Digital Pathology: Data-Intensive Frontier in Medical Imaging

PubMed Central

Cooper, Lee A. D.; Carter, Alexis B.; Farris, Alton B.; Wang, Fusheng; Kong, Jun; Gutman, David A.; Widener, Patrick; Pan, Tony C.; Cholleti, Sharath R.; Sharma, Ashish; Kurc, Tahsin M.; Brat, Daniel J.; Saltz, Joel H.

2013-01-01

Pathology is a medical subspecialty that practices the diagnosis of disease. Microscopic examination of tissue reveals information enabling the pathologist to render accurate diagnoses and to guide therapy. The basic process by which anatomic pathologists render diagnoses has remained relatively unchanged over the last century, yet advances in information technology now offer significant opportunities in image-based diagnostic and research applications. Pathology has lagged behind other healthcare practices such as radiology where digital adoption is widespread. As devices that generate whole slide images become more practical and affordable, practices will increasingly adopt this technology and eventually produce an explosion of data that will quickly eclipse the already vast quantities of radiology imaging data. These advances are accompanied by significant challenges for data management and storage, but they also introduce new opportunities to improve patient care by streamlining and standardizing diagnostic approaches and uncovering disease mechanisms. Computer-based image analysis is already available in commercial diagnostic systems, but further advances in image analysis algorithms are warranted in order to fully realize the benefits of digital pathology in medical discovery and patient care. In coming decades, pathology image analysis will extend beyond the streamlining of diagnostic workflows and minimizing interobserver variability and will begin to provide diagnostic assistance, identify therapeutic targets, and predict patient outcomes and therapeutic responses. PMID:25328166

Integrating advanced visualization technology into the planetary Geoscience workflow

NASA Astrophysics Data System (ADS)

Huffman, John; Forsberg, Andrew; Loomis, Andrew; Head, James; Dickson, James; Fassett, Caleb

2011-09-01

Recent advances in computer visualization have allowed us to develop new tools for analyzing the data gathered during planetary missions, which is important, since these data sets have grown exponentially in recent years to tens of terabytes in size. As part of the Advanced Visualization in Solar System Exploration and Research (ADVISER) project, we utilize several advanced visualization techniques created specifically with planetary image data in mind. The Geoviewer application allows real-time active stereo display of images, which in aggregate have billions of pixels. The ADVISER desktop application platform allows fast three-dimensional visualization of planetary images overlain on digital terrain models. Both applications include tools for easy data ingest and real-time analysis in a programmatic manner. Incorporation of these tools into our everyday scientific workflow has proved important for scientific analysis, discussion, and publication, and enabled effective and exciting educational activities for students from high school through graduate school.

Deep Learning in Medical Image Analysis.

PubMed

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2017-06-21

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

A computational image analysis glossary for biologists.

PubMed

Roeder, Adrienne H K; Cunha, Alexandre; Burl, Michael C; Meyerowitz, Elliot M

2012-09-01

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

Emerging imaging tools for use with traumatic brain injury research.

PubMed

Hunter, Jill V; Wilde, Elisabeth A; Tong, Karen A; Holshouser, Barbara A

2012-03-01

This article identifies emerging neuroimaging measures considered by the inter-agency Pediatric Traumatic Brain Injury (TBI) Neuroimaging Workgroup. This article attempts to address some of the potential uses of more advanced forms of imaging in TBI as well as highlight some of the current considerations and unresolved challenges of using them. We summarize emerging elements likely to gain more widespread use in the coming years, because of 1) their utility in diagnosis, prognosis, and understanding the natural course of degeneration or recovery following TBI, and potential for evaluating treatment strategies; 2) the ability of many centers to acquire these data with scanners and equipment that are readily available in existing clinical and research settings; and 3) advances in software that provide more automated, readily available, and cost-effective analysis methods for large scale data image analysis. These include multi-slice CT, volumetric MRI analysis, susceptibility-weighted imaging (SWI), diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), arterial spin tag labeling (ASL), functional MRI (fMRI), including resting state and connectivity MRI, MR spectroscopy (MRS), and hyperpolarization scanning. However, we also include brief introductions to other specialized forms of advanced imaging that currently do require specialized equipment, for example, single photon emission computed tomography (SPECT), positron emission tomography (PET), encephalography (EEG), and magnetoencephalography (MEG)/magnetic source imaging (MSI). Finally, we identify some of the challenges that users of the emerging imaging CDEs may wish to consider, including quality control, performing multi-site and longitudinal imaging studies, and MR scanning in infants and children.

Purchase of a Raman and Photoluminescence Imaging System for Characterization of Advanced Electrochemical and Electronic Materials

DTIC Science & Technology

2016-01-05

regularly used the Raman imaging system to characterize the doping chemistry of colloidal indium nitride nanoparticles . This material shows an interesting...regularly used the Raman imaging system to characterize the doping chemistry of colloidal indium nitride nanoparticles . This material shows an...analysis of thin film coatings, bulk materials, powders and nanoparticles . The instrument is extensively used to characterize advanced electrochemical and

Computer-aided prognosis on breast cancer with hematoxylin and eosin histopathology images: A review.

PubMed

Chen, Jia-Mei; Li, Yan; Xu, Jun; Gong, Lei; Wang, Lin-Wei; Liu, Wen-Lou; Liu, Juan

2017-03-01

With the advance of digital pathology, image analysis has begun to show its advantages in information analysis of hematoxylin and eosin histopathology images. Generally, histological features in hematoxylin and eosin images are measured to evaluate tumor grade and prognosis for breast cancer. This review summarized recent works in image analysis of hematoxylin and eosin histopathology images for breast cancer prognosis. First, prognostic factors for breast cancer based on hematoxylin and eosin histopathology images were summarized. Then, usual procedures of image analysis for breast cancer prognosis were systematically reviewed, including image acquisition, image preprocessing, image detection and segmentation, and feature extraction. Finally, the prognostic value of image features and image feature-based prognostic models was evaluated. Moreover, we discussed the issues of current analysis, and some directions for future research.

Exploring the complementarity of THz pulse imaging and DCE-MRIs: Toward a unified multi-channel classification and a deep learning framework.

PubMed

Yin, X-X; Zhang, Y; Cao, J; Wu, J-L; Hadjiloucas, S

2016-12-01

We provide a comprehensive account of recent advances in biomedical image analysis and classification from two complementary imaging modalities: terahertz (THz) pulse imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The work aims to highlight underlining commonalities in both data structures so that a common multi-channel data fusion framework can be developed. Signal pre-processing in both datasets is discussed briefly taking into consideration advances in multi-resolution analysis and model based fractional order calculus system identification. Developments in statistical signal processing using principal component and independent component analysis are also considered. These algorithms have been developed independently by the THz-pulse imaging and DCE-MRI communities, and there is scope to place them in a common multi-channel framework to provide better software standardization at the pre-processing de-noising stage. A comprehensive discussion of feature selection strategies is also provided and the importance of preserving textural information is highlighted. Feature extraction and classification methods taking into consideration recent advances in support vector machine (SVM) and extreme learning machine (ELM) classifiers and their complex extensions are presented. An outlook on Clifford algebra classifiers and deep learning techniques suitable to both types of datasets is also provided. The work points toward the direction of developing a new unified multi-channel signal processing framework for biomedical image analysis that will explore synergies from both sensing modalities for inferring disease proliferation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

New approaches in renal microscopy: volumetric imaging and superresolution microscopy.

PubMed

Kim, Alfred H J; Suleiman, Hani; Shaw, Andrey S

2016-05-01

Histologic and electron microscopic analysis of the kidney has provided tremendous insight into structures such as the glomerulus and nephron. Recent advances in imaging, such as deep volumetric approaches and superresolution microscopy, have the capacity to dramatically enhance our current understanding of the structure and function of the kidney. Volumetric imaging can generate images millimeters below the surface of the intact kidney. Superresolution microscopy breaks the diffraction barrier inherent in traditional light microscopy, enabling the visualization of fine structures. Here, we describe new approaches to deep volumetric and superresolution microscopy of the kidney. Rapid advances in lasers, microscopic objectives, and tissue preparation have transformed our ability to deep volumetric image the kidney. Innovations in sample preparation have allowed for superresolution imaging with electron microscopy correlation, providing unprecedented insight into the structures within the glomerulus. Technological advances in imaging have revolutionized our capacity to image both large volumes of tissue and the finest structural details of a cell. These new advances have the potential to provide additional profound observations into the normal and pathologic functions of the kidney.

Cardiac imaging: working towards fully-automated machine analysis & interpretation

PubMed Central

Slomka, Piotr J; Dey, Damini; Sitek, Arkadiusz; Motwani, Manish; Berman, Daniel S; Germano, Guido

2017-01-01

Introduction Non-invasive imaging plays a critical role in managing patients with cardiovascular disease. Although subjective visual interpretation remains the clinical mainstay, quantitative analysis facilitates objective, evidence-based management, and advances in clinical research. This has driven developments in computing and software tools aimed at achieving fully automated image processing and quantitative analysis. In parallel, machine learning techniques have been used to rapidly integrate large amounts of clinical and quantitative imaging data to provide highly personalized individual patient-based conclusions. Areas covered This review summarizes recent advances in automated quantitative imaging in cardiology and describes the latest techniques which incorporate machine learning principles. The review focuses on the cardiac imaging techniques which are in wide clinical use. It also discusses key issues and obstacles for these tools to become utilized in mainstream clinical practice. Expert commentary Fully-automated processing and high-level computer interpretation of cardiac imaging are becoming a reality. Application of machine learning to the vast amounts of quantitative data generated per scan and integration with clinical data also facilitates a move to more patient-specific interpretation. These developments are unlikely to replace interpreting physicians but will provide them with highly accurate tools to detect disease, risk-stratify, and optimize patient-specific treatment. However, with each technological advance, we move further from human dependence and closer to fully-automated machine interpretation. PMID:28277804

Improving Image Drizzling in the HST Archive: Advanced Camera for Surveys

NASA Astrophysics Data System (ADS)

Hoffmann, Samantha L.; Avila, Roberto J.

2017-06-01

The Mikulski Archive for Space Telescopes (MAST) pipeline performs geometric distortion corrections, associated image combinations, and cosmic ray rejections with AstroDrizzle on Hubble Space Telescope (HST) data. The MDRIZTAB reference table contains a list of relevant parameters that controls this program. This document details our photometric analysis of Advanced Camera for Surveys Wide Field Channel (ACS/WFC) data processed by AstroDrizzle. Based on this analysis, we update the MDRIZTAB table to improve the quality of the drizzled products delivered by MAST.

Emerging Imaging Tools for Use with Traumatic Brain Injury Research

PubMed Central

Wilde, Elisabeth A.; Tong, Karen A.; Holshouser, Barbara A.

2012-01-01

Abstract This article identifies emerging neuroimaging measures considered by the inter-agency Pediatric Traumatic Brain Injury (TBI) Neuroimaging Workgroup. This article attempts to address some of the potential uses of more advanced forms of imaging in TBI as well as highlight some of the current considerations and unresolved challenges of using them. We summarize emerging elements likely to gain more widespread use in the coming years, because of 1) their utility in diagnosis, prognosis, and understanding the natural course of degeneration or recovery following TBI, and potential for evaluating treatment strategies; 2) the ability of many centers to acquire these data with scanners and equipment that are readily available in existing clinical and research settings; and 3) advances in software that provide more automated, readily available, and cost-effective analysis methods for large scale data image analysis. These include multi-slice CT, volumetric MRI analysis, susceptibility-weighted imaging (SWI), diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), arterial spin tag labeling (ASL), functional MRI (fMRI), including resting state and connectivity MRI, MR spectroscopy (MRS), and hyperpolarization scanning. However, we also include brief introductions to other specialized forms of advanced imaging that currently do require specialized equipment, for example, single photon emission computed tomography (SPECT), positron emission tomography (PET), encephalography (EEG), and magnetoencephalography (MEG)/magnetic source imaging (MSI). Finally, we identify some of the challenges that users of the emerging imaging CDEs may wish to consider, including quality control, performing multi-site and longitudinal imaging studies, and MR scanning in infants and children. PMID:21787167

Deep Learning in Medical Image Analysis

PubMed Central

Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

2016-01-01

The computer-assisted analysis for better interpreting images have been longstanding issues in the medical imaging field. On the image-understanding front, recent advances in machine learning, especially, in the way of deep learning, have made a big leap to help identify, classify, and quantify patterns in medical images. Specifically, exploiting hierarchical feature representations learned solely from data, instead of handcrafted features mostly designed based on domain-specific knowledge, lies at the core of the advances. In that way, deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. In this article, we introduce the fundamentals of deep learning methods; review their successes to image registration, anatomical/cell structures detection, tissue segmentation, computer-aided disease diagnosis or prognosis, and so on. We conclude by raising research issues and suggesting future directions for further improvements. PMID:28301734

Key Issues in the Analysis of Remote Sensing Data: A report on the workshop

NASA Technical Reports Server (NTRS)

Swain, P. H. (Principal Investigator)

1981-01-01

The procedures of a workshop assessing the state of the art of machine analysis of remotely sensed data are summarized. Areas discussed were: data bases, image registration, image preprocessing operations, map oriented considerations, advanced digital systems, artificial intelligence methods, image classification, and improved classifier training. Recommendations of areas for further research are presented.

An advancement in removing extraneous color from wood for low-magnification reflected-light image analysis of conifer tree rings

Treesearch

Paul R. Sheppard; Alex Wiedenhoeft

2007-01-01

This paper describes the removal of extraneous color from increment cores of conifers prior to reflected-light image analysis of tree rings. Ponderosa pine in central New Mexico was chosen for study. Peroxide bleaching was used as a pretreatment to remove extraneous color and still yield usable wood for image analysis. The cores were bleached in 3% peroxide raised to...

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging.

PubMed

Schultz, Simon R; Copeland, Caroline S; Foust, Amanda J; Quicke, Peter; Schuck, Renaud

2017-01-01

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size.

Advances in two photon scanning and scanless microscopy technologies for functional neural circuit imaging

PubMed Central

Schultz, Simon R.; Copeland, Caroline S.; Foust, Amanda J.; Quicke, Peter; Schuck, Renaud

2017-01-01

Recent years have seen substantial developments in technology for imaging neural circuits, raising the prospect of large scale imaging studies of neural populations involved in information processing, with the potential to lead to step changes in our understanding of brain function and dysfunction. In this article we will review some key recent advances: improved fluorophores for single cell resolution functional neuroimaging using a two photon microscope; improved approaches to the problem of scanning active circuits; and the prospect of scanless microscopes which overcome some of the bandwidth limitations of current imaging techniques. These advances in technology for experimental neuroscience have in themselves led to technical challenges, such as the need for the development of novel signal processing and data analysis tools in order to make the most of the new experimental tools. We review recent work in some active topics, such as region of interest segmentation algorithms capable of demixing overlapping signals, and new highly accurate algorithms for calcium transient detection. These advances motivate the development of new data analysis tools capable of dealing with spatial or spatiotemporal patterns of neural activity, that scale well with pattern size. PMID:28757657

Integrated Imaging and Vision Techniques for Industrial Inspection: A Special Issue on Machine Vision and Applications

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

Liu, Zheng; Ukida, H.; Ramuhalli, Pradeep

2010-06-05

Imaging- and vision-based techniques play an important role in industrial inspection. The sophistication of the techniques assures high- quality performance of the manufacturing process through precise positioning, online monitoring, and real-time classification. Advanced systems incorporating multiple imaging and/or vision modalities provide robust solutions to complex situations and problems in industrial applications. A diverse range of industries, including aerospace, automotive, electronics, pharmaceutical, biomedical, semiconductor, and food/beverage, etc., have benefited from recent advances in multi-modal imaging, data fusion, and computer vision technologies. Many of the open problems in this context are in the general area of image analysis methodologies (preferably in anmore » automated fashion). This editorial article introduces a special issue of this journal highlighting recent advances and demonstrating the successful applications of integrated imaging and vision technologies in industrial inspection.« less

Advanced Cell Classifier: User-Friendly Machine-Learning-Based Software for Discovering Phenotypes in High-Content Imaging Data.

PubMed

Piccinini, Filippo; Balassa, Tamas; Szkalisity, Abel; Molnar, Csaba; Paavolainen, Lassi; Kujala, Kaisa; Buzas, Krisztina; Sarazova, Marie; Pietiainen, Vilja; Kutay, Ulrike; Smith, Kevin; Horvath, Peter

2017-06-28

High-content, imaging-based screens now routinely generate data on a scale that precludes manual verification and interrogation. Software applying machine learning has become an essential tool to automate analysis, but these methods require annotated examples to learn from. Efficiently exploring large datasets to find relevant examples remains a challenging bottleneck. Here, we present Advanced Cell Classifier (ACC), a graphical software package for phenotypic analysis that addresses these difficulties. ACC applies machine-learning and image-analysis methods to high-content data generated by large-scale, cell-based experiments. It features methods to mine microscopic image data, discover new phenotypes, and improve recognition performance. We demonstrate that these features substantially expedite the training process, successfully uncover rare phenotypes, and improve the accuracy of the analysis. ACC is extensively documented, designed to be user-friendly for researchers without machine-learning expertise, and distributed as a free open-source tool at www.cellclassifier.org. Copyright © 2017 Elsevier Inc. All rights reserved.

CT Imaging Findings after Craniosynostosis Reconstructive Surgery.

PubMed

Ginat, Daniel Thomas; Lam, Daniel; Kuhn, Andrew Scott; Reid, Russell

2018-06-06

Several surgical options are available for treating the different types of craniosynostosis, including fronto-orbital advancement and remodeling, total or subtotal cranial vault remodeling, barrel stave osteotomy with cranial remodeling, endoscopic suturectomy, monobloc advancement and cranioplasty, and revision cranioplasty. High-resolution, low-dose CT with 3D reconstructed images and volumetric analysis can be useful for evaluating the craniofacial skeleton following surgery. The various types of craniosynostosis surgery and corresponding imaging findings are reviewed in this article. © 2018 S. Karger AG, Basel.

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

PubMed Central

Goscinski, Wojtek J.; McIntosh, Paul; Felzmann, Ulrich; Maksimenko, Anton; Hall, Christopher J.; Gureyev, Timur; Thompson, Darren; Janke, Andrew; Galloway, Graham; Killeen, Neil E. B.; Raniga, Parnesh; Kaluza, Owen; Ng, Amanda; Poudel, Govinda; Barnes, David G.; Nguyen, Toan; Bonnington, Paul; Egan, Gary F.

2014-01-01

The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research. PMID:24734019

Multimedia Image Technology and Computer Aided Manufacturing Engineering Analysis

NASA Astrophysics Data System (ADS)

Nan, Song

2018-03-01

Since the reform and opening up, with the continuous development of science and technology in China, more and more advanced science and technology have emerged under the trend of diversification. Multimedia imaging technology, for example, has a significant and positive impact on computer aided manufacturing engineering in China. From the perspective of scientific and technological advancement and development, the multimedia image technology has a very positive influence on the application and development of computer-aided manufacturing engineering, whether in function or function play. Therefore, this paper mainly starts from the concept of multimedia image technology to analyze the application of multimedia image technology in computer aided manufacturing engineering.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Systems Biology-Driven Hypotheses Tested In Vivo: The Need to Advancing Molecular Imaging Tools.

PubMed

Verma, Garima; Palombo, Alessandro; Grigioni, Mauro; La Monaca, Morena; D'Avenio, Giuseppe

2018-01-01

Processing and interpretation of biological images may provide invaluable insights on complex, living systems because images capture the overall dynamics as a "whole." Therefore, "extraction" of key, quantitative morphological parameters could be, at least in principle, helpful in building a reliable systems biology approach in understanding living objects. Molecular imaging tools for system biology models have attained widespread usage in modern experimental laboratories. Here, we provide an overview on advances in the computational technology and different instrumentations focused on molecular image processing and analysis. Quantitative data analysis through various open source software and algorithmic protocols will provide a novel approach for modeling the experimental research program. Besides this, we also highlight the predictable future trends regarding methods for automatically analyzing biological data. Such tools will be very useful to understand the detailed biological and mathematical expressions under in-silico system biology processes with modeling properties.

Advancements in mass spectrometry for biological samples: Protein chemical cross-linking and metabolite analysis of plant tissues

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

Klein, Adam

2015-01-01

This thesis presents work on advancements and applications of methodology for the analysis of biological samples using mass spectrometry. Included in this work are improvements to chemical cross-linking mass spectrometry (CXMS) for the study of protein structures and mass spectrometry imaging and quantitative analysis to study plant metabolites. Applications include using matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) to further explore metabolic heterogeneity in plant tissues and chemical interactions at the interface between plants and pests. Additional work was focused on developing liquid chromatography-mass spectrometry (LC-MS) methods to investigate metabolites associated with plant-pest interactions.

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms

PubMed Central

Perez-Sanz, Fernando; Navarro, Pedro J

2017-01-01

Abstract The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. PMID:29048559

Review of automatic detection of pig behaviours by using image analysis

NASA Astrophysics Data System (ADS)

Han, Shuqing; Zhang, Jianhua; Zhu, Mengshuai; Wu, Jianzhai; Kong, Fantao

2017-06-01

Automatic detection of lying, moving, feeding, drinking, and aggressive behaviours of pigs by means of image analysis can save observation input by staff. It would help staff make early detection of diseases or injuries of pigs during breeding and improve management efficiency of swine industry. This study describes the progress of pig behaviour detection based on image analysis and advancement in image segmentation of pig body, segmentation of pig adhesion and extraction of pig behaviour characteristic parameters. Challenges for achieving automatic detection of pig behaviours were summarized.

Image Quality Analysis of Various Gastrointestinal Endoscopes: Why Image Quality Is a Prerequisite for Proper Diagnostic and Therapeutic Endoscopy

PubMed Central

Ko, Weon Jin; An, Pyeong; Ko, Kwang Hyun; Hahm, Ki Baik; Hong, Sung Pyo

2015-01-01

Arising from human curiosity in terms of the desire to look within the human body, endoscopy has undergone significant advances in modern medicine. Direct visualization of the gastrointestinal (GI) tract by traditional endoscopy was first introduced over 50 years ago, after which fairly rapid advancement from rigid esophagogastric scopes to flexible scopes and high definition videoscopes has occurred. In an effort towards early detection of precancerous lesions in the GI tract, several high-technology imaging scopes have been developed, including narrow band imaging, autofocus imaging, magnified endoscopy, and confocal microendoscopy. However, these modern developments have resulted in fundamental imaging technology being skewed towards red-green-blue and this technology has obscured the advantages of other endoscope techniques. In this review article, we have described the importance of image quality analysis using a survey to consider the diversity of endoscope system selection in order to better achieve diagnostic and therapeutic goals. The ultimate aims can be achieved through the adoption of modern endoscopy systems that obtain high image quality. PMID:26473119

Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

PubMed

Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

2014-01-01

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

Satellite image analysis using neural networks

NASA Technical Reports Server (NTRS)

Sheldon, Roger A.

1990-01-01

The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms.

PubMed

Perez-Sanz, Fernando; Navarro, Pedro J; Egea-Cortines, Marcos

2017-11-01

The study of phenomes or phenomics has been a central part of biology. The field of automatic phenotype acquisition technologies based on images has seen an important advance in the last years. As with other high-throughput technologies, it addresses a common set of problems, including data acquisition and analysis. In this review, we give an overview of the main systems developed to acquire images. We give an in-depth analysis of image processing with its major issues and the algorithms that are being used or emerging as useful to obtain data out of images in an automatic fashion. © The Author 2017. Published by Oxford University Press.

DIAGNOSTIC IMAGING IN A DIRECT-ACCESS SPORTS PHYSICAL THERAPY CLINIC: A 2-YEAR RETROSPECTIVE PRACTICE ANALYSIS.

PubMed

Crowell, Michael S; Dedekam, Erik A; Johnson, Michael R; Dembowski, Scott C; Westrick, Richard B; Goss, Donald L

2016-10-01

While advanced diagnostic imaging is a large contributor to the growth in health care costs, direct-access to physical therapy is associated with decreased rates of diagnostic imaging. No study has systematically evaluated with evidence-based criteria the appropriateness of advanced diagnostic imaging, including magnetic resonance imaging (MRI), when ordered by physical therapists. The primary purpose of this study was to describe the appropriateness of magnetic resonance imaging (MRI) or magnetic resonance arthrogram (MRA) exams ordered by physical therapists in a direct-access sports physical therapy clinic. Retrospective observational study of practice. Greater than 80% of advanced diagnostic imaging orders would have an American College of Radiology (ACR) Appropriateness Criteria rating of greater than 6, indicating an imaging order that is usually appropriate. A 2-year retrospective analysis identified 108 MRI/MRA examination orders from four physical therapists. A board-certified radiologist determined the appropriateness of each order based on ACR appropriateness criteria. The principal investigator and co-investigator radiologist assessed agreement between the clinical diagnosis and MRI/surgical findings. Knee (31%) and shoulder (25%) injuries were the most common. Overall, 55% of injuries were acute. The mean ACR rating was 7.7; scores from six to nine have been considered appropriate orders and higher ratings are better. The percentage of orders complying with ACR appropriateness criteria was 83.2%. Physical therapist's clinical diagnosis was confirmed by MRI/MRA findings in 64.8% of cases and was confirmed by surgical findings in 90% of cases. Physical therapists providing musculoskeletal primary care in a direct-access sports physical therapy clinic appropriately ordered advanced diagnostic imaging in over 80% of cases. Future research should prospectively compare physical therapist appropriateness and utilization to other groups of providers and explore the effects of physical therapist imaging privileging on outcomes. Diagnosis, Level 3.

Anima: Modular Workflow System for Comprehensive Image Data Analysis

PubMed Central

Rantanen, Ville; Valori, Miko; Hautaniemi, Sampsa

2014-01-01

Modern microscopes produce vast amounts of image data, and computational methods are needed to analyze and interpret these data. Furthermore, a single image analysis project may require tens or hundreds of analysis steps starting from data import and pre-processing to segmentation and statistical analysis; and ending with visualization and reporting. To manage such large-scale image data analysis projects, we present here a modular workflow system called Anima. Anima is designed for comprehensive and efficient image data analysis development, and it contains several features that are crucial in high-throughput image data analysis: programing language independence, batch processing, easily customized data processing, interoperability with other software via application programing interfaces, and advanced multivariate statistical analysis. The utility of Anima is shown with two case studies focusing on testing different algorithms developed in different imaging platforms and an automated prediction of alive/dead C. elegans worms by integrating several analysis environments. Anima is a fully open source and available with documentation at www.anduril.org/anima. PMID:25126541

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

PubMed Central

Sechopoulos, Ioannis

2013-01-01

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

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

Shoaf, S.; APS Engineering Support Division

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

iScreen: Image-Based High-Content RNAi Screening Analysis Tools.

PubMed

Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua

2015-09-01

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document. © 2014 Society for Laboratory Automation and Screening.

Ultrasonic image analysis and image-guided interventions.

PubMed

Noble, J Alison; Navab, Nassir; Becher, H

2011-08-06

The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research.

Advanced NDE research in electromagnetic, thermal, and coherent optics

NASA Technical Reports Server (NTRS)

Skinner, S. Ballou

1992-01-01

A new inspection technology called magneto-optic/eddy current imaging was investigated. The magneto-optic imager makes readily visible irregularities and inconsistencies in airframe components. Other research observed in electromagnetics included (1) disbond detection via resonant modal analysis; (2) AC magnetic field frequency dependence of magnetoacoustic emission; and (3) multi-view magneto-optic imaging. Research observed in the thermal group included (1) thermographic detection and characterization of corrosion in aircraft aluminum; (2) a multipurpose infrared imaging system for thermoelastic stress detection; (3) thermal diffusivity imaging of stress induced damage in composites; and (4) detection and measurement of ice formation on the space shuttle main fuel tank. Research observed in the optics group included advancements in optical nondestructive evaluation (NDE).

Quantitative analyses for elucidating mechanisms of cell fate commitment in the mouse blastocyst

NASA Astrophysics Data System (ADS)

Saiz, Néstor; Kang, Minjung; Puliafito, Alberto; Schrode, Nadine; Xenopoulos, Panagiotis; Lou, Xinghua; Di Talia, Stefano; Hadjantonakis, Anna-Katerina

2015-03-01

In recent years we have witnessed a shift from qualitative image analysis towards higher resolution, quantitative analyses of imaging data in developmental biology. This shift has been fueled by technological advances in both imaging and analysis software. We have recently developed a tool for accurate, semi-automated nuclear segmentation of imaging data from early mouse embryos and embryonic stem cells. We have applied this software to the study of the first lineage decisions that take place during mouse development and established analysis pipelines for both static and time-lapse imaging experiments. In this paper we summarize the conclusions from these studies to illustrate how quantitative, single-cell level analysis of imaging data can unveil biological processes that cannot be revealed by traditional qualitative studies.

Iodine-131-MIBG imaging to monitor chemotherapy response in advanced neuroblastoma: comparison with laboratory analysis.

PubMed

Maurea, S; Lastoria, S; Caracò, C; Indolfi, P; Casale, F; di Tullio, M T; Salvatore, M

1994-09-01

The rationale of this study was the evaluation of response to chemotherapy in children with advanced neuroblastoma using currently available diagnostic modalities. Iodine-131-metaiodobenzylguanidine (MIBG) imaging and 24-hr urinary vanillylmandelic acid (VMA) measurement were evaluated in 14 patients (7 males, 7 females, age range: 2-68 mo) with advanced neuroblastoma both pre- and postchemotherapy (5.6 +/- 2.8 mo) as well as serum ferritin (FER) and neuron-specific enolase (NSE) levels in 9 and 8 patients, respectively. MIBG images were qualitatively compared in each patient. Prechemotherapy, a total of 39 abnormal foci of MIBG uptake was detected. Postchemotherapy, 15 of these showed unchanged MIBG uptake, 7 had decreased uptake and 17 showed no uptake. In addition, four new abnormal foci of uptake were found. Postchemotherapy, a significant reduction of abnormal MIBG uptake (p < 0.01) was observed using a lesion-by-lesion analysis. When biochemical and MIBG postchemotherapy changes were compared, a significant relationship was found only between MIBG and VMA results (r = 0.84, p < 0.01). In postchemotherapy follow-up of children with advanced neuroblastoma, laboratory evaluation using VMA, FER and NSE measurements reflect only the global functional status of the disease, and are not helpful in defining the response of individual tumor lesions to treatment. Conversely, qualitative analysis using MIBG imaging may allow lesion-by-lesion evaluation of the heterogeneity of neuroblastoma response to chemotherapy. In this setting, changes in MIBG uptake are mirrored by the changes in catecholamine production, as measured by VMA levels.

The contribution of physics to Nuclear Medicine: physicians' perspective on future directions.

PubMed

Mankoff, David A; Pryma, Daniel A

2014-12-01

Advances in Nuclear Medicine physics enabled the specialty of Nuclear Medicine and directed research in other aspects of radiotracer imaging, ultimately leading to Nuclear Medicine's emergence as an important component of current medical practice. Nuclear Medicine's unique ability to characterize in vivo biology without perturbing it will assure its ongoing role in a practice of medicine increasingly driven by molecular biology. However, in the future, it is likely that advances in molecular biology and radiopharmaceutical chemistry will increasingly direct future developments in Nuclear Medicine physics, rather than relying on physics as the primary driver of advances in Nuclear Medicine. Working hand-in-hand with clinicians, chemists, and biologists, Nuclear Medicine physicists can greatly enhance the specialty by creating more sensitive and robust imaging devices, by enabling more facile and sophisticated image analysis to yield quantitative measures of regional in vivo biology, and by combining the strengths of radiotracer imaging with other imaging modalities in hybrid devices, with the overall goal to enhance Nuclear Medicine's ability to characterize regional in vivo biology.

[Medical imaging in tumor precision medicine: opportunities and challenges].

PubMed

Xu, Jingjing; Tan, Yanbin; Zhang, Minming

2017-05-25

Tumor precision medicine is an emerging approach for tumor diagnosis, treatment and prevention, which takes account of individual variability of environment, lifestyle and genetic information. Tumor precision medicine is built up on the medical imaging innovations developed during the past decades, including the new hardware, new imaging agents, standardized protocols, image analysis and multimodal imaging fusion technology. Also the development of automated and reproducible analysis algorithm has extracted large amount of information from image-based features. With the continuous development and mining of tumor clinical and imaging databases, the radiogenomics, radiomics and artificial intelligence have been flourishing. Therefore, these new technological advances bring new opportunities and challenges to the application of imaging in tumor precision medicine.

Are we at a crossroads or a plateau? Radiomics and machine learning in abdominal oncology imaging.

PubMed

Summers, Ronald M

2018-05-05

Advances in radiomics and machine learning have driven a technology boom in the automated analysis of radiology images. For the past several years, expectations have been nearly boundless for these new technologies to revolutionize radiology image analysis and interpretation. In this editorial, I compare the expectations with the realities with particular attention to applications in abdominal oncology imaging. I explore whether these technologies will leave us at a crossroads to an exciting future or to a sustained plateau and disillusionment.

Synergistic advances in diagnostic and therapeutic medical ultrasound

NASA Astrophysics Data System (ADS)

Lizzi, Frederic L.

2003-04-01

Significant advances are more fully exploiting ultrasound's potential for noninvasive diagnosis and treatment. Therapeutic systems employ intense focused beams to thermally kill cancer cells in, e.g., prostate; to stop bleeding; and to treat specific diseases (e.g., glaucoma). Diagnostic ultrasound techniques can quantitatively image an increasingly broad spectrum of physical tissue attributes. An exciting aspect of this progress is the emerging synergy between these modalities. Advanced diagnostic techniques may contribute at several stages in therapy. For example, treatment planning for small ocular tumors uses 50-MHz, 3-D ultrasonic images with 0.05-mm resolution. Thermal simulations employ these images to evaluate desired and undesired effects using exposure stategies with specially designed treatment beams. Therapy beam positioning can use diagnostic elastography to sense tissue motion induced by radiation pressure from high-intensity treatment beams. Therapy monitoring can sense lesion formation using elastography motion sensing (to detect the increased stiffness in lesions); harmonic imaging (to sense altered nonlinear properties); and spectrum analysis images (depicting changes in the sizes, concentration, and configuration of sub-resolution structures.) Experience from these applications will greatly expand the knowledge of acoustic phenomena in living tissues and should lead to further advances in medical ultrasound.

A novel spinal kinematic analysis using X-ray imaging and vicon motion analysis: a case study.

PubMed

Noh, Dong K; Lee, Nam G; You, Joshua H

2014-01-01

This study highlights a novel spinal kinematic analysis method and the feasibility of X-ray imaging measurements to accurately assess thoracic spine motion. The advanced X-ray Nash-Moe method and analysis were used to compute the segmental range of motion in thoracic vertebra pedicles in vivo. This Nash-Moe X-ray imaging method was compared with a standardized method using the Vicon 3-dimensional motion capture system. Linear regression analysis showed an excellent and significant correlation between the two methods (R2 = 0.99, p < 0.05), suggesting that the analysis of spinal segmental range of motion using X-ray imaging measurements was accurate and comparable to the conventional 3-dimensional motion analysis system. Clinically, this novel finding is compelling evidence demonstrating that measurements with X-ray imaging are useful to accurately decipher pathological spinal alignment and movement impairments in idiopathic scoliosis (IS).

Advanced image based methods for structural integrity monitoring: Review and prospects

NASA Astrophysics Data System (ADS)

Farahani, Behzad V.; Sousa, Pedro José; Barros, Francisco; Tavares, Paulo J.; Moreira, Pedro M. G. P.

2018-02-01

There is a growing trend in engineering to develop methods for structural integrity monitoring and characterization of in-service mechanical behaviour of components. The fast growth in recent years of image processing techniques and image-based sensing for experimental mechanics, brought about a paradigm change in phenomena sensing. Hence, several widely applicable optical approaches are playing a significant role in support of experiment. The current review manuscript describes advanced image based methods for structural integrity monitoring, and focuses on methods such as Digital Image Correlation (DIC), Thermoelastic Stress Analysis (TSA), Electronic Speckle Pattern Interferometry (ESPI) and Speckle Pattern Shearing Interferometry (Shearography). These non-contact full-field techniques rely on intensive image processing methods to measure mechanical behaviour, and evolve even as reviews such as this are being written, which justifies a special effort to keep abreast of this progress.

Application of STEM characterization for investigating radiation effects in BCC Fe-based alloys

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

Parish, Chad M.; Field, Kevin G.; Certain, Alicia G.

2015-04-20

This paper provides a general overview of advanced scanning transmission electron microscopy (STEM) techniques used for characterization of irradiated BCC Fe-based alloys. Advanced STEM methods provide the high-resolution imaging and chemical analysis necessary to understand the irradiation response of BCC Fe-based alloys. The use of STEM with energy dispersive x-ray spectroscopy (EDX) for measurement of radiation-induced segregation (RIS) is described, with an illustrated example of RIS in proton- and self-ion irradiated T91. Aberration-corrected STEM-EDX for nanocluster/nanoparticle imaging and chemical analysis is also discussed, and examples are provided from ion-irradiated oxide dispersion strengthened (ODS) alloys. In conclusion, STEM techniques for void,more » cavity, and dislocation loop imaging are described, with examples from various BCC Fe-based alloys.« less

Microfluidic Imaging Flow Cytometry by Asymmetric-detection Time-stretch Optical Microscopy (ATOM).

PubMed

Tang, Anson H L; Lai, Queenie T K; Chung, Bob M F; Lee, Kelvin C M; Mok, Aaron T Y; Yip, G K; Shum, Anderson H C; Wong, Kenneth K Y; Tsia, Kevin K

2017-06-28

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been the main trend in the advanced development of flow cytometry. Notably, adding high-resolution imaging capabilities allows for the complex morphological analysis of cellular/sub-cellular structures. This is not possible with standard flow cytometers. However, it is valuable for advancing our knowledge of cellular functions and can benefit life science research, clinical diagnostics, and environmental monitoring. Incorporating imaging capabilities into flow cytometry compromises the assay throughput, primarily due to the limitations on speed and sensitivity in the camera technologies. To overcome this speed or throughput challenge facing imaging flow cytometry while preserving the image quality, asymmetric-detection time-stretch optical microscopy (ATOM) has been demonstrated to enable high-contrast, single-cell imaging with sub-cellular resolution, at an imaging throughput as high as 100,000 cells/s. Based on the imaging concept of conventional time-stretch imaging, which relies on all-optical image encoding and retrieval through the use of ultrafast broadband laser pulses, ATOM further advances imaging performance by enhancing the image contrast of unlabeled/unstained cells. This is achieved by accessing the phase-gradient information of the cells, which is spectrally encoded into single-shot broadband pulses. Hence, ATOM is particularly advantageous in high-throughput measurements of single-cell morphology and texture - information indicative of cell types, states, and even functions. Ultimately, this could become a powerful imaging flow cytometry platform for the biophysical phenotyping of cells, complementing the current state-of-the-art biochemical-marker-based cellular assay. This work describes a protocol to establish the key modules of an ATOM system (from optical frontend to data processing and visualization backend), as well as the workflow of imaging flow cytometry based on ATOM, using human cells and micro-algae as the examples.

Single-Cell Analysis Using Hyperspectral Imaging Modalities.

