor. An optical arrangement is configured to direct excitation light of less than about 1 mW to a target object in a field of view of that is at least 0.5 mm.sup.2 and to direct epi-fluorescence emission caused by the excitation light to the array of optical sensors. The optical arrangement and array of optical sensors are each sufficiently close to the target object to provide at least 2.5 .mu.m resolution for an image of the field of view.

Microscopy imaging device with advanced imaging properties

DOEpatents

Ghosh, Kunal; Burns, Laurie; El Gamal, Abbas; Schnitzer, Mark J.; Cocker, Eric; Ho, Tatt Wei

2016-11-22

Systems, methods and devices are implemented for microscope imaging solutions. One embodiment of the present disclosure is directed toward an epifluorescence microscope. The microscope includes an image capture circuit including an array of optical sensor. An optical arrangement is configured to direct excitation light of less than about 1 mW to a target object in a field of view of that is at least 0.5 mm.sup.2 and to direct epi-fluorescence emission caused by the excitation light to the array of optical sensors. The optical arrangement and array of optical sensors are each sufficiently close to the target object to provide at least 2.5 .mu.m resolution for an image of the field of view.

Microscopy imaging device with advanced imaging properties

DOEpatents

Ghosh, Kunal; Burns, Laurie; El Gamal, Abbas; Schnitzer, Mark J.; Cocker, Eric; Ho, Tatt Wei

2017-04-25

Systems, methods and devices are implemented for microscope imaging solutions. One embodiment of the present disclosure is directed toward an epifluorescence microscope. The microscope includes an image capture circuit including an array of optical sensor. An optical arrangement is configured to direct excitation light of less than about 1 mW to a target object in a field of view of that is at least 0.5 mm.sup.2 and to direct epi-fluorescence emission caused by the excitation light to the array of optical sensors. The optical arrangement and array of optical sensors are each sufficiently close to the target object to provide at least 2.5 .mu.m resolution for an image of the field of view.

Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images

NASA Astrophysics Data System (ADS)

Nemoto, Mitsutaka; Nomura, Yukihiro; Hanaoka, Shohei; Masutani, Yoshitaka; Yoshikawa, Takeharu; Hayashi, Naoto; Yoshioka, Naoki; Ohtomo, Kuni

Anatomical point landmarks as most primitive anatomical knowledge are useful for medical image understanding. In this study, we propose a detection method for anatomical point landmark based on appearance models, which include gray-level statistical variations at point landmarks and their surrounding area. The models are built based on results of Principal Component Analysis (PCA) of sample data sets. In addition, we employed generative learning method by transforming ROI of sample data. In this study, we evaluated our method with 24 data sets of body trunk CT images and obtained 95.8 ± 7.3 % of the average sensitivity in 28 landmarks.

Extraction of membrane structure in eyeball from MR volumes

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Kin, Taichi; Mori, Kensaku

2017-03-01

This paper presents an accurate extraction method of spherical shaped membrane structures in the eyeball from MR volumes. In ophthalmic surgery, operation field is limited to a small region. Patient specific surgical simulation is useful to reduce complications. Understanding of tissue structure in the eyeball of a patient is required to achieve patient specific surgical simulations. Previous extraction methods of tissue structure in the eyeball use optical coherence tomography (OCT) images. Although OCT images have high resolution, imaging regions are limited to very small. Global structure extraction of the eyeball is difficult from OCT images. We propose an extraction method of spherical shaped membrane structures including the sclerotic coat, choroid, and retina. This method is applied to a T2 weighted MR volume of the head region. MR volume can capture tissue structure of whole eyeball. Because we use MR volumes, out method extracts whole membrane structures in the eyeball. We roughly extract membrane structures by applying a sheet structure enhancement filter. The rough extraction result includes parts of the membrane structures. Then, we apply the Hough transform to extract a sphere structure from the voxels set of the rough extraction result. The Hough transform finds a sphere structure from the rough extraction result. An experimental result using a T2 weighted MR volume of the head region showed that the proposed method can extract spherical shaped membrane structures accurately.

Towards standardized assessment of endoscope optical performance: geometric distortion

NASA Astrophysics Data System (ADS)

Wang, Quanzeng; Desai, Viraj N.; Ngo, Ying Z.; Cheng, Wei-Chung; Pfefer, Joshua

2013-12-01

Technological advances in endoscopes, such as capsule, ultrathin and disposable devices, promise significant improvements in safety, clinical effectiveness and patient acceptance. Unfortunately, the industry lacks test methods for preclinical evaluation of key optical performance characteristics (OPCs) of endoscopic devices that are quantitative, objective and well-validated. As a result, it is difficult for researchers and developers to compare image quality and evaluate equivalence to, or improvement upon, prior technologies. While endoscope OPCs include resolution, field of view, and depth of field, among others, our focus in this paper is geometric image distortion. We reviewed specific test methods for distortion and then developed an objective, quantitative test method based on well-defined experimental and data processing steps to evaluate radial distortion in the full field of view of an endoscopic imaging system. Our measurements and analyses showed that a second-degree polynomial equation could well describe the radial distortion curve of a traditional endoscope. The distortion evaluation method was effective for correcting the image and can be used to explain other widely accepted evaluation methods such as picture height distortion. Development of consensus standards based on promising test methods for image quality assessment, such as the method studied here, will facilitate clinical implementation of innovative endoscopic devices.

Relevance of Whitnall's tubercle and auditory meatus in diagnosing exclusions during skull-photo superimposition.

PubMed

Jayaprakash, Paul T; Hashim, Natassha; Yusop, Ridzuan Abd Aziz Mohd

2015-08-01

Video vision mixer based skull-photo superimposition is a popular method for identifying skulls retrieved from unidentified human remains. A report on the reliability of the superimposition method suggested increased failure rates of 17.3 to 32% to exclude and 15 to 20% to include skulls while using related and unrelated face photographs. Such raise in failures prompted an analysis of the methods employed for the research. The protocols adopted for assessing the reliability are seen to vary from those suggested by the practitioners in the field. The former include overlaying the skull- and face-images on the basis of morphology by relying on anthropometric landmarks on the front plane of the face-images and evaluating the goodness of match depending on mix-mode images; the latter consist of orienting the skull considering landmarks on both the eye and ear planes of the face- and skull-images and evaluating the match utilizing images seen in wipe-mode in addition to those in mix-mode. Superimposition of a skull with face-images of five living individuals in two sets of experiments, one following the procedure described for the research on reliability and the other applying the methods suggested by the practitioners has shown that overlaying the images on the basis of morphology depending on the landmarks on the front plane alone and assessing the match in mix-mode fails to exclude the skull. However, orienting the skull relying on the relationship between the anatomical landmarks on the skull- and face-images such as Whitnall's tubercle and exocanthus in the front (eye) plane and the porion and tragus in the rear (ear) plane as well as assessing the match using wipe-mode images enables excluding that skull while superimposing with the same set of face-images. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Localization microscopy of DNA in situ using Vybrant(®) DyeCycle™ Violet fluorescent probe: A new approach to study nuclear nanostructure at single molecule resolution.