PubMed

Mehta, Nishir; Shaik, Shahensha; Devireddy, Ram; Gartia, Manas Ranjan

2018-02-01

Almost a decade ago, hyperspectral imaging (HSI) was employed by the NASA in satellite imaging applications such as remote sensing technology. This technology has since been extensively used in the exploration of minerals, agricultural purposes, water resources, and urban development needs. Due to recent advancements in optical re-construction and imaging, HSI can now be applied down to micro- and nanometer scales possibly allowing for exquisite control and analysis of single cell to complex biological systems. This short review provides a description of the working principle of the HSI technology and how HSI can be used to assist, substitute, and validate traditional imaging technologies. This is followed by a description of the use of HSI for biological analysis and medical diagnostics with emphasis on single-cell analysis using HSI.

Advances in medical image computing.

PubMed

Tolxdorff, T; Deserno, T M; Handels, H; Meinzer, H-P

2009-01-01

Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care. In this issue, selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing. The winners of scientific awards of the German Conference on Medical Image Processing (BVM) 2008 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, seven excellent papers were selected to describe important aspects of recent advances in the field of medical image processing. The selected papers give an impression of the breadth and heterogeneity of new developments. New methods for improved image segmentation, non-linear image registration and modeling of organs are presented together with applications of image analysis methods in different medical disciplines. Furthermore, state-of-the-art tools and techniques to support the development and evaluation of medical image processing systems in practice are described. The selected articles describe different aspects of the intense development in medical image computing. The image processing methods presented enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

Quantitative analysis of phosphoinositide 3-kinase (PI3K) signaling using live-cell total internal reflection fluorescence (TIRF) microscopy.

PubMed

Johnson, Heath E; Haugh, Jason M

2013-12-02

This unit focuses on the use of total internal reflection fluorescence (TIRF) microscopy and image analysis methods to study the dynamics of signal transduction mediated by class I phosphoinositide 3-kinases (PI3Ks) in mammalian cells. The first four protocols cover live-cell imaging experiments, image acquisition parameters, and basic image processing and segmentation. These methods are generally applicable to live-cell TIRF experiments. The remaining protocols outline more advanced image analysis methods, which were developed in our laboratory for the purpose of characterizing the spatiotemporal dynamics of PI3K signaling. These methods may be extended to analyze other cellular processes monitored using fluorescent biosensors. Copyright © 2013 John Wiley & Sons, Inc.

In vivo imaging of advanced glycation end products (AGEs) of albumin: first observations of significantly reduced clearance and liver deposition properties in mice.

PubMed

Tsutsui, Ayumi; Ogura, Akihiro; Tahara, Tsuyoshi; Nozaki, Satoshi; Urano, Sayaka; Hara, Mitsuko; Kojima, Soichi; Kurbangalieva, Almira; Onoe, Hirotaka; Watanabe, Yasuyoshi; Taniguchi, Naoyuki; Tanaka, Katsunori

2016-06-15

Advanced glycation end products (AGEs) are associated with various diseases, especially during aging and the development of diabetes and uremia. To better understand these biological processes, investigation of the in vivo kinetics of AGEs, i.e., analysis of trafficking and clearance properties, was carried out by molecular imaging. Following the preparation of Cy7.5-labeled AGE-albumin and intravenous injection in BALB/cA-nu/nu mice, noninvasive fluorescence kinetics analysis was performed. In vivo imaging and fluorescence microscopy analysis revealed that non-enzymatic AGEs were smoothly captured by scavenger cells in the liver, i.e., Kupffer and other sinusoidal cells, but were unable to be properly cleared from the body. Overall, these results highlight an important link between AGEs and various disorders associated with them, which may serve as a platform for future research to better understand the processes and mechanisms of these disorders.

Evaluation of Alzheimer's disease by analysis of MR images using Objective Dialectical Classifiers as an alternative to ADC maps.

PubMed

Dos Santos, Wellington P; de Assis, Francisco M; de Souza, Ricardo E; Dos Santos Filho, Plinio B

2008-01-01

Alzheimer's disease is the most common cause of dementia, yet hard to diagnose precisely without invasive techniques, particularly at the onset of the disease. This work approaches image analysis and classification of synthetic multispectral images composed by diffusion-weighted (DW) magnetic resonance (MR) cerebral images for the evaluation of cerebrospinal fluid area and measuring the advance of Alzheimer's disease. A clinical 1.5 T MR imaging system was used to acquire all images presented. The classification methods are based on Objective Dialectical Classifiers, a new method based on Dialectics as defined in the Philosophy of Praxis. A 2-degree polynomial network with supervised training is used to generate the ground truth image. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map.

Recent advances in the development and application of nanoelectrodes.

PubMed

Fan, Yunshan; Han, Chu; Zhang, Bo

2016-10-07

Nanoelectrodes have key advantages compared to electrodes of conventional size and are the tool of choice for numerous applications in both fundamental electrochemistry research and bioelectrochemical analysis. This Minireview summarizes recent advances in the development, characterization, and use of nanoelectrodes in nanoscale electroanalytical chemistry. Methods of nanoelectrode preparation include laser-pulled glass-sealed metal nanoelectrodes, mass-produced nanoelectrodes, carbon nanotube based and carbon-filled nanopipettes, and tunneling nanoelectrodes. Several new topics of their recent application are covered, which include the use of nanoelectrodes for electrochemical imaging at ultrahigh spatial resolution, imaging with nanoelectrodes and nanopipettes, electrochemical analysis of single cells, single enzymes, and single nanoparticles, and the use of nanoelectrodes to understand single nanobubbles.

Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application-Part 2: From Clinical Implementation to Enterprise.

PubMed

Shaikh, Faiq; Franc, Benjamin; Allen, Erastus; Sala, Evis; Awan, Omer; Hendrata, Kenneth; Halabi, Safwan; Mohiuddin, Sohaib; Malik, Sana; Hadley, Dexter; Shrestha, Rasu

2018-03-01

Enterprise imaging has channeled various technological innovations to the field of clinical radiology, ranging from advanced imaging equipment and postacquisition iterative reconstruction tools to image analysis and computer-aided detection tools. More recently, the advancement in the field of quantitative image analysis coupled with machine learning-based data analytics, classification, and integration has ushered in the era of radiomics, a paradigm shift that holds tremendous potential in clinical decision support as well as drug discovery. However, there are important issues to consider to incorporate radiomics into a clinically applicable system and a commercially viable solution. In this two-part series, we offer insights into the development of the translational pipeline for radiomics from methodology to clinical implementation (Part 1) and from that point to enterprise development (Part 2). In Part 2 of this two-part series, we study the components of the strategy pipeline, from clinical implementation to building enterprise solutions. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Functional optical coherence tomography for live dynamic analysis of mouse embryonic cardiogenesis

NASA Astrophysics Data System (ADS)

Wang, Shang; Lopez, Andrew L.; Larina, Irina V.

2018-02-01

Blood flow, heart contraction, and tissue stiffness are important regulators of cardiac morphogenesis and function during embryonic development. Defining how these factors are integrated is critically important to advance prevention, diagnostics, and treatment of congenital heart defects. Mammalian embryonic development is taking place deep within the female body, which makes cardiodynamic imaging and analysis during early developmental stages in humans inaccessible. With thousands of mutant lines available and well-established genetic manipulation tools, mouse is a great model to understand how biomechanical factors are integrated with molecular pathways to regulate cardiac function and development. Dynamic imaging and quantitative analysis of the biomechanics of live mouse embryos have become increasingly important, which demands continuous advancements in imaging techniques and live assessment approaches. This has been one of the major drives to keep pushing the frontier of embryonic imaging for better resolution, higher speed, deeper penetration, and more diverse and effective contrasts. Optical coherence tomography (OCT) has played a significant role in addressing such demands, and its features in non-labeling imaging, 3D capability, a large working distance, and various functional derivatives allow OCT to cover a number of specific applications in embryonic imaging. Recently, our group has made several technical improvements in using OCT to probe the biomechanical aspects of live developing mouse embryos at early stages. These include the direct volumetric structural and functional imaging of the cardiodynamics, four-dimensional quantitative Doppler imaging and analysis of the cardiac blood flow, and fourdimensional blood flow separation from the cardiac wall tissue in the beating embryonic heart. Here, we present a short review of these studies together with brief descriptions of the previous work that demonstrate OCT as a valuable and useful imaging tool for the research in developmental cardiology.

Medical Imaging System

NASA Technical Reports Server (NTRS)

1991-01-01

The MD Image System, a true-color image processing system that serves as a diagnostic aid and tool for storage and distribution of images, was developed by Medical Image Management Systems, Huntsville, AL, as a "spinoff from a spinoff." The original spinoff, Geostar 8800, developed by Crystal Image Technologies, Huntsville, incorporates advanced UNIX versions of ELAS (developed by NASA's Earth Resources Laboratory for analysis of Landsat images) for general purpose image processing. The MD Image System is an application of this technology to a medical system that aids in the diagnosis of cancer, and can accept, store and analyze images from other sources such as Magnetic Resonance Imaging.

An advanced software suite for the processing and analysis of silicon luminescence images

NASA Astrophysics Data System (ADS)

Payne, D. N. R.; Vargas, C.; Hameiri, Z.; Wenham, S. R.; Bagnall, D. M.

2017-06-01

Luminescence imaging is a versatile characterisation technique used for a broad range of research and industrial applications, particularly for the field of photovoltaics where photoluminescence and electroluminescence imaging is routinely carried out for materials analysis and quality control. Luminescence imaging can reveal a wealth of material information, as detailed in extensive literature, yet these techniques are often only used qualitatively instead of being utilised to their full potential. Part of the reason for this is the time and effort required for image processing and analysis in order to convert image data to more meaningful results. In this work, a custom built, Matlab based software suite is presented which aims to dramatically simplify luminescence image processing and analysis. The suite includes four individual programs which can be used in isolation or in conjunction to achieve a broad array of functionality, including but not limited to, point spread function determination and deconvolution, automated sample extraction, image alignment and comparison, minority carrier lifetime calibration and iron impurity concentration mapping.

IDIMS/GEOPAK: Users manual for a geophysical data display and analysis system

NASA Technical Reports Server (NTRS)

Libert, J. M.

1982-01-01

The application of an existing image analysis system to the display and analysis of geophysical data is described, the potential for expanding the capabilities of such a system toward more advanced computer analytic and modeling functions is investigated. The major features of the IDIMS (Interactive Display and Image Manipulation System) and its applicability for image type analysis of geophysical data are described. Development of a basic geophysical data processing system to permit the image representation, coloring, interdisplay and comparison of geophysical data sets using existing IDIMS functions and to provide for the production of hard copies of processed images was described. An instruction manual and documentation for the GEOPAK subsystem was produced. A training course for personnel in the use of the IDIMS/GEOPAK was conducted. The effectiveness of the current IDIMS/GEOPAK system for geophysical data analysis was evaluated.

Radiomics: Extracting more information from medical images using advanced feature analysis

PubMed Central

Lambin, Philippe; Rios-Velazquez, Emmanuel; Leijenaar, Ralph; Carvalho, Sara; van Stiphout, Ruud G.P.M.; Granton, Patrick; Zegers, Catharina M.L.; Gillies, Robert; Boellard, Ronald; Dekker, André; Aerts, Hugo J.W.L.

2015-01-01

Solid cancers are spatially and temporally heterogeneous. This limits the use of invasive biopsy based molecular assays but gives huge potential for medical imaging, which has the ability to capture intra-tumoural heterogeneity in a non-invasive way. During the past decades, medical imaging innovations with new hardware, new imaging agents and standardised protocols, allows the field to move towards quantitative imaging. Therefore, also the development of automated and reproducible analysis methodologies to extract more information from image-based features is a requirement. Radiomics – the high-throughput extraction of large amounts of image features from radiographic images – addresses this problem and is one of the approaches that hold great promises but need further validation in multi-centric settings and in the laboratory. PMID:22257792

A complete database for the Einstein imaging proportional counter

NASA Technical Reports Server (NTRS)

Helfand, David J.

1991-01-01

A complete database for the Einstein Imaging Proportional Counter (IPC) was completed. The original data that makes up the archive is described as well as the structure of the database, the Op-Ed analysis system, the technical advances achieved relative to the analysis of (IPC) data, the data products produced, and some uses to which the database has been put by scientists outside Columbia University over the past year.

The Bushbaby Optic Nerve: Fiber Count and Fiber Diameter Spectrum

DTIC Science & Technology

1986-03-01

laminar organization of rece,)tive field properties in the lateral geniculate nucleus of bushbaby (Norton and Casagrande, 1982), the organization of...field properties in lateral geniculate nucleus of bushbaby (Galago cras- sicaudatus). Journal of Neurophysiology. 47(4):715-741. O’Fiaherty, J.J...employed an advanced digitized image analysis system (Carl Zeiss Inc., Videoplan Image Analysis System)* to more accurately and rapidly collect, analyze, and

Advanced image collection, information extraction, and change detection in support of NN-20 broad area search and analysis

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

Petrie, G.M.; Perry, E.M.; Kirkham, R.R.

1997-09-01

This report describes the work performed at the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy`s Office of Nonproliferation and National Security, Office of Research and Development (NN-20). The work supports the NN-20 Broad Area Search and Analysis, a program initiated by NN-20 to improve the detection and classification of undeclared weapons facilities. Ongoing PNNL research activities are described in three main components: image collection, information processing, and change analysis. The Multispectral Airborne Imaging System, which was developed to collect georeferenced imagery in the visible through infrared regions of the spectrum, and flown on a light aircraftmore » platform, will supply current land use conditions. The image information extraction software (dynamic clustering and end-member extraction) uses imagery, like the multispectral data collected by the PNNL multispectral system, to efficiently generate landcover information. The advanced change detection uses a priori (benchmark) information, current landcover conditions, and user-supplied rules to rank suspect areas by probable risk of undeclared facilities or proliferation activities. These components, both separately and combined, provide important tools for improving the detection of undeclared facilities.« less

Determination of representative elementary areas for soil redoximorphic features by digital image processing

USDA-ARS?s Scientific Manuscript database

Photography has been a welcome tool in documenting and conveying qualitative soil information. When coupled with image analysis software, the usefulness of digital cameras can be increased to advance the field of micropedology. The determination of a Representative Elementary Area (REA) still rema...

Open source software projects of the caBIG In Vivo Imaging Workspace Software special interest group.

PubMed

Prior, Fred W; Erickson, Bradley J; Tarbox, Lawrence

2007-11-01

The Cancer Bioinformatics Grid (caBIG) program was created by the National Cancer Institute to facilitate sharing of IT infrastructure, data, and applications among the National Cancer Institute-sponsored cancer research centers. The program was launched in February 2004 and now links more than 50 cancer centers. In April 2005, the In Vivo Imaging Workspace was added to promote the use of imaging in cancer clinical trials. At the inaugural meeting, four special interest groups (SIGs) were established. The Software SIG was charged with identifying projects that focus on open-source software for image visualization and analysis. To date, two projects have been defined by the Software SIG. The eXtensible Imaging Platform project has produced a rapid application development environment that researchers may use to create targeted workflows customized for specific research projects. The Algorithm Validation Tools project will provide a set of tools and data structures that will be used to capture measurement information and associated needed to allow a gold standard to be defined for the given database against which change analysis algorithms can be tested. Through these and future efforts, the caBIG In Vivo Imaging Workspace Software SIG endeavors to advance imaging informatics and provide new open-source software tools to advance cancer research.

A high-resolution radio image of a young supernova

NASA Technical Reports Server (NTRS)

Bartel, N.; Rupen, M. P.; Shapiro, I. I.; Preston, R. A.; Rius, A.

1991-01-01

A VLBI radio images of the bright supernova 1986J, which occurred in the galaxy NGC891 at a distance of about 12 Mpc, is presented. No detailed image of any supernova or remnant has been obtained before so soon after the explosion. The image shows a shell of emission with jetlike protrusions. Analysis of the images should advance understanding of the dynamics of the expanding debris, the dissipation of energy into the surrounding circumstellar medium, and the evolution of the supernova into the remnant.

Recent Advances in Compressed Sensing: Discrete Uncertainty Principles and Fast Hyperspectral Imaging

DTIC Science & Technology

2015-03-26

Fourier Analysis and Applications, vol. 14, pp. 838–858, 2008. 11. D. J. Cooke, “A discrete X - ray transform for chromotomographic hyperspectral imaging ... medical imaging , e.g., magnetic resonance imaging (MRI). Since the early 1980s, MRI has granted doctors the ability to distinguish between healthy tissue...i.e., at most K entries of x are nonzero. In many settings, this is a valid signal model; for example, JPEG2000 exploits the fact that natural images

Image Analysis of DNA Fiber and Nucleus in Plants.

PubMed

Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

2016-01-01

Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei.

Advancing multiscale structural mapping of the brain through fluorescence imaging and analysis across length scales

PubMed Central

Hogstrom, L. J.; Guo, S. M.; Murugadoss, K.; Bathe, M.

2016-01-01

Brain function emerges from hierarchical neuronal structure that spans orders of magnitude in length scale, from the nanometre-scale organization of synaptic proteins to the macroscopic wiring of neuronal circuits. Because the synaptic electrochemical signal transmission that drives brain function ultimately relies on the organization of neuronal circuits, understanding brain function requires an understanding of the principles that determine hierarchical neuronal structure in living or intact organisms. Recent advances in fluorescence imaging now enable quantitative characterization of neuronal structure across length scales, ranging from single-molecule localization using super-resolution imaging to whole-brain imaging using light-sheet microscopy on cleared samples. These tools, together with correlative electron microscopy and magnetic resonance imaging at the nanoscopic and macroscopic scales, respectively, now facilitate our ability to probe brain structure across its full range of length scales with cellular and molecular specificity. As these imaging datasets become increasingly accessible to researchers, novel statistical and computational frameworks will play an increasing role in efforts to relate hierarchical brain structure to its function. In this perspective, we discuss several prominent experimental advances that are ushering in a new era of quantitative fluorescence-based imaging in neuroscience along with novel computational and statistical strategies that are helping to distil our understanding of complex brain structure. PMID:26855758

Contribution to the benchmark for ternary mixtures: Transient analysis in microgravity conditions.

PubMed

Ahadi, Amirhossein; Ziad Saghir, M

2015-04-01

We present a transient experimental analysis of the DCMIX1 project conducted onboard the International Space Station for a ternary tetrahydronaphtalene, isobutylbenzene, n-dodecane mixture. Raw images taken in microgravity environment using the SODI (Selectable Optical Diagnostic) apparatus which is equipped with two wavelength diagnostic were processed and the results were analyzed in this work. We measured the concentration profile of the mixture containing 80% THN, 10% IBB and 10% nC12 during the entire experiment using an advanced image processing technique and accordingly we determined the Soret coefficients using an advanced curve-fitting and post-processing technique. It must be noted that the experiment has been repeated five times to ensure the repeatability of the experiment.

TU-AB-204-03: Advances in CBCT for Orhtopaedics and Bone Health Imaging

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

Zbijewski, W.

This symposium highlights advanced cone-beam CT (CBCT) technologies in four areas of emerging application in diagnostic imaging and image-guided interventions. Each area includes research that extends the spatial, temporal, and/or contrast resolution characteristics of CBCT beyond conventional limits through advances in scanner technology, acquisition protocols, and 3D image reconstruction techniques. Dr. G. Chen (University of Wisconsin) will present on the topic: Advances in C-arm CBCT for Brain Perfusion Imaging. Stroke is a leading cause of death and disability, and a fraction of people having an acute ischemic stroke are suitable candidates for endovascular therapy. Critical factors that affect both themore » likelihood of successful revascularization and good clinical outcome are: 1) the time between stroke onset and revascularization; and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from patients with a large ischemic core and little or no penumbra. Therefore, “time is brain” in the care of the stroke patients. C-arm CBCT systems widely available in angiography suites have the potential to generate non-contrast-enhanced CBCT images to exclude the presence of hemorrhage, time-resolved CBCT angiography to evaluate the site of occlusion and collaterals, and CBCT perfusion parametric images to assess the extent of the ischemic core and penumbra, thereby fulfilling the imaging requirements of a “one-stop-shop” in the angiography suite to reduce the time between onset and revascularization therapy. The challenges and opportunities to advance CBCT technology to fully enable the one-stop-shop C-arm CBCT platform for brain imaging will be discussed. Dr. R. Fahrig (Stanford University) will present on the topic: Advances in C-arm CBCT for Cardiac Interventions. With the goal of providing functional information during cardiac interventions, significant effort has been expended to improve the quantitative accuracy of C-arm CBCT reconstructions. The challenge is to improve image quality while providing very short turnaround between data acquisition and volume data visualization. Corrections for x-ray scatter, view aliasing and patient motion that require no more than 2 iterations keep processing time short while reducing artifact. Fast, multi-sweep acquisitions can be used to permit assessment of left ventricular function, and visualization of radiofrequency lesions created to treat arrhythmias. Workflows for each imaging goal have been developed and validated against gold standard clinical CT or histology. The challenges, opportunities, and limitations of the new functional C-arm CBCT imaging techniques will be discussed. Dr. W. Zbijewski (Johns Hopkins University) will present on the topic: Advances in CBCT for Orthopaedics and Bone Health Imaging. Cone-beam CT is particularly well suited for imaging of musculoskeletal extremities. Owing to the high spatial resolution of flat-panel detectors, CBCT can surpass conventional CT in imaging tasks involving bone visualization, quantitative analysis of subchondral trabecular structure, and visualization and monitoring of subtle fractures that are common in orthopedic radiology. A dedicated CBCT platform has been developed that offers flexibility in system design and provides not only a compact configuration with improved logistics for extremities imaging but also enables novel diagnostic capabilities such as imaging of weight-bearing lower extremities in a natural stance. The design, development and clinical performance of dedicated extremities CBCT systems will be presented. Advanced capabilities for quantitative volumetric assessment of joint space morphology, dual-energy image-based quantification of bone composition, and in-vivo analysis of bone microarchitecture will be discussed, along with emerging applications in the diagnosis of arthritis and osteoporosis and assessment of novel therapies. Finally, Dr. J. Boone (UC Davis) will present on the topic: Advances in CBCT for Breast Imaging. Breast CT has been studied as an imaging tool for diagnostic breast evaluation and for potential breast cancer screening. The breast CT application lends itself to CBCT because of the small dimensions of the breast, the tapered shape of the breast towards higher cone angle, and the fact that there are no bones in the breast. The performance of various generations of breast CT scanners developed in recent years will be discussed, focusing on advances in spatial resolution and image noise characteristics. The results will also demonstrate the results of clinical trials using both computer and human observers. Learning Objectives: Understand the challenges, key technological advances, and emerging opportunities of CBCT in: Brain perfusion imaging, including assessment of ischemic stroke Cardiac imaging for functional assessment in cardiac interventions Orthopedics imaging for evaluation of musculoskeletal trauma, arthritis, and osteoporosis Breast imaging for screening and diagnosis of breast cancer. Work presented in this symposium includes research support by: Siemens Healthcare (Dr. Chen); NIH and Siemens Healthcare (Dr. Fahrig); NIH and Carestream Health (Dr. Zbijewski); and NIH (Dr. Boone)« less

TU-AB-204-01: Advances in C-Arm CBCT for Brain Perfusion Imaging

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

Chen, G.

This symposium highlights advanced cone-beam CT (CBCT) technologies in four areas of emerging application in diagnostic imaging and image-guided interventions. Each area includes research that extends the spatial, temporal, and/or contrast resolution characteristics of CBCT beyond conventional limits through advances in scanner technology, acquisition protocols, and 3D image reconstruction techniques. Dr. G. Chen (University of Wisconsin) will present on the topic: Advances in C-arm CBCT for Brain Perfusion Imaging. Stroke is a leading cause of death and disability, and a fraction of people having an acute ischemic stroke are suitable candidates for endovascular therapy. Critical factors that affect both themore » likelihood of successful revascularization and good clinical outcome are: 1) the time between stroke onset and revascularization; and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from patients with a large ischemic core and little or no penumbra. Therefore, “time is brain” in the care of the stroke patients. C-arm CBCT systems widely available in angiography suites have the potential to generate non-contrast-enhanced CBCT images to exclude the presence of hemorrhage, time-resolved CBCT angiography to evaluate the site of occlusion and collaterals, and CBCT perfusion parametric images to assess the extent of the ischemic core and penumbra, thereby fulfilling the imaging requirements of a “one-stop-shop” in the angiography suite to reduce the time between onset and revascularization therapy. The challenges and opportunities to advance CBCT technology to fully enable the one-stop-shop C-arm CBCT platform for brain imaging will be discussed. Dr. R. Fahrig (Stanford University) will present on the topic: Advances in C-arm CBCT for Cardiac Interventions. With the goal of providing functional information during cardiac interventions, significant effort has been expended to improve the quantitative accuracy of C-arm CBCT reconstructions. The challenge is to improve image quality while providing very short turnaround between data acquisition and volume data visualization. Corrections for x-ray scatter, view aliasing and patient motion that require no more than 2 iterations keep processing time short while reducing artifact. Fast, multi-sweep acquisitions can be used to permit assessment of left ventricular function, and visualization of radiofrequency lesions created to treat arrhythmias. Workflows for each imaging goal have been developed and validated against gold standard clinical CT or histology. The challenges, opportunities, and limitations of the new functional C-arm CBCT imaging techniques will be discussed. Dr. W. Zbijewski (Johns Hopkins University) will present on the topic: Advances in CBCT for Orthopaedics and Bone Health Imaging. Cone-beam CT is particularly well suited for imaging of musculoskeletal extremities. Owing to the high spatial resolution of flat-panel detectors, CBCT can surpass conventional CT in imaging tasks involving bone visualization, quantitative analysis of subchondral trabecular structure, and visualization and monitoring of subtle fractures that are common in orthopedic radiology. A dedicated CBCT platform has been developed that offers flexibility in system design and provides not only a compact configuration with improved logistics for extremities imaging but also enables novel diagnostic capabilities such as imaging of weight-bearing lower extremities in a natural stance. The design, development and clinical performance of dedicated extremities CBCT systems will be presented. Advanced capabilities for quantitative volumetric assessment of joint space morphology, dual-energy image-based quantification of bone composition, and in-vivo analysis of bone microarchitecture will be discussed, along with emerging applications in the diagnosis of arthritis and osteoporosis and assessment of novel therapies. Finally, Dr. J. Boone (UC Davis) will present on the topic: Advances in CBCT for Breast Imaging. Breast CT has been studied as an imaging tool for diagnostic breast evaluation and for potential breast cancer screening. The breast CT application lends itself to CBCT because of the small dimensions of the breast, the tapered shape of the breast towards higher cone angle, and the fact that there are no bones in the breast. The performance of various generations of breast CT scanners developed in recent years will be discussed, focusing on advances in spatial resolution and image noise characteristics. The results will also demonstrate the results of clinical trials using both computer and human observers. Learning Objectives: Understand the challenges, key technological advances, and emerging opportunities of CBCT in: Brain perfusion imaging, including assessment of ischemic stroke Cardiac imaging for functional assessment in cardiac interventions Orthopedics imaging for evaluation of musculoskeletal trauma, arthritis, and osteoporosis Breast imaging for screening and diagnosis of breast cancer. Work presented in this symposium includes research support by: Siemens Healthcare (Dr. Chen); NIH and Siemens Healthcare (Dr. Fahrig); NIH and Carestream Health (Dr. Zbijewski); and NIH (Dr. Boone)« less

TU-AB-204-04: Advances in CBCT for Breast Imaging

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

Boone, J.

This symposium highlights advanced cone-beam CT (CBCT) technologies in four areas of emerging application in diagnostic imaging and image-guided interventions. Each area includes research that extends the spatial, temporal, and/or contrast resolution characteristics of CBCT beyond conventional limits through advances in scanner technology, acquisition protocols, and 3D image reconstruction techniques. Dr. G. Chen (University of Wisconsin) will present on the topic: Advances in C-arm CBCT for Brain Perfusion Imaging. Stroke is a leading cause of death and disability, and a fraction of people having an acute ischemic stroke are suitable candidates for endovascular therapy. Critical factors that affect both themore » likelihood of successful revascularization and good clinical outcome are: 1) the time between stroke onset and revascularization; and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from patients with a large ischemic core and little or no penumbra. Therefore, “time is brain” in the care of the stroke patients. C-arm CBCT systems widely available in angiography suites have the potential to generate non-contrast-enhanced CBCT images to exclude the presence of hemorrhage, time-resolved CBCT angiography to evaluate the site of occlusion and collaterals, and CBCT perfusion parametric images to assess the extent of the ischemic core and penumbra, thereby fulfilling the imaging requirements of a “one-stop-shop” in the angiography suite to reduce the time between onset and revascularization therapy. The challenges and opportunities to advance CBCT technology to fully enable the one-stop-shop C-arm CBCT platform for brain imaging will be discussed. Dr. R. Fahrig (Stanford University) will present on the topic: Advances in C-arm CBCT for Cardiac Interventions. With the goal of providing functional information during cardiac interventions, significant effort has been expended to improve the quantitative accuracy of C-arm CBCT reconstructions. The challenge is to improve image quality while providing very short turnaround between data acquisition and volume data visualization. Corrections for x-ray scatter, view aliasing and patient motion that require no more than 2 iterations keep processing time short while reducing artifact. Fast, multi-sweep acquisitions can be used to permit assessment of left ventricular function, and visualization of radiofrequency lesions created to treat arrhythmias. Workflows for each imaging goal have been developed and validated against gold standard clinical CT or histology. The challenges, opportunities, and limitations of the new functional C-arm CBCT imaging techniques will be discussed. Dr. W. Zbijewski (Johns Hopkins University) will present on the topic: Advances in CBCT for Orthopaedics and Bone Health Imaging. Cone-beam CT is particularly well suited for imaging of musculoskeletal extremities. Owing to the high spatial resolution of flat-panel detectors, CBCT can surpass conventional CT in imaging tasks involving bone visualization, quantitative analysis of subchondral trabecular structure, and visualization and monitoring of subtle fractures that are common in orthopedic radiology. A dedicated CBCT platform has been developed that offers flexibility in system design and provides not only a compact configuration with improved logistics for extremities imaging but also enables novel diagnostic capabilities such as imaging of weight-bearing lower extremities in a natural stance. The design, development and clinical performance of dedicated extremities CBCT systems will be presented. Advanced capabilities for quantitative volumetric assessment of joint space morphology, dual-energy image-based quantification of bone composition, and in-vivo analysis of bone microarchitecture will be discussed, along with emerging applications in the diagnosis of arthritis and osteoporosis and assessment of novel therapies. Finally, Dr. J. Boone (UC Davis) will present on the topic: Advances in CBCT for Breast Imaging. Breast CT has been studied as an imaging tool for diagnostic breast evaluation and for potential breast cancer screening. The breast CT application lends itself to CBCT because of the small dimensions of the breast, the tapered shape of the breast towards higher cone angle, and the fact that there are no bones in the breast. The performance of various generations of breast CT scanners developed in recent years will be discussed, focusing on advances in spatial resolution and image noise characteristics. The results will also demonstrate the results of clinical trials using both computer and human observers. Learning Objectives: Understand the challenges, key technological advances, and emerging opportunities of CBCT in: Brain perfusion imaging, including assessment of ischemic stroke Cardiac imaging for functional assessment in cardiac interventions Orthopedics imaging for evaluation of musculoskeletal trauma, arthritis, and osteoporosis Breast imaging for screening and diagnosis of breast cancer. Work presented in this symposium includes research support by: Siemens Healthcare (Dr. Chen); NIH and Siemens Healthcare (Dr. Fahrig); NIH and Carestream Health (Dr. Zbijewski); and NIH (Dr. Boone)« less

SU-E-J-275: Review - Computerized PET/CT Image Analysis in the Evaluation of Tumor Response to Therapy

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

Lu, W; Wang, J; Zhang, H

Purpose: To review the literature in using computerized PET/CT image analysis for the evaluation of tumor response to therapy. Methods: We reviewed and summarized more than 100 papers that used computerized image analysis techniques for the evaluation of tumor response with PET/CT. This review mainly covered four aspects: image registration, tumor segmentation, image feature extraction, and response evaluation. Results: Although rigid image registration is straightforward, it has been shown to achieve good alignment between baseline and evaluation scans. Deformable image registration has been shown to improve the alignment when complex deformable distortions occur due to tumor shrinkage, weight loss ormore » gain, and motion. Many semi-automatic tumor segmentation methods have been developed on PET. A comparative study revealed benefits of high levels of user interaction with simultaneous visualization of CT images and PET gradients. On CT, semi-automatic methods have been developed for only tumors that show marked difference in CT attenuation between the tumor and the surrounding normal tissues. Quite a few multi-modality segmentation methods have been shown to improve accuracy compared to single-modality algorithms. Advanced PET image features considering spatial information, such as tumor volume, tumor shape, total glycolytic volume, histogram distance, and texture features have been found more informative than the traditional SUVmax for the prediction of tumor response. Advanced CT features, including volumetric, attenuation, morphologic, structure, and texture descriptors, have also been found advantage over the traditional RECIST and WHO criteria in certain tumor types. Predictive models based on machine learning technique have been constructed for correlating selected image features to response. These models showed improved performance compared to current methods using cutoff value of a single measurement for tumor response. Conclusion: This review showed that computerized PET/CT image analysis holds great potential to improve the accuracy in evaluation of tumor response. This work was supported in part by the National Cancer Institute Grant R01CA172638.« less

Image based performance analysis of thermal imagers

NASA Astrophysics Data System (ADS)

Wegner, D.; Repasi, E.

2016-05-01

Due to advances in technology, modern thermal imagers resemble sophisticated image processing systems in functionality. Advanced signal and image processing tools enclosed into the camera body extend the basic image capturing capability of thermal cameras. This happens in order to enhance the display presentation of the captured scene or specific scene details. Usually, the implemented methods are proprietary company expertise, distributed without extensive documentation. This makes the comparison of thermal imagers especially from different companies a difficult task (or at least a very time consuming/expensive task - e.g. requiring the execution of a field trial and/or an observer trial). For example, a thermal camera equipped with turbulence mitigation capability stands for such a closed system. The Fraunhofer IOSB has started to build up a system for testing thermal imagers by image based methods in the lab environment. This will extend our capability of measuring the classical IR-system parameters (e.g. MTF, MTDP, etc.) in the lab. The system is set up around the IR- scene projector, which is necessary for the thermal display (projection) of an image sequence for the IR-camera under test. The same set of thermal test sequences might be presented to every unit under test. For turbulence mitigation tests, this could be e.g. the same turbulence sequence. During system tests, gradual variation of input parameters (e. g. thermal contrast) can be applied. First ideas of test scenes selection and how to assembly an imaging suite (a set of image sequences) for the analysis of imaging thermal systems containing such black boxes in the image forming path is discussed.

Vision Based Autonomous Robotic Control for Advanced Inspection and Repair

NASA Technical Reports Server (NTRS)

Wehner, Walter S.

2014-01-01

The advanced inspection system is an autonomous control and analysis system that improves the inspection and remediation operations for ground and surface systems. It uses optical imaging technology with intelligent computer vision algorithms to analyze physical features of the real-world environment to make decisions and learn from experience. The advanced inspection system plans to control a robotic manipulator arm, an unmanned ground vehicle and cameras remotely, automatically and autonomously. There are many computer vision, image processing and machine learning techniques available as open source for using vision as a sensory feedback in decision-making and autonomous robotic movement. My responsibilities for the advanced inspection system are to create a software architecture that integrates and provides a framework for all the different subsystem components; identify open-source algorithms and techniques; and integrate robot hardware.

ImageJS: Personalized, participated, pervasive, and reproducible image bioinformatics in the web browser

PubMed Central

Almeida, Jonas S.; Iriabho, Egiebade E.; Gorrepati, Vijaya L.; Wilkinson, Sean R.; Grüneberg, Alexander; Robbins, David E.; Hackney, James R.

2012-01-01

Background: Image bioinformatics infrastructure typically relies on a combination of server-side high-performance computing and client desktop applications tailored for graphic rendering. On the server side, matrix manipulation environments are often used as the back-end where deployment of specialized analytical workflows takes place. However, neither the server-side nor the client-side desktop solution, by themselves or combined, is conducive to the emergence of open, collaborative, computational ecosystems for image analysis that are both self-sustained and user driven. Materials and Methods: ImageJS was developed as a browser-based webApp, untethered from a server-side backend, by making use of recent advances in the modern web browser such as a very efficient compiler, high-end graphical rendering capabilities, and I/O tailored for code migration. Results: Multiple versioned code hosting services were used to develop distinct ImageJS modules to illustrate its amenability to collaborative deployment without compromise of reproducibility or provenance. The illustrative examples include modules for image segmentation, feature extraction, and filtering. The deployment of image analysis by code migration is in sharp contrast with the more conventional, heavier, and less safe reliance on data transfer. Accordingly, code and data are loaded into the browser by exactly the same script tag loading mechanism, which offers a number of interesting applications that would be hard to attain with more conventional platforms, such as NIH's popular ImageJ application. Conclusions: The modern web browser was found to be advantageous for image bioinformatics in both the research and clinical environments. This conclusion reflects advantages in deployment scalability and analysis reproducibility, as well as the critical ability to deliver advanced computational statistical procedures machines where access to sensitive data is controlled, that is, without local “download and installation”. PMID:22934238

ImageJS: Personalized, participated, pervasive, and reproducible image bioinformatics in the web browser.

PubMed

Almeida, Jonas S; Iriabho, Egiebade E; Gorrepati, Vijaya L; Wilkinson, Sean R; Grüneberg, Alexander; Robbins, David E; Hackney, James R

2012-01-01

Image bioinformatics infrastructure typically relies on a combination of server-side high-performance computing and client desktop applications tailored for graphic rendering. On the server side, matrix manipulation environments are often used as the back-end where deployment of specialized analytical workflows takes place. However, neither the server-side nor the client-side desktop solution, by themselves or combined, is conducive to the emergence of open, collaborative, computational ecosystems for image analysis that are both self-sustained and user driven. ImageJS was developed as a browser-based webApp, untethered from a server-side backend, by making use of recent advances in the modern web browser such as a very efficient compiler, high-end graphical rendering capabilities, and I/O tailored for code migration. Multiple versioned code hosting services were used to develop distinct ImageJS modules to illustrate its amenability to collaborative deployment without compromise of reproducibility or provenance. The illustrative examples include modules for image segmentation, feature extraction, and filtering. The deployment of image analysis by code migration is in sharp contrast with the more conventional, heavier, and less safe reliance on data transfer. Accordingly, code and data are loaded into the browser by exactly the same script tag loading mechanism, which offers a number of interesting applications that would be hard to attain with more conventional platforms, such as NIH's popular ImageJ application. The modern web browser was found to be advantageous for image bioinformatics in both the research and clinical environments. This conclusion reflects advantages in deployment scalability and analysis reproducibility, as well as the critical ability to deliver advanced computational statistical procedures machines where access to sensitive data is controlled, that is, without local "download and installation".