PubMed

Żurek-Biesiada, Dominika; Szczurek, Aleksander T; Prakash, Kirti; Mohana, Giriram K; Lee, Hyun-Keun; Roignant, Jean-Yves; Birk, Udo J; Dobrucki, Jurek W; Cremer, Christoph

2016-05-01

Higher order chromatin structure is not only required to compact and spatially arrange long chromatids within a nucleus, but have also important functional roles, including control of gene expression and DNA processing. However, studies of chromatin nanostructures cannot be performed using conventional widefield and confocal microscopy because of the limited optical resolution. Various methods of superresolution microscopy have been described to overcome this difficulty, like structured illumination and single molecule localization microscopy. We report here that the standard DNA dye Vybrant(®) DyeCycle™ Violet can be used to provide single molecule localization microscopy (SMLM) images of DNA in nuclei of fixed mammalian cells. This SMLM method enabled optical isolation and localization of large numbers of DNA-bound molecules, usually in excess of 10(6) signals in one cell nucleus. The technique yielded high-quality images of nuclear DNA density, revealing subdiffraction chromatin structures of the size in the order of 100nm; the interchromatin compartment was visualized at unprecedented optical resolution. The approach offers several advantages over previously described high resolution DNA imaging methods, including high specificity, an ability to record images using a single wavelength excitation, and a higher density of single molecule signals than reported in previous SMLM studies. The method is compatible with DNA/multicolor SMLM imaging which employs simple staining methods suited also for conventional optical microscopy. Copyright © 2016. Published by Elsevier Inc.

Feature-based registration of historical aerial images by Area Minimization

NASA Astrophysics Data System (ADS)

Nagarajan, Sudhagar; Schenk, Toni

2016-06-01

The registration of historical images plays a significant role in assessing changes in land topography over time. By comparing historical aerial images with recent data, geometric changes that have taken place over the years can be quantified. However, the lack of ground control information and precise camera parameters has limited scientists' ability to reliably incorporate historical images into change detection studies. Other limitations include the methods of determining identical points between recent and historical images, which has proven to be a cumbersome task due to continuous land cover changes. Our research demonstrates a method of registering historical images using Time Invariant Line (TIL) features. TIL features are different representations of the same line features in multi-temporal data without explicit point-to-point or straight line-to-straight line correspondence. We successfully determined the exterior orientation of historical images by minimizing the area formed between corresponding TIL features in recent and historical images. We then tested the feasibility of the approach with synthetic and real data and analyzed the results. Based on our analysis, this method shows promise for long-term 3D change detection studies.

Chemical imaging analysis of the brain with X-ray methods

NASA Astrophysics Data System (ADS)

Collingwood, Joanna F.; Adams, Freddy

2017-04-01

Cells employ various metal and metalloid ions to augment the structure and the function of proteins and to assist with vital biological processes. In the brain they mediate biochemical processes, and disrupted metabolism of metals may be a contributing factor in neurodegenerative disorders. In this tutorial review we will discuss the particular role of X-ray methods for elemental imaging analysis of accumulated metal species and metal-containing compounds in biological materials, in the context of post-mortem brain tissue. X-rays have the advantage that they have a short wavelength and can penetrate through a thick biological sample. Many of the X-ray microscopy techniques that provide the greatest sensitivity and specificity for trace metal concentrations in biological materials are emerging at synchrotron X-ray facilities. Here, the extremely high flux available across a wide range of soft and hard X-rays, combined with state-of-the-art focusing techniques and ultra-sensitive detectors, makes it viable to undertake direct imaging of a number of elements in brain tissue. The different methods for synchrotron imaging of metals in brain tissues at regional, cellular, and sub-cellular spatial resolution are discussed. Methods covered include X-ray fluorescence for elemental imaging, X-ray absorption spectrometry for speciation imaging, X-ray diffraction for structural imaging, phase contrast for enhanced contrast imaging and scanning transmission X-ray microscopy for spectromicroscopy. Two- and three-dimensional (confocal and tomographic) imaging methods are considered as well as the correlation of X-ray microscopy with other imaging tools.

ImageParser: a tool for finite element generation from three-dimensional medical images

PubMed Central

Yin, HM; Sun, LZ; Wang, G; Yamada, T; Wang, J; Vannier, MW

2004-01-01

Background The finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures) of interest (ROIs) may be irregular and fuzzy. Methods A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements. Results The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues. Conclusion The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information. PMID:15461787

Innovations in Nuclear Imaging Instrumentation: Cerenkov Imaging.

PubMed

Tamura, Ryo; Pratt, Edwin C; Grimm, Jan

2018-07-01

Cerenkov luminescence (CL) is blue glow light produced by charged subatomic particles travelling faster than the phase velocity of light in a dielectric medium such as water or tissue. CL was first discovered in 1934, but for biomedical research it was recognized only in 2009 after advances in optical camera sensors brought the required high sensitivity. Recently, applications of CL from clinical radionuclides have been rapidly expanding to include not only preclinical and clinical biomedical imaging but also an approach to therapy. Cerenkov Luminescence Imaging (CLI) utilizes CL generated from clinically relevant radionuclides alongside optical imaging instrumentation. CLI is advantageous over traditional nuclear imaging methods in terms of infrastructure cost, resolution, and imaging time. Furthermore, CLI is a truly multimodal imaging method where the same agent can be detected by two independent modalities, with optical (CL) imaging and with positron emission tomography (PET) imaging. CL has been combined with small molecules, biomolecules and nanoparticles to improve diagnosis and therapy in cancer research. Here, we cover the fundamental breakthroughs and recent advances in reagents and instrumentation methods for CLI as well as therapeutic application of CL. Copyright © 2018 Elsevier Inc. All rights reserved.

Infrared imagery acquisition process supporting simulation and real image training

NASA Astrophysics Data System (ADS)

O'Connor, John

2012-05-01

The increasing use of infrared sensors requires development of advanced infrared training and simulation tools to meet current Warfighter needs. In order to prepare the force, a challenge exists for training and simulation images to be both realistic and consistent with each other to be effective and avoid negative training. The US Army Night Vision and Electronic Sensors Directorate has corrected this deficiency by developing and implementing infrared image collection methods that meet the needs of both real image trainers and real-time simulations. The author presents innovative methods for collection of high-fidelity digital infrared images and the associated equipment and environmental standards. The collected images are the foundation for US Army, and USMC Recognition of Combat Vehicles (ROC-V) real image combat ID training and also support simulations including the Night Vision Image Generator and Synthetic Environment Core. The characteristics, consistency, and quality of these images have contributed to the success of these and other programs. To date, this method has been employed to generate signature sets for over 350 vehicles. The needs of future physics-based simulations will also be met by this data. NVESD's ROC-V image database will support the development of training and simulation capabilities as Warfighter needs evolve.

A Novel Image Recuperation Approach for Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image

PubMed Central

2015-01-01

Retinal fundus images are widely used in diagnosing and providing treatment for several eye diseases. Prior works using retinal fundus images detected the presence of exudation with the aid of publicly available dataset using extensive segmentation process. Though it was proved to be computationally efficient, it failed to create a diabetic retinopathy feature selection system for transparently diagnosing the disease state. Also the diagnosis of diseases did not employ machine learning methods to categorize candidate fundus images into true positive and true negative ratio. Several candidate fundus images did not include more detailed feature selection technique for diabetic retinopathy. To apply machine learning methods and classify the candidate fundus images on the basis of sliding window a method called, Diabetic Fundus Image Recuperation (DFIR) is designed in this paper. The initial phase of DFIR method select the feature of optic cup in digital retinal fundus images based on Sliding Window Approach. With this, the disease state for diabetic retinopathy is assessed. The feature selection in DFIR method uses collection of sliding windows to obtain the features based on the histogram value. The histogram based feature selection with the aid of Group Sparsity Non-overlapping function provides more detailed information of features. Using Support Vector Model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy diseases. The ranking of disease level for each candidate set provides a much promising result for developing practically automated diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, specificity rate, ranking efficiency and feature selection time. PMID:25974230

Electronic Holography with a Broad Spectrum Laser for Time Gated Imaging Through Highly Scattering Media.