Quantitative Analysis of {sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated With Stereotactic Body Radiation Therapy

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

Cui, Yi; Global Institution for Collaborative Research and Education, Hokkaido University, Sapporo; Song, Jie

Purpose: To identify prognostic biomarkers in pancreatic cancer using high-throughput quantitative image analysis. Methods and Materials: In this institutional review board–approved study, we retrospectively analyzed images and outcomes for 139 locally advanced pancreatic cancer patients treated with stereotactic body radiation therapy (SBRT). The overall population was split into a training cohort (n=90) and a validation cohort (n=49) according to the time of treatment. We extracted quantitative imaging characteristics from pre-SBRT {sup 18}F-fluorodeoxyglucose positron emission tomography, including statistical, morphologic, and texture features. A Cox proportional hazard regression model was built to predict overall survival (OS) in the training cohort using 162more » robust image features. To avoid over-fitting, we applied the elastic net to obtain a sparse set of image features, whose linear combination constitutes a prognostic imaging signature. Univariate and multivariate Cox regression analyses were used to evaluate the association with OS, and concordance index (CI) was used to evaluate the survival prediction accuracy. Results: The prognostic imaging signature included 7 features characterizing different tumor phenotypes, including shape, intensity, and texture. On the validation cohort, univariate analysis showed that this prognostic signature was significantly associated with OS (P=.002, hazard ratio 2.74), which improved upon conventional imaging predictors including tumor volume, maximum standardized uptake value, and total legion glycolysis (P=.018-.028, hazard ratio 1.51-1.57). On multivariate analysis, the proposed signature was the only significant prognostic index (P=.037, hazard ratio 3.72) when adjusted for conventional imaging and clinical factors (P=.123-.870, hazard ratio 0.53-1.30). In terms of CI, the proposed signature scored 0.66 and was significantly better than competing prognostic indices (CI 0.48-0.64, Wilcoxon rank sum test P<1e-6). Conclusion: Quantitative analysis identified novel {sup 18}F-fluorodeoxyglucose positron emission tomography image features that showed improved prognostic value over conventional imaging metrics. If validated in large, prospective cohorts, the new prognostic signature might be used to identify patients for individualized risk-adaptive therapy.« less

Directional ratio based on parabolic molecules and its application to the analysis of tubular structures

NASA Astrophysics Data System (ADS)

Labate, Demetrio; Negi, Pooran; Ozcan, Burcin; Papadakis, Manos

2015-09-01

As advances in imaging technologies make more and more data available for biomedical applications, there is an increasing need to develop efficient quantitative algorithms for the analysis and processing of imaging data. In this paper, we introduce an innovative multiscale approach called Directional Ratio which is especially effective to distingush isotropic from anisotropic structures. This task is especially useful in the analysis of images of neurons, the main units of the nervous systems which consist of a main cell body called the soma and many elongated processes called neurites. We analyze the theoretical properties of our method on idealized models of neurons and develop a numerical implementation of this approach for analysis of fluorescent images of cultured neurons. We show that this algorithm is very effective for the detection of somas and the extraction of neurites in images of small circuits of neurons.

TU-AB-204-02: Advances in C-Arm CBCT for Cardiac Interventions

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

Fahrig, R.

This symposium highlights advanced cone-beam CT (CBCT) technologies in four areas of emerging application in diagnostic imaging and image-guided interventions. Each area includes research that extends the spatial, temporal, and/or contrast resolution characteristics of CBCT beyond conventional limits through advances in scanner technology, acquisition protocols, and 3D image reconstruction techniques. Dr. G. Chen (University of Wisconsin) will present on the topic: Advances in C-arm CBCT for Brain Perfusion Imaging. Stroke is a leading cause of death and disability, and a fraction of people having an acute ischemic stroke are suitable candidates for endovascular therapy. Critical factors that affect both themore » likelihood of successful revascularization and good clinical outcome are: 1) the time between stroke onset and revascularization; and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from patients with a large ischemic core and little or no penumbra. Therefore, “time is brain” in the care of the stroke patients. C-arm CBCT systems widely available in angiography suites have the potential to generate non-contrast-enhanced CBCT images to exclude the presence of hemorrhage, time-resolved CBCT angiography to evaluate the site of occlusion and collaterals, and CBCT perfusion parametric images to assess the extent of the ischemic core and penumbra, thereby fulfilling the imaging requirements of a “one-stop-shop” in the angiography suite to reduce the time between onset and revascularization therapy. The challenges and opportunities to advance CBCT technology to fully enable the one-stop-shop C-arm CBCT platform for brain imaging will be discussed. Dr. R. Fahrig (Stanford University) will present on the topic: Advances in C-arm CBCT for Cardiac Interventions. With the goal of providing functional information during cardiac interventions, significant effort has been expended to improve the quantitative accuracy of C-arm CBCT reconstructions. The challenge is to improve image quality while providing very short turnaround between data acquisition and volume data visualization. Corrections for x-ray scatter, view aliasing and patient motion that require no more than 2 iterations keep processing time short while reducing artifact. Fast, multi-sweep acquisitions can be used to permit assessment of left ventricular function, and visualization of radiofrequency lesions created to treat arrhythmias. Workflows for each imaging goal have been developed and validated against gold standard clinical CT or histology. The challenges, opportunities, and limitations of the new functional C-arm CBCT imaging techniques will be discussed. Dr. W. Zbijewski (Johns Hopkins University) will present on the topic: Advances in CBCT for Orthopaedics and Bone Health Imaging. Cone-beam CT is particularly well suited for imaging of musculoskeletal extremities. Owing to the high spatial resolution of flat-panel detectors, CBCT can surpass conventional CT in imaging tasks involving bone visualization, quantitative analysis of subchondral trabecular structure, and visualization and monitoring of subtle fractures that are common in orthopedic radiology. A dedicated CBCT platform has been developed that offers flexibility in system design and provides not only a compact configuration with improved logistics for extremities imaging but also enables novel diagnostic capabilities such as imaging of weight-bearing lower extremities in a natural stance. The design, development and clinical performance of dedicated extremities CBCT systems will be presented. Advanced capabilities for quantitative volumetric assessment of joint space morphology, dual-energy image-based quantification of bone composition, and in-vivo analysis of bone microarchitecture will be discussed, along with emerging applications in the diagnosis of arthritis and osteoporosis and assessment of novel therapies. Finally, Dr. J. Boone (UC Davis) will present on the topic: Advances in CBCT for Breast Imaging. Breast CT has been studied as an imaging tool for diagnostic breast evaluation and for potential breast cancer screening. The breast CT application lends itself to CBCT because of the small dimensions of the breast, the tapered shape of the breast towards higher cone angle, and the fact that there are no bones in the breast. The performance of various generations of breast CT scanners developed in recent years will be discussed, focusing on advances in spatial resolution and image noise characteristics. The results will also demonstrate the results of clinical trials using both computer and human observers. Learning Objectives: Understand the challenges, key technological advances, and emerging opportunities of CBCT in: Brain perfusion imaging, including assessment of ischemic stroke Cardiac imaging for functional assessment in cardiac interventions Orthopedics imaging for evaluation of musculoskeletal trauma, arthritis, and osteoporosis Breast imaging for screening and diagnosis of breast cancer. Work presented in this symposium includes research support by: Siemens Healthcare (Dr. Chen); NIH and Siemens Healthcare (Dr. Fahrig); NIH and Carestream Health (Dr. Zbijewski); and NIH (Dr. Boone)« less

TU-AB-204-00: Advances in Cone-Beam CT and Emerging Applications

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

NONE

This symposium highlights advanced cone-beam CT (CBCT) technologies in four areas of emerging application in diagnostic imaging and image-guided interventions. Each area includes research that extends the spatial, temporal, and/or contrast resolution characteristics of CBCT beyond conventional limits through advances in scanner technology, acquisition protocols, and 3D image reconstruction techniques. Dr. G. Chen (University of Wisconsin) will present on the topic: Advances in C-arm CBCT for Brain Perfusion Imaging. Stroke is a leading cause of death and disability, and a fraction of people having an acute ischemic stroke are suitable candidates for endovascular therapy. Critical factors that affect both themore » likelihood of successful revascularization and good clinical outcome are: 1) the time between stroke onset and revascularization; and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from patients with a large ischemic core and little or no penumbra. Therefore, “time is brain” in the care of the stroke patients. C-arm CBCT systems widely available in angiography suites have the potential to generate non-contrast-enhanced CBCT images to exclude the presence of hemorrhage, time-resolved CBCT angiography to evaluate the site of occlusion and collaterals, and CBCT perfusion parametric images to assess the extent of the ischemic core and penumbra, thereby fulfilling the imaging requirements of a “one-stop-shop” in the angiography suite to reduce the time between onset and revascularization therapy. The challenges and opportunities to advance CBCT technology to fully enable the one-stop-shop C-arm CBCT platform for brain imaging will be discussed. Dr. R. Fahrig (Stanford University) will present on the topic: Advances in C-arm CBCT for Cardiac Interventions. With the goal of providing functional information during cardiac interventions, significant effort has been expended to improve the quantitative accuracy of C-arm CBCT reconstructions. The challenge is to improve image quality while providing very short turnaround between data acquisition and volume data visualization. Corrections for x-ray scatter, view aliasing and patient motion that require no more than 2 iterations keep processing time short while reducing artifact. Fast, multi-sweep acquisitions can be used to permit assessment of left ventricular function, and visualization of radiofrequency lesions created to treat arrhythmias. Workflows for each imaging goal have been developed and validated against gold standard clinical CT or histology. The challenges, opportunities, and limitations of the new functional C-arm CBCT imaging techniques will be discussed. Dr. W. Zbijewski (Johns Hopkins University) will present on the topic: Advances in CBCT for Orthopaedics and Bone Health Imaging. Cone-beam CT is particularly well suited for imaging of musculoskeletal extremities. Owing to the high spatial resolution of flat-panel detectors, CBCT can surpass conventional CT in imaging tasks involving bone visualization, quantitative analysis of subchondral trabecular structure, and visualization and monitoring of subtle fractures that are common in orthopedic radiology. A dedicated CBCT platform has been developed that offers flexibility in system design and provides not only a compact configuration with improved logistics for extremities imaging but also enables novel diagnostic capabilities such as imaging of weight-bearing lower extremities in a natural stance. The design, development and clinical performance of dedicated extremities CBCT systems will be presented. Advanced capabilities for quantitative volumetric assessment of joint space morphology, dual-energy image-based quantification of bone composition, and in-vivo analysis of bone microarchitecture will be discussed, along with emerging applications in the diagnosis of arthritis and osteoporosis and assessment of novel therapies. Finally, Dr. J. Boone (UC Davis) will present on the topic: Advances in CBCT for Breast Imaging. Breast CT has been studied as an imaging tool for diagnostic breast evaluation and for potential breast cancer screening. The breast CT application lends itself to CBCT because of the small dimensions of the breast, the tapered shape of the breast towards higher cone angle, and the fact that there are no bones in the breast. The performance of various generations of breast CT scanners developed in recent years will be discussed, focusing on advances in spatial resolution and image noise characteristics. The results will also demonstrate the results of clinical trials using both computer and human observers. Learning Objectives: Understand the challenges, key technological advances, and emerging opportunities of CBCT in: Brain perfusion imaging, including assessment of ischemic stroke Cardiac imaging for functional assessment in cardiac interventions Orthopedics imaging for evaluation of musculoskeletal trauma, arthritis, and osteoporosis Breast imaging for screening and diagnosis of breast cancer. Work presented in this symposium includes research support by: Siemens Healthcare (Dr. Chen); NIH and Siemens Healthcare (Dr. Fahrig); NIH and Carestream Health (Dr. Zbijewski); and NIH (Dr. Boone)« less

Artificial intelligence in radiology.

PubMed

Hosny, Ahmed; Parmar, Chintan; Quackenbush, John; Schwartz, Lawrence H; Aerts, Hugo J W L

2018-05-17

Artificial intelligence (AI) algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks. Methods ranging from convolutional neural networks to variational autoencoders have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. Historically, in radiology practice, trained physicians visually assessed medical images for the detection, characterization and monitoring of diseases. AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics. In this Opinion article, we establish a general understanding of AI methods, particularly those pertaining to image-based tasks. We explore how these methods could impact multiple facets of radiology, with a general focus on applications in oncology, and demonstrate ways in which these methods are advancing the field. Finally, we discuss the challenges facing clinical implementation and provide our perspective on how the domain could be advanced.

Advanced image fusion algorithms for Gamma Knife treatment planning. Evaluation and proposal for clinical use.

PubMed

Apostolou, N; Papazoglou, Th; Koutsouris, D

2006-01-01

Image fusion is a process of combining information from multiple sensors. It is a useful tool implemented in the treatment planning programme of Gamma Knife Radiosurgery. In this paper we evaluate advanced image fusion algorithms for Matlab platform and head images. We develop nine level grayscale image fusion methods: average, principal component analysis (PCA), discrete wavelet transform (DWT) and Laplacian, filter - subtract - decimate (FSD), contrast, gradient, morphological pyramid and a shift invariant discrete wavelet transform (SIDWT) method in Matlab platform. We test these methods qualitatively and quantitatively. The quantitative criteria we use are the Root Mean Square Error (RMSE), the Mutual Information (MI), the Standard Deviation (STD), the Entropy (H), the Difference Entropy (DH) and the Cross Entropy (CEN). The qualitative are: natural appearance, brilliance contrast, presence of complementary features and enhancement of common features. Finally we make clinically useful suggestions.

Spatiotemporal image correlation analysis of blood flow in branched vessel networks of zebrafish embryos

NASA Astrophysics Data System (ADS)

Ceffa, Nicolo G.; Cesana, Ilaria; Collini, Maddalena; D'Alfonso, Laura; Carra, Silvia; Cotelli, Franco; Sironi, Laura; Chirico, Giuseppe

2017-10-01

Ramification of blood circulation is relevant in a number of physiological and pathological conditions. The oxygen exchange occurs largely in the capillary bed, and the cancer progression is closely linked to the angiogenesis around the tumor mass. Optical microscopy has made impressive improvements in in vivo imaging and dynamic studies based on correlation analysis of time stacks of images. Here, we develop and test advanced methods that allow mapping the flow fields in branched vessel networks at the resolution of 10 to 20 μm. The methods, based on the application of spatiotemporal image correlation spectroscopy and its extension to cross-correlation analysis, are applied here to the case of early stage embryos of zebrafish.

LesionTracker: Extensible Open-Source Zero-Footprint Web Viewer for Cancer Imaging Research and Clinical Trials.

PubMed

Urban, Trinity; Ziegler, Erik; Lewis, Rob; Hafey, Chris; Sadow, Cheryl; Van den Abbeele, Annick D; Harris, Gordon J

2017-11-01

Oncology clinical trials have become increasingly dependent upon image-based surrogate endpoints for determining patient eligibility and treatment efficacy. As therapeutics have evolved and multiplied in number, the tumor metrics criteria used to characterize therapeutic response have become progressively more varied and complex. The growing intricacies of image-based response evaluation, together with rising expectations for rapid and consistent results reporting, make it difficult for site radiologists to adequately address local and multicenter imaging demands. These challenges demonstrate the need for advanced cancer imaging informatics tools that can help ensure protocol-compliant image evaluation while simultaneously promoting reviewer efficiency. LesionTracker is a quantitative imaging package optimized for oncology clinical trial workflows. The goal of the project is to create an open source zero-footprint viewer for image analysis that is designed to be extensible as well as capable of being integrated into third-party systems for advanced imaging tools and clinical trials informatics platforms. Cancer Res; 77(21); e119-22. ©2017 AACR . ©2017 American Association for Cancer Research.

Integrated analysis of remote sensing products from basic geological surveys. [Brazil

NASA Technical Reports Server (NTRS)

Dasilvafagundesfilho, E. (Principal Investigator)

1984-01-01

Recent advances in remote sensing led to the development of several techniques to obtain image information. These techniques as effective tools in geological maping are analyzed. A strategy for optimizing the images in basic geological surveying is presented. It embraces as integrated analysis of spatial, spectral, and temporal data through photoptic (color additive viewer) and computer processing at different scales, allowing large areas survey in a fast, precise, and low cost manner.

Advanced Land Imager Assessment System

NASA Technical Reports Server (NTRS)

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

Segmenting Images for a Better Diagnosis

NASA Technical Reports Server (NTRS)

2004-01-01

NASA's Hierarchical Segmentation (HSEG) software has been adapted by Bartron Medical Imaging, LLC, for use in segmentation feature extraction, pattern recognition, and classification of medical images. Bartron acquired licenses from NASA Goddard Space Flight Center for application of the HSEG concept to medical imaging, from the California Institute of Technology/Jet Propulsion Laboratory to incorporate pattern-matching software, and from Kennedy Space Center for data-mining and edge-detection programs. The Med-Seg[TM] united developed by Bartron provides improved diagnoses for a wide range of medical images, including computed tomography scans, positron emission tomography scans, magnetic resonance imaging, ultrasound, digitized Z-ray, digitized mammography, dental X-ray, soft tissue analysis, and moving object analysis. It also can be used in analysis of soft-tissue slides. Bartron's future plans include the application of HSEG technology to drug development. NASA is advancing it's HSEG software to learn more about the Earth's magnetosphere.

Could MRI Be Used To Image Kidney Fibrosis? A Review of Recent Advances and Remaining Barriers.

PubMed

Leung, General; Kirpalani, Anish; Szeto, Stephen G; Deeb, Maya; Foltz, Warren; Simmons, Craig A; Yuen, Darren A

2017-06-07

A key contributor to the progression of nearly all forms of CKD is fibrosis, a largely irreversible process that drives further kidney injury. Despite its importance, clinicians currently have no means of noninvasively assessing renal scar, and thus have historically relied on percutaneous renal biopsy to assess fibrotic burden. Although helpful in the initial diagnostic assessment, renal biopsy remains an imperfect test for fibrosis measurement, limited not only by its invasiveness, but also, because of the small amounts of tissue analyzed, its susceptibility to sampling bias. These concerns have limited not only the prognostic utility of biopsy analysis and its ability to guide therapeutic decisions, but also the clinical translation of experimental antifibrotic agents. Recent advances in imaging technology have raised the exciting possibility of magnetic resonance imaging (MRI)-based renal scar analysis, by capitalizing on the differing physical features of fibrotic and nonfibrotic tissue. In this review, we describe two key fibrosis-induced pathologic changes (capillary loss and kidney stiffening) that can be imaged by MRI techniques, and the potential for these new MRI-based technologies to noninvasively image renal scar. Copyright © 2017 by the American Society of Nephrology.

Could MRI Be Used To Image Kidney Fibrosis? A Review of Recent Advances and Remaining Barriers

PubMed Central

Leung, General; Kirpalani, Anish; Szeto, Stephen G.; Deeb, Maya; Foltz, Warren; Simmons, Craig A.

2017-01-01

A key contributor to the progression of nearly all forms of CKD is fibrosis, a largely irreversible process that drives further kidney injury. Despite its importance, clinicians currently have no means of noninvasively assessing renal scar, and thus have historically relied on percutaneous renal biopsy to assess fibrotic burden. Although helpful in the initial diagnostic assessment, renal biopsy remains an imperfect test for fibrosis measurement, limited not only by its invasiveness, but also, because of the small amounts of tissue analyzed, its susceptibility to sampling bias. These concerns have limited not only the prognostic utility of biopsy analysis and its ability to guide therapeutic decisions, but also the clinical translation of experimental antifibrotic agents. Recent advances in imaging technology have raised the exciting possibility of magnetic resonance imaging (MRI)–based renal scar analysis, by capitalizing on the differing physical features of fibrotic and nonfibrotic tissue. In this review, we describe two key fibrosis-induced pathologic changes (capillary loss and kidney stiffening) that can be imaged by MRI techniques, and the potential for these new MRI-based technologies to noninvasively image renal scar. PMID:28298435

3D Slicer as an Image Computing Platform for the Quantitative Imaging Network

PubMed Central

Fedorov, Andriy; Beichel, Reinhard; Kalpathy-Cramer, Jayashree; Finet, Julien; Fillion-Robin, Jean-Christophe; Pujol, Sonia; Bauer, Christian; Jennings, Dominique; Fennessy, Fiona; Sonka, Milan; Buatti, John; Aylward, Stephen; Miller, James V.; Pieper, Steve; Kikinis, Ron

2012-01-01

Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future directions that can further facilitate development and validation of imaging biomarkers using 3D Slicer. PMID:22770690

Benefit from NASA

NASA Image and Video Library

1985-01-01

The NASA imaging processing technology, an advanced computer technique to enhance images sent to Earth in digital form by distant spacecraft, helped develop a new vision screening process. The Ocular Vision Screening system, an important step in preventing vision impairment, is a portable device designed especially to detect eye problems in children through the analysis of retinal reflexes.

Cancer Biotechnology | Center for Cancer Research

Cancer.gov

Biotechnology advances continue to underscore the need to educate NCI fellows in new methodologies. The Cancer Biotechnology course will be held on the NCI-Frederick campus on January 29, 2016 (Bldg. 549, Main Auditorium) and the course will be repeated on the Bethesda campus on February 9, 2016 (Natcher Balcony C). The latest advances in DNA, protein and image analysis will

Recent advances in the applications of vibrational spectroscopic imaging and mapping to pharmaceutical formulations

NASA Astrophysics Data System (ADS)

Ewing, Andrew V.; Kazarian, Sergei G.

2018-05-01

Vibrational spectroscopic imaging and mapping approaches have continued in their development and applications for the analysis of pharmaceutical formulations. Obtaining spatially resolved chemical information about the distribution of different components within pharmaceutical formulations is integral for improving the understanding and quality of final drug products. This review aims to summarise some key advances of these technologies over recent years, primarily since 2010. An overview of FTIR, NIR, terahertz spectroscopic imaging and Raman mapping will be presented to give a perspective of the current state-of-the-art of these techniques for studying pharmaceutical samples. This will include their application to reveal spatial information of components that reveals molecular insight of polymorphic or structural changes, behaviour of formulations during dissolution experiments, uniformity of materials and detection of counterfeit products. Furthermore, new advancements will be presented that demonstrate the continuing novel applications of spectroscopic imaging and mapping, namely in FTIR spectroscopy, for studies of microfluidic devices. Whilst much of the recently developed work has been reported by academic groups, examples of the potential impacts of utilising these imaging and mapping technologies to support industrial applications have also been reviewed.

Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping

PubMed Central

Keith, Lauren; Ross, Brian D.; Galbán, Craig J.; Luker, Gary D.; Galbán, Stefanie; Zhao, Binsheng; Guo, Xiaotao; Chenevert, Thomas L.; Hoff, Benjamin A.

2017-01-01

Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice. PMID:28286871

Contrast-enhanced endoscopic ultrasonography: advance and current status

PubMed Central

2014-01-01

Endoscopic ultrasonography (EUS) technology has undergone a great deal of progress along with the color and power Doppler imaging, three-dimensional imaging, electronic scanning, tissue harmonic imaging, and elastography, and one of the most important developments is the ability to acquire contrast-enhanced images. The blood flow in small vessels and the parenchymal microvasculature of the target lesion can be observed non-invasively by contrast-enhanced EUS (CE-EUS). Through a hemodynamic analysis, CE-EUS permits the diagnosis of various gastrointestinal diseases and differential diagnoses between benign and malignant tumors. Recently, mechanical innovations and the development of contrast agents have increased the use of CE-EUS in the diagnostic field, as well as for the assessment of the efficacy of therapeutic agents. The advances in and the current status of CE-EUS are discussed in this review. PMID:25038805

IDEAL: Images Across Domains, Experiments, Algorithms and Learning

NASA Astrophysics Data System (ADS)

Ushizima, Daniela M.; Bale, Hrishikesh A.; Bethel, E. Wes; Ercius, Peter; Helms, Brett A.; Krishnan, Harinarayan; Grinberg, Lea T.; Haranczyk, Maciej; Macdowell, Alastair A.; Odziomek, Katarzyna; Parkinson, Dilworth Y.; Perciano, Talita; Ritchie, Robert O.; Yang, Chao

2016-11-01

Research across science domains is increasingly reliant on image-centric data. Software tools are in high demand to uncover relevant, but hidden, information in digital images, such as those coming from faster next generation high-throughput imaging platforms. The challenge is to analyze the data torrent generated by the advanced instruments efficiently, and provide insights such as measurements for decision-making. In this paper, we overview work performed by an interdisciplinary team of computational and materials scientists, aimed at designing software applications and coordinating research efforts connecting (1) emerging algorithms for dealing with large and complex datasets; (2) data analysis methods with emphasis in pattern recognition and machine learning; and (3) advances in evolving computer architectures. Engineering tools around these efforts accelerate the analyses of image-based recordings, improve reusability and reproducibility, scale scientific procedures by reducing time between experiments, increase efficiency, and open opportunities for more users of the imaging facilities. This paper describes our algorithms and software tools, showing results across image scales, demonstrating how our framework plays a role in improving image understanding for quality control of existent materials and discovery of new compounds.

Effect of automated tube voltage selection, integrated circuit detector and advanced iterative reconstruction on radiation dose and image quality of 3rd generation dual-source aortic CT angiography: An intra-individual comparison.

PubMed

Mangold, Stefanie; De Cecco, Carlo N; Wichmann, Julian L; Canstein, Christian; Varga-Szemes, Akos; Caruso, Damiano; Fuller, Stephen R; Bamberg, Fabian; Nikolaou, Konstantin; Schoepf, U Joseph

2016-05-01

To compare, on an intra-individual basis, the effect of automated tube voltage selection (ATVS), integrated circuit detector and advanced iterative reconstruction on radiation dose and image quality of aortic CTA studies using 2nd and 3rd generation dual-source CT (DSCT). We retrospectively evaluated 32 patients who had undergone CTA of the entire aorta with both 2nd generation DSCT at 120kV using filtered back projection (FBP) (protocol 1) and 3rd generation DSCT using ATVS, an integrated circuit detector and advanced iterative reconstruction (protocol 2). Contrast-to-noise ratio (CNR) was calculated. Image quality was subjectively evaluated using a five-point scale. Radiation dose parameters were recorded. All studies were considered of diagnostic image quality. CNR was significantly higher with protocol 2 (15.0±5.2 vs 11.0±4.2; p<.0001). Subjective image quality analysis revealed no significant differences for evaluation of attenuation (p=0.08501) but image noise was rated significantly lower with protocol 2 (p=0.0005). Mean tube voltage and effective dose were 94.7±14.1kV and 6.7±3.9mSv with protocol 2; 120±0kV and 11.5±5.2mSv with protocol 1 (p<0.0001, respectively). Aortic CTA performed with 3rd generation DSCT, ATVS, integrated circuit detector, and advanced iterative reconstruction allow a substantial reduction of radiation exposure while improving image quality in comparison to 120kV imaging with FBP. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis.

PubMed

Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L; Hwang, Jae Youn

2016-12-01

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis.

Geometric error analysis for shuttle imaging spectrometer experiment

NASA Technical Reports Server (NTRS)

Wang, S. J.; Ih, C. H.

1984-01-01

The demand of more powerful tools for remote sensing and management of earth resources steadily increased over the last decade. With the recent advancement of area array detectors, high resolution multichannel imaging spectrometers can be realistically constructed. The error analysis study for the Shuttle Imaging Spectrometer Experiment system is documented for the purpose of providing information for design, tradeoff, and performance prediction. Error sources including the Shuttle attitude determination and control system, instrument pointing and misalignment, disturbances, ephemeris, Earth rotation, etc., were investigated. Geometric error mapping functions were developed, characterized, and illustrated extensively with tables and charts. Selected ground patterns and the corresponding image distortions were generated for direct visual inspection of how the various error sources affect the appearance of the ground object images.

Advanced electron microscopy methods for the analysis of MgB2 superconductor

NASA Astrophysics Data System (ADS)

Birajdar, B.; Peranio, N.; Eibl, O.

2008-02-01

Advanced electron microscopy methods used for the analysis of superconducting MgB2 wires and tapes are described. The wires and tapes were prepared by the powder in tube method using different processing technologies and thoroughly characterised for their superconducting properties within the HIPERMAG project. Microstructure analysis on μm to nm length scales is necessary to understand the superconducting properties of MgB2. For the MgB2 phase analysis on μm scale an analytical SEM, and for the analysis on nm scale a energy-filtered STEM is used. Both the microscopes were equipped with EDX detector and field emission gun. Electron microscopy and spectroscopy of MgB2 is challenging because of the boron analysis, carbon and oxygen contamination, and the presence of large number of secondary phases. Advanced electron microscopy involves, combined SEM, EPMA and TEM analysis with artefact free sample preparation, elemental mapping and chemical quantification of point spectra. Details of the acquisition conditions and achieved accuracy are presented. Ex-situ wires show oxygen-free MgB2 colonies (a colony is a dense arrangement of several MgB2 grains) embedded in a porous and oxygen-rich matrix, introducing structural granularity. In comparison, in-situ wires are generally more dense, but show inhibited MgB2 phase formation with significantly higher fraction of B-rich secondary phases. SiC additives in the in-situ wires forms Mg2Si secondary phases. The advanced electron microscopy has been used to extract the microstructure parameters like colony size, B-rich secondary phase fraction, O mole fraction and MgB2 grain size, and establish a microstructure-critical current density model [1]. In summary, conventional secondary electron imaging in SEM and diffraction contrast imaging in the TEM are by far not sufficient and advanced electron microscopy methods are essential for the analysis of superconducting MgB2 wires and tapes.

Cancer Biotechnology | Center for Cancer Research

Cancer.gov

Biotechnology advances continue to underscore the need to educate NCI fellows in new methodologies. The Cancer Biotechnology course will be held on the NCI-Frederick campus on January 29, 2016 (Bldg. 549, Main Auditorium) and the course will be repeated on the Bethesda campus on February 9, 2016 (Natcher Balcony C). The latest advances in DNA, protein and image analysis will be presented. Clinical and postdoctoral fellows who want to learn about new biotechnology advances are encouraged to attend this course.

Automatic microscopy for mitotic cell location.

NASA Technical Reports Server (NTRS)

Herron, J.; Ranshaw, R.; Castle, J.; Wald, N.

1972-01-01

Advances are reported in the development of an automatic microscope with which to locate hematologic or other cells in mitosis for subsequent chromosome analysis. The system under development is designed to perform the functions of: slide scanning to locate metaphase cells; conversion of images of selected cells into binary form; and on-line computer analysis of the digitized image for significant cytogenetic data. Cell detection criteria are evaluated using a test sample of 100 mitotic cells and 100 artifacts.

Analytic programming with FMRI data: a quick-start guide for statisticians using R.

PubMed

Eloyan, Ani; Li, Shanshan; Muschelli, John; Pekar, Jim J; Mostofsky, Stewart H; Caffo, Brian S

2014-01-01

Functional magnetic resonance imaging (fMRI) is a thriving field that plays an important role in medical imaging analysis, biological and neuroscience research and practice. This manuscript gives a didactic introduction to the statistical analysis of fMRI data using the R project, along with the relevant R code. The goal is to give statisticians who would like to pursue research in this area a quick tutorial for programming with fMRI data. References of relevant packages and papers are provided for those interested in more advanced analysis.

High throughput imaging and analysis for biological interpretation of agricultural plants and environmental interaction

NASA Astrophysics Data System (ADS)

Hong, Hyundae; Benac, Jasenka; Riggsbee, Daniel; Koutsky, Keith

2014-03-01

High throughput (HT) phenotyping of crops is essential to increase yield in environments deteriorated by climate change. The controlled environment of a greenhouse offers an ideal platform to study the genotype to phenotype linkages for crop screening. Advanced imaging technologies are used to study plants' responses to resource limitations such as water and nutrient deficiency. Advanced imaging technologies coupled with automation make HT phenotyping in the greenhouse not only feasible, but practical. Monsanto has a state of the art automated greenhouse (AGH) facility. Handling of the soil, pots water and nutrients are all completely automated. Images of the plants are acquired by multiple hyperspectral and broadband cameras. The hyperspectral cameras cover wavelengths from visible light through short wave infra-red (SWIR). Inhouse developed software analyzes the images to measure plant morphological and biochemical properties. We measure phenotypic metrics like plant area, height, and width as well as biomass. Hyperspectral imaging allows us to measure biochemcical metrics such as chlorophyll, anthocyanin, and foliar water content. The last 4 years of AGH operations on crops like corn, soybean, and cotton have demonstrated successful application of imaging and analysis technologies for high throughput plant phenotyping. Using HT phenotyping, scientists have been showing strong correlations to environmental conditions, such as water and nutrient deficits, as well as the ability to tease apart distinct differences in the genetic backgrounds of crops.

Multiscale Analysis of Solar Image Data

NASA Astrophysics Data System (ADS)

Young, C. A.; Myers, D. C.

2001-12-01

It is often said that the blessing and curse of solar physics is that there is too much data. Solar missions such as Yohkoh, SOHO and TRACE have shown us the Sun with amazing clarity but have also cursed us with an increased amount of higher complexity data than previous missions. We have improved our view of the Sun yet we have not improved our analysis techniques. The standard techniques used for analysis of solar images generally consist of observing the evolution of features in a sequence of byte scaled images or a sequence of byte scaled difference images. The determination of features and structures in the images are done qualitatively by the observer. There is little quantitative and objective analysis done with these images. Many advances in image processing techniques have occured in the past decade. Many of these methods are possibly suited for solar image analysis. Multiscale/Multiresolution methods are perhaps the most promising. These methods have been used to formulate the human ability to view and comprehend phenomena on different scales. So these techniques could be used to quantitify the imaging processing done by the observers eyes and brains. In this work we present a preliminary analysis of multiscale techniques applied to solar image data. Specifically, we explore the use of the 2-d wavelet transform and related transforms with EIT, LASCO and TRACE images. This work was supported by NASA contract NAS5-00220.

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis.

PubMed

Downie, H F; Adu, M O; Schmidt, S; Otten, W; Dupuy, L X; White, P J; Valentine, T A

2015-07-01

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions. © 2014 John Wiley & Sons Ltd.

Pre-trained convolutional neural networks as feature extractors for tuberculosis detection.

PubMed

Lopes, U K; Valiati, J F

2017-10-01

It is estimated that in 2015, approximately 1.8 million people infected by tuberculosis died, most of them in developing countries. Many of those deaths could have been prevented if the disease had been detected at an earlier stage, but the most advanced diagnosis methods are still cost prohibitive for mass adoption. One of the most popular tuberculosis diagnosis methods is the analysis of frontal thoracic radiographs; however, the impact of this method is diminished by the need for individual analysis of each radiography by properly trained radiologists. Significant research can be found on automating diagnosis by applying computational techniques to medical images, thereby eliminating the need for individual image analysis and greatly diminishing overall costs. In addition, recent improvements on deep learning accomplished excellent results classifying images on diverse domains, but its application for tuberculosis diagnosis remains limited. Thus, the focus of this work is to produce an investigation that will advance the research in the area, presenting three proposals to the application of pre-trained convolutional neural networks as feature extractors to detect the disease. The proposals presented in this work are implemented and compared to the current literature. The obtained results are competitive with published works demonstrating the potential of pre-trained convolutional networks as medical image feature extractors. Copyright © 2017 Elsevier Ltd. All rights reserved.

Techniques in helical scanning, dynamic imaging and image segmentation for improved quantitative analysis with X-ray micro-CT

NASA Astrophysics Data System (ADS)

Sheppard, Adrian; Latham, Shane; Middleton, Jill; Kingston, Andrew; Myers, Glenn; Varslot, Trond; Fogden, Andrew; Sawkins, Tim; Cruikshank, Ron; Saadatfar, Mohammad; Francois, Nicolas; Arns, Christoph; Senden, Tim

2014-04-01

This paper reports on recent advances at the micro-computed tomography facility at the Australian National University. Since 2000 this facility has been a significant centre for developments in imaging hardware and associated software for image reconstruction, image analysis and image-based modelling. In 2010 a new instrument was constructed that utilises theoretically-exact image reconstruction based on helical scanning trajectories, allowing higher cone angles and thus better utilisation of the available X-ray flux. We discuss the technical hurdles that needed to be overcome to allow imaging with cone angles in excess of 60°. We also present dynamic tomography algorithms that enable the changes between one moment and the next to be reconstructed from a sparse set of projections, allowing higher speed imaging of time-varying samples. Researchers at the facility have also created a sizeable distributed-memory image analysis toolkit with capabilities ranging from tomographic image reconstruction to 3D shape characterisation. We show results from image registration and present some of the new imaging and experimental techniques that it enables. Finally, we discuss the crucial question of image segmentation and evaluate some recently proposed techniques for automated segmentation.

Impact of Delayed Time to Advanced Imaging on Missed Appointments Across Different Demographic and Socioeconomic Factors.

PubMed

Daye, Dania; Carrodeguas, Emmanuel; Glover, McKinley; Guerrier, Claude Emmanuel; Harvey, H Benjamin; Flores, Efrén J

2018-05-01

The aim of this study was to investigate the impact of wait days (WDs) on missed outpatient MRI appointments across different demographic and socioeconomic factors. An institutional review board-approved retrospective study was conducted among adult patients scheduled for outpatient MRI during a 12-month period. Scheduling data and demographic information were obtained. Imaging missed appointments were defined as missed scheduled imaging encounters. WDs were defined as the number of days from study order to appointment. Multivariate logistic regression was applied to assess the contribution of race and socioeconomic factors to missed appointments. Linear regression was performed to assess the relationship between missed appointment rates and WDs stratified by race, income, and patient insurance groups with analysis of covariance statistics. A total of 42,727 patients met the inclusion criteria. Mean WDs were 7.95 days. Multivariate regression showed increased odds ratio for missed appointments for patients with increased WDs (7-21 days: odds ratio [OR], 1.39; >21 days: OR, 1.77), African American patients (OR, 1.71), Hispanic patients (OR, 1.30), patients with noncommercial insurance (OR, 2.00-2.55), and those with imaging performed at the main hospital campus (OR, 1.51). Missed appointment rate linearly increased with WDs, with analysis of covariance revealing underrepresented minorities and Medicaid insurance as significant effect modifiers. Increased WDs for advanced imaging significantly increases the likelihood of missed appointments. This effect is most pronounced among underrepresented minorities and patients with lower socioeconomic status. Efforts to reduce WDs may improve equity in access to and utilization of advanced diagnostic imaging for all patients. Copyright © 2018. Published by Elsevier Inc.

Imaging mass spectrometry data reduction: automated feature identification and extraction.

PubMed

McDonnell, Liam A; van Remoortere, Alexandra; de Velde, Nico; van Zeijl, René J M; Deelder, André M

2010-12-01

Imaging MS now enables the parallel analysis of hundreds of biomolecules, spanning multiple molecular classes, which allows tissues to be described by their molecular content and distribution. When combined with advanced data analysis routines, tissues can be analyzed and classified based solely on their molecular content. Such molecular histology techniques have been used to distinguish regions with differential molecular signatures that could not be distinguished using established histologic tools. However, its potential to provide an independent, complementary analysis of clinical tissues has been limited by the very large file sizes and large number of discrete variables associated with imaging MS experiments. Here we demonstrate data reduction tools, based on automated feature identification and extraction, for peptide, protein, and lipid imaging MS, using multiple imaging MS technologies, that reduce data loads and the number of variables by >100×, and that highlight highly-localized features that can be missed using standard data analysis strategies. It is then demonstrated how these capabilities enable multivariate analysis on large imaging MS datasets spanning multiple tissues. Copyright © 2010 American Society for Mass Spectrometry. Published by Elsevier Inc. All rights reserved.

IMAGE EXPLORER: Astronomical Image Analysis on an HTML5-based Web Application

NASA Astrophysics Data System (ADS)

Gopu, A.; Hayashi, S.; Young, M. D.

2014-05-01

Large datasets produced by recent astronomical imagers cause the traditional paradigm for basic visual analysis - typically downloading one's entire image dataset and using desktop clients like DS9, Aladin, etc. - to not scale, despite advances in desktop computing power and storage. This paper describes Image Explorer, a web framework that offers several of the basic visualization and analysis functionality commonly provided by tools like DS9, on any HTML5 capable web browser on various platforms. It uses a combination of the modern HTML5 canvas, JavaScript, and several layers of lossless PNG tiles producted from the FITS image data. Astronomers are able to rapidly and simultaneously open up several images on their web-browser, adjust the intensity min/max cutoff or its scaling function, and zoom level, apply color-maps, view position and FITS header information, execute typically used data reduction codes on the corresponding FITS data using the FRIAA framework, and overlay tiles for source catalog objects, etc.

The Image Data Resource: A Bioimage Data Integration and Publication Platform.