NASA Astrophysics Data System (ADS)

Shih, Marian Pei-Ling

The problem of optical imaging through a highly scattering volume diffuser, in particular, biological tissue, has received renewed interest in recent years because of a search for alternative imaging diagnostics in the optical wavelengths for the early detection of human breast cancer. This dissertation discusses the optical imaging of objects obscured by diffusers that contribute an otherwise overwhelming degree of multiple scatter. Many optical imaging techniques are based on the first-arriving light principle. These methods usually combine a transilluminating optical short pulse with a time windowing gate in order to form a flat shadowgraph image of absorbing objects either embedded within or hidden behind a scattering medium. The gate selectively records an image of the first-arriving light, while simultaneously rejecting the later-arriving scattered light. One set of the many implementations of the first -arriving light principle relies on the gating property of holography. This thesis presents several holographic optical gating experiments that demonstrate the role that the temporal coherence function of the illumination source plays in the imaging of all objects with short coherence length holography, with special emphasis on the application to image through diffusers and its resolution capabilities. Previous researchers have already successfully combined electronic holography, holography in which the recording medium is a two dimensional detector array instead of photographic film, with light-in-flight holography into a short coherence length holography method that images through various types of multiply scattering random media, including chicken breast tissue and wax. This thesis reports further experimental exploration of the short coherence holography method for imaging through severely scattering diffusers. There is a study on the effectiveness of spatial filtering of the first-arriving light, as well as a report of the imaging, by means of the short coherence holographic method, of an absorber through a living human hand. This thesis also includes both theoretical analyses and experimental results of a spectral dispersion holography system which, instead of optically synthesizing the broad spectrum illumination source that is used for the short coherence holography method, digitally synthesizes a broad spectrum hologram from a collection of single frequency component holograms. This system has the time gating properties of short coherence length holography, as well as experimentally demonstrated applications for imaging through multiply scattering media.

3D conditional generative adversarial networks for high-quality PET image estimation at low dose.

PubMed

Wang, Yan; Yu, Biting; Wang, Lei; Zu, Chen; Lalush, David S; Lin, Weili; Wu, Xi; Zhou, Jiliu; Shen, Dinggang; Zhou, Luping

2018-07-01

Positron emission tomography (PET) is a widely used imaging modality, providing insight into both the biochemical and physiological processes of human body. Usually, a full dose radioactive tracer is required to obtain high-quality PET images for clinical needs. This inevitably raises concerns about potential health hazards. On the other hand, dose reduction may cause the increased noise in the reconstructed PET images, which impacts the image quality to a certain extent. In this paper, in order to reduce the radiation exposure while maintaining the high quality of PET images, we propose a novel method based on 3D conditional generative adversarial networks (3D c-GANs) to estimate the high-quality full-dose PET images from low-dose ones. Generative adversarial networks (GANs) include a generator network and a discriminator network which are trained simultaneously with the goal of one beating the other. Similar to GANs, in the proposed 3D c-GANs, we condition the model on an input low-dose PET image and generate a corresponding output full-dose PET image. Specifically, to render the same underlying information between the low-dose and full-dose PET images, a 3D U-net-like deep architecture which can combine hierarchical features by using skip connection is designed as the generator network to synthesize the full-dose image. In order to guarantee the synthesized PET image to be close to the real one, we take into account of the estimation error loss in addition to the discriminator feedback to train the generator network. Furthermore, a concatenated 3D c-GANs based progressive refinement scheme is also proposed to further improve the quality of estimated images. Validation was done on a real human brain dataset including both the normal subjects and the subjects diagnosed as mild cognitive impairment (MCI). Experimental results show that our proposed 3D c-GANs method outperforms the benchmark methods and achieves much better performance than the state-of-the-art methods in both qualitative and quantitative measures. Copyright © 2018 Elsevier Inc. All rights reserved.

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods

PubMed Central

Wells, Darren M.; French, Andrew P.; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein; Bennett, Malcolm J.; Pridmore, Tony P.

2012-01-01

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana. PMID:22527394

Imaging of human vertebral surface using ultrasound RF data received at each element of probe for thoracic anesthesia

NASA Astrophysics Data System (ADS)

Takahashi, Kazuki; Taki, Hirofumi; Onishi, Eiko; Yamauchi, Masanori; Kanai, Hiroshi

2017-07-01

Epidural anesthesia is a common technique for perioperative analgesia and chronic pain treatment. Since ultrasonography is insufficient for depicting the human vertebral surface, most examiners apply epidural puncture by body surface landmarks on the back such as the spinous process and scapulae without any imaging, including ultrasonography. The puncture route to the epidural space at thoracic vertebrae is much narrower than that at lumber vertebrae, and therefore, epidural anesthesia at thoracic vertebrae is difficult, especially for a beginner. Herein, a novel imaging method is proposed based on a bi-static imaging technique by making use of the transmit beam width and direction. In an in vivo experimental study on human thoracic vertebrae, the proposed method succeeded in depicting the vertebral surface clearly as compared with conventional B-mode imaging and the conventional envelope method. This indicates the potential of the proposed method in visualizing the vertebral surface for the proper and safe execution of epidural anesthesia.

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods.

PubMed

Wells, Darren M; French, Andrew P; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein I; Hijazi, Hussein; Bennett, Malcolm J; Pridmore, Tony P

2012-06-05

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana.

Quantum imaging with incoherently scattered light from a free-electron laser

NASA Astrophysics Data System (ADS)

Schneider, Raimund; Mehringer, Thomas; Mercurio, Giuseppe; Wenthaus, Lukas; Classen, Anton; Brenner, Günter; Gorobtsov, Oleg; Benz, Adrian; Bhatti, Daniel; Bocklage, Lars; Fischer, Birgit; Lazarev, Sergey; Obukhov, Yuri; Schlage, Kai; Skopintsev, Petr; Wagner, Jochen; Waldmann, Felix; Willing, Svenja; Zaluzhnyy, Ivan; Wurth, Wilfried; Vartanyants, Ivan A.; Röhlsberger, Ralf; von Zanthier, Joachim

2018-02-01

The advent of accelerator-driven free-electron lasers (FEL) has opened new avenues for high-resolution structure determination via diffraction methods that go far beyond conventional X-ray crystallography methods. These techniques rely on coherent scattering processes that require the maintenance of first-order coherence of the radiation field throughout the imaging procedure. Here we show that higher-order degrees of coherence, displayed in the intensity correlations of incoherently scattered X-rays from an FEL, can be used to image two-dimensional objects with a spatial resolution close to or even below the Abbe limit. This constitutes a new approach towards structure determination based on incoherent processes, including fluorescence emission or wavefront distortions, generally considered detrimental for imaging applications. Our method is an extension of the landmark intensity correlation measurements of Hanbury Brown and Twiss to higher than second order, paving the way towards determination of structure and dynamics of matter in regimes where coherent imaging methods have intrinsic limitations.

Mosaic CCD method: A new technique for observing dynamics of cometary magnetospheres

NASA Technical Reports Server (NTRS)

Saito, T.; Takeuchi, H.; Kozuba, Y.; Okamura, S.; Konno, I.; Hamabe, M.; Aoki, T.; Minami, S.; Isobe, S.