PubMed

Williams, Eleanor; Moore, Josh; Li, Simon W; Rustici, Gabriella; Tarkowska, Aleksandra; Chessel, Anatole; Leo, Simone; Antal, Bálint; Ferguson, Richard K; Sarkans, Ugis; Brazma, Alvis; Salas, Rafael E Carazo; Swedlow, Jason R

2017-08-01

Access to primary research data is vital for the advancement of science. To extend the data types supported by community repositories, we built a prototype Image Data Resource (IDR) that collects and integrates imaging data acquired across many different imaging modalities. IDR links data from several imaging modalities, including high-content screening, super-resolution and time-lapse microscopy, digital pathology, public genetic or chemical databases, and cell and tissue phenotypes expressed using controlled ontologies. Using this integration, IDR facilitates the analysis of gene networks and reveals functional interactions that are inaccessible to individual studies. To enable re-analysis, we also established a computational resource based on Jupyter notebooks that allows remote access to the entire IDR. IDR is also an open source platform that others can use to publish their own image data. Thus IDR provides both a novel on-line resource and a software infrastructure that promotes and extends publication and re-analysis of scientific image data.

Nuclear cardiograph and scintigraphy

NASA Technical Reports Server (NTRS)

Mclaughlin, P.

1975-01-01

Extensive advances in the technology of detectors, data analysis systems, and tracers used have resulted in greatly expanded applications of radioisotopes to the assessment of cardiac function and disease. The development of nuclear cardiology has proceeded along four lines: (1) radionuclide angiography, (2) myocardial perfusion imaging, (3) intracoronary microsphere imaging, and (4) regional myocardial blood flow determination using inert gases.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis

PubMed Central

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine

2018-01-01

Background Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. Objective The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. Methods The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Results Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. Conclusions MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians’ skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. PMID:29720361

Toshiba TDF-500 High Resolution Viewing And Analysis System

NASA Astrophysics Data System (ADS)

Roberts, Barry; Kakegawa, M.; Nishikawa, M.; Oikawa, D.

1988-06-01

A high resolution, operator interactive, medical viewing and analysis system has been developed by Toshiba and Bio-Imaging Research. This system provides many advanced features including high resolution displays, a very large image memory and advanced image processing capability. In particular, the system provides CRT frame buffers capable of update in one frame period, an array processor capable of image processing at operator interactive speeds, and a memory system capable of updating multiple frame buffers at frame rates whilst supporting multiple array processors. The display system provides 1024 x 1536 display resolution at 40Hz frame and 80Hz field rates. In particular, the ability to provide whole or partial update of the screen at the scanning rate is a key feature. This allows multiple viewports or windows in the display buffer with both fixed and cine capability. To support image processing features such as windowing, pan, zoom, minification, filtering, ROI analysis, multiplanar and 3D reconstruction, a high performance CPU is integrated into the system. This CPU is an array processor capable of up to 400 million instructions per second. To support the multiple viewer and array processors' instantaneous high memory bandwidth requirement, an ultra fast memory system is used. This memory system has a bandwidth capability of 400MB/sec and a total capacity of 256MB. This bandwidth is more than adequate to support several high resolution CRT's and also the fast processing unit. This fully integrated approach allows effective real time image processing. The integrated design of viewing system, memory system and array processor are key to the imaging system. It is the intention to describe the architecture of the image system in this paper.

Processing and analysis of commercial satellite image data of the nuclear accident near Chernobyl, U.S.S.R.

USGS Publications Warehouse

Sadowski, Franklin G.; Covington, Steven J.

1987-01-01

Advanced digital processing techniques were applied to Landsat-5 Thematic Mapper (TM) data and SPOT highresolution visible (HRV) panchromatic data to maximize the utility of images of a nuclear powerplant emergency at Chernobyl in the Soviet Ukraine. The images demonstrate the unique interpretive capabilities provided by the numerous spectral bands of the Thematic Mapper and the high spatial resolution of the SPOT HRV sensor.

Multiscale Image Processing of Solar Image Data

NASA Astrophysics Data System (ADS)

Young, C.; Myers, D. C.

2001-12-01

It is often said that the blessing and curse of solar physics is too much data. Solar missions such as Yohkoh, SOHO and TRACE have shown us the Sun with amazing clarity but have also increased the amount of highly complex data. We have improved our view of the Sun yet we have not improved our analysis techniques. The standard techniques used for analysis of solar images generally consist of observing the evolution of features in a sequence of byte scaled images or a sequence of byte scaled difference images. The determination of features and structures in the images are done qualitatively by the observer. There is little quantitative and objective analysis done with these images. Many advances in image processing techniques have occured in the past decade. Many of these methods are possibly suited for solar image analysis. Multiscale/Multiresolution methods are perhaps the most promising. These methods have been used to formulate the human ability to view and comprehend phenomena on different scales. So these techniques could be used to quantitify the imaging processing done by the observers eyes and brains. In this work we present several applications of multiscale techniques applied to solar image data. Specifically, we discuss uses of the wavelet, curvelet, and related transforms to define a multiresolution support for EIT, LASCO and TRACE images.

Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury

PubMed Central

Bigler, Erin D.

2016-01-01

The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology perspective could represent a significant advancement for the field. PMID:27555810

Connectome imaging for mapping human brain pathways

PubMed Central

Shi, Y; Toga, A W

2017-01-01

With the fast advance of connectome imaging techniques, we have the opportunity of mapping the human brain pathways in vivo at unprecedented resolution. In this article we review the current developments of diffusion magnetic resonance imaging (MRI) for the reconstruction of anatomical pathways in connectome studies. We first introduce the background of diffusion MRI with an emphasis on the technical advances and challenges in state-of-the-art multi-shell acquisition schemes used in the Human Connectome Project. Characterization of the microstructural environment in the human brain is discussed from the tensor model to the general fiber orientation distribution (FOD) models that can resolve crossing fibers in each voxel of the image. Using FOD-based tractography, we describe novel methods for fiber bundle reconstruction and graph-based connectivity analysis. Building upon these novel developments, there have already been successful applications of connectome imaging techniques in reconstructing challenging brain pathways. Examples including retinofugal and brainstem pathways will be reviewed. Finally, we discuss future directions in connectome imaging and its interaction with other aspects of brain imaging research. PMID:28461700

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques

PubMed Central

Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M.; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V.; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L.; Bilello, Michel; O'Rourke, Donald M.; Davatzikos, Christos

2016-01-01

Background MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). Methods One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Results Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. Conclusions By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood–brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. PMID:26188015

Emergency physician perceptions of medically unnecessary advanced diagnostic imaging.

PubMed

Kanzaria, Hemal K; Hoffman, Jerome R; Probst, Marc A; Caloyeras, John P; Berry, Sandra H; Brook, Robert H

2015-04-01

The objective was to determine emergency physician (EP) perceptions regarding 1) the extent to which they order medically unnecessary advanced diagnostic imaging, 2) factors that contribute to this behavior, and 3) proposed solutions for curbing this practice. As part of a larger study to engage physicians in the delivery of high-value health care, two multispecialty focus groups were conducted to explore the topic of decision-making around resource utilization, after which qualitative analysis was used to generate survey questions. The survey was extensively pilot-tested and refined for emergency medicine (EM) to focus on advanced diagnostic imaging (i.e., computed tomography [CT] or magnetic resonance imaging [MRI]). The survey was then administered to a national, purposive sample of EPs and EM trainees. Simple descriptive statistics to summarize physician responses are presented. In this study, 478 EPs were approached, of whom 435 (91%) completed the survey; 68% of respondents were board-certified, and roughly half worked in academic emergency departments (EDs). Over 85% of respondents believe too many diagnostic tests are ordered in their own EDs, and 97% said at least some (mean = 22%) of the advanced imaging studies they personally order are medically unnecessary. The main perceived contributors were fear of missing a low-probability diagnosis and fear of litigation. Solutions most commonly felt to be "extremely" or "very" helpful for reducing unnecessary imaging included malpractice reform (79%), increased patient involvement through education (70%) and shared decision-making (56%), feedback to physicians on test-ordering metrics (55%), and improved education of physicians on diagnostic testing (50%). Overordering of advanced imaging may be a systemic problem, as many EPs believe a substantial proportion of such studies, including some they personally order, are medically unnecessary. Respondents cited multiple complex factors with several potential high-yield solutions that must be addressed simultaneously to curb overimaging. © 2015 by the Society for Academic Emergency Medicine.

Dual-isotope Cryo-imaging Quantitative Autoradiography (CIQA): Anvestigating Antibody-Drug Conjugate Distribution And Payload Delivery Through Imaging.

PubMed

Ilovich, Ohad; Qutaish, Mohammed; Hesterman, Jacob; Orcutt, Kelly; Hoppin, Jack; Polyak, Ildiko; Seaman, Marc; Abu-Yousif, Adnan; Cvet, Donna; Bradley, Daniel

2018-05-04

In vitro properties of antibody drug conjugates (ADCs) such as binding, internalization, and cytotoxicity are often well characterized prior to in vivo studies. Interpretation of in vivo studies could significantly be enhanced by molecular imaging tools. We present here a dual-isotope cryo-imaging quantitative autoradiography (CIQA) methodology combined with advanced 3D imaging and analysis allowing for the simultaneous study of both antibody and payload distribution in tissues of interest. in a pre-clinical setting. Methods: TAK-264, an investigational anti-guanylyl cyclase C (GCC) targeting ADC was synthesized utilizing tritiated Monomethyl auristatin E (MMAE). The tritiated ADC was then conjugated to DTPA, labeled with indium-111 and evaluated in vivo in GCC-positive and GCC-negative tumor-bearing animals. Results: Cryo-imaging Quantitative Autoradiography (CIQA) reveals the time course of drug release from ADC and its distribution into various tumor regions seemingly impenetrablethat are less accessible to the antibody. For GCC-positive tumors, a representative section obtained 96 hours post tracer injection showed only 0.8% of the voxels have co-localized signal versus over 15% of the voxels for a GCC-negative tumor section., suggesting successful and specific cleaving of the toxin in the antigen positive lesions. Conclusion: The combination of a veteran established autoradiography technology with advanced image analysis methodologies affords an experimental tool that can support detailed characterization of ADC tumor penetration and pharmacokinetics. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

An enhanced MMW and SMMW/THz imaging system performance prediction and analysis tool for concealed weapon detection and pilotage obstacle avoidance

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Jacobs, Eddie L.; Franck, Charmaine C.; Petkie, Douglas T.; De Lucia, Frank C.

2015-10-01

The U.S. Army Research Laboratory (ARL) has continued to develop and enhance a millimeter-wave (MMW) and submillimeter- wave (SMMW)/terahertz (THz)-band imaging system performance prediction and analysis tool for both the detection and identification of concealed weaponry, and for pilotage obstacle avoidance. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security and Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). Further development of this tool that includes a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures was reported on at the 2011 SPIE Europe Security and Defence Symposium (Prague). This paper provides a comprehensive review of a newly enhanced MMW and SMMW/THz imaging system analysis and design tool that now includes an improved noise sub-model for more accurate and reliable performance predictions, the capability to account for postcapture image contrast enhancement, and the capability to account for concealment material backscatter with active-illumination- based systems. Present plans for additional expansion of the model's predictive capabilities are also outlined.

TU-CD-BRB-08: Radiomic Analysis of FDG-PET Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated with SBRT

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

Cui, Y; Shirato, H; Song, J

2015-06-15

Purpose: This study aims to identify novel prognostic imaging biomarkers in locally advanced pancreatic cancer (LAPC) using quantitative, high-throughput image analysis. Methods: 86 patients with LAPC receiving chemotherapy followed by SBRT were retrospectively studied. All patients had a baseline FDG-PET scan prior to SBRT. For each patient, we extracted 435 PET imaging features of five types: statistical, morphological, textural, histogram, and wavelet. These features went through redundancy checks, robustness analysis, as well as a prescreening process based on their concordance indices with respect to the relevant outcomes. We then performed principle component analysis on the remaining features (number ranged frommore » 10 to 16), and fitted a Cox proportional hazard regression model using the first 3 principle components. Kaplan-Meier analysis was used to assess the ability to distinguish high versus low-risk patients separated by median predicted survival. To avoid overfitting, all evaluations were based on leave-one-out cross validation (LOOCV), in which each holdout patient was assigned to a risk group according to the model obtained from a separate training set. Results: For predicting overall survival (OS), the most dominant imaging features were wavelet coefficients. There was a statistically significant difference in OS between patients with predicted high and low-risk based on LOOCV (hazard ratio: 2.26, p<0.001). Similar imaging features were also strongly associated with local progression-free survival (LPFS) (hazard ratio: 1.53, p=0.026) on LOOCV. In comparison, neither SUVmax nor TLG was associated with LPFS (p=0.103, p=0.433) (Table 1). Results for progression-free survival and distant progression-free survival showed similar trends. Conclusion: Radiomic analysis identified novel imaging features that showed improved prognostic value over conventional methods. These features characterize the degree of intra-tumor heterogeneity reflected on FDG-PET images, and their biological underpinnings warrant further investigation. If validated in large, prospective cohorts, this method could be used to stratify patients based on individualized risk.« less

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

PubMed Central

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

Developing students’ ideas about lens imaging: teaching experiments with an image-based approach

NASA Astrophysics Data System (ADS)

Grusche, Sascha

2017-07-01

Lens imaging is a classic topic in physics education. To guide students from their holistic viewpoint to the scientists’ analytic viewpoint, an image-based approach to lens imaging has recently been proposed. To study the effect of the image-based approach on undergraduate students’ ideas, teaching experiments are performed and evaluated using qualitative content analysis. Some of the students’ ideas have not been reported before, namely those related to blurry lens images, and those developed by the proposed teaching approach. To describe learning pathways systematically, a conception-versus-time coordinate system is introduced, specifying how teaching actions help students advance toward a scientific understanding.

Processing and analysis of commercial satellite image data of the nuclear accident near Chernobyl, U. S. S. R

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

Sadowski, F.G.; Covington, S.J.

1987-01-01

Advanced digital processing techniques were applied to Landsat-5 Thematic Mapper (TM) data and SPOT high-resolution visible (HRV) panchromatic data to maximize the utility of images of a nuclear power plant emergency at Chernobyl in the Soviet Ukraine. The results of the data processing and analysis illustrate the spectral and spatial capabilities of the two sensor systems and provide information about the severity and duration of the events occurring at the power plant site.

Software for visualization, analysis, and manipulation of laser scan images

NASA Astrophysics Data System (ADS)

Burnsides, Dennis B.

1997-03-01

The recent introduction of laser surface scanning to scientific applications presents a challenge to computer scientists and engineers. Full utilization of this two- dimensional (2-D) and three-dimensional (3-D) data requires advances in techniques and methods for data processing and visualization. This paper explores the development of software to support the visualization, analysis and manipulation of laser scan images. Specific examples presented are from on-going efforts at the Air Force Computerized Anthropometric Research and Design (CARD) Laboratory.

Advanced IR System For Supersonic Boundary Layer Transition Flight Experiment

NASA Technical Reports Server (NTRS)

Banks, Daniel W.

2008-01-01

Infrared thermography is a preferred method investigating transition in flight: a) Global and non-intrusive; b) Can also be used to visualize and characterize other fluid mechanic phenomena such as shock impingement, separation etc. F-15 based system was updated with new camera and digital video recorder to support high Reynolds number transition tests. Digital Recording improves image quality and analysis capability and allows for accurate quantitative (temperature) measurements and greater enhancement through image processing allows analysis of smaller scale phenomena.

Fast interactive exploration of 4D MRI flow data

NASA Astrophysics Data System (ADS)

Hennemuth, A.; Friman, O.; Schumann, C.; Bock, J.; Drexl, J.; Huellebrand, M.; Markl, M.; Peitgen, H.-O.

2011-03-01

1- or 2-directional MRI blood flow mapping sequences are an integral part of standard MR protocols for diagnosis and therapy control in heart diseases. Recent progress in rapid MRI has made it possible to acquire volumetric, 3-directional cine images in reasonable scan time. In addition to flow and velocity measurements relative to arbitrarily oriented image planes, the analysis of 3-dimensional trajectories enables the visualization of flow patterns, local features of flow trajectories or possible paths into specific regions. The anatomical and functional information allows for advanced hemodynamic analysis in different application areas like stroke risk assessment, congenital and acquired heart disease, aneurysms or abdominal collaterals and cranial blood flow. The complexity of the 4D MRI flow datasets and the flow related image analysis tasks makes the development of fast comprehensive data exploration software for advanced flow analysis a challenging task. Most existing tools address only individual aspects of the analysis pipeline such as pre-processing, quantification or visualization, or are difficult to use for clinicians. The goal of the presented work is to provide a software solution that supports the whole image analysis pipeline and enables data exploration with fast intuitive interaction and visualization methods. The implemented methods facilitate the segmentation and inspection of different vascular systems. Arbitrary 2- or 3-dimensional regions for quantitative analysis and particle tracing can be defined interactively. Synchronized views of animated 3D path lines, 2D velocity or flow overlays and flow curves offer a detailed insight into local hemodynamics. The application of the analysis pipeline is shown for 6 cases from clinical practice, illustrating the usefulness for different clinical questions. Initial user tests show that the software is intuitive to learn and even inexperienced users achieve good results within reasonable processing times.

Semiautomated analysis of embryoscope images: Using localized variance of image intensity to detect embryo developmental stages.

PubMed

Mölder, Anna; Drury, Sarah; Costen, Nicholas; Hartshorne, Geraldine M; Czanner, Silvester

2015-02-01

Embryo selection in in vitro fertilization (IVF) treatment has traditionally been done manually using microscopy at intermittent time points during embryo development. Novel technique has made it possible to monitor embryos using time lapse for long periods of time and together with the reduced cost of data storage, this has opened the door to long-term time-lapse monitoring, and large amounts of image material is now routinely gathered. However, the analysis is still to a large extent performed manually, and images are mostly used as qualitative reference. To make full use of the increased amount of microscopic image material, (semi)automated computer-aided tools are needed. An additional benefit of automation is the establishment of standardization tools for embryo selection and transfer, making decisions more transparent and less subjective. Another is the possibility to gather and analyze data in a high-throughput manner, gathering data from multiple clinics and increasing our knowledge of early human embryo development. In this study, the extraction of data to automatically select and track spatio-temporal events and features from sets of embryo images has been achieved using localized variance based on the distribution of image grey scale levels. A retrospective cohort study was performed using time-lapse imaging data derived from 39 human embryos from seven couples, covering the time from fertilization up to 6.3 days. The profile of localized variance has been used to characterize syngamy, mitotic division and stages of cleavage, compaction, and blastocoel formation. Prior to analysis, focal plane and embryo location were automatically detected, limiting precomputational user interaction to a calibration step and usable for automatic detection of region of interest (ROI) regardless of the method of analysis. The results were validated against the opinion of clinical experts. © 2015 International Society for Advancement of Cytometry. © 2015 International Society for Advancement of Cytometry.

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis

PubMed Central

Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L.; Hwang, Jae Youn

2016-01-01

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis. PMID:28018743

Recent Advances in Techniques for Hyperspectral Image Processing

NASA Technical Reports Server (NTRS)

Plaza, Antonio; Benediktsson, Jon Atli; Boardman, Joseph W.; Brazile, Jason; Bruzzone, Lorenzo; Camps-Valls, Gustavo; Chanussot, Jocelyn; Fauvel, Mathieu; Gamba, Paolo; Gualtieri, Anthony;

Point-of-care and point-of-procedure optical imaging technologies for primary care and global health.

PubMed

Boppart, Stephen A; Richards-Kortum, Rebecca

2014-09-10

Leveraging advances in consumer electronics and wireless telecommunications, low-cost, portable optical imaging devices have the potential to improve screening and detection of disease at the point of care in primary health care settings in both low- and high-resource countries. Similarly, real-time optical imaging technologies can improve diagnosis and treatment at the point of procedure by circumventing the need for biopsy and analysis by expert pathologists, who are scarce in developing countries. Although many optical imaging technologies have been translated from bench to bedside, industry support is needed to commercialize and broadly disseminate these from the patient level to the population level to transform the standard of care. This review provides an overview of promising optical imaging technologies, the infrastructure needed to integrate them into widespread clinical use, and the challenges that must be addressed to harness the potential of these technologies to improve health care systems around the world. Copyright © 2014, American Association for the Advancement of Science.

Advanced Renal Cell Carcinoma: Role of the Radiologist in the Era of Precision Medicine.

PubMed

Shinagare, Atul B; Krajewski, Katherine M; Braschi-Amirfarzan, Marta; Ramaiya, Nikhil H

2017-08-01

For the past decade, advanced renal cell carcinoma (RCC) has been at the forefront of oncologic innovation. Our rapidly evolving understanding of the molecular and genetic basis of RCC has revolutionized the management of advanced RCC; 10 novel molecular targeted agents and immune checkpoint inhibitor have received U.S. Food and Drug Administration approval for treatment of advanced RCC in a little over a decade. Amid this progress, imaging has assumed a central role in metastatic surveillance and follow-up of advanced RCC. State-of-the-art knowledge of the molecular basis of RCC and its treatment and imaging will help ensure that the radiology community remains relevant and central in the care of patients with advanced RCC. This article will review developments in management of advanced RCC from a radiologist's perspective to highlight our clinical role. It will describe how the underlying molecular mechanisms of RCC provide specific targets for novel anticancer agents. The relationship between the mechanisms of action of these novel anticancer agents and the imaging appearance of tumor response will be discussed, along with the available tumor response criteria and their strengths and weaknesses, thus assisting radiologists in response assessment in the setting of clinical trials or routine practice. The class- and drug-specific toxicities and complications associated with the novel anticancer agents will be summarized, since these are frequently missed or misinterpreted and require the radiologist's input in prompt detection and management. The potential role of radiogenomics and texture analysis in the management of advanced RCC will also be discussed. © RSNA, 2017.

Advances in image compression and automatic target recognition; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

NASA Technical Reports Server (NTRS)

Tescher, Andrew G. (Editor)

1989-01-01

Various papers on image compression and automatic target recognition are presented. Individual topics addressed include: target cluster detection in cluttered SAR imagery, model-based target recognition using laser radar imagery, Smart Sensor front-end processor for feature extraction of images, object attitude estimation and tracking from a single video sensor, symmetry detection in human vision, analysis of high resolution aerial images for object detection, obscured object recognition for an ATR application, neural networks for adaptive shape tracking, statistical mechanics and pattern recognition, detection of cylinders in aerial range images, moving object tracking using local windows, new transform method for image data compression, quad-tree product vector quantization of images, predictive trellis encoding of imagery, reduced generalized chain code for contour description, compact architecture for a real-time vision system, use of human visibility functions in segmentation coding, color texture analysis and synthesis using Gibbs random fields.

Theory and applications of structured light single pixel imaging

NASA Astrophysics Data System (ADS)

Stokoe, Robert J.; Stockton, Patrick A.; Pezeshki, Ali; Bartels, Randy A.

2018-02-01

Many single-pixel imaging techniques have been developed in recent years. Though the methods of image acquisition vary considerably, the methods share unifying features that make general analysis possible. Furthermore, the methods developed thus far are based on intuitive processes that enable simple and physically-motivated reconstruction algorithms, however, this approach may not leverage the full potential of single-pixel imaging. We present a general theoretical framework of single-pixel imaging based on frame theory, which enables general, mathematically rigorous analysis. We apply our theoretical framework to existing single-pixel imaging techniques, as well as provide a foundation for developing more-advanced methods of image acquisition and reconstruction. The proposed frame theoretic framework for single-pixel imaging results in improved noise robustness, decrease in acquisition time, and can take advantage of special properties of the specimen under study. By building on this framework, new methods of imaging with a single element detector can be developed to realize the full potential associated with single-pixel imaging.

Single-Cell and Single-Molecule Analysis of Gene Expression Regulation.

PubMed

Vera, Maria; Biswas, Jeetayu; Senecal, Adrien; Singer, Robert H; Park, Hye Yoon

2016-11-23

Recent advancements in single-cell and single-molecule imaging technologies have resolved biological processes in time and space that are fundamental to understanding the regulation of gene expression. Observations of single-molecule events in their cellular context have revealed highly dynamic aspects of transcriptional and post-transcriptional control in eukaryotic cells. This approach can relate transcription with mRNA abundance and lifetimes. Another key aspect of single-cell analysis is the cell-to-cell variability among populations of cells. Definition of heterogeneity has revealed stochastic processes, determined characteristics of under-represented cell types or transitional states, and integrated cellular behaviors in the context of multicellular organisms. In this review, we discuss novel aspects of gene expression of eukaryotic cells and multicellular organisms revealed by the latest advances in single-cell and single-molecule imaging technology.

Advanced ECG in 2016: is there more than just a tracing?

PubMed

Reichlin, Tobias; Abächerli, Roger; Twerenbold, Raphael; Kühne, Michael; Schaer, Beat; Müller, Christian; Sticherling, Christian; Osswald, Stefan

2016-01-01

The 12-lead electrocardiogram (ECG) is the most frequently used technology in clinical cardiology. It is critical for evidence-based management of patients with most cardiovascular conditions, including patients with acute myocardial infarction, suspected chronic cardiac ischaemia, cardiac arrhythmias, heart failure and implantable cardiac devices. In contrast to many other techniques in cardiology, the ECG is simple, small, mobile, universally available and cheap, and therefore particularly attractive. Standard ECG interpretation mainly relies on direct visual assessment. The progress in biomedical computing and signal processing, and the available computational power offer fascinating new options for ECG analysis relevant to all fields of cardiology. Several digital ECG markers and advanced ECG technologies have shown promise in preliminary studies. This article reviews promising novel surface ECG technologies in three different fields. (1) For the detection of myocardial ischaemia and infarction, QRS morphology feature analysis, the analysis of high frequency QRS components (HF-QRS) and methods using vectorcardiography as well as ECG imaging are discussed. (2) For the identification and management of patients with cardiac arrhythmias, methods of advanced P-wave analysis are discussed and the concept of ECG imaging for noninvasive localisation of cardiac arrhythmias is presented. (3) For risk stratification of sudden cardiac death and the selection of patients for medical device therapy, several novel markers including an automated QRS-score for scar quantification, the QRS-T angle or the T-wave peak-to-end-interval are discussed. Despite the existing preliminary data, none of the advanced ECG markers and technologies has yet accomplished the transition into clinical practice. Further refinement of these technologies and broader validation in large unselected patient cohorts are the critical next step needed to facilitate translation of advanced ECG technologies into clinical cardiology.

Stereoscopic video analysis of Anopheles gambiae behavior in the field: challenges and opportunities

USDA-ARS?s Scientific Manuscript database

Advances in our ability to localize and track individual swarming mosquitoes in the field via stereoscopic image analysis have enabled us to test long standing ideas about individual male behavior and directly observe coupling. These studies further our fundamental understanding of the reproductive ...

Earth remote sensing - 1970-1995

NASA Technical Reports Server (NTRS)

Thome, P. G.

1984-01-01

The past-achievements, current status, and future prospects of the Landsat terrestrial-remote-sensing satellite program are surveyed. Topics examined include the early history of space flight; the development of analysis techniques to interpret the multispectral images obtained by Landsats 1, 2, and 3; the characteristics of the advanced Landsat-4 Thematic Mapper; microwave scanning by Seasat and the Shuttle Imaging Radar; the usefulness of low-resolution AVHRR data from the NOAA satellites; improvements in Landsats 4 and 5 to permit tailoring of information to user needs; expansion and internationalization of the remote-sensing market in the late 1980s; and technological advances in both instrumentation and data-processing predicted by the 1990s.

Earth Observing-1 Advanced Imager Flight Performance Assessment: Investigating Dark Current Stability Over One-Half Orbit Period during the First 60 Days

NASA Technical Reports Server (NTRS)

Mendenhall, J. A.

2001-01-01

The stability of the EO-1 Advanced Land Imager dark current levels over the period of one-half orbit is investigated. A series of two-second dark current collections, over the course of 40 minutes, was performed during the first sixty days the instrument was in orbit. Analysis of this data indicates only two dark current reference periods, obtained entering and exiting eclipse, are required to remove ALI dark current offsets for 99.9% of the focal plane to within 1.5 digital numbers for any observation on the solar illuminated portion of the orbit.

Spacecraft Alignment Determination and Control for Dual Spacecraft Precision Formation Flying

NASA Technical Reports Server (NTRS)

Calhoun, Philip; Novo-Gradac, Anne-Marie; Shah, Neerav

2017-01-01

Many proposed formation flying missions seek to advance the state of the art in spacecraft science imaging by utilizing precision dual spacecraft formation flying to enable a virtual space telescope. Using precision dual spacecraft alignment, very long focal lengths can be achieved by locating the optics on one spacecraft and the detector on the other. Proposed science missions include astrophysics concepts with spacecraft separations from 1000 km to 25,000 km, such as the Milli-Arc-Second Structure Imager (MASSIM) and the New Worlds Observer, and Heliophysics concepts for solar coronagraphs and X-ray imaging with smaller separations (50m-500m). All of these proposed missions require advances in guidance, navigation, and control (GNC) for precision formation flying. In particular, very precise astrometric alignment control and estimation is required for precise inertial pointing of the virtual space telescope to enable science imaging orders of magnitude better than can be achieved with conventional single spacecraft instruments. This work develops design architectures, algorithms, and performance analysis of proposed GNC systems for precision dual spacecraft astrometric alignment. These systems employ a variety of GNC sensors and actuators, including laser-based alignment and ranging systems, optical imaging sensors (e.g. guide star telescope), inertial measurement units (IMU), as well as microthruster and precision stabilized platforms. A comprehensive GNC performance analysis is given for Heliophysics dual spacecraft PFF imaging mission concept.

Spacecraft Alignment Determination and Control for Dual Spacecraft Precision Formation Flying

NASA Technical Reports Server (NTRS)

Calhoun, Philip C.; Novo-Gradac, Anne-Marie; Shah, Neerav

2017-01-01

Many proposed formation flying missions seek to advance the state of the art in spacecraft science imaging by utilizing precision dual spacecraft formation flying to enable a virtual space telescope. Using precision dual spacecraft alignment, very long focal lengths can be achieved by locating the optics on one spacecraft and the detector on the other. Proposed science missions include astrophysics concepts with spacecraft separations from 1000 km to 25,000 km, such as the Milli-Arc-Second Structure Imager (MASSIM) and the New Worlds Observer, and Heliophysics concepts for solar coronagraphs and X-ray imaging with smaller separations (50m 500m). All of these proposed missions require advances in guidance, navigation, and control (GNC) for precision formation flying. In particular, very precise astrometric alignment control and estimation is required for precise inertial pointing of the virtual space telescope to enable science imaging orders of magnitude better than can be achieved with conventional single spacecraft instruments. This work develops design architectures, algorithms, and performance analysis of proposed GNC systems for precision dual spacecraft astrometric alignment. These systems employ a variety of GNC sensors and actuators, including laser-based alignment and ranging systems, optical imaging sensors (e.g. guide star telescope), inertial measurement units (IMU), as well as micro-thruster and precision stabilized platforms. A comprehensive GNC performance analysis is given for Heliophysics dual spacecraft PFF imaging mission concept.

Design Criteria For Networked Image Analysis System

NASA Astrophysics Data System (ADS)

Reader, Cliff; Nitteberg, Alan

1982-01-01

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

Recent advances in imaging technologies in dentistry.

PubMed

Shah, Naseem; Bansal, Nikhil; Logani, Ajay

2014-10-28

Dentistry has witnessed tremendous advances in all its branches over the past three decades. With these advances, the need for more precise diagnostic tools, specially imaging methods, have become mandatory. From the simple intra-oral periapical X-rays, advanced imaging techniques like computed tomography, cone beam computed tomography, magnetic resonance imaging and ultrasound have also found place in modern dentistry. Changing from analogue to digital radiography has not only made the process simpler and faster but also made image storage, manipulation (brightness/contrast, image cropping, etc.) and retrieval easier. The three-dimensional imaging has made the complex cranio-facial structures more accessible for examination and early and accurate diagnosis of deep seated lesions. This paper is to review current advances in imaging technology and their uses in different disciplines of dentistry.

Recent advances in imaging technologies in dentistry

PubMed Central

Shah, Naseem; Bansal, Nikhil; Logani, Ajay

2014-01-01

Dentistry has witnessed tremendous advances in all its branches over the past three decades. With these advances, the need for more precise diagnostic tools, specially imaging methods, have become mandatory. From the simple intra-oral periapical X-rays, advanced imaging techniques like computed tomography, cone beam computed tomography, magnetic resonance imaging and ultrasound have also found place in modern dentistry. Changing from analogue to digital radiography has not only made the process simpler and faster but also made image storage, manipulation (brightness/contrast, image cropping, etc.) and retrieval easier. The three-dimensional imaging has made the complex cranio-facial structures more accessible for examination and early and accurate diagnosis of deep seated lesions. This paper is to review current advances in imaging technology and their uses in different disciplines of dentistry. PMID:25349663

Progress in analysis of computed tomography (CT) images of hardwood logs for defect detection

Treesearch

Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt

2003-01-01

This paper addresses the problem of automatically detecting internal defects in logs using computed tomography (CT) images. The overall purpose is to assist in breakdown optimization. Several studies have shown that the commercial value of resulting boards can be increased substantially if defect locations are known in advance, and if this information is used to make...

Medical ultrasound - From inner space to outer space

NASA Technical Reports Server (NTRS)

Rooney, J. A.

1984-01-01

During the last decade, medical ultrasound has rapidly become a widely accepted imaging modality used in many medical specialties. It has the advantages that it is noninvasive, does not use ionizing radiation, is relatively inexpensive and is easy to use. Future trends in ultrasound include expanded areas of use, advanced signal processing and digital image analysis including tissue characterization and three-dimensional reconstructions.

High resolution image processing on low-cost microcomputers

NASA Technical Reports Server (NTRS)

Miller, R. L.

1993-01-01

Recent advances in microcomputer technology have resulted in systems that rival the speed, storage, and display capabilities of traditionally larger machines. Low-cost microcomputers can provide a powerful environment for image processing. A new software program which offers sophisticated image display and analysis on IBM-based systems is presented. Designed specifically for a microcomputer, this program provides a wide-range of functions normally found only on dedicated graphics systems, and therefore can provide most students, universities and research groups with an affordable computer platform for processing digital images. The processing of AVHRR images within this environment is presented as an example.

Advanced 3-D analysis, client-server systems, and cloud computing-Integration of cardiovascular imaging data into clinical workflows of transcatheter aortic valve replacement.

PubMed

Schoenhagen, Paul; Zimmermann, Mathis; Falkner, Juergen

2013-06-01

Degenerative aortic stenosis is highly prevalent in the aging populations of industrialized countries and is associated with poor prognosis. Surgical valve replacement has been the only established treatment with documented improvement of long-term outcome. However, many of the older patients with aortic stenosis (AS) are high-risk or ineligible for surgery. For these patients, transcatheter aortic valve replacement (TAVR) has emerged as a treatment alternative. The TAVR procedure is characterized by a lack of visualization of the operative field. Therefore, pre- and intra-procedural imaging is critical for patient selection, pre-procedural planning, and intra-operative decision-making. Incremental to conventional angiography and 2-D echocardiography, multidetector computed tomography (CT) has assumed an important role before TAVR. The analysis of 3-D CT data requires extensive post-processing during direct interaction with the dataset, using advance analysis software. Organization and storage of the data according to complex clinical workflows and sharing of image information have become a critical part of these novel treatment approaches. Optimally, the data are integrated into a comprehensive image data file accessible to multiple groups of practitioners across the hospital. This creates new challenges for data management requiring a complex IT infrastructure, spanning across multiple locations, but is increasingly achieved with client-server solutions and private cloud technology. This article describes the challenges and opportunities created by the increased amount of patient-specific imaging data in the context of TAVR.

The Wide-Field Imaging Interferometry Testbed (WIIT): Recent Progress and Results

NASA Technical Reports Server (NTRS)

Rinehart, Stephen A.; Frey, Bradley J.; Leisawitz, David T.; Lyon, Richard G.; Maher, Stephen F.; Martino, Anthony J.

2008-01-01

Continued research with the Wide-Field Imaging Interferometry Testbed (WIIT) has achieved several important milestones. We have moved WIIT into the Advanced Interferometry and Metrology (AIM) Laboratory at Goddard, and have characterized the testbed in this well-controlled environment. The system is now completely automated and we are in the process of acquiring large data sets for analysis. In this paper, we discuss these new developments and outline our future research directions. The WIIT testbed, combined with new data analysis techniques and algorithms, provides a demonstration of the technique of wide-field interferometric imaging, a powerful tool for future space-borne interferometers.

Performance characterization of image and video analysis systems at Siemens Corporate Research

NASA Astrophysics Data System (ADS)

Ramesh, Visvanathan; Jolly, Marie-Pierre; Greiffenhagen, Michael

2000-06-01

There has been a significant increase in commercial products using imaging analysis techniques to solve real-world problems in diverse fields such as manufacturing, medical imaging, document analysis, transportation and public security, etc. This has been accelerated by various factors: more advanced algorithms, the availability of cheaper sensors, and faster processors. While algorithms continue to improve in performance, a major stumbling block in translating improvements in algorithms to faster deployment of image analysis systems is the lack of characterization of limits of algorithms and how they affect total system performance. The research community has realized the need for performance analysis and there have been significant efforts in the last few years to remedy the situation. Our efforts at SCR have been on statistical modeling and characterization of modules and systems. The emphasis is on both white-box and black box methodologies to evaluate and optimize vision systems. In the first part of this paper we review the literature on performance characterization and then provide an overview of the status of research in performance characterization of image and video understanding systems. The second part of the paper is on performance evaluation of medical image segmentation algorithms. Finally, we highlight some research issues in performance analysis in medical imaging systems.

Bio-image warehouse system: concept and implementation of a diagnosis-based data warehouse for advanced imaging modalities in neuroradiology.

PubMed

Minati, L; Ghielmetti, F; Ciobanu, V; D'Incerti, L; Maccagnano, C; Bizzi, A; Bruzzone, M G

2007-03-01

Advanced neuroimaging techniques, such as functional magnetic resonance imaging (fMRI), chemical shift spectroscopy imaging (CSI), diffusion tensor imaging (DTI), and perfusion-weighted imaging (PWI) create novel challenges in terms of data storage and management: huge amounts of raw data are generated, the results of analysis may depend on the software and settings that have been used, and most often intermediate files are inherently not compliant with the current DICOM (digital imaging and communication in medicine) standard, as they contain multidimensional complex and tensor arrays and various other types of data structures. A software architecture, referred to as Bio-Image Warehouse System (BIWS), which can be used alongside a radiology information system/picture archiving and communication system (RIS/PACS) system to store neuroimaging data for research purposes, is presented. The system architecture is conceived with the purpose of enabling to query by diagnosis according to a predefined two-layered classification taxonomy. The operational impact of the system and the time needed to get acquainted with the web-based interface and with the taxonomy are found to be limited. The development of modules enabling automated creation of statistical templates is proposed.

Multiparametric [18F]Fluorodeoxyglucose/ [18F]Fluoromisonidazole Positron Emission Tomography/ Magnetic Resonance Imaging of Locally Advanced Cervical Cancer for the Non-Invasive Detection of Tumor Heterogeneity: A Pilot Study

PubMed Central

Andrzejewski, Piotr; Baltzer, Pascal; Polanec, Stephan H.; Sturdza, Alina; Georg, Dietmar; Helbich, Thomas H.; Karanikas, Georgios; Grimm, Christoph; Polterauer, Stephan; Poetter, Richard; Wadsak, Wolfgang; Mitterhauser, Markus; Georg, Petra

2016-01-01

Objectives To investigate fused multiparametric positron emission tomography/magnetic resonance imaging (MP PET/MRI) at 3T in patients with locally advanced cervical cancer, using high-resolution T2-weighted, contrast-enhanced MRI (CE-MRI), diffusion-weighted imaging (DWI), and the radiotracers [18F]fluorodeoxyglucose ([18F]FDG) and [18F]fluoromisonidazol ([18F]FMISO) for the non-invasive detection of tumor heterogeneity for an improved planning of chemo-radiation therapy (CRT). Materials and Methods Sixteen patients with locally advanced cervix were enrolled in this IRB approved and were examined with fused MP [18F]FDG/ [18F]FMISO PET/MRI and in eleven patients complete data sets were acquired. MP PET/MRI was assessed for tumor volume, enhancement (EH)-kinetics, diffusivity, and [18F]FDG/ [18F]FMISO-avidity. Descriptive statistics and voxel-by-voxel analysis of MRI and PET parameters were performed. Correlations were assessed using multiple correlation analysis. Results All tumors displayed imaging parameters concordant with cervix cancer, i.e. type II/III EH-kinetics, restricted diffusivity (median ADC 0.80x10-3mm2/sec), [18F]FDG- (median SUVmax16.2) and [18F]FMISO-avidity (median SUVmax3.1). In all patients, [18F]FMISO PET identified the hypoxic tumor subvolume, which was independent of tumor volume. A voxel-by-voxel analysis revealed only weak correlations between the MRI and PET parameters (0.05–0.22), indicating that each individual parameter yields independent information and the presence of tumor heterogeneity. Conclusion MP [18F]FDG/ [18F]FMISO PET/MRI in patients with cervical cancer facilitates the acquisition of independent predictive and prognostic imaging parameters. MP [18F]FDG/ [18F]FMISO PET/MRI enables insights into tumor biology on multiple levels and provides information on tumor heterogeneity, which has the potential to improve the planning of CRT. PMID:27167829

Multiparametric [18F]Fluorodeoxyglucose/ [18F]Fluoromisonidazole Positron Emission Tomography/ Magnetic Resonance Imaging of Locally Advanced Cervical Cancer for the Non-Invasive Detection of Tumor Heterogeneity: A Pilot Study.

PubMed

Pinker, Katja; Andrzejewski, Piotr; Baltzer, Pascal; Polanec, Stephan H; Sturdza, Alina; Georg, Dietmar; Helbich, Thomas H; Karanikas, Georgios; Grimm, Christoph; Polterauer, Stephan; Poetter, Richard; Wadsak, Wolfgang; Mitterhauser, Markus; Georg, Petra

2016-01-01

To investigate fused multiparametric positron emission tomography/magnetic resonance imaging (MP PET/MRI) at 3T in patients with locally advanced cervical cancer, using high-resolution T2-weighted, contrast-enhanced MRI (CE-MRI), diffusion-weighted imaging (DWI), and the radiotracers [18F]fluorodeoxyglucose ([18F]FDG) and [18F]fluoromisonidazol ([18F]FMISO) for the non-invasive detection of tumor heterogeneity for an improved planning of chemo-radiation therapy (CRT). Sixteen patients with locally advanced cervix were enrolled in this IRB approved and were examined with fused MP [18F]FDG/ [18F]FMISO PET/MRI and in eleven patients complete data sets were acquired. MP PET/MRI was assessed for tumor volume, enhancement (EH)-kinetics, diffusivity, and [18F]FDG/ [18F]FMISO-avidity. Descriptive statistics and voxel-by-voxel analysis of MRI and PET parameters were performed. Correlations were assessed using multiple correlation analysis. All tumors displayed imaging parameters concordant with cervix cancer, i.e. type II/III EH-kinetics, restricted diffusivity (median ADC 0.80x10-3mm2/sec), [18F]FDG- (median SUVmax16.2) and [18F]FMISO-avidity (median SUVmax3.1). In all patients, [18F]FMISO PET identified the hypoxic tumor subvolume, which was independent of tumor volume. A voxel-by-voxel analysis revealed only weak correlations between the MRI and PET parameters (0.05-0.22), indicating that each individual parameter yields independent information and the presence of tumor heterogeneity. MP [18F]FDG/ [18F]FMISO PET/MRI in patients with cervical cancer facilitates the acquisition of independent predictive and prognostic imaging parameters. MP [18F]FDG/ [18F]FMISO PET/MRI enables insights into tumor biology on multiple levels and provides information on tumor heterogeneity, which has the potential to improve the planning of CRT.

[Advances in automatic detection technology for images of thin blood film of malaria parasite].

PubMed

Juan-Sheng, Zhang; Di-Qiang, Zhang; Wei, Wang; Xiao-Guang, Wei; Zeng-Guo, Wang

2017-05-05

This paper reviews the computer vision and image analysis studies aiming at automated diagnosis or screening of malaria in microscope images of thin blood film smears. On the basis of introducing the background and significance of automatic detection technology, the existing detection technologies are summarized and divided into several steps, including image acquisition, pre-processing, morphological analysis, segmentation, count, and pattern classification components. Then, the principles and implementation methods of each step are given in detail. In addition, the promotion and application in automatic detection technology of thick blood film smears are put forwarded as questions worthy of study, and a perspective of the future work for realization of automated microscopy diagnosis of malaria is provided.

Image-Based Predictive Modeling of Heart Mechanics.

PubMed

Wang, V Y; Nielsen, P M F; Nash, M P

2015-01-01

Personalized biophysical modeling of the heart is a useful approach for noninvasively analyzing and predicting in vivo cardiac mechanics. Three main developments support this style of analysis: state-of-the-art cardiac imaging technologies, modern computational infrastructure, and advanced mathematical modeling techniques. In vivo measurements of cardiac structure and function can be integrated using sophisticated computational methods to investigate mechanisms of myocardial function and dysfunction, and can aid in clinical diagnosis and developing personalized treatment. In this article, we review the state-of-the-art in cardiac imaging modalities, model-based interpretation of 3D images of cardiac structure and function, and recent advances in modeling that allow personalized predictions of heart mechanics. We discuss how using such image-based modeling frameworks can increase the understanding of the fundamental biophysics behind cardiac mechanics, and assist with diagnosis, surgical guidance, and treatment planning. Addressing the challenges in this field will require a coordinated effort from both the clinical-imaging and modeling communities. We also discuss future directions that can be taken to bridge the gap between basic science and clinical translation.

Orientational imaging of a single plasmonic nanoparticle using dark-field hyperspectral imaging

NASA Astrophysics Data System (ADS)

Mehta, Nishir; Mahigir, Amirreza; Veronis, Georgios; Gartia, Manas Ranjan

2017-08-01

Orientation of plasmonic nanostructures is an important feature in many nanoscale applications such as catalyst, biosensors DNA interactions, protein detections, hotspot of surface enhanced Raman spectroscopy (SERS), and fluorescence resonant energy transfer (FRET) experiments. However, due to diffraction limit, it is challenging to obtain the exact orientation of the nanostructure using standard optical microscope. Hyperspectral Imaging Microscopy is a state-of-the-art visualization technology that combines modern optics with hyperspectral imaging and computer system to provide the identification and quantitative spectral analysis of nano- and microscale structures. In this work, initially we use transmitted dark field imaging technique to locate single nanoparticle on a glass substrate. Then we employ hyperspectral imaging technique at the same spot to investigate orientation of single nanoparticle. No special tagging or staining of nanoparticle has been done, as more likely required in traditional microscopy techniques. Different orientations have been identified by carefully understanding and calibrating shift in spectral response from each different orientations of similar sized nanoparticles. Wavelengths recorded are between 300 nm to 900 nm. The orientations measured by hyperspectral microscopy was validated using finite difference time domain (FDTD) electrodynamics calculations and scanning electron microscopy (SEM) analysis. The combination of high resolution nanometer-scale imaging techniques and the modern numerical modeling capacities thus enables a meaningful advance in our knowledge of manipulating and fabricating shaped nanostructures. This work will advance our understanding of the behavior of small nanoparticle clusters useful for sensing, nanomedicine, and surface sciences.

Biomedical surface analysis: Evolution and future directions (Review)

PubMed Central

Castner, David G.

2017-01-01

This review describes some of the major advances made in biomedical surface analysis over the past 30–40 years. Starting from a single technique analysis of homogeneous surfaces, it has been developed into a complementary, multitechnique approach for obtaining detailed, comprehensive information about a wide range of surfaces and interfaces of interest to the biomedical community. Significant advances have been made in each surface analysis technique, as well as how the techniques are combined to provide detailed information about biological surfaces and interfaces. The driving force for these advances has been that the surface of a biomaterial is the interface between the biological environment and the biomaterial, and so, the state-of-the-art in instrumentation, experimental protocols, and data analysis methods need to be developed so that the detailed surface structure and composition of biomedical devices can be determined and related to their biological performance. Examples of these advances, as well as areas for future developments, are described for immobilized proteins, complex biomedical surfaces, nanoparticles, and 2D/3D imaging of biological materials. PMID:28438024

Cryo-EM in drug discovery: achievements, limitations and prospects.

PubMed

Renaud, Jean-Paul; Chari, Ashwin; Ciferri, Claudio; Liu, Wen-Ti; Rémigy, Hervé-William; Stark, Holger; Wiesmann, Christian

2018-06-08

Cryo-electron microscopy (cryo-EM) of non-crystalline single particles is a biophysical technique that can be used to determine the structure of biological macromolecules and assemblies. Historically, its potential for application in drug discovery has been heavily limited by two issues: the minimum size of the structures it can be used to study and the resolution of the images. However, recent technological advances - including the development of direct electron detectors and more effective computational image analysis techniques - are revolutionizing the utility of cryo-EM, leading to a burst of high-resolution structures of large macromolecular assemblies. These advances have raised hopes that single-particle cryo-EM might soon become an important tool for drug discovery, particularly if they could enable structural determination for 'intractable' targets that are still not accessible to X-ray crystallographic analysis. This article describes the recent advances in the field and critically assesses their relevance for drug discovery as well as discussing at what stages of the drug discovery pipeline cryo-EM can be useful today and what to expect in the near future.

Untangling cell tracks: Quantifying cell migration by time lapse image data analysis.

PubMed

Svensson, Carl-Magnus; Medyukhina, Anna; Belyaev, Ivan; Al-Zaben, Naim; Figge, Marc Thilo

2018-03-01

Automated microscopy has given researchers access to great amounts of live cell imaging data from in vitro and in vivo experiments. Much focus has been put on extracting cell tracks from such data using a plethora of segmentation and tracking algorithms, but further analysis is normally required to draw biologically relevant conclusions. Such relevant conclusions may be whether the migration is directed or not, whether the population has homogeneous or heterogeneous migration patterns. This review focuses on the analysis of cell migration data that are extracted from time lapse images. We discuss a range of measures and models used to analyze cell tracks independent of the biological system or the way the tracks were obtained. For single-cell migration, we focus on measures and models giving examples of biological systems where they have been applied, for example, migration of bacteria, fibroblasts, and immune cells. For collective migration, we describe the model systems wound healing, neural crest migration, and Drosophila gastrulation and discuss methods for cell migration within these systems. We also discuss the role of the extracellular matrix and subsequent differences between track analysis in vitro and in vivo. Besides methods and measures, we are putting special focus on the need for openly available data and code, as well as a lack of common vocabulary in cell track analysis. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Rapid analysis and exploration of fluorescence microscopy images.

PubMed

Pavie, Benjamin; Rajaram, Satwik; Ouyang, Austin; Altschuler, Jason M; Steininger, Robert J; Wu, Lani F; Altschuler, Steven J

2014-03-19

Despite rapid advances in high-throughput microscopy, quantitative image-based assays still pose significant challenges. While a variety of specialized image analysis tools are available, most traditional image-analysis-based workflows have steep learning curves (for fine tuning of analysis parameters) and result in long turnaround times between imaging and analysis. In particular, cell segmentation, the process of identifying individual cells in an image, is a major bottleneck in this regard. Here we present an alternate, cell-segmentation-free workflow based on PhenoRipper, an open-source software platform designed for the rapid analysis and exploration of microscopy images. The pipeline presented here is optimized for immunofluorescence microscopy images of cell cultures and requires minimal user intervention. Within half an hour, PhenoRipper can analyze data from a typical 96-well experiment and generate image profiles. Users can then visually explore their data, perform quality control on their experiment, ensure response to perturbations and check reproducibility of replicates. This facilitates a rapid feedback cycle between analysis and experiment, which is crucial during assay optimization. This protocol is useful not just as a first pass analysis for quality control, but also may be used as an end-to-end solution, especially for screening. The workflow described here scales to large data sets such as those generated by high-throughput screens, and has been shown to group experimental conditions by phenotype accurately over a wide range of biological systems. The PhenoBrowser interface provides an intuitive framework to explore the phenotypic space and relate image properties to biological annotations. Taken together, the protocol described here will lower the barriers to adopting quantitative analysis of image based screens.

The Java Image Science Toolkit (JIST) for rapid prototyping and publishing of neuroimaging software.

PubMed

Lucas, Blake C; Bogovic, John A; Carass, Aaron; Bazin, Pierre-Louis; Prince, Jerry L; Pham, Dzung L; Landman, Bennett A

2010-03-01

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC).

The Java Image Science Toolkit (JIST) for Rapid Prototyping and Publishing of Neuroimaging Software

PubMed Central

Lucas, Blake C.; Bogovic, John A.; Carass, Aaron; Bazin, Pierre-Louis; Prince, Jerry L.; Pham, Dzung

2010-01-01

Non-invasive neuroimaging techniques enable extraordinarily sensitive and specific in vivo study of the structure, functional response and connectivity of biological mechanisms. With these advanced methods comes a heavy reliance on computer-based processing, analysis and interpretation. While the neuroimaging community has produced many excellent academic and commercial tool packages, new tools are often required to interpret new modalities and paradigms. Developing custom tools and ensuring interoperability with existing tools is a significant hurdle. To address these limitations, we present a new framework for algorithm development that implicitly ensures tool interoperability, generates graphical user interfaces, provides advanced batch processing tools, and, most importantly, requires minimal additional programming or computational overhead. Java-based rapid prototyping with this system is an efficient and practical approach to evaluate new algorithms since the proposed system ensures that rapidly constructed prototypes are actually fully-functional processing modules with support for multiple GUI's, a broad range of file formats, and distributed computation. Herein, we demonstrate MRI image processing with the proposed system for cortical surface extraction in large cross-sectional cohorts, provide a system for fully automated diffusion tensor image analysis, and illustrate how the system can be used as a simulation framework for the development of a new image analysis method. The system is released as open source under the Lesser GNU Public License (LGPL) through the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). PMID:20077162

The Advanced Rapid Imaging and Analysis (ARIA) Project: Status of SAR products for Earthquakes, Floods, Volcanoes and Groundwater-related Subsidence

NASA Astrophysics Data System (ADS)

Owen, S. E.; Yun, S. H.; Hua, H.; Agram, P. S.; Liu, Z.; Sacco, G. F.; Manipon, G.; Linick, J. P.; Fielding, E. J.; Lundgren, P.; Farr, T. G.; Webb, F.; Rosen, P. A.; Simons, M.

2017-12-01

The Advanced Rapid Imaging and Analysis (ARIA) project for Natural Hazards is focused on rapidly generating high-level geodetic imaging products and placing them in the hands of the solid earth science and local, national, and international natural hazard communities by providing science product generation, exploration, and delivery capabilities at an operational level. Space-based geodetic measurement techniques including Interferometric Synthetic Aperture Radar (InSAR), differential Global Positioning System, and SAR-based change detection have become critical additions to our toolset for understanding and mapping the damage and deformation caused by earthquakes, volcanic eruptions, floods, landslides, and groundwater extraction. Up until recently, processing of these data sets has been handcrafted for each study or event and has not generated products rapidly and reliably enough for response to natural disasters or for timely analysis of large data sets. The ARIA project, a joint venture co-sponsored by the California Institute of Technology and by NASA through the Jet Propulsion Laboratory, has been capturing the knowledge applied to these responses and building it into an automated infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. In addition to supporting the growing science and hazard response communities, the ARIA project has developed the capabilities to provide automated imaging and analysis capabilities necessary to keep up with the influx of raw SAR data from geodetic imaging missions such as ESA's Sentinel-1A/B, now operating with repeat intervals as short as 6 days, and the upcoming NASA NISAR mission. We will present the progress and results we have made on automating the analysis of Sentinel-1A/B SAR data for hazard monitoring and response, with emphasis on recent developments and end user engagement in flood extent mapping and deformation time series for both volcano monitoring and mapping of groundwater-related subsidence

Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques.

PubMed

Macyszyn, Luke; Akbari, Hamed; Pisapia, Jared M; Da, Xiao; Attiah, Mark; Pigrish, Vadim; Bi, Yingtao; Pal, Sharmistha; Davuluri, Ramana V; Roccograndi, Laura; Dahmane, Nadia; Martinez-Lage, Maria; Biros, George; Wolf, Ronald L; Bilello, Michel; O'Rourke, Donald M; Davatzikos, Christos

2016-03-01

MRI characteristics of brain gliomas have been used to predict clinical outcome and molecular tumor characteristics. However, previously reported imaging biomarkers have not been sufficiently accurate or reproducible to enter routine clinical practice and often rely on relatively simple MRI measures. The current study leverages advanced image analysis and machine learning algorithms to identify complex and reproducible imaging patterns predictive of overall survival and molecular subtype in glioblastoma (GB). One hundred five patients with GB were first used to extract approximately 60 diverse features from preoperative multiparametric MRIs. These imaging features were used by a machine learning algorithm to derive imaging predictors of patient survival and molecular subtype. Cross-validation ensured generalizability of these predictors to new patients. Subsequently, the predictors were evaluated in a prospective cohort of 29 new patients. Survival curves yielded a hazard ratio of 10.64 for predicted long versus short survivors. The overall, 3-way (long/medium/short survival) accuracy in the prospective cohort approached 80%. Classification of patients into the 4 molecular subtypes of GB achieved 76% accuracy. By employing machine learning techniques, we were able to demonstrate that imaging patterns are highly predictive of patient survival. Additionally, we found that GB subtypes have distinctive imaging phenotypes. These results reveal that when imaging markers related to infiltration, cell density, microvascularity, and blood-brain barrier compromise are integrated via advanced pattern analysis methods, they form very accurate predictive biomarkers. These predictive markers used solely preoperative images, hence they can significantly augment diagnosis and treatment of GB patients. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Citrus Inventory

NASA Technical Reports Server (NTRS)

1994-01-01

An aerial color infrared (CIR) mapping system developed by Kennedy Space Center enables Florida's Charlotte County to accurately appraise its citrus groves while reducing appraisal costs. The technology was further advanced by development of a dual video system making it possible to simultaneously view images of the same area and detect changes. An image analysis system automatically surveys and photo interprets grove images as well as automatically counts trees and reports totals. The system, which saves both time and money, has potential beyond citrus grove valuation.

Advanced Forensic Format: an Open Extensible Format for Disk Imaging

NASA Astrophysics Data System (ADS)

Garfinkel, Simson; Malan, David; Dubec, Karl-Alexander; Stevens, Christopher; Pham, Cecile

This paper describes the Advanced Forensic Format (AFF), which is designed as an alternative to current proprietary disk image formats. AFF offers two significant benefits. First, it is more flexible because it allows extensive metadata to be stored with images. Second, AFF images consume less disk space than images in other formats (e.g., EnCase images). This paper also describes the Advanced Disk Imager, a new program for acquiring disk images that compares favorably with existing alternatives.

Genome-wide association analysis of secondary imaging phenotypes from the Alzheimer's disease neuroimaging initiative study.

PubMed

Zhu, Wensheng; Yuan, Ying; Zhang, Jingwen; Zhou, Fan; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-02-01

The aim of this paper is to systematically evaluate a biased sampling issue associated with genome-wide association analysis (GWAS) of imaging phenotypes for most imaging genetic studies, including the Alzheimer's Disease Neuroimaging Initiative (ADNI). Specifically, the original sampling scheme of these imaging genetic studies is primarily the retrospective case-control design, whereas most existing statistical analyses of these studies ignore such sampling scheme by directly correlating imaging phenotypes (called the secondary traits) with genotype. Although it has been well documented in genetic epidemiology that ignoring the case-control sampling scheme can produce highly biased estimates, and subsequently lead to misleading results and suspicious associations, such findings are not well documented in imaging genetics. We use extensive simulations and a large-scale imaging genetic data analysis of the Alzheimer's Disease Neuroimaging Initiative (ADNI) data to evaluate the effects of the case-control sampling scheme on GWAS results based on some standard statistical methods, such as linear regression methods, while comparing it with several advanced statistical methods that appropriately adjust for the case-control sampling scheme. Copyright © 2016 Elsevier Inc. All rights reserved.

Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels.

PubMed

Sornapudi, Sudhir; Stanley, Ronald Joe; Stoecker, William V; Almubarak, Haidar; Long, Rodney; Antani, Sameer; Thoma, George; Zuna, Rosemary; Frazier, Shelliane R

2018-01-01

Advances in image analysis and computational techniques have facilitated automatic detection of critical features in histopathology images. Detection of nuclei is critical for squamous epithelium cervical intraepithelial neoplasia (CIN) classification into normal, CIN1, CIN2, and CIN3 grades. In this study, a deep learning (DL)-based nuclei segmentation approach is investigated based on gathering localized information through the generation of superpixels using a simple linear iterative clustering algorithm and training with a convolutional neural network. The proposed approach was evaluated on a dataset of 133 digitized histology images and achieved an overall nuclei detection (object-based) accuracy of 95.97%, with demonstrated improvement over imaging-based and clustering-based benchmark techniques. The proposed DL-based nuclei segmentation Method with superpixel analysis has shown improved segmentation results in comparison to state-of-the-art methods.

Advances in Surface Plasmon Resonance Imaging allowing for quantitative measurement of laterally heterogeneous samples

NASA Astrophysics Data System (ADS)

Raegen, Adam; Reiter, Kyle; Clarke, Anthony; Lipkowski, Jacek; Dutcher, John

2012-02-01

The Surface Plasmon Resonance (SPR) phenomenon is routinely exploited to qualitatively probe changes to materials on metallic surfaces for use in probes and sensors. Unfortunately, extracting truly quantitative information is usually limited to a select few cases -- uniform absorption/desorption of small biomolecules and films, in which a continuous ``slab'' model is a good approximation. We present advancements in the SPR technique that expand the number of cases for which the technique can provide meaningful results. Use of a custom, angle-scanning SPR imaging system, together with a refined data analysis method, allow for quantitative kinetic measurements of laterally heterogeneous systems. The degradation of cellulose microfibrils and bundles of microfibrils due to the action of cellulolytic enzymes will be presented as an excellent example of the capabilities of the SPR imaging system.

Bioinformatics approaches to single-cell analysis in developmental biology.

PubMed

Yalcin, Dicle; Hakguder, Zeynep M; Otu, Hasan H

2016-03-01

Individual cells within the same population show various degrees of heterogeneity, which may be better handled with single-cell analysis to address biological and clinical questions. Single-cell analysis is especially important in developmental biology as subtle spatial and temporal differences in cells have significant associations with cell fate decisions during differentiation and with the description of a particular state of a cell exhibiting an aberrant phenotype. Biotechnological advances, especially in the area of microfluidics, have led to a robust, massively parallel and multi-dimensional capturing, sorting, and lysis of single-cells and amplification of related macromolecules, which have enabled the use of imaging and omics techniques on single cells. There have been improvements in computational single-cell image analysis in developmental biology regarding feature extraction, segmentation, image enhancement and machine learning, handling limitations of optical resolution to gain new perspectives from the raw microscopy images. Omics approaches, such as transcriptomics, genomics and epigenomics, targeting gene and small RNA expression, single nucleotide and structural variations and methylation and histone modifications, rely heavily on high-throughput sequencing technologies. Although there are well-established bioinformatics methods for analysis of sequence data, there are limited bioinformatics approaches which address experimental design, sample size considerations, amplification bias, normalization, differential expression, coverage, clustering and classification issues, specifically applied at the single-cell level. In this review, we summarize biological and technological advancements, discuss challenges faced in the aforementioned data acquisition and analysis issues and present future prospects for application of single-cell analyses to developmental biology. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Molecular Iodine Spectral Data Set for Rovibronic Analysis

ERIC Educational Resources Information Center

Williamson, J. Charles; Kuntzleman, Thomas S.; Kafader, Rachael A.

2013-01-01

A data set of 7,381 molecular iodine vapor rovibronic transitions between the X and B electronic states has been prepared for an advanced undergraduate spectroscopic analysis project. Students apply standard theoretical techniques to these data and determine the values of three X-state constants (image omitted) and four B-state constants (image…

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

PubMed

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

2015-10-06

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

Segment and Fit Thresholding: A New Method for Image Analysis Applied to Microarray and Immunofluorescence Data

PubMed Central

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M.; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E.; Allen, Peter J.; Sempere, Lorenzo F.; Haab, Brian B.

2016-01-01

Certain experiments involve the high-throughput quantification of image data, thus requiring algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multi-color, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu’s method for selected images. SFT promises to advance the goal of full automation in image analysis. PMID:26339978

Fabrication of Advanced Thermoelectric Materials by Hierarchical Nanovoid Generation

NASA Technical Reports Server (NTRS)

Park, Yeonjoon (Inventor); Elliott, James R. (Inventor); Stoakley, Diane M. (Inventor); Chu, Sang-Hyon (Inventor); King, Glen C. (Inventor); Kim, Jae-Woo (Inventor); Choi, Sang Hyouk (Inventor); Lillehei, Peter T. (Inventor)

2011-01-01

A novel method to prepare an advanced thermoelectric material has hierarchical structures embedded with nanometer-sized voids which are key to enhancement of the thermoelectric performance. Solution-based thin film deposition technique enables preparation of stable film of thermoelectric material and void generator (voigen). A subsequent thermal process creates hierarchical nanovoid structure inside the thermoelectric material. Potential application areas of this advanced thermoelectric material with nanovoid structure are commercial applications (electronics cooling), medical and scientific applications (biological analysis device, medical imaging systems), telecommunications, and defense and military applications (night vision equipments).

Diagnostic imaging advances in murine models of colitis.

PubMed

Brückner, Markus; Lenz, Philipp; Mücke, Marcus M; Gohar, Faekah; Willeke, Peter; Domagk, Dirk; Bettenworth, Dominik

2016-01-21

Inflammatory bowel diseases (IBD) such as Crohn's disease and ulcerative colitis are chronic-remittent inflammatory disorders of the gastrointestinal tract still evoking challenging clinical diagnostic and therapeutic situations. Murine models of experimental colitis are a vital component of research into human IBD concerning questions of its complex pathogenesis or the evaluation of potential new drugs. To monitor the course of colitis, to the present day, classical parameters like histological tissue alterations or analysis of mucosal cytokine/chemokine expression often require euthanasia of animals. Recent advances mean revolutionary non-invasive imaging techniques for in vivo murine colitis diagnostics are increasingly available. These novel and emerging imaging techniques not only allow direct visualization of intestinal inflammation, but also enable molecular imaging and targeting of specific alterations of the inflamed murine mucosa. For the first time, in vivo imaging techniques allow for longitudinal examinations and evaluation of intra-individual therapeutic response. This review discusses the latest developments in the different fields of ultrasound, molecularly targeted contrast agent ultrasound, fluorescence endoscopy, confocal laser endomicroscopy as well as tomographic imaging with magnetic resonance imaging, computed tomography and fluorescence-mediated tomography, discussing their individual limitations and potential future diagnostic applications in the management of human patients with IBD.

Radiologic Assessment of Patellofemoral Pain in the Athlete

PubMed Central

Endo, Yoshimi; Stein, Beth E. Shubin; Potter, Hollis G.

2011-01-01

Context: Although disorders of the patellofemoral joint are common in the athlete, their management can be challenging and require a thorough physical examination and radiologic evaluation, including advanced magnetic resonance imaging techniques. Evidence Acquisition: Relevant articles were searched under OVID and MEDLINE (1968 to 2010) using the keywords patellofemoral joint, patellofemoral pain or patella and radiography, imaging, or magnetic resonance imaging, and the referenced sources were reviewed for additional articles. The quality and validity of the studies were assessed on the basis of careful analysis of the materials and methods before their inclusion in this article. Results: Physical examination and imaging evaluation including standard radiographs are crucial in identifying evidence of malalignment or instability. Magnetic resonance imaging provides valuable information about concomitant soft tissue injuries to the medial stabilizers as well as injuries to the articular cartilage, including chondral shears and osteochondral fractures. Quantitative magnetic resonance imaging assessing the ultrastructure of cartilage has shown high correlation with histology and may be useful for timing surgery. Conclusions: Evaluation of patellofemoral disorders is complex and requires a comprehensive assessment. Recent advancements in imaging have made possible a more precise evaluation of the individual anatomy of the patient, addressing issues of malalignment, instability, and underlying cartilage damage. PMID:23016009

Development and applications of single particle orientation and rotational tracking in dynamic systems

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

Chen, Kuangcai

The goal of this study is to help with future data analysis and experiment designs in rotational dynamics research using DIC-based SPORT technique. Most of the current studies using DIC-based SPORT techniques are technical demonstrations. Understanding the mechanisms behind the observed rotational behaviors of the imaging probes should be the focus of the future SPORT studies. More efforts are still needed in the development of new imaging probes, particle tracking methods, instrumentations, and advanced data analysis methods to further extend the potential of DIC-based SPORT technique.

An advanced scanning method for space-borne hyper-spectral imaging system

NASA Astrophysics Data System (ADS)

Wang, Yue-ming; Lang, Jun-Wei; Wang, Jian-Yu; Jiang, Zi-Qing

2011-08-01

Space-borne hyper-spectral imagery is an important means for the studies and applications of earth science. High cost efficiency could be acquired by optimized system design. In this paper, an advanced scanning method is proposed, which contributes to implement both high temporal and spatial resolution imaging system. Revisit frequency and effective working time of space-borne hyper-spectral imagers could be greatly improved by adopting two-axis scanning system if spatial resolution and radiometric accuracy are not harshly demanded. In order to avoid the quality degradation caused by image rotation, an idea of two-axis rotation has been presented based on the analysis and simulation of two-dimensional scanning motion path and features. Further improvement of the imagers' detection ability under the conditions of small solar altitude angle and low surface reflectance can be realized by the Ground Motion Compensation on pitch axis. The structure and control performance are also described. An intelligent integration technology of two-dimensional scanning and image motion compensation is elaborated in this paper. With this technology, sun-synchronous hyper-spectral imagers are able to pay quick visit to hot spots, acquiring both high spatial and temporal resolution hyper-spectral images, which enables rapid response of emergencies. The result has reference value for developing operational space-borne hyper-spectral imagers.

Advanced Imaging Adds Little Value in the Diagnosis of Femoroacetabular Impingement Syndrome.

PubMed

Cunningham, Daniel J; Paranjape, Chinmay S; Harris, Joshua D; Nho, Shane J; Olson, Steven A; Mather, Richard C

2017-12-20

Femoroacetabular impingement (FAI) syndrome is an increasingly recognized source of hip pain and disability in young active adults. In order to confirm the diagnosis, providers often supplement physical examination maneuvers and radiographs with intra-articular hip injection, magnetic resonance imaging (MRI), or magnetic resonance arthrography (MRA). Since diagnostic imaging represents the fastest rising cost segment in U.S. health care, there is a need for value-driven diagnostic algorithms. The purpose of this study was to identify cost-effective diagnostic strategies for symptomatic FAI, comparing history and physical examination (H&P) alone (utilizing only radiographic imaging) with supplementation with injection, MRI, or MRA. A simple-chain decision model run as a cost-utility analysis was constructed to assess the diagnostic value of the MRI, MRA, and injection that are added to the H&P and radiographs in diagnosing symptomatic FAI. Strategies were compared using the incremental cost-utility ratio (ICUR) with a willingness to pay (WTP) of $100,000/QALY (quality-adjusted life year). Direct costs were measured using the Humana database (PearlDiver). Diagnostic test accuracy, treatment outcome probabilities, and utilities were extracted from the literature. H&P with and without supplemental diagnostic injection was the most cost-effective. Adjunct injection was preferred in situations with a WTP of >$60,000/QALY, low examination sensitivity, and high FAI prevalence. With low disease prevalence and low examination sensitivity, as may occur in a general practitioner's office, H&P with injection was the most cost-effective strategy, whereas in the reciprocal scenario, H&P with injection was only favored at exceptionally high WTP (∼$990,000). H&P and radiographs with supplemental diagnostic injection are preferred over advanced imaging, even with reasonable deviations from published values of disease prevalence, test sensitivity, and test specificity. Providers with low examination sensitivity in situations with low disease prevalence may benefit most from including injection in their diagnostic strategy. Providers with high examination sensitivity in situations with high disease prevalence may not benefit from including injection in their diagnostic strategy. Providers should not routinely rely on advanced imaging to diagnose FAI syndrome, although advanced imaging may have a role in challenging clinical scenarios. Economic and Decision Analysis Level IV. See Instructions for Authors for a complete description of levels of evidence.

Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods

NASA Astrophysics Data System (ADS)

Maximov, Ivan I.; Vinding, Mads S.; Tse, Desmond H. Y.; Nielsen, Niels Chr.; Shah, N. Jon

2015-05-01

There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community.

An update: improvements in imaging perfluorocarbon-mounted plant leaves with implications for studies of plant pathology, physiology, development and cell biology

PubMed Central

Littlejohn, George R.; Mansfield, Jessica C.; Christmas, Jacqueline T.; Witterick, Eleanor; Fricker, Mark D.; Grant, Murray R.; Smirnoff, Nicholas; Everson, Richard M.; Moger, Julian; Love, John

2014-01-01

Plant leaves are optically complex, which makes them difficult to image by light microscopy. Careful sample preparation is therefore required to enable researchers to maximize the information gained from advances in fluorescent protein labeling, cell dyes and innovations in microscope technologies and techniques. We have previously shown that mounting leaves in the non-toxic, non-fluorescent perfluorocarbon (PFC), perfluorodecalin (PFD) enhances the optical properties of the leaf with minimal impact on physiology. Here, we assess the use of the PFCs, PFD, and perfluoroperhydrophenanthrene (PP11) for in vivo plant leaf imaging using four advanced modes of microscopy: laser scanning confocal microscopy (LSCM), two-photon fluorescence microscopy, second harmonic generation microscopy, and stimulated Raman scattering (SRS) microscopy. For every mode of imaging tested, we observed an improved signal when leaves were mounted in PFD or in PP11, compared to mounting the samples in water. Using an image analysis technique based on autocorrelation to quantitatively assess LSCM image deterioration with depth, we show that PP11 outperformed PFD as a mounting medium by enabling the acquisition of clearer images deeper into the tissue. In addition, we show that SRS microscopy can be used to image PFCs directly in the mesophyll and thereby easily delimit the “negative space” within a leaf, which may have important implications for studies of leaf development. Direct comparison of on and off resonance SRS micrographs show that PFCs do not to form intracellular aggregates in live plants. We conclude that the application of PFCs as mounting media substantially increases advanced microscopy image quality of living mesophyll and leaf vascular bundle cells. PMID:24795734

Hyperspectral Imaging and SPA-LDA Quantitative Analysis for Detection of Colon Cancer Tissue

NASA Astrophysics Data System (ADS)

Yuan, X.; Zhang, D.; Wang, Ch.; Dai, B.; Zhao, M.; Li, B.

2018-05-01

Hyperspectral imaging (HSI) has been demonstrated to provide a rapid, precise, and noninvasive method for cancer detection. However, because HSI contains many data, quantitative analysis is often necessary to distill information useful for distinguishing cancerous from normal tissue. To demonstrate that HSI with our proposed algorithm can make this distinction, we built a Vis-NIR HSI setup and made many spectral images of colon tissues, and then used a successive projection algorithm (SPA) to analyze the hyperspectral image data of the tissues. This was used to build an identification model based on linear discrimination analysis (LDA) using the relative reflectance values of the effective wavelengths. Other tissues were used as a prediction set to verify the reliability of the identification model. The results suggest that Vis-NIR hyperspectral images, together with the spectroscopic classification method, provide a new approach for reliable and safe diagnosis of colon cancer and could lead to advances in cancer diagnosis generally.

Optofluidic time-stretch microscopy: recent advances

NASA Astrophysics Data System (ADS)

Lei, Cheng; Nitta, Nao; Ozeki, Yasuyuki; Goda, Keisuke

2018-06-01

Flow cytometry is an indispensable method for valuable applications in numerous fields such as immunology, pathology, pharmacology, molecular biology, and marine biology. Optofluidic time-stretch microscopy is superior to conventional flow cytometry methods for its capability to acquire high-quality images of single cells at a high-throughput exceeding 10,000 cells per second. This makes it possible to extract copious information from cellular images for accurate cell detection and analysis with the assistance of machine learning. Optofluidic time-stretch microscopy has proven its effectivity in various applications, including microalga-based biofuel production, evaluation of thrombotic disorders, as well as drug screening and discovery. In this review, we discuss the principles and recent advances of optofluidic time-stretch microscopy.

Computer-assisted detection of epileptiform focuses on SPECT images

NASA Astrophysics Data System (ADS)

Grzegorczyk, Dawid; Dunin-Wąsowicz, Dorota; Mulawka, Jan J.

2010-09-01

Epilepsy is a common nervous system disease often related to consciousness disturbances and muscular spasm which affects about 1% of the human population. Despite major technological advances done in medicine in the last years there was no sufficient progress towards overcoming it. Application of advanced statistical methods and computer image analysis offers the hope for accurate detection and later removal of an epileptiform focuses which are the cause of some types of epilepsy. The aim of this work was to create a computer system that would help to find and diagnose disorders of blood circulation in the brain This may be helpful for the diagnosis of the epileptic seizures onset in the brain.

Optofluidic time-stretch microscopy: recent advances

NASA Astrophysics Data System (ADS)

Lei, Cheng; Nitta, Nao; Ozeki, Yasuyuki; Goda, Keisuke

2018-04-01

Flow cytometry is an indispensable method for valuable applications in numerous fields such as immunology, pathology, pharmacology, molecular biology, and marine biology. Optofluidic time-stretch microscopy is superior to conventional flow cytometry methods for its capability to acquire high-quality images of single cells at a high-throughput exceeding 10,000 cells per second. This makes it possible to extract copious information from cellular images for accurate cell detection and analysis with the assistance of machine learning. Optofluidic time-stretch microscopy has proven its effectivity in various applications, including microalga-based biofuel production, evaluation of thrombotic disorders, as well as drug screening and discovery. In this review, we discuss the principles and recent advances of optofluidic time-stretch microscopy.

Earth benefits from space life sciences

NASA Technical Reports Server (NTRS)

Garshnek, V.; Nicogossian, A. E.; Griffiths, L.

1988-01-01

The applications to medicine of various results from space exploration are examined. Improvements have been made in the management of cardiovascular disease, in particular the use of the ultrasonic scanner to image arteries in three dimensions, the use of excimer lasers to disrupt arterial plaques in coronary blood vessels, and the use of advanced electrodes for cardiac monitoring. A bone stiffness analyzer has helped to diagnose osteoporosis and aid in its treatment. An automated light microscope system is used for chromosome analysis, and an X-ray image intensifier called Lixiscope is used in emergency medical care. An advanced portable defibrillator has been developed for the heart, and an insulin delivery system has been derived from space microminiaturization techniques.

Contribution of high-resolution correlative imaging techniques in the study of the liver sieve in three-dimensions.