1992-01-01

On April 29, 1990, the plasma tail of Comet Austin was observed with a CCD camera on the 105-cm Schmidt telescope at the Kiso Observatory of the University of Tokyo. The area of the CCD used in this observation is only about 1 sq cm. When this CCD is used on the 105-cm Schmidt telescope at the Kiso Observatory, the area corresponds to a narrow square view of 12 ft x 12 ft. By comparison with the photograph of Comet Austin taken by Numazawa (personal communication) on the same night, we see that only a small part of the plasma tail can be photographed at one time with the CCD. However, by shifting the view on the CCD after each exposure, we succeeded in imaging the entire length of the cometary magnetosphere of 1.6 x 10(exp 6) km. This new technique is called 'the mosaic CCD method'. In order to study the dynamics of cometary plasma tails, seven frames of the comet from the head to the tail region were twice imaged with the mosaic CCD method and two sets of images were obtained. Six microstructures, including arcade structures, were identified in both the images. Sketches of the plasma tail including microstructures are included.

Near-infrared fluorescence image quality test methods for standardized performance evaluation

NASA Astrophysics Data System (ADS)

Kanniyappan, Udayakumar; Wang, Bohan; Yang, Charles; Ghassemi, Pejhman; Wang, Quanzeng; Chen, Yu; Pfefer, Joshua

2017-03-01

Near-infrared fluorescence (NIRF) imaging has gained much attention as a clinical method for enhancing visualization of cancers, perfusion and biological structures in surgical applications where a fluorescent dye is monitored by an imaging system. In order to address the emerging need for standardization of this innovative technology, it is necessary to develop and validate test methods suitable for objective, quantitative assessment of device performance. Towards this goal, we develop target-based test methods and investigate best practices for key NIRF imaging system performance characteristics including spatial resolution, depth of field and sensitivity. Characterization of fluorescence properties was performed by generating excitation-emission matrix properties of indocyanine green and quantum dots in biological solutions and matrix materials. A turbid, fluorophore-doped target was used, along with a resolution target for assessing image sharpness. Multi-well plates filled with either liquid or solid targets were generated to explore best practices for evaluating detection sensitivity. Overall, our results demonstrate the utility of objective, quantitative, target-based testing approaches as well as the need to consider a wide range of factors in establishing standardized approaches for NIRF imaging system performance.

Two-dimensional imaging via a narrowband MIMO radar system with two perpendicular linear arrays.

PubMed

Wang, Dang-wei; Ma, Xiao-yan; Su, Yi

2010-05-01

This paper presents a system model and method for the 2-D imaging application via a narrowband multiple-input multiple-output (MIMO) radar system with two perpendicular linear arrays. Furthermore, the imaging formulation for our method is developed through a Fourier integral processing, and the parameters of antenna array including the cross-range resolution, required size, and sampling interval are also examined. Different from the spatial sequential procedure sampling the scattered echoes during multiple snapshot illuminations in inverse synthetic aperture radar (ISAR) imaging, the proposed method utilizes a spatial parallel procedure to sample the scattered echoes during a single snapshot illumination. Consequently, the complex motion compensation in ISAR imaging can be avoided. Moreover, in our array configuration, multiple narrowband spectrum-shared waveforms coded with orthogonal polyphase sequences are employed. The mainlobes of the compressed echoes from the different filter band could be located in the same range bin, and thus, the range alignment in classical ISAR imaging is not necessary. Numerical simulations based on synthetic data are provided for testing our proposed method.

A Comparison of Earthquake Back-Projection Imaging Methods for Dense Local Arrays, and Application to the 2011 Virginia Aftershock Sequence

NASA Astrophysics Data System (ADS)

Beskardes, G. D.; Hole, J. A.; Wang, K.; Wu, Q.; Chapman, M. C.; Davenport, K. K.; Michaelides, M.; Brown, L. D.; Quiros, D. A.

2016-12-01

Back-projection imaging has recently become a practical method for local earthquake detection and location due to the deployment of densely sampled, continuously recorded, local seismograph arrays. Back-projection is scalable to earthquakes with a wide range of magnitudes from very tiny to very large. Local dense arrays provide the opportunity to capture very tiny events for a range applications, such as tectonic microseismicity, source scaling studies, wastewater injection-induced seismicity, hydraulic fracturing, CO2 injection monitoring, volcano studies, and mining safety. While back-projection sometimes utilizes the full seismic waveform, the waveforms are often pre-processed to overcome imaging issues. We compare the performance of back-projection using four previously used data pre-processing methods: full waveform, envelope, short-term averaging / long-term averaging (STA/LTA), and kurtosis. The goal is to identify an optimized strategy for an entirely automated imaging process that is robust in the presence of real-data issues, has the lowest signal-to-noise thresholds for detection and for location, has the best spatial resolution of the energy imaged at the source, preserves magnitude information, and considers computational cost. Real data issues include aliased station spacing, low signal-to-noise ratio (to <1), large noise bursts and spatially varying waveform polarity. For evaluation, the four imaging methods were applied to the aftershock sequence of the 2011 Virginia earthquake as recorded by the AIDA array with 200-400 m station spacing. These data include earthquake magnitudes from -2 to 3 with highly variable signal to noise, spatially aliased noise, and large noise bursts: realistic issues in many environments. Each of the four back-projection methods has advantages and disadvantages, and a combined multi-pass method achieves the best of all criteria. Preliminary imaging results from the 2011 Virginia dataset will be presented.

Time reversal acoustics for small targets using decomposition of the time reversal operator

NASA Astrophysics Data System (ADS)

Simko, Peter C.

The method of time reversal acoustics has been the focus of considerable interest over the last twenty years. Time reversal imaging methods have made consistent progress as effective methods for signal processing since the initial demonstration that physical time reversal methods can be used to form convergent wave fields on a localized target, even under conditions of severe multipathing. Computational time reversal methods rely on the properties of the so-called 'time reversal operator' in order to extract information about the target medium. Applications for which time reversal imaging have previously been explored include medical imaging, non-destructive evaluation, and mine detection. Emphasis in this paper will fall on two topics within the general field of computational time reversal imaging. First, we will examine previous work on developing a time reversal imaging algorithm based on the MUltiple SIgnal Classification (MUSIC) algorithm. MUSIC, though computationally very intensive, has demonstrated early promise in simulations using array-based methods applicable to true volumetric (three-dimensional) imaging. We will provide a simple algorithm through which the rank of the time reversal operator subspaces can be properly quantified so that the rank of the associated null subspace can be accurately estimated near the central pulse wavelength in broadband imaging. Second, we will focus on the scattering from small acoustically rigid two dimensional cylindrical targets of elliptical cross section. Analysis of the time reversal operator eigenmodes has been well-studied for symmetric response matrices associated with symmetric systems of scattering targets. We will expand these previous results to include more general scattering systems leading to asymmetric response matrices, for which the analytical complexity increases but the physical interpretation of the time reversal operator remains unchanged. For asymmetric responses, the qualitative properties of the time reversal operator eigenmodes remain consistent with those obtained from the more tightly constrained systems.

Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface

PubMed Central

Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Wenzel, Sally E.; Lin, Ching-Long

2016-01-01

We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11% of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches. PMID:27704229

Recovery of Background Structures in Nanoscale Helium Ion Microscope Imaging

PubMed Central

Carasso, Alfred S; Vladár, András E

2014-01-01

This paper discusses a two step enhancement technique applicable to noisy Helium Ion Microscope images in which background structures are not easily discernible due to a weak signal. The method is based on a preliminary adaptive histogram equalization, followed by ‘slow motion’ low-exponent Lévy fractional diffusion smoothing. This combined approach is unexpectedly effective, resulting in a companion enhanced image in which background structures are rendered much more visible, and noise is significantly reduced, all with minimal loss of image sharpness. The method also provides useful enhancements of scanning charged-particle microscopy images obtained by composing multiple drift-corrected ‘fast scan’ frames. The paper includes software routines, written in Interactive Data Language (IDL),1 that can perform the above image processing tasks. PMID:26601050

A novel optical gating method for laser gated imaging

NASA Astrophysics Data System (ADS)

Ginat, Ran; Schneider, Ron; Zohar, Eyal; Nesher, Ofer

2013-06-01

For the past 15 years, Elbit Systems is developing time-resolved active laser-gated imaging (LGI) systems for various applications. Traditional LGI systems are based on high sensitive gated sensors, synchronized to pulsed laser sources. Elbit propriety multi-pulse per frame method, which is being implemented in LGI systems, improves significantly the imaging quality. A significant characteristic of the LGI is its ability to penetrate a disturbing media, such as rain, haze and some fog types. Current LGI systems are based on image intensifier (II) sensors, limiting the system in spectral response, image quality, reliability and cost. A novel propriety optical gating module was developed in Elbit, untying the dependency of LGI system on II. The optical gating module is not bounded to the radiance wavelength and positioned between the system optics and the sensor. This optical gating method supports the use of conventional solid state sensors. By selecting the appropriate solid state sensor, the new LGI systems can operate at any desired wavelength. In this paper we present the new gating method characteristics, performance and its advantages over the II gating method. The use of the gated imaging systems is described in a variety of applications, including results from latest field experiments.

Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions.

PubMed

Sun, Xiaofei; Shi, Lin; Luo, Yishan; Yang, Wei; Li, Hongpeng; Liang, Peipeng; Li, Kuncheng; Mok, Vincent C T; Chu, Winnie C W; Wang, Defeng

2015-07-28

Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. We have proposed a histogram-based MRI intensity normalization method. The method can normalize scans which were acquired on different MRI units. We have validated that the method can greatly improve the image analysis performance. Furthermore, it is demonstrated that with the help of our normalization method, we can create a higher quality Chinese brain template.

Image analysis methods for assessing levels of image plane nonuniformity and stochastic noise in a magnetic resonance image of a homogeneous phantom.

PubMed

Magnusson, P; Olsson, L E

2000-08-01

Magnetic response image plane nonuniformity and stochastic noise are properties that greatly influence the outcome of quantitative magnetic resonance imaging (MRI) evaluations such as gel dosimetry measurements using MRI. To study these properties, robust and accurate image analysis methods are required. New nonuniformity level assessment methods were designed, since previous methods were found to be insufficiently robust and accurate. The new and previously reported nonuniformity level assessment methods were analyzed with respect to, for example, insensitivity to stochastic noise; and previously reported stochastic noise level assessment methods with respect to insensitivity to nonuniformity. Using the same image data, different methods were found to assess significantly different levels of nonuniformity. Nonuniformity levels obtained using methods that count pixels in an intensity interval, and obtained using methods that use only intensity values, were found not to be comparable. The latter were found preferable, since they assess the quantity intrinsically sought. A new method which calculates a deviation image, with every pixel representing the deviation from a reference intensity, was least sensitive to stochastic noise. Furthermore, unlike any other analyzed method, it includes all intensity variations across the phantom area and allows for studies of nonuniformity shapes. This new method was designed for accurate studies of nonuniformities in gel dosimetry measurements, but could also be used with benefit in quality assurance and acceptance testing of MRI, scintillation camera, and computer tomography systems. The stochastic noise level was found to be greatly method dependent. Two methods were found to be insensitive to nonuniformity and also simple to use in practice. One method assesses the stochastic noise level as the average of the levels at five different positions within the phantom area, and the other assesses the stochastic noise in a region outside the phantom area.

System and Method for Null-Lens Wavefront Sensing

NASA Technical Reports Server (NTRS)

Hill, Peter C. (Inventor); Thompson, Patrick L. (Inventor); Aronstein, David L. (Inventor); Bolcar, Matthew R. (Inventor); Smith, Jeffrey S. (Inventor)

2015-01-01

A method of measuring aberrations in a null-lens including assembly and alignment aberrations. The null-lens may be used for measuring aberrations in an aspheric optic with the null-lens. Light propagates from the aspheric optic location through the null-lens, while sweeping a detector through the null-lens focal plane. Image data being is collected at locations about said focal plane. Light is simulated propagating to the collection locations for each collected image. Null-lens aberrations may extracted, e.g., applying image-based wavefront-sensing to collected images and simulation results. The null-lens aberrations improve accuracy in measuring aspheric optic aberrations.

Fingerprint image enhancement by differential hysteresis processing.

PubMed

Blotta, Eduardo; Moler, Emilce

2004-05-10

A new method to enhance defective fingerprints images through image digital processing tools is presented in this work. When the fingerprints have been taken without any care, blurred and in some cases mostly illegible, as in the case presented here, their classification and comparison becomes nearly impossible. A combination of spatial domain filters, including a technique called differential hysteresis processing (DHP), is applied to improve these kind of images. This set of filtering methods proved to be satisfactory in a wide range of cases by uncovering hidden details that helped to identify persons. Dactyloscopy experts from Policia Federal Argentina and the EAAF have validated these results.

An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS.

PubMed

Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu

2017-01-23

Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

ARCOCT: Automatic detection of lumen border in intravascular OCT images.

PubMed

Cheimariotis, Grigorios-Aris; Chatzizisis, Yiannis S; Koutkias, Vassilis G; Toutouzas, Konstantinos; Giannopoulos, Andreas; Riga, Maria; Chouvarda, Ioanna; Antoniadis, Antonios P; Doulaverakis, Charalambos; Tsamboulatidis, Ioannis; Kompatsiaris, Ioannis; Giannoglou, George D; Maglaveras, Nicos

2017-11-01

Intravascular optical coherence tomography (OCT) is an invaluable tool for the detection of pathological features on the arterial wall and the investigation of post-stenting complications. Computational lumen border detection in OCT images is highly advantageous, since it may support rapid morphometric analysis. However, automatic detection is very challenging, since OCT images typically include various artifacts that impact image clarity, including features such as side branches and intraluminal blood presence. This paper presents ARCOCT, a segmentation method for fully-automatic detection of lumen border in OCT images. ARCOCT relies on multiple, consecutive processing steps, accounting for image preparation, contour extraction and refinement. In particular, for contour extraction ARCOCT employs the transformation of OCT images based on physical characteristics such as reflectivity and absorption of the tissue and, for contour refinement, local regression using weighted linear least squares and a 2nd degree polynomial model is employed to achieve artifact and small-branch correction as well as smoothness of the artery mesh. Our major focus was to achieve accurate contour delineation in the various types of OCT images, i.e., even in challenging cases with branches and artifacts. ARCOCT has been assessed in a dataset of 1812 images (308 from stented and 1504 from native segments) obtained from 20 patients. ARCOCT was compared against ground-truth manual segmentation performed by experts on the basis of various geometric features (e.g. area, perimeter, radius, diameter, centroid, etc.) and closed contour matching indicators (the Dice index, the Hausdorff distance and the undirected average distance), using standard statistical analysis methods. The proposed method was proven very efficient and close to the ground-truth, exhibiting non statistically-significant differences for most of the examined metrics. ARCOCT allows accurate and fully-automated lumen border detection in OCT images. Copyright © 2017 Elsevier B.V. All rights reserved.