PubMed

Braet, Filip; Wisse, Eddie; Bomans, Paul; Frederik, Peter; Geerts, Willie; Koster, Abraham; Soon, Lilian; Ringer, Simon

2007-03-01

Correlative microscopy has become increasingly important for the analysis of the structure, function, and dynamics of cells. This is largely due to the result of recent advances in light-, probe-, laser- and various electron microscopy techniques that facilitate three-dimensional studies. Furthermore, the improved understanding in the past decade of imaging cell compartments in the third dimension has resulted largely from the availability of powerful computers, fast high-resolution CCD cameras, specifically developed imaging analysis software, and various probes designed for labeling living and or fixed cells. In this paper, we review different correlative high-resolution imaging methodologies and how these microscopy techniques facilitated the accumulation of new insights in the morpho-functional and structural organization of the hepatic sieve. Various aspects of hepatic endothelial fenestrae regarding their structure, origin, dynamics, and formation will be explored throughout this paper by comparing the results of confocal laser scanning-, correlative fluorescence and scanning electron-, atomic force-, and whole-mount electron microscopy. Furthermore, the recent advances of vitrifying cells with the vitrobot in combination with the glove box for the preparation of cells for cryo-electron microscopic investigation will be discussed. Finally, the first transmission electron tomography data of the liver sieve in three-dimensions are presented. The obtained data unambiguously show the involvement of special domains in the de novo formation and disappearance of hepatic fenestrae, and focuses future research into the (supra)molecular structure of the fenestrae-forming center, defenestration center and fenestrae-, and sieve plate cytoskeleton ring by using advanced cryo-electron tomography. (c) 2007 Wiley-Liss, Inc.

An onboard data analysis method to track the seasonal polar caps on Mars

USGS Publications Warehouse

Wagstaff, K.L.; Castano, R.; Chien, S.; Ivanov, A.B.; Pounders, E.; Titus, T.N.; ,

2005-01-01

The Martian seasonal CO2 ice caps advance and retreat each year. They are currently studied using instruments such as the THermal EMission Imaging System (THEMIS), a visible and infra-red camera on the Mars Odyssey spacecraft [1]. However, each image must be downlinked to Earth prior to analysis. In contrast, we have developed the Bimodal Image Temperature (BIT) histogram analysis method for onboard detection of the cap edge, before transmission. In downlink-limited scenarios when the entire image cannot be transmitted, the location of the cap edge can still be identified and sent to Earth. In this paper, we evaluate our method on uncalibrated THEMIS data and find 1) agreement with manual cap edge identifications to within 28.2 km, and 2) high accuracy even with a smaller analysis window, yielding large reductions in memory requirements. This algorithm is currently being considered as a capability enhancement for the Odyssey second extended mission, beginning in fall 2006.

Algorithms for Image Analysis and Combination of Pattern Classifiers with Application to Medical Diagnosis

NASA Astrophysics Data System (ADS)

Georgiou, Harris

2009-10-01

Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related to the general problem of medical image analysis, specifically in mammography, and presents a series of algorithms and design approaches for all the intermediate levels of a modern system for computer-aided diagnosis (CAD). The diagnostic problem is analyzed with a systematic approach, first defining the imaging characteristics and features that are relevant to probable pathology in mammo-grams. Next, these features are quantified and fused into new, integrated radio-logical systems that exhibit embedded digital signal processing, in order to improve the final result and minimize the radiological dose for the patient. In a higher level, special algorithms are designed for detecting and encoding these clinically interest-ing imaging features, in order to be used as input to advanced pattern classifiers and machine learning models. Finally, these approaches are extended in multi-classifier models under the scope of Game Theory and optimum collective deci-sion, in order to produce efficient solutions for combining classifiers with minimum computational costs for advanced diagnostic systems. The material covered in this thesis is related to a total of 18 published papers, 6 in scientific journals and 12 in international conferences.

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.

Hyperspectral data analysis for estimation of foliar biochemical content along the Oregon transect

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Peterson, David L.

1991-01-01

The NASA Oregon Transect Ecosystem Research (OTTER) project completed a data acquisition phase. Data were acquired with several airborne imaging spectrometers. Included were the Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) aboard the ER-2, the Advanced Solidstate Array Spectrometer (ASAS) aboard the C-130, and the Fluorescence Line Imager (FLI) and Compact Airborne Spectrographic Imager (CASI), both aboard light aircraft. In addition, Spectron visible and near-infrared data were acquired in transects across study areas from a low-altitude ultralight craft. Sunphotometer data were taken approximately coincident with each overflight for atmospheric correction of the aircraft data.

What can imaging tell us about physiology? Lung growth and regional mechanical strain.

PubMed

Hsia, Connie C W; Tawhai, Merryn H

2012-09-01

The interplay of mechanical forces transduces diverse physico-biochemical processes to influence lung morphogenesis, growth, maturation, remodeling and repair. Because tissue stress is difficult to measure in vivo, mechano-sensitive responses are commonly inferred from global changes in lung volume, shape, or compliance and correlated with structural changes in tissue blocks sampled from postmortem-fixed lungs. Recent advances in noninvasive volumetric imaging technology, nonrigid image registration, and deformation analysis provide valuable tools for the quantitative analysis of in vivo regional anatomy and air and tissue-blood distributions and when combined with transpulmonary pressure measurements, allow characterization of regional mechanical function, e.g., displacement, strain, shear, within and among intact lobes, as well as between the lung and the components of its container-rib cage, diaphragm, and mediastinum-thereby yielding new insights into the inter-related metrics of mechanical stress-strain and growth/remodeling. Here, we review the state-of-the-art imaging applications for mapping asymmetric heterogeneous physical interactions within the thorax and how these interactions permit as well as constrain lung growth, remodeling, and compensation during development and following pneumonectomy to illustrate how advanced imaging could facilitate the understanding of physiology and pathophysiology. Functional imaging promises to facilitate the formulation of realistic computational models of lung growth that integrate mechano-sensitive events over multiple spatial and temporal scales to accurately describe in vivo physiology and pathophysiology. Improved computational models in turn could enhance our ability to predict regional as well as global responses to experimental and therapeutic interventions.

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

Functional optical coherence tomography: principles and progress

NASA Astrophysics Data System (ADS)

Kim, Jina; Brown, William; Maher, Jason R.; Levinson, Howard; Wax, Adam

2015-05-01

In the past decade, several functional extensions of optical coherence tomography (OCT) have emerged, and this review highlights key advances in instrumentation, theoretical analysis, signal processing and clinical application of these extensions. We review five principal extensions: Doppler OCT (DOCT), polarization-sensitive OCT (PS-OCT), optical coherence elastography (OCE), spectroscopic OCT (SOCT), and molecular imaging OCT. The former three have been further developed with studies in both ex vivo and in vivo human tissues. This review emphasizes the newer techniques of SOCT and molecular imaging OCT, which show excellent potential for clinical application but have yet to be well reviewed in the literature. SOCT elucidates tissue characteristics, such as oxygenation and carcinogenesis, by detecting wavelength-dependent absorption and scattering of light in tissues. While SOCT measures endogenous biochemical distributions, molecular imaging OCT detects exogenous molecular contrast agents. These newer advances in functional OCT broaden the potential clinical application of OCT by providing novel ways to understand tissue activity that cannot be accomplished by other current imaging methodologies.

Functional Optical Coherence Tomography: Principles and Progress

PubMed Central

Kim, Jina; Brown, William; Maher, Jason R.; Levinson, Howard; Wax, Adam

2015-01-01

In the past decade, several functional extensions of optical coherence tomography (OCT) have emerged, and this review highlights key advances in instrumentation, theoretical analysis, signal processing and clinical application of these extensions. We review five principal extensions: Doppler OCT (DOCT), polarization-sensitive OCT (PS-OCT), optical coherence elastography (OCE), spectroscopic OCT (SOCT), and molecular imaging OCT. The former three have been further developed with studies in both ex vivo and in vivo human tissues. This review emphasizes the newer techniques of SOCT and molecular imaging OCT, which show excellent potential for clinical application but have yet to be well reviewed in the literature. SOCT elucidates tissue characteristics, such as oxygenation and carcinogenesis, by detecting wavelength-dependent absorption and scattering of light in tissues. While SOCT measures endogenous biochemical distributions, molecular imaging OCT detects exogenous molecular contrast agents. These newer advances in functional OCT broaden the potential clinical application of OCT by providing novel ways to understand tissue activity that cannot be accomplished by other current imaging methodologies. PMID:25951836

Towards native-state imaging in biological context in the electron microscope

PubMed Central

Weston, Anne E.; Armer, Hannah E. J.

2009-01-01

Modern cell biology is reliant on light and fluorescence microscopy for analysis of cells, tissues and protein localisation. However, these powerful techniques are ultimately limited in resolution by the wavelength of light. Electron microscopes offer much greater resolution due to the shorter effective wavelength of electrons, allowing direct imaging of sub-cellular architecture. The harsh environment of the electron microscope chamber and the properties of the electron beam have led to complex chemical and mechanical preparation techniques, which distance biological samples from their native state and complicate data interpretation. Here we describe recent advances in sample preparation and instrumentation, which push the boundaries of high-resolution imaging. Cryopreparation, cryoelectron microscopy and environmental scanning electron microscopy strive to image samples in near native state. Advances in correlative microscopy and markers enable high-resolution localisation of proteins. Innovation in microscope design has pushed the boundaries of resolution to atomic scale, whilst automatic acquisition of high-resolution electron microscopy data through large volumes is finally able to place ultrastructure in biological context. PMID:19916039

Advances in real-time magnetic resonance imaging of the vocal tract for speech science and technology research.

PubMed

Toutios, Asterios; Narayanan, Shrikanth S

2016-01-01

Real-time magnetic resonance imaging (rtMRI) of the moving vocal tract during running speech production is an important emerging tool for speech production research providing dynamic information of a speaker's upper airway from the entire mid-sagittal plane or any other scan plane of interest. There have been several advances in the development of speech rtMRI and corresponding analysis tools, and their application to domains such as phonetics and phonological theory, articulatory modeling, and speaker characterization. An important recent development has been the open release of a database that includes speech rtMRI data from five male and five female speakers of American English each producing 460 phonetically balanced sentences. The purpose of the present paper is to give an overview and outlook of the advances in rtMRI as a tool for speech research and technology development.

Advances in real-time magnetic resonance imaging of the vocal tract for speech science and technology research

PubMed Central

TOUTIOS, ASTERIOS; NARAYANAN, SHRIKANTH S.

2016-01-01

Real-time magnetic resonance imaging (rtMRI) of the moving vocal tract during running speech production is an important emerging tool for speech production research providing dynamic information of a speaker's upper airway from the entire mid-sagittal plane or any other scan plane of interest. There have been several advances in the development of speech rtMRI and corresponding analysis tools, and their application to domains such as phonetics and phonological theory, articulatory modeling, and speaker characterization. An important recent development has been the open release of a database that includes speech rtMRI data from five male and five female speakers of American English each producing 460 phonetically balanced sentences. The purpose of the present paper is to give an overview and outlook of the advances in rtMRI as a tool for speech research and technology development. PMID:27833745

Large-scale retrieval for medical image analytics: A comprehensive review.

PubMed

Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

2018-01-01

Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Advances in Pancreatic CT Imaging.

PubMed

Almeida, Renata R; Lo, Grace C; Patino, Manuel; Bizzo, Bernardo; Canellas, Rodrigo; Sahani, Dushyant V

2018-07-01

The purpose of this article is to discuss the advances in CT acquisition and image postprocessing as they apply to imaging the pancreas and to conceptualize the role of radiogenomics and machine learning in pancreatic imaging. CT is the preferred imaging modality for assessment of pancreatic diseases. Recent advances in CT (dual-energy CT, CT perfusion, CT volumetry, and radiogenomics) and emerging computational algorithms (machine learning) have the potential to further increase the value of CT in pancreatic imaging.

Mapping Environmental Contaminants at Ray Mine, AZ

NASA Technical Reports Server (NTRS)

McCubbin, Ian; Lang, Harold

2000-01-01

Airborne Visible and InfraRed Imaging Spectrometer (AVIRIS) data was collected over Ray Mine as part of a demonstration project for the Environmental Protection Agency (EPA) through the Advanced Measurement Initiative (AMI). The overall goal of AMI is to accelerate adoption and application of advanced measurement technologies for cost effective environmental monitoring. The site was selected to demonstrate the benefit to EPA in using advanced remote sensing technologies for the detection of environmental contaminants due to the mineral extraction industry. The role of the Jet Propulsion Laboratory in this pilot study is to provide data as well as performing calibration, data analysis, and validation of the AVIRIS results. EPA is also interested in developing protocols that use commercial software to perform such work on other high priority EPA sites. Reflectance retrieval was performed using outputs generated by the MODTRAN radiative transfer model and field spectra collected for the purpose of calibration. We are presenting advanced applications of the ENVI software package using n-Dimensional Partial Unmixing to identify image-derived endmembers that best match target materials reference spectra from multiple spectral libraries. Upon identification of the image endmembers the Mixture Tuned Match Filter algorithm was applied to map the endmembers within each scene. Using this technique it was possible to map four different mineral classes that are associated with mine generated acid waste.

Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis.

PubMed

Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew

2018-05-02

Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias, Katharine Foster, Andrew Peet. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 02.05.2018.

Promise of new imaging technologies for assessing ovarian function.

PubMed

Singh, Jaswant; Adams, Gregg P; Pierson, Roger A

2003-10-15

Advancements in imaging technologies over the last two decades have ushered a quiet revolution in research approaches to the study of ovarian structure and function. The most significant changes in our understanding of the ovary have resulted from the use of ultrasonography which has enabled sequential analyses in live animals. Computer-assisted image analysis and mathematical modeling of the dynamic changes within the ovary has permitted exciting new avenues of research with readily quantifiable endpoints. Spectral, color-flow and power Doppler imaging now facilitate physiologic interpretations of vascular dynamics over time. Similarly, magnetic resonance imaging (MRI) is emerging as a research tool in ovarian imaging. New technologies, such as three-dimensional ultrasonography and MRI, ultrasound-based biomicroscopy and synchrotron-based techniques each have the potential to enhance our real-time picture of ovarian function to the near-cellular level. Collectively, information available in ultrasonography, MRI, computer-assisted image analysis and mathematical modeling heralds a new era in our understanding of the basic processes of female and male reproduction.

An overview of state-of-the-art image restoration in electron microscopy.

PubMed

Roels, J; Aelterman, J; Luong, H Q; Lippens, S; Pižurica, A; Saeys, Y; Philips, W

2018-06-08

In Life Science research, electron microscopy (EM) is an essential tool for morphological analysis at the subcellular level as it allows for visualization at nanometer resolution. However, electron micrographs contain image degradations such as noise and blur caused by electromagnetic interference, electron counting errors, magnetic lens imperfections, electron diffraction, etc. These imperfections in raw image quality are inevitable and hamper subsequent image analysis and visualization. In an effort to mitigate these artefacts, many electron microscopy image restoration algorithms have been proposed in the last years. Most of these methods rely on generic assumptions on the image or degradations and are therefore outperformed by advanced methods that are based on more accurate models. Ideally, a method will accurately model the specific degradations that fit the physical acquisition settings. In this overview paper, we discuss different electron microscopy image degradation solutions and demonstrate that dedicated artefact regularisation results in higher quality restoration and is applicable through recently developed probabilistic methods. © 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.

Advanced endoscopic imaging: European Society of Gastrointestinal Endoscopy (ESGE) Technology Review.

PubMed

East, James E; Vleugels, Jasper L; Roelandt, Philip; Bhandari, Pradeep; Bisschops, Raf; Dekker, Evelien; Hassan, Cesare; Horgan, Gareth; Kiesslich, Ralf; Longcroft-Wheaton, Gaius; Wilson, Ana; Dumonceau, Jean-Marc

2016-11-01

Background and aim: This technical review is an official statement of the European Society of Gastrointestinal Endoscopy (ESGE). It addresses the utilization of advanced endoscopic imaging in gastrointestinal (GI) endoscopy. Methods: This technical review is based on a systematic literature search to evaluate the evidence supporting the use of advanced endoscopic imaging throughout the GI tract. Technologies considered include narrowed-spectrum endoscopy (narrow band imaging [NBI]; flexible spectral imaging color enhancement [FICE]; i-Scan digital contrast [I-SCAN]), autofluorescence imaging (AFI), and confocal laser endomicroscopy (CLE). The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was adopted to define the strength of recommendation and the quality of evidence. Main recommendations: 1. We suggest advanced endoscopic imaging technologies improve mucosal visualization and enhance fine structural and microvascular detail. Expert endoscopic diagnosis may be improved by advanced imaging, but as yet in community-based practice no technology has been shown consistently to be diagnostically superior to current practice with high definition white light. (Low quality evidence.) 2. We recommend the use of validated classification systems to support the use of optical diagnosis with advanced endoscopic imaging in the upper and lower GI tracts (strong recommendation, moderate quality evidence). 3. We suggest that training improves performance in the use of advanced endoscopic imaging techniques and that it is a prerequisite for use in clinical practice. A learning curve exists and training alone does not guarantee sustained high performances in clinical practice. (Weak recommendation, low quality evidence.) Conclusion: Advanced endoscopic imaging can improve mucosal visualization and endoscopic diagnosis; however it requires training and the use of validated classification systems. © Georg Thieme Verlag KG Stuttgart · New York.

The multiple sclerosis visual pathway cohort: understanding neurodegeneration in MS.

PubMed

Martínez-Lapiscina, Elena H; Fraga-Pumar, Elena; Gabilondo, Iñigo; Martínez-Heras, Eloy; Torres-Torres, Ruben; Ortiz-Pérez, Santiago; Llufriu, Sara; Tercero, Ana; Andorra, Magi; Roca, Marc Figueras; Lampert, Erika; Zubizarreta, Irati; Saiz, Albert; Sanchez-Dalmau, Bernardo; Villoslada, Pablo

2014-12-15

Multiple Sclerosis (MS) is an immune-mediated disease of the Central Nervous System with two major underlying etiopathogenic processes: inflammation and neurodegeneration. The latter determines the prognosis of this disease. MS is the main cause of non-traumatic disability in middle-aged populations. The MS-VisualPath Cohort was set up to study the neurodegenerative component of MS using advanced imaging techniques by focusing on analysis of the visual pathway in a middle-aged MS population in Barcelona, Spain. We started the recruitment of patients in the early phase of MS in 2010 and it remains permanently open. All patients undergo a complete neurological and ophthalmological examination including measurements of physical and disability (Expanded Disability Status Scale; Multiple Sclerosis Functional Composite and neuropsychological tests), disease activity (relapses) and visual function testing (visual acuity, color vision and visual field). The MS-VisualPath protocol also assesses the presence of anxiety and depressive symptoms (Hospital Anxiety and Depression Scale), general quality of life (SF-36) and visual quality of life (25-Item National Eye Institute Visual Function Questionnaire with the 10-Item Neuro-Ophthalmic Supplement). In addition, the imaging protocol includes both retinal (Optical Coherence Tomography and Wide-Field Fundus Imaging) and brain imaging (Magnetic Resonance Imaging). Finally, multifocal Visual Evoked Potentials are used to perform neurophysiological assessment of the visual pathway. The analysis of the visual pathway with advance imaging and electrophysilogical tools in parallel with clinical information will provide significant and new knowledge regarding neurodegeneration in MS and provide new clinical and imaging biomarkers to help monitor disease progression in these patients.

Advanced Medical Technology and Network Systems Research.

DTIC Science & Technology

1999-09-01

for image-guided therapies . Advanced technologies included in this report are impedance imaging and a palpation training system. 14. SUBJECT...Summary 1 Virtual Clinic for Patients with Chronic Illness Project Planning Document • 2 Telemedicine for Hemodialysis 21 A...imaging systems and’ surgical procedures effort is accomplished in part by establishing the technology requirements for image-guided therapies . Advanced

KENNEDY SPACE CENTER, FLA. - Armando Oliu, Final Inspection Team lead for the Shuttle program, speaks to reporters about the aid the Image Analysis Lab is giving the FBI in a kidnapping case. Oliu oversees the image lab that is using an advanced SGI® TP9500 data management system to review the tape of the kidnapping in progress in Sarasota, Fla. KSC installed the new $3.2 million system in preparation for Return to Flight of the Space Shuttle fleet. The lab is studying the Sarasota kidnapping video to provide any new information possible to law enforcement officers. KSC is joining NASA’s Marshall Space Flight Center in Alabama in reviewing the tape.

NASA Image and Video Library

2004-02-04

KENNEDY SPACE CENTER, FLA. - Armando Oliu, Final Inspection Team lead for the Shuttle program, speaks to reporters about the aid the Image Analysis Lab is giving the FBI in a kidnapping case. Oliu oversees the image lab that is using an advanced SGI® TP9500 data management system to review the tape of the kidnapping in progress in Sarasota, Fla. KSC installed the new $3.2 million system in preparation for Return to Flight of the Space Shuttle fleet. The lab is studying the Sarasota kidnapping video to provide any new information possible to law enforcement officers. KSC is joining NASA’s Marshall Space Flight Center in Alabama in reviewing the tape.

Image analysis algorithms for the advanced radiographic capability (ARC) grating tilt sensor at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Roberts, Randy S.; Bliss, Erlan S.; Rushford, Michael C.; Halpin, John M.; Awwal, Abdul A. S.; Leach, Richard R.

2014-09-01

The Advance Radiographic Capability (ARC) at the National Ignition Facility (NIF) is a laser system designed to produce a sequence of short pulses used to backlight imploding fuel capsules. Laser pulses from a short-pulse oscillator are dispersed in wavelength into long, low-power pulses, injected in the NIF main laser for amplification, and then compressed into high-power pulses before being directed into the NIF target chamber. In the target chamber, the laser pulses hit targets which produce x-rays used to backlight imploding fuel capsules. Compression of the ARC laser pulses is accomplished with a set of precision-surveyed optical gratings mounted inside of vacuum vessels. The tilt of each grating is monitored by a measurement system consisting of a laser diode, camera and crosshair, all mounted in a pedestal outside of the vacuum vessel, and a mirror mounted on the back of a grating inside the vacuum vessel. The crosshair is mounted in front of the camera, and a diffraction pattern is formed when illuminated with the laser diode beam reflected from the mirror. This diffraction pattern contains information related to relative movements between the grating and the pedestal. Image analysis algorithms have been developed to determine the relative movements between the gratings and pedestal. In the paper we elaborate on features in the diffraction pattern, and describe the image analysis algorithms used to monitor grating tilt changes. Experimental results are provided which indicate the high degree of sensitivity provided by the tilt sensor and image analysis algorithms.

Recent technological advancements in cardiac ultrasound imaging.

PubMed

Dave, Jaydev K; Mc Donald, Maureen E; Mehrotra, Praveen; Kohut, Andrew R; Eisenbrey, John R; Forsberg, Flemming

2018-03-01

About 92.1 million Americans suffer from at least one type of cardiovascular disease. Worldwide, cardiovascular diseases are the number one cause of death (about 31% of all global deaths). Recent technological advancements in cardiac ultrasound imaging are expected to aid in the clinical diagnosis of many cardiovascular diseases. This article provides an overview of such recent technological advancements, specifically focusing on tissue Doppler imaging, strain imaging, contrast echocardiography, 3D echocardiography, point-of-care echocardiography, 3D volumetric flow assessments, and elastography. With these advancements ultrasound imaging is rapidly changing the domain of cardiac imaging. The advantages offered by ultrasound imaging include real-time imaging, imaging at patient bed-side, cost-effectiveness and ionizing-radiation-free imaging. Along with these advantages, the steps taken towards standardization of ultrasound based quantitative markers, reviewed here, will play a major role in addressing the healthcare burden associated with cardiovascular diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

Technical Advance: Live-imaging analysis of human dendritic cell migrating behavior under the influence of immune-stimulating reagents in an organotypic model of lung

PubMed Central

Nguyen Hoang, Anh Thu; Chen, Puran; Björnfot, Sofia; Högstrand, Kari; Lock, John G.; Grandien, Alf; Coles, Mark; Svensson, Mattias

2014-01-01

This manuscript describes technical advances allowing manipulation and quantitative analyses of human DC migratory behavior in lung epithelial tissue. DCs are hematopoietic cells essential for the maintenance of tissue homeostasis and the induction of tissue-specific immune responses. Important functions include cytokine production and migration in response to infection for the induction of proper immune responses. To design appropriate strategies to exploit human DC functional properties in lung tissue for the purpose of clinical evaluation, e.g., candidate vaccination and immunotherapy strategies, we have developed a live-imaging assay based on our previously described organotypic model of the human lung. This assay allows provocations and subsequent quantitative investigations of DC functional properties under conditions mimicking morphological and functional features of the in vivo parental tissue. We present protocols to set up and prepare tissue models for 4D (x, y, z, time) fluorescence-imaging analysis that allow spatial and temporal studies of human DCs in live epithelial tissue, followed by flow cytometry analysis of DCs retrieved from digested tissue models. This model system can be useful for elucidating incompletely defined pathways controlling DC functional responses to infection and inflammation in lung epithelial tissue, as well as the efficacy of locally administered candidate interventions. PMID:24899587

Simulation of bright-field microscopy images depicting pap-smear specimen

PubMed Central

Malm, Patrik; Brun, Anders; Bengtsson, Ewert

2015-01-01

As digital imaging is becoming a fundamental part of medical and biomedical research, the demand for computer-based evaluation using advanced image analysis is becoming an integral part of many research projects. A common problem when developing new image analysis algorithms is the need of large datasets with ground truth on which the algorithms can be tested and optimized. Generating such datasets is often tedious and introduces subjectivity and interindividual and intraindividual variations. An alternative to manually created ground-truth data is to generate synthetic images where the ground truth is known. The challenge then is to make the images sufficiently similar to the real ones to be useful in algorithm development. One of the first and most widely studied medical image analysis tasks is to automate screening for cervical cancer through Pap-smear analysis. As part of an effort to develop a new generation cervical cancer screening system, we have developed a framework for the creation of realistic synthetic bright-field microscopy images that can be used for algorithm development and benchmarking. The resulting framework has been assessed through a visual evaluation by experts with extensive experience of Pap-smear images. The results show that images produced using our described methods are realistic enough to be mistaken for real microscopy images. The developed simulation framework is very flexible and can be modified to mimic many other types of bright-field microscopy images. © 2015 The Authors. Published by Wiley Periodicals, Inc. on behalf of ISAC PMID:25573002

Study of fish response using particle image velocimetry and high-speed, high-resolution imaging

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

Deng, Z.; Richmond, M. C.; Mueller, R. P.

2004-10-01

Fish swimming has fascinated both engineers and fish biologists for decades. Digital particle image velocimetry (DPIV) and high-speed, high-resolution digital imaging are recently developed analysis tools that can help engineers and biologists better understand how fish respond to turbulent environments. This report details studies to evaluate DPIV. The studies included a review of existing literature on DPIV, preliminary studies to test the feasibility of using DPIV conducted at our Flow Biology Laboratory in Richland, Washington September through December 2003, and applications of high-speed, high-resolution digital imaging with advanced motion analysis to investigations of fish injury mechanisms in turbulent shear flowsmore » and bead trajectories in laboratory physical models. Several conclusions were drawn based on these studies, which are summarized as recommendations for proposed research at the end of this report.« less

Hyperspectral imaging for non-contact analysis of forensic traces.

PubMed

Edelman, G J; Gaston, E; van Leeuwen, T G; Cullen, P J; Aalders, M C G

2012-11-30

Hyperspectral imaging (HSI) integrates conventional imaging and spectroscopy, to obtain both spatial and spectral information from a specimen. This technique enables investigators to analyze the chemical composition of traces and simultaneously visualize their spatial distribution. HSI offers significant potential for the detection, visualization, identification and age estimation of forensic traces. The rapid, non-destructive and non-contact features of HSI mark its suitability as an analytical tool for forensic science. This paper provides an overview of the principles, instrumentation and analytical techniques involved in hyperspectral imaging. We describe recent advances in HSI technology motivating forensic science applications, e.g. the development of portable and fast image acquisition systems. Reported forensic science applications are reviewed. Challenges are addressed, such as the analysis of traces on backgrounds encountered in casework, concluded by a summary of possible future applications. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels

PubMed Central

Sornapudi, Sudhir; Stanley, Ronald Joe; Stoecker, William V.; Almubarak, Haidar; Long, Rodney; Antani, Sameer; Thoma, George; Zuna, Rosemary; Frazier, Shelliane R.

2018-01-01

Background: Advances in image analysis and computational techniques have facilitated automatic detection of critical features in histopathology images. Detection of nuclei is critical for squamous epithelium cervical intraepithelial neoplasia (CIN) classification into normal, CIN1, CIN2, and CIN3 grades. Methods: In this study, a deep learning (DL)-based nuclei segmentation approach is investigated based on gathering localized information through the generation of superpixels using a simple linear iterative clustering algorithm and training with a convolutional neural network. Results: The proposed approach was evaluated on a dataset of 133 digitized histology images and achieved an overall nuclei detection (object-based) accuracy of 95.97%, with demonstrated improvement over imaging-based and clustering-based benchmark techniques. Conclusions: The proposed DL-based nuclei segmentation Method with superpixel analysis has shown improved segmentation results in comparison to state-of-the-art methods. PMID:29619277

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

Thompson, David R.

2011-01-01

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

Image analysis tools and emerging algorithms for expression proteomics

PubMed Central

English, Jane A.; Lisacek, Frederique; Morris, Jeffrey S.; Yang, Guang-Zhong; Dunn, Michael J.

2012-01-01

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-D Gel Electrophoresis (2-DE) technique of protein separation, and by first covering signal analysis for Mass Spectrometry (MS), we also explain the current image analysis workflow for the emerging high-throughput ‘shotgun’ proteomics platform of Liquid Chromatography coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whilst existing commercial and academic packages and their workflows are described from both a user’s and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS. PMID:21046614

Incorporating Colour Information for Computer-Aided Diagnosis of Melanoma from Dermoscopy Images: A Retrospective Survey and Critical Analysis

PubMed Central

Drew, Mark S.

2016-01-01

Cutaneous melanoma is the most life-threatening form of skin cancer. Although advanced melanoma is often considered as incurable, if detected and excised early, the prognosis is promising. Today, clinicians use computer vision in an increasing number of applications to aid early detection of melanoma through dermatological image analysis (dermoscopy images, in particular). Colour assessment is essential for the clinical diagnosis of skin cancers. Due to this diagnostic importance, many studies have either focused on or employed colour features as a constituent part of their skin lesion analysis systems. These studies range from using low-level colour features, such as simple statistical measures of colours occurring in the lesion, to availing themselves of high-level semantic features such as the presence of blue-white veil, globules, or colour variegation in the lesion. This paper provides a retrospective survey and critical analysis of contributions in this research direction. PMID:28096807

European Union RACE program contributions to digital audiovisual communications and services

NASA Astrophysics Data System (ADS)

de Albuquerque, Augusto; van Noorden, Leon; Badique', Eric

1995-02-01

The European Union RACE (R&D in advanced communications technologies in Europe) and the future ACTS (advanced communications technologies and services) programs have been contributing and continue to contribute to world-wide developments in audio-visual services. The paper focuses on research progress in: (1) Image data compression. Several methods of image analysis leading to the use of encoders based on improved hybrid DCT-DPCM (MPEG or not), object oriented, hybrid region/waveform or knowledge-based coding methods are discussed. (2) Program production in the aspects of 3D imaging, data acquisition, virtual scene construction, pre-processing and sequence generation. (3) Interoperability and multimedia access systems. The diversity of material available and the introduction of interactive or near- interactive audio-visual services led to the development of prestandards for video-on-demand (VoD) and interworking of multimedia services storage systems and customer premises equipment.

Animal models for the study of inflammatory bowel diseases: a meta-analysis on modalities for imaging inflammatory lesions.

PubMed

Auletta, Sveva; Bonfiglio, Rita; Wunder, Andreas; Varani, Michela; Galli, Filippo; Borri, Filippo; Scimeca, Manuel; Niessen, Heiko G; Schönberger, Tanja; Bonanno, Elena

2018-03-01

Inflammatory bowel diseases are lifelong disorders affecting the gastrointestinal tract characterized by intermittent disease flares and periods of remission with a progressive and destructive nature. Unfortunately, the exact etiology is still not completely known, therefore a causal therapy to cure the disease is not yet available. Current treatment options mainly encompass the use of non-specific anti-inflammatory agents and immunosuppressive drugs that cause significant side effects that often have a negative impact on patients' quality of life. As the majority of patients need a long-term follow-up it would be ideal to rely on a non-invasive technique with good compliance. Currently, the gold standard diagnostic tools for managing IBD are represented by invasive procedures such as colonoscopy and histopathology. Nevertheless, recent advances in imaging technology continue to improve the ability of imaging techniques to non-invasively monitor disease activity and treatment response in preclinical models of IBD. Novel and emerging imaging techniques not only allow direct visualization of intestinal inflammation, but also enable molecular imaging and targeting of specific alterations of the inflamed murine mucosa. Furthermore, molecular imaging advances allow us to increase our knowledge on the critical biological pathways involved in disease progression by characterizing in vivo processes at a cellular and molecular level and enabling significant improvements in the understanding of the etiology of IBD. This review presents a critical and updated overview on the imaging advances in animal models of IBD. Our aim is to highlight the potential beneficial impact and the range of applications that imaging techniques could offer for the improvement of the clinical monitoring and management of IBD patients: diagnosis, staging, determination of therapeutic targets, monitoring therapy and evaluation of the prognosis, personalized therapeutic approaches.

Ultrasonographic analysis versus histopathologic evaluation of carotid advanced atherosclerotic stenosis in an experimental rabbit model.

PubMed

Mehrad, Hossein; Mokhtari-Dizaji, Manijhe; Ghanaati, Hossein; Shahbazfar, Amir-Ali; Salehnia, Mojdeh

2012-08-01

Advanced carotid atherosclerosis with severe stenosis (>70%) is a major clinical risk factor for ischemic stroke. Our ability to test new protocols for the treatment of atherosclerotic stenosis in humans is limited for obvious ethical reasons; therefore, a suitable animal model is required. The aim of this study was to generate an easily reproducible and inexpensive experimental rabbit carotid model of advanced atherosclerosis with morphological similarities to the human disease and the subsequent assessment of the reliability of B-mode ultrasound technology in the study of lumen area stenosis in this model. Briefly, New Zealand white rabbits underwent primary perivascular cold injury at the right common carotid artery followed by a 1.5% cholesterol-rich diet injury for eight weeks. All of the rabbits' arteries were imaged by B-mode ultrasound weekly, after which the rabbits were sacrificed, and their vessels were processed for histopathology. Ultrasound longitudinal view images from three cardiac cycles were processed by a new computerized analyzing method based on dynamic programming and maximum gradient algorithm for measurement of instantaneous changes in arterial wall thickness and lumen diameter in sequential ultrasound images. Histopathology results showed progressive changes, from the lipid-laden cells and fibrous connective tissue proliferation in neointimal layer, up to the fibro-lipid plaque formation, resulting in vessel wall thickening, remodeling and lumen stenosis. The B-mode ultrasound images and the histologic measurements showed an increase in the mean wall thickness and the lumen area stenosis within eight weeks. Quantitative and morphometric analysis of the mean wall thickness and the lumen area stenosis percentage showed a significant correlation between the B-mode ultrasound and the histological measurements at each time point (R = 0.989 and R = 0.995, p < 0.05, respectively). In conclusion, we successfully produced advanced atherosclerosis in the rabbit carotid artery that is similar to the condition seen in patients. This condition in rabbits can be properly assessed by B-mode ultrasound image processing. Copyright © 2012 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

TU-D-207B-03: Early Assessment of Response to Chemoradiotherapy Based On Textural Analysis of Pre and Mid-Treatment FDG-PET Image in Locally Advanced Head and Neck Cancer

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

Cui, Y; Pollom, E; Loo, B

Purpose: To evaluate whether tumor textural features extracted from both pre- and mid-treatment FDG-PET images predict early response to chemoradiotherapy in locally advanced head and neck cancer, and investigate whether they provide complementary value to conventional volume-based measurements. Methods: Ninety-four patients with locally advanced head and neck cancers were retrospectively studied. All patients received definitive chemoradiotherapy and underwent FDG-PET planning scans both before and during treatment. Within the primary tumor we extracted 6 textural features based on gray-level co-occurrence matrices (GLCM): entropy, dissimilarity, contrast, correlation, energy, and homogeneity. These image features were evaluated for their predictive power of treatment responsemore » to chemoradiotherapy in terms of local recurrence free survival (LRFS) and progression free survival (PFS). Logrank test were used to assess the statistical significance of the stratification between low- and high-risk groups. P-values were adjusted for multiple comparisons by the false discovery rate (FDR) method. Results: All six textural features extracted from pre-treatment PET images significantly differentiated low- and high-risk patient groups for LRFS (P=0.011–0.038) and PFS (P=0.029–0.034). On the other hand, none of the textural features on mid-treatment PET images was statistically significant in stratifying LRFS (P=0.212–0.445) or PFS (P=0.168–0.299). An imaging signature that combines textural feature (GLCM homogeneity) and metabolic tumor volume showed an improved performance for predicting LRFS (hazard ratio: 22.8, P<0.0001) and PFS (hazard ratio: 13.9, P=0.0005) in leave-one-out cross validation. Intra-tumor heterogeneity measured by textural features was significantly lower in mid-treatment PET images than in pre-treatment PET images (T-test: P<1.4e-6). Conclusion: Tumor textural features on pretreatment FDG-PET images are predictive for response to chemoradiotherapy in locally advanced head and neck cancer. The complementary information offered by textural features improves patient stratification and may potentially aid in personalized risk-adaptive therapy.« less

Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience.

PubMed

Paninski, L; Cunningham, J P

2018-06-01

Modern large-scale multineuronal recording methodologies, including multielectrode arrays, calcium imaging, and optogenetic techniques, produce single-neuron resolution data of a magnitude and precision that were the realm of science fiction twenty years ago. The major bottlenecks in systems and circuit neuroscience no longer lie in simply collecting data from large neural populations, but also in understanding this data: developing novel scientific questions, with corresponding analysis techniques and experimental designs to fully harness these new capabilities and meaningfully interrogate these questions. Advances in methods for signal processing, network analysis, dimensionality reduction, and optimal control-developed in lockstep with advances in experimental neurotechnology-promise major breakthroughs in multiple fundamental neuroscience problems. These trends are clear in a broad array of subfields of modern neuroscience; this review focuses on recent advances in methods for analyzing neural time-series data with single-neuronal precision. Copyright © 2018 Elsevier Ltd. All rights reserved.

Advanced Pediatric Brain Imaging Research and Training Program

DTIC Science & Technology

2013-10-01

diffusion tensor imaging and perfusion ( arterial spin labeling) MRI data and to relate measures of global and regional brain microstructural organization...AD_________________ Award Number: W81XWH-11-2-0198 TITLE: Advanced Pediatric Brain Imaging...September 2013 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Advanced Pediatric Brain Imaging Research and Training Program 5b. GRANT NUMBER W81XWH

Advanced Diffusion-Weighted Magnetic Resonance Imaging Techniques of the Human Spinal Cord

PubMed Central

Andre, Jalal B.; Bammer, Roland

2012-01-01

Unlike those of the brain, advances in diffusion-weighted imaging (DWI) of the human spinal cord have been challenged by the more complicated and inhomogeneous anatomy of the spine, the differences in magnetic susceptibility between adjacent air and fluid-filled structures and the surrounding soft tissues, and the inherent limitations of the initially used echo-planar imaging techniques used to image the spine. Interval advances in DWI techniques for imaging the human spinal cord, with the specific aims of improving the diagnostic quality of the images, and the simultaneous reduction in unwanted artifacts have resulted in higher-quality images that are now able to more accurately portray the complicated underlying anatomy and depict pathologic abnormality with improved sensitivity and specificity. Diffusion tensor imaging (DTI) has benefited from the advances in DWI techniques, as DWI images form the foundation for all tractography and DTI. This review provides a synopsis of the many recent advances in DWI of the human spinal cord, as well as some of the more common clinical uses for these techniques, including DTI and tractography. PMID:22158130

Transmission ultrasonography. [time delay spectrometry for soft tissue transmission imaging

NASA Technical Reports Server (NTRS)

Heyser, R. C.; Le Croissette, D. H.