Hybrid region merging method for segmentation of high-resolution remote sensing images

NASA Astrophysics Data System (ADS)

Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi; Wang, Jiangeng; Wang, Zuo

2014-12-01

Image segmentation remains a challenging problem for object-based image analysis. In this paper, a hybrid region merging (HRM) method is proposed to segment high-resolution remote sensing images. HRM integrates the advantages of global-oriented and local-oriented region merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region, which provides an elegant way to avoid the problem of starting point assignment and to enhance the optimization ability for local-oriented region merging. During the region growing procedure, the merging iterations are constrained within the local vicinity, so that the segmentation is accelerated and can reflect the local context, as compared with the global-oriented method. A set of high-resolution remote sensing images is used to test the effectiveness of the HRM method, and three region-based remote sensing image segmentation methods are adopted for comparison, including the hierarchical stepwise optimization (HSWO) method, the local-mutual best region merging (LMM) method, and the multiresolution segmentation (MRS) method embedded in eCognition Developer software. Both the supervised evaluation and visual assessment show that HRM performs better than HSWO and LMM by combining both their advantages. The segmentation results of HRM and MRS are visually comparable, but HRM can describe objects as single regions better than MRS, and the supervised and unsupervised evaluation results further prove the superiority of HRM.

Image guidance doses delivered during radiotherapy: Quantification, management, and reduction: Report of the AAPM Therapy Physics Committee Task Group 180.

PubMed

Ding, George X; Alaei, Parham; Curran, Bruce; Flynn, Ryan; Gossman, Michael; Mackie, T Rock; Miften, Moyed; Morin, Richard; Xu, X George; Zhu, Timothy C

2018-05-01

With radiotherapy having entered the era of image guidance, or image-guided radiation therapy (IGRT), imaging procedures are routinely performed for patient positioning and target localization. The imaging dose delivered may result in excessive dose to sensitive organs and potentially increase the chance of secondary cancers and, therefore, needs to be managed. This task group was charged with: a) providing an overview on imaging dose, including megavoltage electronic portal imaging (MV EPI), kilovoltage digital radiography (kV DR), Tomotherapy MV-CT, megavoltage cone-beam CT (MV-CBCT) and kilovoltage cone-beam CT (kV-CBCT), and b) providing general guidelines for commissioning dose calculation methods and managing imaging dose to patients. We briefly review the dose to radiotherapy (RT) patients resulting from different image guidance procedures and list typical organ doses resulting from MV and kV image acquisition procedures. We provide recommendations for managing the imaging dose, including different methods for its calculation, and techniques for reducing it. The recommended threshold beyond which imaging dose should be considered in the treatment planning process is 5% of the therapeutic target dose. Although the imaging dose resulting from current kV acquisition procedures is generally below this threshold, the ALARA principle should always be applied in practice. Medical physicists should make radiation oncologists aware of the imaging doses delivered to patients under their care. Balancing ALARA with the requirement for effective target localization requires that imaging dose be managed based on the consideration of weighing risks and benefits to the patient. © 2018 American Association of Physicists in Medicine.

Optimized optical clearing method for imaging central nervous system

NASA Astrophysics Data System (ADS)

Yu, Tingting; Qi, Yisong; Gong, Hui; Luo, Qingming; Zhu, Dan

2015-03-01

The development of various optical clearing methods provides a great potential for imaging entire central nervous system by combining with multiple-labelling and microscopic imaging techniques. These methods had made certain clearing contributions with respective weaknesses, including tissue deformation, fluorescence quenching, execution complexity and antibody penetration limitation that makes immunostaining of tissue blocks difficult. The passive clarity technique (PACT) bypasses those problems and clears the samples with simple implementation, excellent transparency with fine fluorescence retention, but the passive tissue clearing method needs too long time. In this study, we not only accelerate the clearing speed of brain blocks but also preserve GFP fluorescence well by screening an optimal clearing temperature. The selection of proper temperature will make PACT more applicable, which evidently broaden the application range of this method.

Accuracy comparison in mapping water bodies using Landsat images and Google Earth Images

NASA Astrophysics Data System (ADS)

Zhou, Z.; Zhou, X.

2016-12-01

A lot of research has been done for the extraction of water bodies with multiple satellite images. The Water Indexes with the use of multi-spectral images are the mostly used methods for the water bodies' extraction. In order to extract area of water bodies from satellite images, accuracy may depend on the spatial resolution of images and relative size of the water bodies. To quantify the impact of spatial resolution and size (major and minor lengths) of the water bodies on the accuracy of water area extraction, we use Georgetown Lake, Montana and coalbed methane (CBM) water retention ponds in the Montana Powder River Basin as test sites to evaluate the impact of spatial resolution and the size of water bodies on water area extraction. Data sources used include Landsat images and Google Earth images covering both large water bodies and small ponds. Firstly we used water indices to extract water coverage from Landsat images for both large lake and small ponds. Secondly we used a newly developed visible-index method to extract water coverage from Google Earth images covering both large lake and small ponds. Thirdly, we used the image fusion method in which the Google Earth Images are fused with multi-spectral Landsat images to obtain multi-spectral images of the same high spatial resolution as the Google earth images. The actual area of the lake and ponds are measured using GPS surveys. Results will be compared and the optimal method will be selected for water body extraction.

Edge enhancement algorithm for low-dose X-ray fluoroscopic imaging.

PubMed

Lee, Min Seok; Park, Chul Hee; Kang, Moon Gi

2017-12-01

Low-dose X-ray fluoroscopy has continually evolved to reduce radiation risk to patients during clinical diagnosis and surgery. However, the reduction in dose exposure causes quality degradation of the acquired images. In general, an X-ray device has a time-average pre-processor to remove the generated quantum noise. However, this pre-processor causes blurring and artifacts within the moving edge regions, and noise remains in the image. During high-pass filtering (HPF) to enhance edge detail, this noise in the image is amplified. In this study, a 2D edge enhancement algorithm comprising region adaptive HPF with the transient improvement (TI) method, as well as artifacts and noise reduction (ANR), was developed for degraded X-ray fluoroscopic images. The proposed method was applied in a static scene pre-processed by a low-dose X-ray fluoroscopy device. First, the sharpness of the X-ray image was improved using region adaptive HPF with the TI method, which facilitates sharpening of edge details without overshoot problems. Then, an ANR filter that uses an edge directional kernel was developed to remove the artifacts and noise that can occur during sharpening, while preserving edge details. The quantitative and qualitative results obtained by applying the developed method to low-dose X-ray fluoroscopic images and visually and numerically comparing the final images with images improved using conventional edge enhancement techniques indicate that the proposed method outperforms existing edge enhancement methods in terms of objective criteria and subjective visual perception of the actual X-ray fluoroscopic image. The developed edge enhancement algorithm performed well when applied to actual low-dose X-ray fluoroscopic images, not only by improving the sharpness, but also by removing artifacts and noise, including overshoot. Copyright © 2017 Elsevier B.V. All rights reserved.

Processing the image gradient field using a topographic primal sketch approach.

PubMed

Gambaruto, A M

2015-03-01

The spatial derivatives of the image intensity provide topographic information that may be used to identify and segment objects. The accurate computation of the derivatives is often hampered in medical images by the presence of noise and a limited resolution. This paper focuses on accurate computation of spatial derivatives and their subsequent use to process an image gradient field directly, from which an image with improved characteristics can be reconstructed. The improvements include noise reduction, contrast enhancement, thinning object contours and the preservation of edges. Processing the gradient field directly instead of the image is shown to have numerous benefits. The approach is developed such that the steps are modular, allowing the overall method to be improved and possibly tailored to different applications. As presented, the approach relies on a topographic representation and primal sketch of an image. Comparisons with existing image processing methods on a synthetic image and different medical images show improved results and accuracy in segmentation. Here, the focus is on objects with low spatial resolution, which is often the case in medical images. The methods developed show the importance of improved accuracy in derivative calculation and the potential in processing the image gradient field directly. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

A new registration method with voxel-matching technique for temporal subtraction images

NASA Astrophysics Data System (ADS)

Itai, Yoshinori; Kim, Hyoungseop; Ishikawa, Seiji; Katsuragawa, Shigehiko; Doi, Kunio

2008-03-01

A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can be used for enhancing interval changes on medical images by removing most of normal structures. One of the important problems in temporal subtraction is that subtraction images commonly include artifacts created by slight differences in the size, shape, and/or location of anatomical structures. In this paper, we developed a new registration method with voxel-matching technique for substantially removing the subtraction artifacts on the temporal subtraction image obtained from multiple-detector computed tomography (MDCT). With this technique, the voxel value in a warped (or non-warped) previous image is replaced by a voxel value within a kernel, such as a small cube centered at a given location, which would be closest (identical or nearly equal) to the voxel value in the corresponding location in the current image. Our new method was examined on 16 clinical cases with MDCT images. Preliminary results indicated that interval changes on the subtraction images were enhanced considerably, with a substantial reduction of misregistration artifacts. The temporal subtraction images obtained by use of the voxel-matching technique would be very useful for radiologists in the detection of interval changes on MDCT images.

Live-cell imaging of endogenous mRNAs with a small molecule.

PubMed

Sato, Shin-ichi; Watanabe, Mizuki; Katsuda, Yousuke; Murata, Asako; Wang, Dan Ohtan; Uesugi, Motonari

2015-02-02

Determination of subcellular localization and dynamics of mRNA is increasingly important to understanding gene expression. A new convenient and versatile method is reported that permits spatiotemporal imaging of specific non-engineered RNAs in living cells. The method uses transfection of a plasmid encoding a gene-specific RNA aptamer, combined with a cell-permeable synthetic small molecule, the fluorescence of which is restored only when the RNA aptamer hybridizes with its cognitive mRNA. The method was validated by live-cell imaging of the endogenous mRNA of β-actin. Application of the technology to mRNAs of a total of 84 human cytoskeletal genes allowed us to observe cellular dynamics of several endogenous mRNAs including arfaptin-2, cortactin, and cytoplasmic FMR1-interacting protein 2. The RNA-imaging technology and its further optimization might permit live-cell imaging of any RNA molecules. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Swept-frequency feedback interferometry using terahertz frequency QCLs: a method for imaging and materials analysis.

PubMed

Rakić, Aleksandar D; Taimre, Thomas; Bertling, Karl; Lim, Yah Leng; Dean, Paul; Indjin, Dragan; Ikonić, Zoran; Harrison, Paul; Valavanis, Alexander; Khanna, Suraj P; Lachab, Mohammad; Wilson, Stephen J; Linfield, Edmund H; Davies, A Giles

2013-09-23

The terahertz (THz) frequency quantum cascade laser (QCL) is a compact source of high-power radiation with a narrow intrinsic linewidth. As such, THz QCLs are extremely promising sources for applications including high-resolution spectroscopy, heterodyne detection, and coherent imaging. We exploit the remarkable phase-stability of THz QCLs to create a coherent swept-frequency delayed self-homodyning method for both imaging and materials analysis, using laser feedback interferometry. Using our scheme we obtain amplitude-like and phase-like images with minimal signal processing. We determine the physical relationship between the operating parameters of the laser under feedback and the complex refractive index of the target and demonstrate that this coherent detection method enables extraction of complex refractive indices with high accuracy. This establishes an ultimately compact and easy-to-implement THz imaging and materials analysis system, in which the local oscillator, mixer, and detector are all combined into a single laser.

Ultrasound fusion image error correction using subject-specific liver motion model and automatic image registration.

PubMed

Yang, Minglei; Ding, Hui; Zhu, Lei; Wang, Guangzhi

2016-12-01

Ultrasound fusion imaging is an emerging tool and benefits a variety of clinical applications, such as image-guided diagnosis and treatment of hepatocellular carcinoma and unresectable liver metastases. However, respiratory liver motion-induced misalignment of multimodal images (i.e., fusion error) compromises the effectiveness and practicability of this method. The purpose of this paper is to develop a subject-specific liver motion model and automatic registration-based method to correct the fusion error. An online-built subject-specific motion model and automatic image registration method for 2D ultrasound-3D magnetic resonance (MR) images were combined to compensate for the respiratory liver motion. The key steps included: 1) Build a subject-specific liver motion model for current subject online and perform the initial registration of pre-acquired 3D MR and intra-operative ultrasound images; 2) During fusion imaging, compensate for liver motion first using the motion model, and then using an automatic registration method to further correct the respiratory fusion error. Evaluation experiments were conducted on liver phantom and five subjects. In the phantom study, the fusion error (superior-inferior axis) was reduced from 13.90±2.38mm to 4.26±0.78mm by using the motion model only. The fusion error further decreased to 0.63±0.53mm by using the registration method. The registration method also decreased the rotation error from 7.06±0.21° to 1.18±0.66°. In the clinical study, the fusion error was reduced from 12.90±9.58mm to 6.12±2.90mm by using the motion model alone. Moreover, the fusion error decreased to 1.96±0.33mm by using the registration method. The proposed method can effectively correct the respiration-induced fusion error to improve the fusion image quality. This method can also reduce the error correction dependency on the initial registration of ultrasound and MR images. Overall, the proposed method can improve the clinical practicability of ultrasound fusion imaging. Copyright © 2016 Elsevier Ltd. All rights reserved.

Star tracking method based on multiexposure imaging for intensified star trackers.

PubMed

Yu, Wenbo; Jiang, Jie; Zhang, Guangjun

2017-07-20

The requirements for the dynamic performance of star trackers are rapidly increasing with the development of space exploration technologies. However, insufficient knowledge of the angular acceleration has largely decreased the performance of the existing star tracking methods, and star trackers may even fail to track under highly dynamic conditions. This study proposes a star tracking method based on multiexposure imaging for intensified star trackers. The accurate estimation model of the complete motion parameters, including the angular velocity and angular acceleration, is established according to the working characteristic of multiexposure imaging. The estimation of the complete motion parameters is utilized to generate the predictive star image accurately. Therefore, the correct matching and tracking between stars in the real and predictive star images can be reliably accomplished under highly dynamic conditions. Simulations with specific dynamic conditions are conducted to verify the feasibility and effectiveness of the proposed method. Experiments with real starry night sky observation are also conducted for further verification. Simulations and experiments demonstrate that the proposed method is effective and shows excellent performance under highly dynamic conditions.

Star centroiding error compensation for intensified star sensors.