1973-01-01

Review of the results of the application of an advanced signal-processing technique, called time delay spectrometry, in obtaining soft tissue transmission images by transmission ultrasonography, both in vivo and in vitro. The presented results include amplitude ultrasound pictures and phase ultrasound pictures obtained by this technique. While amplitude ultrasonographs of tissue are closely analogous to X-ray pictures in that differential absorption is imaged, phase ultrasonographs represent an entirely new source of information based on differential time of propagation. Thus, a new source of information is made available for detailed analysis.

Physics and engineering aspects of cell and tissue imaging systems: microscopic devices and computer assisted diagnosis.

PubMed

Chen, Xiaodong; Ren, Liqiang; Zheng, Bin; Liu, Hong

2013-01-01

The conventional optical microscopes have been used widely in scientific research and in clinical practice. The modern digital microscopic devices combine the power of optical imaging and computerized analysis, archiving and communication techniques. It has a great potential in pathological examinations for improving the efficiency and accuracy of clinical diagnosis. This chapter reviews the basic optical principles of conventional microscopes, fluorescence microscopes and electron microscopes. The recent developments and future clinical applications of advanced digital microscopic imaging methods and computer assisted diagnosis schemes are also discussed.

Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

PubMed

Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

2017-11-01

Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

An Automated Method of Scanning Probe Microscopy (SPM) Data Analysis and Reactive Site Tracking for Mineral-Water Interface Reactions Observed at the Nanometer Scale

NASA Astrophysics Data System (ADS)

Campbell, B. D.; Higgins, S. R.

2008-12-01

Developing a method for bridging the gap between macroscopic and microscopic measurements of reaction kinetics at the mineral-water interface has important implications in geological and chemical fields. Investigating these reactions on the nanometer scale with SPM is often limited by image analysis and data extraction due to the large quantity of data usually obtained in SPM experiments. Here we present a computer algorithm for automated analysis of mineral-water interface reactions. This algorithm automates the analysis of sequential SPM images by identifying the kinetically active surface sites (i.e., step edges), and by tracking the displacement of these sites from image to image. The step edge positions in each image are readily identified and tracked through time by a standard edge detection algorithm followed by statistical analysis on the Hough Transform of the edge-mapped image. By quantifying this displacement as a function of time, the rate of step edge displacement is determined. Furthermore, the total edge length, also determined from analysis of the Hough Transform, combined with the computed step speed, yields the surface area normalized rate of the reaction. The algorithm was applied to a study of the spiral growth of the calcite(104) surface from supersaturated solutions, yielding results almost 20 times faster than performing this analysis by hand, with results being statistically similar for both analysis methods. This advance in analysis of kinetic data from SPM images will facilitate the building of experimental databases on the microscopic kinetics of mineral-water interface reactions.

Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

PubMed Central

Bayır, Şafak

2016-01-01

With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC. PMID:27110272

Advanced imaging in COPD: insights into pulmonary pathophysiology

PubMed Central

Milne, Stephen

2014-01-01

Chronic obstructive pulmonary disease (COPD) involves a complex interaction of structural and functional abnormalities. The two have long been studied in isolation. However, advanced imaging techniques allow us to simultaneously assess pathological processes and their physiological consequences. This review gives a comprehensive account of the various advanced imaging modalities used to study COPD, including computed tomography (CT), magnetic resonance imaging (MRI), and the nuclear medicine techniques positron emission tomography (PET) and single-photon emission computed tomography (SPECT). Some more recent developments in imaging technology, including micro-CT, synchrotron imaging, optical coherence tomography (OCT) and electrical impedance tomography (EIT), are also described. The authors identify the pathophysiological insights gained from these techniques, and speculate on the future role of advanced imaging in both clinical and research settings. PMID:25478198

Framing Service, Benefit, and Credibility Through Images and Texts: A Content Analysis of Online Promotional Messages of Korean Medical Tourism Industry.

PubMed

Jun, Jungmi

2016-07-01

This study examines how the Korean medical tourism industry frames its service, benefit, and credibility issues through texts and images of online brochures. The results of content analysis suggest that the Korean medical tourism industry attempts to frame their medical/health services as "excellence in surgeries and cancer care" and "advanced health technology and facilities." However, the use of cost-saving appeals was limited, which can be seen as a strategy to avoid consumers' association of lower cost with lower quality services, and to stress safety and credibility.

Satellite land remote sensing advancements for the eighties; Proceedings of the Eighth Pecora Symposium, Sioux Falls, SD, October 4-7, 1983

NASA Technical Reports Server (NTRS)

1984-01-01

Among the topics discussed are NASA's land remote sensing plans for the 1980s, the evolution of Landsat 4 and the performance of its sensors, the Landsat 4 thematic mapper image processing system radiometric and geometric characteristics, data quality, image data radiometric analysis and spectral/stratigraphic analysis, and thematic mapper agricultural, forest resource and geological applications. Also covered are geologic applications of side-looking airborne radar, digital image processing, the large format camera, the RADARSAT program, the SPOT 1 system's program status, distribution plans, and simulation program, Space Shuttle multispectral linear array studies of the optical and biological properties of terrestrial land cover, orbital surveys of solar-stimulated luminescence, the Space Shuttle imaging radar research facility, and Space Shuttle-based polar ice sounding altimetry.

A simultaneous multimodal imaging system for tissue functional parameters

NASA Astrophysics Data System (ADS)

Ren, Wenqi; Zhang, Zhiwu; Wu, Qiang; Zhang, Shiwu; Xu, Ronald

2014-02-01

Simultaneous and quantitative assessment of skin functional characteristics in different modalities will facilitate diagnosis and therapy in many clinical applications such as wound healing. However, many existing clinical practices and multimodal imaging systems are subjective, qualitative, sequential for multimodal data collection, and need co-registration between different modalities. To overcome these limitations, we developed a multimodal imaging system for quantitative, non-invasive, and simultaneous imaging of cutaneous tissue oxygenation and blood perfusion parameters. The imaging system integrated multispectral and laser speckle imaging technologies into one experimental setup. A Labview interface was developed for equipment control, synchronization, and image acquisition. Advanced algorithms based on a wide gap second derivative reflectometry and laser speckle contrast analysis (LASCA) were developed for accurate reconstruction of tissue oxygenation and blood perfusion respectively. Quantitative calibration experiments and a new style of skinsimulating phantom were designed to verify the accuracy and reliability of the imaging system. The experimental results were compared with a Moor tissue oxygenation and perfusion monitor. For In vivo testing, a post-occlusion reactive hyperemia (PORH) procedure in human subject and an ongoing wound healing monitoring experiment using dorsal skinfold chamber models were conducted to validate the usability of our system for dynamic detection of oxygenation and perfusion parameters. In this study, we have not only setup an advanced multimodal imaging system for cutaneous tissue oxygenation and perfusion parameters but also elucidated its potential for wound healing assessment in clinical practice.

MTF analysis using lunar observations for Himawari-8/AHI

NASA Astrophysics Data System (ADS)

Keller, Graziela R.; Chang, Tiejun; Xiong, Xiaoxiong

2017-09-01

The modulation transfer function, or MTF, is a common measure of image fidelity, which has been historically characterized on-orbit using high contrast images of the lunar limb obtained by remote sensing instruments onboard both low-orbit and geostationary satellites. Himawari-8, launched in 2014, is a Japanese geostationary satellite that carries the Advanced Himawari Imager (AHI), a near-identical copy of the Advanced Baseline Imager (ABI) instrument onboard the GOES-16 satellite. In this paper, we apply a variation of the slantededge method for deriving the MTF from lunar images, first verified by us on simulated test images, to the Himawari-8/AHI L1A and L1B data. The MTF is derived along the North/South and East/West directions separately. The AHI L1A images used in the characterization of the MTF are obtained from lunar observations routinely acquired for validating the radiometric calibration. The L1B data, which is spatially re-sampled, come from serendipitous lunar observations where the Moon appears close to the Earth's disk. We developed and implemented an algorithm to identify such occurrences using the SPICE/Icy package to predict the times where the Moon is visible in the L1B imagery and demonstrate their use for MTF derivation.

Semantic segmentation of mFISH images using convolutional networks.

PubMed

Pardo, Esteban; Morgado, José Mário T; Malpica, Norberto

2018-04-30

Multicolor in situ hybridization (mFISH) is a karyotyping technique used to detect major chromosomal alterations using fluorescent probes and imaging techniques. Manual interpretation of mFISH images is a time consuming step that can be automated using machine learning; in previous works, pixel or patch wise classification was employed, overlooking spatial information which can help identify chromosomes. In this work, we propose a fully convolutional semantic segmentation network for the interpretation of mFISH images, which uses both spatial and spectral information to classify each pixel in an end-to-end fashion. The semantic segmentation network developed was tested on samples extracted from a public dataset using cross validation. Despite having no labeling information of the image it was tested on, our algorithm yielded an average correct classification ratio (CCR) of 87.41%. Previously, this level of accuracy was only achieved with state of the art algorithms when classifying pixels from the same image in which the classifier has been trained. These results provide evidence that fully convolutional semantic segmentation networks may be employed in the computer aided diagnosis of genetic diseases with improved performance over the current image analysis methods. © 2018 International Society for Advancement of Cytometry. © 2018 International Society for Advancement of Cytometry.

Large-scale quantitative analysis of painting arts.

PubMed

Kim, Daniel; Son, Seung-Woo; Jeong, Hawoong

2014-12-11

Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images - the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances.

Application of conventional and advanced techniques for the interpretation of LANDSAT 2 images for the study of linears in the Friuli earthquake area

NASA Technical Reports Server (NTRS)

Cardamone, P.; Lechi, G. M.; Cavallin, A.; Marino, C. M.; Zanferrari, A.

1977-01-01

The results obtained in the study of linears derived from the analysis of LANDSAT 2 images recorded over Friuli during 1975 are described. Particular attention is devoted to the comparison of several passes in different bands, scales and photographic supports. Moreover reference is made to aerial photographic interpretation in selected sites and to the information obtained by laser techniques.

Design Analysis of a Space Based Chromotomographic Hyperspectral Imaging Experiment

DTIC Science & Technology

2010-03-01

Tilt Platforms S-340 Platform Recommended Models Mirror Aluminum Aluminum S-340.Ax Invar Zerodur glass S-340.ix Titanium BK7 glass S-340.Tx Steel S-340...composed of a telescope, two grating spectrometers, calibration lamps, and focal plane electronics and cooling system. The telescope is a three mirror ...advanced hyperspectral imager for coastal bathymetry is that the experiment will closely mirror that of the proposed space-based chromotomographic hy

Image analysis in modern ophthalmology: from acquisition to computer assisted diagnosis and telemedicine

NASA Astrophysics Data System (ADS)

Marrugo, Andrés G.; Millán, María S.; Cristóbal, Gabriel; Gabarda, Salvador; Sorel, Michal; Sroubek, Filip

2012-06-01

Medical digital imaging has become a key element of modern health care procedures. It provides visual documentation and a permanent record for the patients, and most important the ability to extract information about many diseases. Modern ophthalmology thrives and develops on the advances in digital imaging and computing power. In this work we present an overview of recent image processing techniques proposed by the authors in the area of digital eye fundus photography. Our applications range from retinal image quality assessment to image restoration via blind deconvolution and visualization of structural changes in time between patient visits. All proposed within a framework for improving and assisting the medical practice and the forthcoming scenario of the information chain in telemedicine.

Advances in the Use of Thermography to Inspect Composite Tanks for Liquid Fuel Propulsion Systems

NASA Technical Reports Server (NTRS)

Lansing, Matthew D.; Russell, Samuel S.; Walker, James L.; Jones, Clyde S. (Technical Monitor)

2001-01-01

This viewgraph presentation gives an overview of advances in the use of thermography to inspect composite tanks for liquid fuel propulsion systems. Details are given on the thermographic inspection system, thermographic analysis method (includes scan and defect map, method of inspection, and inclusions, ply wrinkle, and delamination defects), graphite composite cryogenic feedline (including method, image map, and deep/shallow inclusions and resin rich area defects), and material degradation nondestructive evaluation.

Local plate/rod descriptors of 3D trabecular bone micro-CT images from medial axis topologic analysis

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

Peyrin, Francoise; Attali, Dominique; Chappard, Christine

Purpose: Trabecular bone microarchitecture is made of a complex network of plate and rod structures evolving with age and disease. The purpose of this article is to propose a new 3D local analysis method for the quantitative assessment of parameters related to the geometry of trabecular bone microarchitecture. Methods: The method is based on the topologic classification of the medial axis of the 3D image into branches, rods, and plates. Thanks to the reversibility of the medial axis, the classification is next extended to the whole 3D image. Finally, the percentages of rods and plates as well as their meanmore » thicknesses are calculated. The method was applied both to simulated test images and 3D micro-CT images of human trabecular bone. Results: The classification of simulated phantoms made of plates and rods shows that the maximum error in the quantitative percentages of plate and rods is less than 6% and smaller than with the structure model index (SMI). Micro-CT images of human femoral bone taken in osteoporosis and early or advanced osteoarthritis were analyzed. Despite the large physiological variability, the present method avoids the underestimation of rods observed with other local methods. The relative percentages of rods and plates were not significantly different between osteoarthritis and osteoporotic groups, whereas their absolute percentages were in relation to an increase of rod and plate thicknesses in advanced osteoarthritis with also higher relative and absolute number of nodes. Conclusions: The proposed method is model-independent, robust to surface irregularities, and enables geometrical characterization of not only skeletal structures but entire 3D images. Its application provided more accurate results than the standard SMI on simple simulated phantoms, but the discrepancy observed on the advanced osteoarthritis group raises questions that will require further investigations. The systematic use of such a local method in the characterization of trabecular bone samples could provide new insight in bone microarchitecture changes related to bone diseases or to those induced by drugs or therapy.« less

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format.

PubMed

Ahmed, Zeeshan; Dandekar, Thomas

2015-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool 'Mining Scientific Literature (MSL)', which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system's output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format.

Hyperspectral imaging in SWIR: from stain-free microscopy to deep tissue imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Berezin, Mikhail Y.

2016-03-01

Recent advances in relatively unexplored short wave infrared (SWIR) range from 800-1600 nm detectors make wide-field imaging in this spectral range attractive to biology. The distinct advantages of SWIR region over the visible and near infrared (NIR) in tissue analysis are two-fold: (i) high abundance endogenous chromophores (i.e. water and lipids) enable tissue component differentiation based on wavelength-dependent absorption properties and (ii) the weak scattering of tissue permits better resolution of imaging in thick specimens. When combined with high spectral resolution, SWIR imaging produces a spectroscopic image, where every pixel corresponds to the entire high-resolution spectrum. This hyperspectral (HS) approach provides rich information about the relative abundance of individual chromophores and their interactions that contribute to the intensity and location of the optical signal. The presentation discusses the challenges in the SWIR-HS instrument design and data analysis and demonstrates some of the promising applications of this technology in life science and medicine.

Deep Lake Explorer: Using citizen science to analyze underwater video from the Great Lakes

EPA Science Inventory

While underwater video collection technology continues to improve, advancements in underwater video analysis techniques have lagged. Crowdsourcing image interpretation using the Zooniverse platform has proven successful for many projects, but few projects to date have included vi...

42 CFR 414.68 - Imaging accreditation.

Code of Federal Regulations, 2011 CFR

2011-10-01

... of the organization's data management and analysis system for its surveys and accreditation decisions... organizations. (iv) Notify CMS, in writing, at least 30 calendar days in advance of the effective date of any... to designate and approve independent accreditation organizations for purposes of accrediting...

42 CFR 414.68 - Imaging accreditation.

Code of Federal Regulations, 2010 CFR

2010-10-01

... of the organization's data management and analysis system for its surveys and accreditation decisions... organizations. (iv) Notify CMS, in writing, at least 30 calendar days in advance of the effective date of any... to designate and approve independent accreditation organizations for purposes of accrediting...

Integrating medical imaging analyses through a high-throughput bundled resource imaging system

NASA Astrophysics Data System (ADS)

Covington, Kelsie; Welch, E. Brian; Jeong, Ha-Kyu; Landman, Bennett A.

2011-03-01

Exploitation of advanced, PACS-centric image analysis and interpretation pipelines provides well-developed storage, retrieval, and archival capabilities along with state-of-the-art data providence, visualization, and clinical collaboration technologies. However, pursuit of integrated medical imaging analysis through a PACS environment can be limiting in terms of the overhead required to validate, evaluate and integrate emerging research technologies. Herein, we address this challenge through presentation of a high-throughput bundled resource imaging system (HUBRIS) as an extension to the Philips Research Imaging Development Environment (PRIDE). HUBRIS enables PACS-connected medical imaging equipment to invoke tools provided by the Java Imaging Science Toolkit (JIST) so that a medical imaging platform (e.g., a magnetic resonance imaging scanner) can pass images and parameters to a server, which communicates with a grid computing facility to invoke the selected algorithms. Generated images are passed back to the server and subsequently to the imaging platform from which the images can be sent to a PACS. JIST makes use of an open application program interface layer so that research technologies can be implemented in any language capable of communicating through a system shell environment (e.g., Matlab, Java, C/C++, Perl, LISP, etc.). As demonstrated in this proof-of-concept approach, HUBRIS enables evaluation and analysis of emerging technologies within well-developed PACS systems with minimal adaptation of research software, which simplifies evaluation of new technologies in clinical research and provides a more convenient use of PACS technology by imaging scientists.

Advanced Ecosystem Mapping Techniques for Large Arctic Study Domains Using Calibrated High-Resolution Imagery

NASA Astrophysics Data System (ADS)

Macander, M. J.; Frost, G. V., Jr.

2015-12-01

Regional-scale mapping of vegetation and other ecosystem properties has traditionally relied on medium-resolution remote sensing such as Landsat (30 m) and MODIS (250 m). Yet, the burgeoning availability of high-resolution (<=2 m) imagery and ongoing advances in computing power and analysis tools raises the prospect of performing ecosystem mapping at fine spatial scales over large study domains. Here we demonstrate cutting-edge mapping approaches over a ~35,000 km² study area on Alaska's North Slope using calibrated and atmospherically-corrected mosaics of high-resolution WorldView-2 and GeoEye-1 imagery: (1) an a priori spectral approach incorporating the Satellite Imagery Automatic Mapper (SIAM) algorithms; (2) image segmentation techniques; and (3) texture metrics. The SIAM spectral approach classifies radiometrically-calibrated imagery to general vegetation density categories and non-vegetated classes. The SIAM classes were developed globally and their applicability in arctic tundra environments has not been previously evaluated. Image segmentation, or object-based image analysis, automatically partitions high-resolution imagery into homogeneous image regions that can then be analyzed based on spectral, textural, and contextual information. We applied eCognition software to delineate waterbodies and vegetation classes, in combination with other techniques. Texture metrics were evaluated to determine the feasibility of using high-resolution imagery to algorithmically characterize periglacial surface forms (e.g., ice-wedge polygons), which are an important physical characteristic of permafrost-dominated regions but which cannot be distinguished by medium-resolution remote sensing. These advanced mapping techniques provide products which can provide essential information supporting a broad range of ecosystem science and land-use planning applications in northern Alaska and elsewhere in the circumpolar Arctic.

Cardiovascular imaging and image processing: Theory and practice - 1975; Proceedings of the Conference, Stanford University, Stanford, Calif., July 10-12, 1975

NASA Technical Reports Server (NTRS)

Harrison, D. C.; Sandler, H.; Miller, H. A.

1975-01-01

The present collection of papers outlines advances in ultrasonography, scintigraphy, and commercialization of medical technology as applied to cardiovascular diagnosis in research and clinical practice. Particular attention is given to instrumentation, image processing and display. As necessary concomitants to mathematical analysis, recently improved magnetic recording methods using tape or disks and high-speed computers of large capacity are coming into use. Major topics include Doppler ultrasonic techniques, high-speed cineradiography, three-dimensional imaging of the myocardium with isotopes, sector-scanning echocardiography, and commercialization of the echocardioscope. Individual items are announced in this issue.

Registration of free-hand OCT daughter endoscopy to 3D organ reconstruction

PubMed Central

Lurie, Kristen L.; Angst, Roland; Seibel, Eric J.; Liao, Joseph C.; Ellerbee Bowden, Audrey K.

2016-01-01

Despite the trend to pair white light endoscopy with secondary image modalities for in vivo characterization of suspicious lesions, challenges remain to co-register such data. We present an algorithm to co-register two different optical imaging modalities as a mother-daughter endoscopy pair. Using white light cystoscopy (mother) and optical coherence tomography (OCT) (daughter) as an example, we developed the first forward-viewing OCT endoscope that fits in the working channel of flexible cystoscopes and demonstrated our algorithm’s performance with optical phantom and clinical imaging data. The ability to register multimodal data opens opportunities for advanced analysis in cancer imaging applications. PMID:28018720

Development and Current Status of Skull-Image Superimposition - Methodology and Instrumentation.

PubMed

Lan, Y

1992-12-01

This article presents a review of the literature and an evaluation on the development and application of skull-image superimposition technology - both instrumentation and methodology - contributed by a number of scholars since 1935. Along with a comparison of the methodologies involved in the two superimposition techniques - photographic and video - the author characterized the techniques in action and the recent advances in computer image superimposition processing technology. The major disadvantage of conventional approaches is its relying on subjective interpretation. Through painstaking comparison and analysis, computer image processing technology can make more conclusive identifications by direct testing and evaluating the various programmed indices. Copyright © 1992 Central Police University.

Optical Coherence Tomography in the UK Biobank Study - Rapid Automated Analysis of Retinal Thickness for Large Population-Based Studies.

PubMed

Keane, Pearse A; Grossi, Carlota M; Foster, Paul J; Yang, Qi; Reisman, Charles A; Chan, Kinpui; Peto, Tunde; Thomas, Dhanes; Patel, Praveen J

2016-01-01

To describe an approach to the use of optical coherence tomography (OCT) imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness. In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available "spectral domain" OCT device (3D OCT-1000, Topcon). Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL). This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion. 67,321 participants (134,642 eyes) in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days. We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging.

Optical Coherence Tomography in the UK Biobank Study – Rapid Automated Analysis of Retinal Thickness for Large Population-Based Studies

PubMed Central

Grossi, Carlota M.; Foster, Paul J.; Yang, Qi; Reisman, Charles A.; Chan, Kinpui; Peto, Tunde; Thomas, Dhanes; Patel, Praveen J.

2016-01-01

Purpose To describe an approach to the use of optical coherence tomography (OCT) imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness. Methods In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available “spectral domain” OCT device (3D OCT-1000, Topcon). Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL). This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion. Results 67,321 participants (134,642 eyes) in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days. Conclusions We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging. PMID:27716837

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.

Real-time 2D spatially selective MRI experiments: Comparative analysis of optimal control design methods.

PubMed

Maximov, Ivan I; Vinding, Mads S; Tse, Desmond H Y; Nielsen, Niels Chr; Shah, N Jon

2015-05-01

There is an increasing need for development of advanced radio-frequency (RF) pulse techniques in modern magnetic resonance imaging (MRI) systems driven by recent advancements in ultra-high magnetic field systems, new parallel transmit/receive coil designs, and accessible powerful computational facilities. 2D spatially selective RF pulses are an example of advanced pulses that have many applications of clinical relevance, e.g., reduced field of view imaging, and MR spectroscopy. The 2D spatially selective RF pulses are mostly generated and optimised with numerical methods that can handle vast controls and multiple constraints. With this study we aim at demonstrating that numerical, optimal control (OC) algorithms are efficient for the design of 2D spatially selective MRI experiments, when robustness towards e.g. field inhomogeneity is in focus. We have chosen three popular OC algorithms; two which are gradient-based, concurrent methods using first- and second-order derivatives, respectively; and a third that belongs to the sequential, monotonically convergent family. We used two experimental models: a water phantom, and an in vivo human head. Taking into consideration the challenging experimental setup, our analysis suggests the use of the sequential, monotonic approach and the second-order gradient-based approach as computational speed, experimental robustness, and image quality is key. All algorithms used in this work were implemented in the MATLAB environment and are freely available to the MRI community. Copyright © 2015 Elsevier Inc. All rights reserved.

A Review on Segmentation of Positron Emission Tomography Images

PubMed Central

Foster, Brent; Bagci, Ulas; Mansoor, Awais; Xu, Ziyue; Mollura, Daniel J.

2014-01-01

Positron Emission Tomography (PET), a non-invasive functional imaging method at the molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. PET imaging provides detailed quantitative information about many diseases and is often used to evaluate inflammation, infection, and cancer by detecting emitted photons from a radiotracer localized to abnormal cells. In order to differentiate abnormal tissue from surrounding areas in PET images, image segmentation methods play a vital role; therefore, accurate image segmentation is often necessary for proper disease detection, diagnosis, treatment planning, and follow-ups. In this review paper, we present state-of-the-art PET image segmentation methods, as well as the recent advances in image segmentation techniques. In order to make this manuscript self-contained, we also briefly explain the fundamentals of PET imaging, the challenges of diagnostic PET image analysis, and the effects of these challenges on the segmentation results. PMID:24845019

Fixed-Cell Imaging of Schizosaccharomyces pombe.

PubMed

Hagan, Iain M; Bagley, Steven

2016-07-01

The acknowledged genetic malleability of fission yeast has been matched by impressive cytology to drive major advances in our understanding of basic molecular cell biological processes. In many of the more recent studies, traditional approaches of fixation followed by processing to accommodate classical staining procedures have been superseded by live-cell imaging approaches that monitor the distribution of fusion proteins between a molecule of interest and a fluorescent protein. Although such live-cell imaging is uniquely informative for many questions, fixed-cell imaging remains the better option for others and is an important-sometimes critical-complement to the analysis of fluorescent fusion proteins by live-cell imaging. Here, we discuss the merits of fixed- and live-cell imaging as well as specific issues for fluorescence microscopy imaging of fission yeast. © 2016 Cold Spring Harbor Laboratory Press.

The history of MR imaging as seen through the pages of radiology.

PubMed

Edelman, Robert R

2014-11-01

The first reports in Radiology pertaining to magnetic resonance (MR) imaging were published in 1980, 7 years after Paul Lauterbur pioneered the first MR images and 9 years after the first human computed tomographic images were obtained. Historical advances in the research and clinical applications of MR imaging very much parallel the remarkable advances in MR imaging technology. These advances can be roughly classified into hardware (eg, magnets, gradients, radiofrequency [RF] coils, RF transmitter and receiver, MR imaging-compatible biopsy devices) and imaging techniques (eg, pulse sequences, parallel imaging, and so forth). Image quality has been dramatically improved with the introduction of high-field-strength superconducting magnets, digital RF systems, and phased-array coils. Hybrid systems, such as MR/positron emission tomography (PET), combine the superb anatomic and functional imaging capabilities of MR imaging with the unsurpassed capability of PET to demonstrate tissue metabolism. Supported by the improvements in hardware, advances in pulse sequence design and image reconstruction techniques have spurred dramatic improvements in imaging speed and the capability for studying tissue function. In this historical review, the history of MR imaging technology and developing research and clinical applications, as seen through the pages of Radiology, will be considered.

What can imaging tell us about physiology? Lung growth and regional mechanical strain

PubMed Central

Tawhai, Merryn H.

2012-01-01

The interplay of mechanical forces transduces diverse physico-biochemical processes to influence lung morphogenesis, growth, maturation, remodeling and repair. Because tissue stress is difficult to measure in vivo, mechano-sensitive responses are commonly inferred from global changes in lung volume, shape, or compliance and correlated with structural changes in tissue blocks sampled from postmortem-fixed lungs. Recent advances in noninvasive volumetric imaging technology, nonrigid image registration, and deformation analysis provide valuable tools for the quantitative analysis of in vivo regional anatomy and air and tissue-blood distributions and when combined with transpulmonary pressure measurements, allow characterization of regional mechanical function, e.g., displacement, strain, shear, within and among intact lobes, as well as between the lung and the components of its container—rib cage, diaphragm, and mediastinum—thereby yielding new insights into the inter-related metrics of mechanical stress-strain and growth/remodeling. Here, we review the state-of-the-art imaging applications for mapping asymmetric heterogeneous physical interactions within the thorax and how these interactions permit as well as constrain lung growth, remodeling, and compensation during development and following pneumonectomy to illustrate how advanced imaging could facilitate the understanding of physiology and pathophysiology. Functional imaging promises to facilitate the formulation of realistic computational models of lung growth that integrate mechano-sensitive events over multiple spatial and temporal scales to accurately describe in vivo physiology and pathophysiology. Improved computational models in turn could enhance our ability to predict regional as well as global responses to experimental and therapeutic interventions. PMID:22582216

iSBatch: a batch-processing platform for data analysis and exploration of live-cell single-molecule microscopy images and other hierarchical datasets.

PubMed

Caldas, Victor E A; Punter, Christiaan M; Ghodke, Harshad; Robinson, Andrew; van Oijen, Antoine M

2015-10-01

Recent technical advances have made it possible to visualize single molecules inside live cells. Microscopes with single-molecule sensitivity enable the imaging of low-abundance proteins, allowing for a quantitative characterization of molecular properties. Such data sets contain information on a wide spectrum of important molecular properties, with different aspects highlighted in different imaging strategies. The time-lapsed acquisition of images provides information on protein dynamics over long time scales, giving insight into expression dynamics and localization properties. Rapid burst imaging reveals properties of individual molecules in real-time, informing on their diffusion characteristics, binding dynamics and stoichiometries within complexes. This richness of information, however, adds significant complexity to analysis protocols. In general, large datasets of images must be collected and processed in order to produce statistically robust results and identify rare events. More importantly, as live-cell single-molecule measurements remain on the cutting edge of imaging, few protocols for analysis have been established and thus analysis strategies often need to be explored for each individual scenario. Existing analysis packages are geared towards either single-cell imaging data or in vitro single-molecule data and typically operate with highly specific algorithms developed for particular situations. Our tool, iSBatch, instead allows users to exploit the inherent flexibility of the popular open-source package ImageJ, providing a hierarchical framework in which existing plugins or custom macros may be executed over entire datasets or portions thereof. This strategy affords users freedom to explore new analysis protocols within large imaging datasets, while maintaining hierarchical relationships between experiments, samples, fields of view, cells, and individual molecules.

Generalized Majority Logic Criterion to Analyze the Statistical Strength of S-Boxes

NASA Astrophysics Data System (ADS)

Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan

2012-05-01

The majority logic criterion is applicable in the evaluation process of substitution boxes used in the advanced encryption standard (AES). The performance of modified or advanced substitution boxes is predicted by processing the results of statistical analysis by the majority logic criteria. In this paper, we use the majority logic criteria to analyze some popular and prevailing substitution boxes used in encryption processes. In particular, the majority logic criterion is applied to AES, affine power affine (APA), Gray, Lui J, residue prime, S8 AES, Skipjack, and Xyi substitution boxes. The majority logic criterion is further extended into a generalized majority logic criterion which has a broader spectrum of analyzing the effectiveness of substitution boxes in image encryption applications. The integral components of the statistical analyses used for the generalized majority logic criterion are derived from results of entropy analysis, contrast analysis, correlation analysis, homogeneity analysis, energy analysis, and mean of absolute deviation (MAD) analysis.

Solar Data Mining at Georgia State University

NASA Astrophysics Data System (ADS)

Angryk, R.; Martens, P. C.; Schuh, M.; Aydin, B.; Kempton, D.; Banda, J.; Ma, R.; Naduvil-Vadukootu, S.; Akkineni, V.; Küçük, A.; Filali Boubrahimi, S.; Hamdi, S. M.

2016-12-01

In this talk we give an overview of research projects related to solar data analysis that are conducted at Georgia State University. We will provide update on multiple advances made by our research team on the analysis of image parameters, spatio-temporal patterns mining, temporal data analysis and our experiences with big, heterogeneous solar data visualization, analysis, processing and storage. We will talk about up-to-date data mining methodologies, and their importance for big data-driven solar physics research.

Prenatal diagnosis of fetal respiratory function: evaluation of fetal lung maturity using lung-to-liver signal intensity ratio at magnetic resonance imaging.

PubMed

Oka, Yasuko; Rahman, Mosfequr; Sasakura, Chihaya; Waseda, Tomoo; Watanabe, Yukio; Fujii, Ryota; Makinoda, Satoru

2014-12-01

The purpose of this retrospective study is to determine the fetal lung-to-liver signal intensity ratio (LLSIR) on T2-weighted images for the prediction of neonatal respiratory outcome. One hundred ten fetuses who underwent magnetic resonance imaging (MRI) examination for various indications after 22 weeks of gestation participated in this study. LLSIR was measured as the ratio of signal intensities of the fetal lung and liver on T2-weighted images at MRI. We examined the changes of the ratio with advancing gestation and the relations between LLSIR and the presence of the severe respiratory disorder (SRD) after birth. The best cut-off value of the LLSIR to predict respiratory outcome after birth was calculated using receiver operating characteristic (ROC) curve analysis. Lung-to-liver signal intensity ratio correlated significantly with advancing gestational age (R = 0.35, p < 0.001). The non-SRD group had higher LLSIR compared with the SRD group (2.15 ± 0.30 vs. 1.53 ± 0.40, p < 0.001). ROC curve analysis showed that fetuses with an LLSIR < 2.00 were more likely to develop SRD [sensitivity: 100%, 95% confidence interval (CI): 52-100%; specificity: 73%, 95% CI 54-88%]. The fetal LLSIR on T2-weighted images is an accurate marker to diagnose the fetal lung maturity. © 2014 The Authors. Prenatal Diagnosis published by John Wiley & Sons, Ltd.

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology

PubMed Central

Di Ruberto, Cecilia; Kocher, Michel

2018-01-01

Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images. PMID:29419781

Big Data in Reciprocal Space: Sliding Fast Fourier Transforms for Determining Periodicity

DOE PAGES

Vasudevan, Rama K.; Belianinov, Alex; Gianfrancesco, Anthony G.; ...

2015-03-03

Significant advances in atomically resolved imaging of crystals and surfaces have occurred in the last decade allowing unprecedented insight into local crystal structures and periodicity. Yet, the analysis of the long-range periodicity from the local imaging data, critical to correlation of functional properties and chemistry to the local crystallography, remains a challenge. Here, we introduce a Sliding Fast Fourier Transform (FFT) filter to analyze atomically resolved images of in-situ grown La5/8Ca3/8MnO3 films. We demonstrate the ability of sliding FFT algorithm to differentiate two sub-lattices, resulting from a mixed-terminated surface. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) of themore » Sliding FFT dataset reveal the distinct changes in crystallography, step edges and boundaries between the multiple sub-lattices. The method is universal for images with any periodicity, and is especially amenable to atomically resolved probe and electron-microscopy data for rapid identification of the sub-lattices present.« less

Big Data in Reciprocal Space: Sliding Fast Fourier Transforms for Determining Periodicity

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

Vasudevan, Rama K.; Belianinov, Alex; Gianfrancesco, Anthony G.

Significant advances in atomically resolved imaging of crystals and surfaces have occurred in the last decade allowing unprecedented insight into local crystal structures and periodicity. Yet, the analysis of the long-range periodicity from the local imaging data, critical to correlation of functional properties and chemistry to the local crystallography, remains a challenge. Here, we introduce a Sliding Fast Fourier Transform (FFT) filter to analyze atomically resolved images of in-situ grown La5/8Ca3/8MnO3 films. We demonstrate the ability of sliding FFT algorithm to differentiate two sub-lattices, resulting from a mixed-terminated surface. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) of themore » Sliding FFT dataset reveal the distinct changes in crystallography, step edges and boundaries between the multiple sub-lattices. The method is universal for images with any periodicity, and is especially amenable to atomically resolved probe and electron-microscopy data for rapid identification of the sub-lattices present.« less

Recent Advances of Malaria Parasites Detection Systems Based on Mathematical Morphology.

PubMed

Loddo, Andrea; Di Ruberto, Cecilia; Kocher, Michel

2018-02-08

Malaria is an epidemic health disease and a rapid, accurate diagnosis is necessary for proper intervention. Generally, pathologists visually examine blood stained slides for malaria diagnosis. Nevertheless, this kind of visual inspection is subjective, error-prone and time-consuming. In order to overcome the issues, numerous methods of automatic malaria diagnosis have been proposed so far. In particular, many researchers have used mathematical morphology as a powerful tool for computer aided malaria detection and classification. Mathematical morphology is not only a theory for the analysis of spatial structures, but also a very powerful technique widely used for image processing purposes and employed successfully in biomedical image analysis, especially in preprocessing and segmentation tasks. Microscopic image analysis and particularly malaria detection and classification can greatly benefit from the use of morphological operators. The aim of this paper is to present a review of recent mathematical morphology based methods for malaria parasite detection and identification in stained blood smears images.

Imaging Transcriptional Regulation of Eukaryotic mRNA Genes: Advances and Outlook.

PubMed

Yao, Jie

2017-01-06

Regulation of eukaryotic transcription in vivo occurs at distinct stages. Previous research has identified many active or repressive transcription factors (TFs) and core transcription components and studied their functions in vitro and in vivo. Nonetheless, how individual TFs act in concert to regulate mRNA gene expression in a single cell remains poorly understood. Direct observation of TF assembly and disassembly and various biochemical reactions during transcription of a single-copy gene in vivo is the ideal approach to study this problem. Research in this area requires developing novel techniques for single-cell transcription imaging and integrating imaging studies into understanding the molecular biology of transcription. In the past decade, advanced cell imaging has enabled unprecedented capabilities to visualize individual TF molecules, to track single transcription sites, and to detect individual mRNA in fixed and living cells. These studies have raised several novel insights on transcriptional regulation such as the "hit-and-run" model and transcription bursting that could not be obtained by in vitro biochemistry analysis. At this point, the key question is how to achieve deeper understandings or discover novel mechanisms of eukaryotic transcriptional regulation by imaging transcription in single cells. Meanwhile, further technical advancements are likely required for visualizing distinct kinetic steps of transcription on a single-copy gene in vivo. This review article summarizes recent progress in the field and describes the challenges and opportunities ahead. Copyright © 2016 Elsevier Ltd. All rights reserved.

Cutting-edge analysis of extracellular microparticles using ImageStream(X) imaging flow cytometry.

PubMed

Headland, Sarah E; Jones, Hefin R; D'Sa, Adelina S V; Perretti, Mauro; Norling, Lucy V

2014-06-10

Interest in extracellular vesicle biology has exploded in the past decade, since these microstructures seem endowed with multiple roles, from blood coagulation to inter-cellular communication in pathophysiology. In order for microparticle research to evolve as a preclinical and clinical tool, accurate quantification of microparticle levels is a fundamental requirement, but their size and the complexity of sample fluids present major technical challenges. Flow cytometry is commonly used, but suffers from low sensitivity and accuracy. Use of Amnis ImageStream(X) Mk II imaging flow cytometer afforded accurate analysis of calibration beads ranging from 1 μm to 20 nm; and microparticles, which could be observed and quantified in whole blood, platelet-rich and platelet-free plasma and in leukocyte supernatants. Another advantage was the minimal sample preparation and volume required. Use of this high throughput analyzer allowed simultaneous phenotypic definition of the parent cells and offspring microparticles along with real time microparticle generation kinetics. With the current paucity of reliable techniques for the analysis of microparticles, we propose that the ImageStream(X) could be used effectively to advance this scientific field.