PubMed

Jiang, Jie; Xiong, Kun; Yu, Wenbo; Yan, Jinyun; Zhang, Guangjun

2016-12-26

A star sensor provides high-precision attitude information by capturing a stellar image; however, the traditional star sensor has poor dynamic performance, which is attributed to its low sensitivity. Regarding the intensified star sensor, the image intensifier is utilized to improve the sensitivity, thereby further improving the dynamic performance of the star sensor. However, the introduction of image intensifier results in star centroiding accuracy decrease, further influencing the attitude measurement precision of the star sensor. A star centroiding error compensation method for intensified star sensors is proposed in this paper to reduce the influences. First, the imaging model of the intensified detector, which includes the deformation parameter of the optical fiber panel, is established based on the orthographic projection through the analysis of errors introduced by the image intensifier. Thereafter, the position errors at the target points based on the model are obtained by using the Levenberg-Marquardt (LM) optimization method. Last, the nearest trigonometric interpolation method is presented to compensate for the arbitrary centroiding error of the image plane. Laboratory calibration result and night sky experiment result show that the compensation method effectively eliminates the error introduced by the image intensifier, thus remarkably improving the precision of the intensified star sensors.

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.

Comparison of three-dimensional particle tracking and sizing using plenoptic imaging and digital in-line holography

DOE PAGES

Hall, Elise M.; Thurow, Brian S.; Guildenbecher, Daniel R.

2016-08-08

Digital in-line holography (DIH) and plenoptic photography are two techniques for single-shot, volumetric measurement of 3D particle fields. Here we present a comparison of the two methods by applying plenoptic imaging to experimental configurations that have been previously investigated with DIH. These experiments include the tracking of secondary droplets from the impact of a water drop on a thin film of water and tracking of pellets from a shotgun. Both plenoptic imaging and DIH successfully quantify the 3D nature of these particle fields. Furthermore, this includes measurement of the 3D particle position, individual particle sizes, and three-component velocity vectors. Formore » the initial processing methods presented here, both techniques give out-of-plane positional accuracy of approximately 1–2 particle diameters. For a fixed image sensor, digital holography achieves higher effective in-plane spatial resolutions. However, collimated and coherent illumination makes holography susceptible to image distortion through index of refraction gradients, as demonstrated in the shotgun experiments. In contrast, plenoptic imaging allows for a simpler experimental configuration and, due to the use of diffuse, white-light illumination, plenoptic imaging is less susceptible to image distortion in the shotgun experiments.« less

Method and apparatus for acoustic imaging of objects in water

DOEpatents

Deason, Vance A.; Telschow, Kenneth L.

2005-01-25

A method, system and underwater camera for acoustic imaging of objects in water or other liquids includes an acoustic source for generating an acoustic wavefront for reflecting from a target object as a reflected wavefront. The reflected acoustic wavefront deforms a screen on an acoustic side and correspondingly deforms the opposing optical side of the screen. An optical processing system is optically coupled to the optical side of the screen and converts the deformations on the optical side of the screen into an optical intensity image of the target object.

Overview of chemical imaging methods to address biological questions.

PubMed

da Cunha, Marcel Menezes Lyra; Trepout, Sylvain; Messaoudi, Cédric; Wu, Ting-Di; Ortega, Richard; Guerquin-Kern, Jean-Luc; Marco, Sergio

2016-05-01

Chemical imaging offers extensive possibilities for better understanding of biological systems by allowing the identification of chemical components at the tissue, cellular, and subcellular levels. In this review, we introduce modern methods for chemical imaging that can be applied to biological samples. This work is mainly addressed to the biological sciences community and includes the bases of different technologies, some examples of its application, as well as an introduction to approaches on combining multimodal data. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Augmented reality system

NASA Astrophysics Data System (ADS)

Lin, Chien-Liang; Su, Yu-Zheng; Hung, Min-Wei; Huang, Kuo-Cheng

2010-08-01

In recent years, Augmented Reality (AR)[1][2][3] is very popular in universities and research organizations. The AR technology has been widely used in Virtual Reality (VR) fields, such as sophisticated weapons, flight vehicle development, data model visualization, virtual training, entertainment and arts. AR has characteristics to enhance the display output as a real environment with specific user interactive functions or specific object recognitions. It can be use in medical treatment, anatomy training, precision instrument casting, warplane guidance, engineering and distance robot control. AR has a lot of vantages than VR. This system developed combines sensors, software and imaging algorithms to make users feel real, actual and existing. Imaging algorithms include gray level method, image binarization method, and white balance method in order to make accurate image recognition and overcome the effects of light.

Research of an optimization design method of integral imaging three-dimensional display system

NASA Astrophysics Data System (ADS)

Gao, Hui; Yan, Zhiqiang; Wen, Jun; Jiang, Guanwu

2016-03-01

The information warfare needs a highly transparent environment of battlefield, it follows that true three-dimensional display technology has obvious advantages than traditional display technology in the current field of military science and technology. It also focuses on the research progress of lens array imaging technology and aims at what restrict the development of integral imaging, main including low spatial resolution, narrow depth range and small viewing angle. This paper summarizes the principle, characteristics and development history of the integral imaging. A variety of methods are compared and analyzed that how to improve the resolution, extend depth of field, increase scope and eliminate the artifact aiming at problems currently. And makes a discussion about the experimental results of the research, comparing the display performance of different methods.

Measurement of wood/plant cell or composite material attributes with computer assisted tomography

DOEpatents

West, Darrell C.; Paulus, Michael J.; Tuskan, Gerald A.; Wimmer, Rupert

2004-06-08

A method for obtaining wood-cell attributes from cellulose containing samples includes the steps of radiating a cellulose containing sample with a beam of radiation. Radiation attenuation information is collected from radiation which passes through the sample. The source is rotated relative to the sample and the radiation and collecting steps repeated. A projected image of the sample is formed from the collected radiation attenuation information, the projected image including resolvable features of the cellulose containing sample. Cell wall thickness, cell diameter (length) and cell vacoule diameter can be determined. A system for obtaining physical measures from cellulose containing samples includes a radiation source, a radiation detector, and structure for rotating the source relative to said sample. The system forms an image of the sample from the radiation attenuation information, the image including resolvable features of the sample.

Blurred Star Image Processing for Star Sensors under Dynamic Conditions

PubMed Central

Zhang, Weina; Quan, Wei; Guo, Lei

2012-01-01

The precision of star point location is significant to identify the star map and to acquire the aircraft attitude for star sensors. Under dynamic conditions, star images are not only corrupted by various noises, but also blurred due to the angular rate of the star sensor. According to different angular rates under dynamic conditions, a novel method is proposed in this article, which includes a denoising method based on adaptive wavelet threshold and a restoration method based on the large angular rate. The adaptive threshold is adopted for denoising the star image when the angular rate is in the dynamic range. Then, the mathematical model of motion blur is deduced so as to restore the blurred star map due to large angular rate. Simulation results validate the effectiveness of the proposed method, which is suitable for blurred star image processing and practical for attitude determination of satellites under dynamic conditions. PMID:22778666

Peripleural lung disease detection based on multi-slice CT images

NASA Astrophysics Data System (ADS)

Matsuhiro, M.; Suzuki, H.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2015-03-01

With the development of multi-slice CT technology, obtaining accurate 3D images of lung field in a short time become possible. To support that, a lot of image processing methods need to be developed. Detection peripleural lung disease is difficult due to its existence out of lung region, because lung extraction is often performed based on threshold processing. The proposed method uses thoracic inner region extracted by inner cavity of bone as well as air region, covers peripleural lung diseased cases such as lung nodule, calcification, pleural effusion and pleural plaque. We applied this method to 50 cases including 39 peripleural lung diseased cases. This method was able to detect 39 peripleural lung disease with 2.9 false positive per case.