Statistical image quantification toward optimal scan fusion and change quantification

NASA Astrophysics Data System (ADS)

Potesil, Vaclav; Zhou, Xiang Sean

2007-03-01

Recent advance of imaging technology has brought new challenges and opportunities for automatic and quantitative analysis of medical images. With broader accessibility of more imaging modalities for more patients, fusion of modalities/scans from one time point and longitudinal analysis of changes across time points have become the two most critical differentiators to support more informed, more reliable and more reproducible diagnosis and therapy decisions. Unfortunately, scan fusion and longitudinal analysis are both inherently plagued with increased levels of statistical errors. A lack of comprehensive analysis by imaging scientists and a lack of full awareness by physicians pose potential risks in clinical practice. In this paper, we discuss several key error factors affecting imaging quantification, studying their interactions, and introducing a simulation strategy to establish general error bounds for change quantification across time. We quantitatively show that image resolution, voxel anisotropy, lesion size, eccentricity, and orientation are all contributing factors to quantification error; and there is an intricate relationship between voxel anisotropy and lesion shape in affecting quantification error. Specifically, when two or more scans are to be fused at feature level, optimal linear fusion analysis reveals that scans with voxel anisotropy aligned with lesion elongation should receive a higher weight than other scans. As a result of such optimal linear fusion, we will achieve a lower variance than naïve averaging. Simulated experiments are used to validate theoretical predictions. Future work based on the proposed simulation methods may lead to general guidelines and error lower bounds for quantitative image analysis and change detection.

Abnormal Image Detection in Endoscopy Videos Using a Filter Bank and Local Binary Patterns

PubMed Central

Nawarathna, Ruwan; Oh, JungHwan; Muthukudage, Jayantha; Tavanapong, Wallapak; Wong, Johnny; de Groen, Piet C.; Tang, Shou Jiang

2014-01-01

Finding mucosal abnormalities (e.g., erythema, blood, ulcer, erosion, and polyp) is one of the most essential tasks during endoscopy video review. Since these abnormalities typically appear in a small number of frames (around 5% of the total frame number), automated detection of frames with an abnormality can save physician’s time significantly. In this paper, we propose a new multi-texture analysis method that effectively discerns images showing mucosal abnormalities from the ones without any abnormality since most abnormalities in endoscopy images have textures that are clearly distinguishable from normal textures using an advanced image texture analysis method. The method uses a “texton histogram” of an image block as features. The histogram captures the distribution of different “textons” representing various textures in an endoscopy image. The textons are representative response vectors of an application of a combination of Leung and Malik (LM) filter bank (i.e., a set of image filters) and a set of Local Binary Patterns on the image. Our experimental results indicate that the proposed method achieves 92% recall and 91.8% specificity on wireless capsule endoscopy (WCE) images and 91% recall and 90.8% specificity on colonoscopy images. PMID:25132723

7 CFR 1208.24 - Research.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 10 2014-01-01 2014-01-01 false Research. 1208.24 Section 1208.24 Agriculture..., RESEARCH, AND INFORMATION ORDER Processed Raspberry Promotion, Research, and Information Order Definitions § 1208.24 Research. Research means any type of test, study, or analysis designed to advance the image...

7 CFR 1208.24 - Research.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 10 2013-01-01 2013-01-01 false Research. 1208.24 Section 1208.24 Agriculture..., RESEARCH, AND INFORMATION ORDER Processed Raspberry Promotion, Research, and Information Order Definitions § 1208.24 Research. Research means any type of test, study, or analysis designed to advance the image...

Neuroanatomical Correlates of Intelligence

ERIC Educational Resources Information Center

Luders, Eileen; Narr, Katherine L.; Thompson, Paul M.; Toga, Arthur W.

2009-01-01

With the advancement of image acquisition and analysis methods in recent decades, unique opportunities have emerged to study the neuroanatomical correlates of intelligence. Traditional approaches examining global measures have been complemented by insights from more regional analyses based on pre-defined areas. Newer state-of-the-art approaches…

Resolving Fast, Confined Diffusion in Bacteria with Image Correlation Spectroscopy.

PubMed

Rowland, David J; Tuson, Hannah H; Biteen, Julie S

2016-05-24

By following single fluorescent molecules in a microscope, single-particle tracking (SPT) can measure diffusion and binding on the nanometer and millisecond scales. Still, although SPT can at its limits characterize the fastest biomolecules as they interact with subcellular environments, this measurement may require advanced illumination techniques such as stroboscopic illumination. Here, we address the challenge of measuring fast subcellular motion by instead analyzing single-molecule data with spatiotemporal image correlation spectroscopy (STICS) with a focus on measurements of confined motion. Our SPT and STICS analysis of simulations of the fast diffusion of confined molecules shows that image blur affects both STICS and SPT, and we find biased diffusion rate measurements for STICS analysis in the limits of fast diffusion and tight confinement due to fitting STICS correlation functions to a Gaussian approximation. However, we determine that with STICS, it is possible to correctly interpret the motion that blurs single-molecule images without advanced illumination techniques or fast cameras. In particular, we present a method to overcome the bias due to image blur by properly estimating the width of the correlation function by directly calculating the correlation function variance instead of using the typical Gaussian fitting procedure. Our simulation results are validated by applying the STICS method to experimental measurements of fast, confined motion: we measure the diffusion of cytosolic mMaple3 in living Escherichia coli cells at 25 frames/s under continuous illumination to illustrate the utility of STICS in an experimental parameter regime for which in-frame motion prevents SPT and tight confinement of fast diffusion precludes stroboscopic illumination. Overall, our application of STICS to freely diffusing cytosolic protein in small cells extends the utility of single-molecule experiments to the regime of fast confined diffusion without requiring advanced microscopy techniques. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Robust Bayesian Fluorescence Lifetime Estimation, Decay Model Selection and Instrument Response Determination for Low-Intensity FLIM Imaging

PubMed Central

Rowley, Mark I.; Coolen, Anthonius C. C.; Vojnovic, Borivoj; Barber, Paul R.

2016-01-01

We present novel Bayesian methods for the analysis of exponential decay data that exploit the evidence carried by every detected decay event and enables robust extension to advanced processing. Our algorithms are presented in the context of fluorescence lifetime imaging microscopy (FLIM) and particular attention has been paid to model the time-domain system (based on time-correlated single photon counting) with unprecedented accuracy. We present estimates of decay parameters for mono- and bi-exponential systems, offering up to a factor of two improvement in accuracy compared to previous popular techniques. Results of the analysis of synthetic and experimental data are presented, and areas where the superior precision of our techniques can be exploited in Förster Resonance Energy Transfer (FRET) experiments are described. Furthermore, we demonstrate two advanced processing methods: decay model selection to choose between differing models such as mono- and bi-exponential, and the simultaneous estimation of instrument and decay parameters. PMID:27355322

A Novel Murine Model for Localized Radiation Necrosis and its Characterization Using Advanced Magnetic Resonance Imaging

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

Jost, Sarah C.; Hope, Andrew; Kiehl, Erich

Purpose: To develop a murine model of radiation necrosis using fractionated, subtotal cranial irradiation; and to investigate the imaging signature of radiation-induced tissue damage using advanced magnetic resonance imaging techniques. Methods and Materials: Twenty-four mice each received 60 Gy of hemispheric (left) irradiation in 10 equal fractions. Magnetic resonance images at 4.7 T were subsequently collected using T1-, T2-, and diffusion sequences at selected time points after irradiation. After imaging, animals were killed and their brains fixed for correlative histologic analysis. Results: Contrast-enhanced T1- and T2-weighted magnetic resonance images at months 2, 3, and 4 showed changes consistent with progressivemore » radiation necrosis. Quantitatively, mean diffusivity was significantly higher (mean = 0.86, 1.13, and 1.24 {mu}m{sup 2}/ms at 2, 3, and 4 months, respectively) in radiated brain, compared with contralateral untreated brain tissue (mean = 0.78, 0.82, and 0.83 {mu}m{sup 2}/ms) (p < 0.0001). Histology reflected changes typically seen in radiation necrosis. Conclusions: This murine model of radiation necrosis will facilitate investigation of imaging biomarkers that distinguish between radiation necrosis and tumor recurrence. In addition, this preclinical study supports clinical data suggesting that diffusion-weighted imaging may be helpful in answering this diagnostic question in clinical settings.« less

Advanced imaging techniques for the study of plant growth and development.

PubMed

Sozzani, Rosangela; Busch, Wolfgang; Spalding, Edgar P; Benfey, Philip N

2014-05-01

A variety of imaging methodologies are being used to collect data for quantitative studies of plant growth and development from living plants. Multi-level data, from macroscopic to molecular, and from weeks to seconds, can be acquired. Furthermore, advances in parallelized and automated image acquisition enable the throughput to capture images from large populations of plants under specific growth conditions. Image-processing capabilities allow for 3D or 4D reconstruction of image data and automated quantification of biological features. These advances facilitate the integration of imaging data with genome-wide molecular data to enable systems-level modeling. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ultra-wide-field imaging in diabetic retinopathy.

PubMed

Ghasemi Falavarjani, Khalil; Tsui, Irena; Sadda, Srinivas R

2017-10-01

Since 1991, 7-field images captured with 30-50 degree cameras in the Early Treatment Diabetic Retinopathy Study were the gold standard for fundus imaging to study diabetic retinopathy. Ultra-wide-field images cover significantly more area (up to 82%) of the fundus and with ocular steering can in many cases image 100% of the fundus ("panretinal"). Recent advances in image analysis of ultra-wide-field imaging allow for precise measurements of the peripheral retinal lesions. There is a growing consensus in the literature that ultra-wide-field imaging improves detection of peripheral lesions in diabetic retinopathy and leads to more accurate classification of the disease. There is discordance among studies, however, on the correlation between peripheral diabetic lesions and diabetic macular edema and optimal management strategies to treat diabetic retinopathy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Review of advanced imaging techniques

PubMed Central

Chen, Yu; Liang, Chia-Pin; Liu, Yang; Fischer, Andrew H.; Parwani, Anil V.; Pantanowitz, Liron

2012-01-01

Pathology informatics encompasses digital imaging and related applications. Several specialized microscopy techniques have emerged which permit the acquisition of digital images (“optical biopsies”) at high resolution. Coupled with fiber-optic and micro-optic components, some of these imaging techniques (e.g., optical coherence tomography) are now integrated with a wide range of imaging devices such as endoscopes, laparoscopes, catheters, and needles that enable imaging inside the body. These advanced imaging modalities have exciting diagnostic potential and introduce new opportunities in pathology. Therefore, it is important that pathology informaticists understand these advanced imaging techniques and the impact they have on pathology. This paper reviews several recently developed microscopic techniques, including diffraction-limited methods (e.g., confocal microscopy, 2-photon microscopy, 4Pi microscopy, and spatially modulated illumination microscopy) and subdiffraction techniques (e.g., photoactivated localization microscopy, stochastic optical reconstruction microscopy, and stimulated emission depletion microscopy). This article serves as a primer for pathology informaticists, highlighting the fundamentals and applications of advanced optical imaging techniques. PMID:22754737

Imaging in the evaluation and follow-up of early and advanced breast cancer: When, why, and how often?

PubMed

Bychkovsky, Brittany L; Lin, Nancy U

2017-02-01

Imaging in the evaluation and follow-up of patients with early or advanced breast cancer is an important aspect of cancer care. The role of imaging in breast cancer depends on the goal and should only be performed to guide clinical decisions. Imaging is valuable if a finding will change the course of treatment and improve outcomes, whether this is disease-free survival, overall survival or quality-of-life. In the last decade, imaging is often overused in oncology and contributes to rising healthcare costs. In this context, we review the data that supports the appropriate use of imaging for breast cancer patients. We will discuss: 1) the optimal use of staging imaging in both early (Stage 0-II) and locally advanced (Stage III) breast cancer, 2) the role of surveillance imaging to detect recurrent disease in Stage 0-III breast cancer and 3) how patients with metastatic breast cancer should be followed with advanced imaging. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gold nanoparticle contrast agents in advanced X-ray imaging technologies.

PubMed

Ahn, Sungsook; Jung, Sung Yong; Lee, Sang Joon

2013-05-17

Recently, there has been significant progress in the field of soft- and hard-X-ray imaging for a wide range of applications, both technically and scientifically, via developments in sources, optics and imaging methodologies. While one community is pursuing extensive applications of available X-ray tools, others are investigating improvements in techniques, including new optics, higher spatial resolutions and brighter compact sources. For increased image quality and more exquisite investigation on characteristic biological phenomena, contrast agents have been employed extensively in imaging technologies. Heavy metal nanoparticles are excellent absorbers of X-rays and can offer excellent improvements in medical diagnosis and X-ray imaging. In this context, the role of gold (Au) is important for advanced X-ray imaging applications. Au has a long-history in a wide range of medical applications and exhibits characteristic interactions with X-rays. Therefore, Au can offer a particular advantage as a tracer and a contrast enhancer in X-ray imaging technologies by sensing the variation in X-ray attenuation in a given sample volume. This review summarizes basic understanding on X-ray imaging from device set-up to technologies. Then this review covers recent studies in the development of X-ray imaging techniques utilizing gold nanoparticles (AuNPs) and their relevant applications, including two- and three-dimensional biological imaging, dynamical processes in a living system, single cell-based imaging and quantitative analysis of circulatory systems and so on. In addition to conventional medical applications, various novel research areas have been developed and are expected to be further developed through AuNP-based X-ray imaging technologies.

Comparative study of different approaches for multivariate image analysis in HPTLC fingerprinting of natural products such as plant resin.

PubMed

Ristivojević, Petar; Trifković, Jelena; Vovk, Irena; Milojković-Opsenica, Dušanka

2017-01-01

Considering the introduction of phytochemical fingerprint analysis, as a method of screening the complex natural products for the presence of most bioactive compounds, use of chemometric classification methods, application of powerful scanning and image capturing and processing devices and algorithms, advancement in development of novel stationary phases as well as various separation modalities, high-performance thin-layer chromatography (HPTLC) fingerprinting is becoming attractive and fruitful field of separation science. Multivariate image analysis is crucial in the light of proper data acquisition. In a current study, different image processing procedures were studied and compared in detail on the example of HPTLC chromatograms of plant resins. In that sense, obtained variables such as gray intensities of pixels along the solvent front, peak area and mean values of peak were used as input data and compared to obtained best classification models. Important steps in image analysis, baseline removal, denoising, target peak alignment and normalization were pointed out. Numerical data set based on mean value of selected bands and intensities of pixels along the solvent front proved to be the most convenient for planar-chromatographic profiling, although required at least the basic knowledge on image processing methodology, and could be proposed for further investigation in HPLTC fingerprinting. Copyright © 2016 Elsevier B.V. All rights reserved.

Color image analysis technique for measuring of fat in meat: an application for the meat industry

NASA Astrophysics Data System (ADS)

Ballerini, Lucia; Hogberg, Anders; Lundstrom, Kerstin; Borgefors, Gunilla

2001-04-01

Intramuscular fat content in meat influences some important meat quality characteristics. The aim of the present study was to develop and apply image processing techniques to quantify intramuscular fat content in beefs together with the visual appearance of fat in meat (marbling). Color images of M. longissimus dorsi meat samples with a variability of intramuscular fat content and marbling were captured. Image analysis software was specially developed for the interpretation of these images. In particular, a segmentation algorithm (i.e. classification of different substances: fat, muscle and connective tissue) was optimized in order to obtain a proper classification and perform subsequent analysis. Segmentation of muscle from fat was achieved based on their characteristics in the 3D color space, and on the intrinsic fuzzy nature of these structures. The method is fully automatic and it combines a fuzzy clustering algorithm, the Fuzzy c-Means Algorithm, with a Genetic Algorithm. The percentages of various colors (i.e. substances) within the sample are then determined; the number, size distribution, and spatial distributions of the extracted fat flecks are measured. Measurements are correlated with chemical and sensory properties. Results so far show that advanced image analysis is useful for quantify the visual appearance of meat.

Simultaneous automatic scoring and co-registration of hormone receptors in tumor areas in whole slide images of breast cancer tissue slides.

PubMed

Trahearn, Nicholas; Tsang, Yee Wah; Cree, Ian A; Snead, David; Epstein, David; Rajpoot, Nasir

2017-06-01

Automation of downstream analysis may offer many potential benefits to routine histopathology. One area of interest for automation is in the scoring of multiple immunohistochemical markers to predict the patient's response to targeted therapies. Automated serial slide analysis of this kind requires robust registration to identify common tissue regions across sections. We present an automated method for co-localized scoring of Estrogen Receptor and Progesterone Receptor (ER/PR) in breast cancer core biopsies using whole slide images. Regions of tumor in a series of fifty consecutive breast core biopsies were identified by annotation on H&E whole slide images. Sequentially cut immunohistochemical stained sections were scored manually, before being digitally scanned and then exported into JPEG 2000 format. A two-stage registration process was performed to identify the annotated regions of interest in the immunohistochemistry sections, which were then scored using the Allred system. Overall correlation between manual and automated scoring for ER and PR was 0.944 and 0.883, respectively, with 90% of ER and 80% of PR scores within in one point or less of agreement. This proof of principle study indicates slide registration can be used as a basis for automation of the downstream analysis for clinically relevant biomarkers in the majority of cases. The approach is likely to be improved by implantation of safeguarding analysis steps post registration. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

An integrative approach for analyzing hundreds of neurons in task performing mice using wide-field calcium imaging.

PubMed

Mohammed, Ali I; Gritton, Howard J; Tseng, Hua-an; Bucklin, Mark E; Yao, Zhaojie; Han, Xue

2016-02-08

Advances in neurotechnology have been integral to the investigation of neural circuit function in systems neuroscience. Recent improvements in high performance fluorescent sensors and scientific CMOS cameras enables optical imaging of neural networks at a much larger scale. While exciting technical advances demonstrate the potential of this technique, further improvement in data acquisition and analysis, especially those that allow effective processing of increasingly larger datasets, would greatly promote the application of optical imaging in systems neuroscience. Here we demonstrate the ability of wide-field imaging to capture the concurrent dynamic activity from hundreds to thousands of neurons over millimeters of brain tissue in behaving mice. This system allows the visualization of morphological details at a higher spatial resolution than has been previously achieved using similar functional imaging modalities. To analyze the expansive data sets, we developed software to facilitate rapid downstream data processing. Using this system, we show that a large fraction of anatomically distinct hippocampal neurons respond to discrete environmental stimuli associated with classical conditioning, and that the observed temporal dynamics of transient calcium signals are sufficient for exploring certain spatiotemporal features of large neural networks.

Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research.

PubMed

Milchenko, Mikhail; Snyder, Abraham Z; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L; Fouke, Sarah Jost; Marcus, Daniel S

2016-07-01

Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis. Given this heterogeneity, conventional processing workflows developed for research purposes are not optimal for clinical data. In this work, we describe an approach called Heterogeneous Optimization Framework (HOF) for developing image analysis pipelines that can handle the high degree of clinical data non-uniformity. HOF provides a set of guidelines for configuration, algorithm development, deployment, interpretation of results and quality control for such pipelines. At each step, we illustrate the HOF approach using the implementation of an automated pipeline for Multimodal Glioma Analysis (MGA) as an example. The MGA pipeline computes tissue diffusion characteristics of diffusion tensor imaging (DTI) acquisitions, hemodynamic characteristics using a perfusion model of susceptibility contrast (DSC) MRI, and spatial cross-modal co-registration of available anatomical, physiological and derived patient images. Developing MGA within HOF enabled the processing of neuro-oncology MR imaging studies to be fully automated. MGA has been successfully used to analyze over 160 clinical tumor studies to date within several research projects. Introduction of the MGA pipeline improved image processing throughput and, most importantly, effectively produced co-registered datasets that were suitable for advanced analysis despite high heterogeneity in acquisition protocols.

SSC Geopositional Assessment of the Advanced Wide Field Sensor

NASA Technical Reports Server (NTRS)

Ross, Kenton

2006-01-01

The geopositional accuracy of the standard geocorrected product from the Advanced Wide Field Sensor (AWiFS) was evaluated using digital orthophoto quarter quadrangles and other reference sources of similar accuracy. Images were analyzed from summer 2004 through spring 2005. Forty to fifty check points were collected manually per scene and analyzed to determine overall circular error, estimates of horizontal bias, and other systematic errors. Measured errors were somewhat higher than the specifications for the data, but they were consistent with the analysis of the distributing vendor.

Common hyperspectral image database design

NASA Astrophysics Data System (ADS)

Tian, Lixun; Liao, Ningfang; Chai, Ali

2009-11-01

This paper is to introduce Common hyperspectral image database with a demand-oriented Database design method (CHIDB), which comprehensively set ground-based spectra, standardized hyperspectral cube, spectral analysis together to meet some applications. The paper presents an integrated approach to retrieving spectral and spatial patterns from remotely sensed imagery using state-of-the-art data mining and advanced database technologies, some data mining ideas and functions were associated into CHIDB to make it more suitable to serve in agriculture, geological and environmental areas. A broad range of data from multiple regions of the electromagnetic spectrum is supported, including ultraviolet, visible, near-infrared, thermal infrared, and fluorescence. CHIDB is based on dotnet framework and designed by MVC architecture including five main functional modules: Data importer/exporter, Image/spectrum Viewer, Data Processor, Parameter Extractor, and On-line Analyzer. The original data were all stored in SQL server2008 for efficient search, query and update, and some advance Spectral image data Processing technology are used such as Parallel processing in C#; Finally an application case is presented in agricultural disease detecting area.

Imaging in Central Nervous System Drug Discovery.

PubMed

Gunn, Roger N; Rabiner, Eugenii A

2017-01-01

The discovery and development of central nervous system (CNS) drugs is an extremely challenging process requiring large resources, timelines, and associated costs. The high risk of failure leads to high levels of risk. Over the past couple of decades PET imaging has become a central component of the CNS drug-development process, enabling decision-making in phase I studies, where early discharge of risk provides increased confidence to progress a candidate to more costly later phase testing at the right dose level or alternatively to kill a compound through failure to meet key criteria. The so called "3 pillars" of drug survival, namely; tissue exposure, target engagement, and pharmacologic activity, are particularly well suited for evaluation by PET imaging. This review introduces the process of CNS drug development before considering how PET imaging of the "3 pillars" has advanced to provide valuable tools for decision-making on the critical path of CNS drug development. Finally, we review the advances in PET science of biomarker development and analysis that enable sophisticated drug-development studies in man. Copyright © 2017 Elsevier Inc. All rights reserved.

[Big data in imaging].

PubMed

Sewerin, Philipp; Ostendorf, Benedikt; Hueber, Axel J; Kleyer, Arnd

2018-04-01

Until now, most major medical advancements have been achieved through hypothesis-driven research within the scope of clinical trials. However, due to a multitude of variables, only a certain number of research questions could be addressed during a single study, thus rendering these studies expensive and time consuming. Big data acquisition enables a new data-based approach in which large volumes of data can be used to investigate all variables, thus opening new horizons. Due to universal digitalization of the data as well as ever-improving hard- and software solutions, imaging would appear to be predestined for such analyses. Several small studies have already demonstrated that automated analysis algorithms and artificial intelligence can identify pathologies with high precision. Such automated systems would also seem well suited for rheumatology imaging, since a method for individualized risk stratification has long been sought for these patients. However, despite all the promising options, the heterogeneity of the data and highly complex regulations covering data protection in Germany would still render a big data solution for imaging difficult today. Overcoming these boundaries is challenging, but the enormous potential advances in clinical management and science render pursuit of this goal worthwhile.

Chapter 17: Bioimage Informatics for Systems Pharmacology

PubMed Central

Li, Fuhai; Yin, Zheng; Jin, Guangxu; Zhao, Hong; Wong, Stephen T. C.

2013-01-01

Recent advances in automated high-resolution fluorescence microscopy and robotic handling have made the systematic and cost effective study of diverse morphological changes within a large population of cells possible under a variety of perturbations, e.g., drugs, compounds, metal catalysts, RNA interference (RNAi). Cell population-based studies deviate from conventional microscopy studies on a few cells, and could provide stronger statistical power for drawing experimental observations and conclusions. However, it is challenging to manually extract and quantify phenotypic changes from the large amounts of complex image data generated. Thus, bioimage informatics approaches are needed to rapidly and objectively quantify and analyze the image data. This paper provides an overview of the bioimage informatics challenges and approaches in image-based studies for drug and target discovery. The concepts and capabilities of image-based screening are first illustrated by a few practical examples investigating different kinds of phenotypic changes caEditorsused by drugs, compounds, or RNAi. The bioimage analysis approaches, including object detection, segmentation, and tracking, are then described. Subsequently, the quantitative features, phenotype identification, and multidimensional profile analysis for profiling the effects of drugs and targets are summarized. Moreover, a number of publicly available software packages for bioimage informatics are listed for further reference. It is expected that this review will help readers, including those without bioimage informatics expertise, understand the capabilities, approaches, and tools of bioimage informatics and apply them to advance their own studies. PMID:23633943

KENNEDY SPACE CENTER, FLA. - Armando Oliu, Final Inspection Team lead for the Shuttle program, speaks to reporters about the aid the Image Analysis Lab is giving the FBI in a kidnapping case. Behind him at right is Mike Rein, External Affairs division chief. Oliu oversees the image lab that is using an advanced SGI® TP9500 data management system to review the tape of the kidnapping in progress in Sarasota, Fla. KSC installed the new $3.2 million system in preparation for Return to Flight of the Space Shuttle fleet. The lab is studying the Sarasota kidnapping video to provide any new information possible to law enforcement officers. KSC is joining NASA’s Marshall Space Flight Center in Alabama in reviewing the tape.

NASA Image and Video Library

2004-02-04

KENNEDY SPACE CENTER, FLA. - Armando Oliu, Final Inspection Team lead for the Shuttle program, speaks to reporters about the aid the Image Analysis Lab is giving the FBI in a kidnapping case. Behind him at right is Mike Rein, External Affairs division chief. Oliu oversees the image lab that is using an advanced SGI® TP9500 data management system to review the tape of the kidnapping in progress in Sarasota, Fla. KSC installed the new $3.2 million system in preparation for Return to Flight of the Space Shuttle fleet. The lab is studying the Sarasota kidnapping video to provide any new information possible to law enforcement officers. KSC is joining NASA’s Marshall Space Flight Center in Alabama in reviewing the tape.

Structure and properties of clinical coralline implants measured via 3D imaging and analysis.

PubMed

Knackstedt, Mark Alexander; Arns, Christoph H; Senden, Tim J; Gross, Karlis

2006-05-01

The development and design of advanced porous materials for biomedical applications requires a thorough understanding of how material structure impacts on mechanical and transport properties. This paper illustrates a 3D imaging and analysis study of two clinically proven coral bone graft samples (Porites and Goniopora). Images are obtained from X-ray micro-computed tomography (micro-CT) at a resolution of 16.8 microm. A visual comparison of the two images shows very different structure; Porites has a homogeneous structure and consistent pore size while Goniopora has a bimodal pore size and a strongly disordered structure. A number of 3D structural characteristics are measured directly on the images including pore volume-to-surface-area, pore and solid size distributions, chord length measurements and tortuosity. Computational results made directly on the digitized tomographic images are presented for the permeability, diffusivity and elastic modulus of the coral samples. The results allow one to quantify differences between the two samples. 3D digital analysis can provide a more thorough assessment of biomaterial structure including the pore wall thickness, local flow, mechanical properties and diffusion pathways. We discuss the implications of these results to the development of optimal scaffold design for tissue ingrowth.

Automatic detection of cone photoreceptors in split detector adaptive optics scanning light ophthalmoscope images.

PubMed

Cunefare, David; Cooper, Robert F; Higgins, Brian; Katz, David F; Dubra, Alfredo; Carroll, Joseph; Farsiu, Sina

2016-05-01

Quantitative analysis of the cone photoreceptor mosaic in the living retina is potentially useful for early diagnosis and prognosis of many ocular diseases. Non-confocal split detector based adaptive optics scanning light ophthalmoscope (AOSLO) imaging reveals the cone photoreceptor inner segment mosaics often not visualized on confocal AOSLO imaging. Despite recent advances in automated cone segmentation algorithms for confocal AOSLO imagery, quantitative analysis of split detector AOSLO images is currently a time-consuming manual process. In this paper, we present the fully automatic adaptive filtering and local detection (AFLD) method for detecting cones in split detector AOSLO images. We validated our algorithm on 80 images from 10 subjects, showing an overall mean Dice's coefficient of 0.95 (standard deviation 0.03), when comparing our AFLD algorithm to an expert grader. This is comparable to the inter-observer Dice's coefficient of 0.94 (standard deviation 0.04). To the best of our knowledge, this is the first validated, fully-automated segmentation method which has been applied to split detector AOSLO images.

Digital Transplantation Pathology: Combining Whole Slide Imaging, Multiplex Staining, and Automated Image Analysis

PubMed Central

Isse, Kumiko; Lesniak, Andrew; Grama, Kedar; Roysam, Badrinath; Minervini, Martha I.; Demetris, Anthony J

2013-01-01

Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. “-Omics” analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: a) spatial-temporal relationships; b) rare events/cells; c) complex structural context; and d) integration into a “systems” model. Nevertheless, except for immunostaining, no transformative advancements have “modernized” routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology - global “–omic” analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes. PMID:22053785

Technical advance: live-imaging analysis of human dendritic cell migrating behavior under the influence of immune-stimulating reagents in an organotypic model of lung.

PubMed

Nguyen Hoang, Anh Thu; Chen, Puran; Björnfot, Sofia; Högstrand, Kari; Lock, John G; Grandien, Alf; Coles, Mark; Svensson, Mattias

2014-09-01

This manuscript describes technical advances allowing manipulation and quantitative analyses of human DC migratory behavior in lung epithelial tissue. DCs are hematopoietic cells essential for the maintenance of tissue homeostasis and the induction of tissue-specific immune responses. Important functions include cytokine production and migration in response to infection for the induction of proper immune responses. To design appropriate strategies to exploit human DC functional properties in lung tissue for the purpose of clinical evaluation, e.g., candidate vaccination and immunotherapy strategies, we have developed a live-imaging assay based on our previously described organotypic model of the human lung. This assay allows provocations and subsequent quantitative investigations of DC functional properties under conditions mimicking morphological and functional features of the in vivo parental tissue. We present protocols to set up and prepare tissue models for 4D (x, y, z, time) fluorescence-imaging analysis that allow spatial and temporal studies of human DCs in live epithelial tissue, followed by flow cytometry analysis of DCs retrieved from digested tissue models. This model system can be useful for elucidating incompletely defined pathways controlling DC functional responses to infection and inflammation in lung epithelial tissue, as well as the efficacy of locally administered candidate interventions. © 2014 Society for Leukocyte Biology.

Advanced forensic validation for human spermatozoa identification using SPERM HY-LITER™ Express with quantitative image analysis.

PubMed

Takamura, Ayari; Watanabe, Ken; Akutsu, Tomoko

2017-07-01

Identification of human semen is indispensable for the investigation of sexual assaults. Fluorescence staining methods using commercial kits, such as the series of SPERM HY-LITER™ kits, have been useful to detect human sperm via strong fluorescence. These kits have been examined from various forensic aspects. However, because of a lack of evaluation methods, these studies did not provide objective, or quantitative, descriptions of the results nor clear criteria for the decisions reached. In addition, the variety of validations was considerably limited. In this study, we conducted more advanced validations of SPERM HY-LITER™ Express using our established image analysis method. Use of this method enabled objective and specific identification of fluorescent sperm's spots and quantitative comparisons of the sperm detection performance under complex experimental conditions. For body fluid mixtures, we examined interference with the fluorescence staining from other body fluid components. Effects of sample decomposition were simulated in high humidity and high temperature conditions. Semen with quite low sperm concentrations, such as azoospermia and oligospermia samples, represented the most challenging cases in application of the kit. Finally, the tolerance of the kit against various acidic and basic environments was analyzed. The validations herein provide useful information for the practical applications of the SPERM HY-LITER™ Express kit, which were previously unobtainable. Moreover, the versatility of our image analysis method toward various complex cases was demonstrated.

Multispectral Photography

NASA Technical Reports Server (NTRS)

1982-01-01

Model II Multispectral Camera is an advanced aerial camera that provides optimum enhancement of a scene by recording spectral signatures of ground objects only in narrow, preselected bands of the electromagnetic spectrum. Its photos have applications in such areas as agriculture, forestry, water pollution investigations, soil analysis, geologic exploration, water depth studies and camouflage detection. The target scene is simultaneously photographed in four separate spectral bands. Using a multispectral viewer, such as their Model 75 Spectral Data creates a color image from the black and white positives taken by the camera. With this optical image analysis unit, all four bands are superimposed in accurate registration and illuminated with combinations of blue green, red, and white light. Best color combination for displaying the target object is selected and printed. Spectral Data Corporation produces several types of remote sensing equipment and also provides aerial survey, image processing and analysis and number of other remote sensing services.

Cell motion predicts human epidermal stemness

PubMed Central

Toki, Fujio; Tate, Sota; Imai, Matome; Matsushita, Natsuki; Shiraishi, Ken; Sayama, Koji; Toki, Hiroshi; Higashiyama, Shigeki

2015-01-01

Image-based identification of cultured stem cells and noninvasive evaluation of their proliferative capacity advance cell therapy and stem cell research. Here we demonstrate that human keratinocyte stem cells can be identified in situ by analyzing cell motion during their cultivation. Modeling experiments suggested that the clonal type of cultured human clonogenic keratinocytes can be efficiently determined by analysis of early cell movement. Image analysis experiments demonstrated that keratinocyte stem cells indeed display a unique rotational movement that can be identified as early as the two-cell stage colony. We also demonstrate that α6 integrin is required for both rotational and collective cell motion. Our experiments provide, for the first time, strong evidence that cell motion and epidermal stemness are linked. We conclude that early identification of human keratinocyte stem cells by image analysis of cell movement is a valid parameter for quality control of cultured keratinocytes for transplantation. PMID:25897083

Recent advances in quantitative high throughput and high content data analysis.

PubMed

Moutsatsos, Ioannis K; Parker, Christian N

2016-01-01

High throughput screening has become a basic technique with which to explore biological systems. Advances in technology, including increased screening capacity, as well as methods that generate multiparametric readouts, are driving the need for improvements in the analysis of data sets derived from such screens. This article covers the recent advances in the analysis of high throughput screening data sets from arrayed samples, as well as the recent advances in the analysis of cell-by-cell data sets derived from image or flow cytometry application. Screening multiple genomic reagents targeting any given gene creates additional challenges and so methods that prioritize individual gene targets have been developed. The article reviews many of the open source data analysis methods that are now available and which are helping to define a consensus on the best practices to use when analyzing screening data. As data sets become larger, and more complex, the need for easily accessible data analysis tools will continue to grow. The presentation of such complex data sets, to facilitate quality control monitoring and interpretation of the results will require the development of novel visualizations. In addition, advanced statistical and machine learning algorithms that can help identify patterns, correlations and the best features in massive data sets will be required. The ease of use for these tools will be important, as they will need to be used iteratively by laboratory scientists to improve the outcomes of complex analyses.

Differentiation of early from advanced coronary atherosclerotic lesions: systematic comparison of CT, intravascular US, and optical frequency domain imaging with histopathologic examination in ex vivo human hearts.

PubMed

Maurovich-Horvat, Pál; Schlett, Christopher L; Alkadhi, Hatem; Nakano, Masataka; Stolzmann, Paul; Vorpahl, Marc; Scheffel, Hans; Tanaka, Atsushi; Warger, William C; Maehara, Akiko; Ma, Shixin; Kriegel, Matthias F; Kaple, Ryan K; Seifarth, Harald; Bamberg, Fabian; Mintz, Gary S; Tearney, Guillermo J; Virmani, Renu; Hoffmann, Udo

2012-11-01

To establish an ex vivo experimental setup for imaging coronary atherosclerosis with coronary computed tomographic (CT) angiography, intravascular ultrasonography (US), and optical frequency domain imaging (OFDI) and to investigate their ability to help differentiate early from advanced coronary plaques. All procedures were performed in accordance with local and federal regulations and the Declaration of Helsinki. Approval of the local Ethics Committee was obtained. Overall, 379 histologic cuts from nine coronary arteries from three donor hearts were acquired, coregistered among modalities, and assessed for the presence and composition of atherosclerotic plaque. To assess the discriminatory capacity of the different modalities in the detection of advanced lesions, c statistic analysis was used. Interobserver agreement was assessed with the Cohen κ statistic. Cross sections without plaque at coronary CT angiography and with fibrous plaque at OFDI almost never showed advanced lesions at histopathologic examination (odds ratio [OR]: 0.02 and 0.06, respectively; both P<.0001), while mixed plaque at coronary CT angiography, calcified plaque at intravascular US, and lipid-rich plaque at OFDI were associated with advanced lesions (OR: 2.49, P=.0003; OR: 2.60, P=.002; and OR: 31.2, P<.0001, respectively). OFDI had higher accuracy for discriminating early from advanced lesions than intravascular US and coronary CT angiography (area under the receiver operating characteristic curve: 0.858 [95% confidence interval {CI}: 0.802, 0.913], 0.631 [95% CI: 0.554, 0.709], and 0.679 [95% CI: 0.618, 0.740]; respectively, P<.0001). Interobserver agreement was excellent for OFDI and coronary CT angiography (κ=0.87 and 0.85, respectively) and was good for intravascular US (κ=0.66). Systematic and standardized comparison between invasive and noninvasive modalities for coronary plaque characterization in ex vivo specimens demonstrated that coronary CT angiography and intravascular US are reasonably associated with plaque composition and lesion grading according to histopathologic findings, while OFDI was strongly associated. These data may help to develop initial concepts of sequential imaging strategies to identify patients with advanced coronary plaques. © RSNA, 2012

Sparse models for correlative and integrative analysis of imaging and genetic data

PubMed Central

Lin, Dongdong; Cao, Hongbao; Calhoun, Vince D.

2014-01-01

The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our ability to understand their interplay as well as their relationship with human behavior by integrating these two types of datasets. However, the high dimensionality and heterogeneity of these datasets presents a challenge to conventional statistical methods; there is a high demand for the development of both correlative and integrative analysis approaches. Here, we review our recent work on developing sparse representation based approaches to address this challenge. We show how sparse models are applied to the correlation and integration of imaging and genetic data for biomarker identification. We present examples on how these approaches are used for the detection of risk genes and classification of complex diseases such as schizophrenia. Finally, we discuss future directions on the integration of multiple imaging and genomic datasets including their interactions such as epistasis. PMID:25218561

On the release of cppxfel for processing X-ray free-electron laser images.

PubMed

Ginn, Helen Mary; Evans, Gwyndaf; Sauter, Nicholas K; Stuart, David Ian

2016-06-01

As serial femtosecond crystallography expands towards a variety of delivery methods, including chip-based methods, and smaller collected data sets, the requirement to optimize the data analysis to produce maximum structure quality is becoming increasingly pressing. Here cppxfel , a software package primarily written in C++, which showcases several data analysis techniques, is released. This software package presently indexes images using DIALS (diffraction integration for advanced light sources) and performs an initial orientation matrix refinement, followed by post-refinement of individual images against a reference data set. Cppxfel is released with the hope that the unique and useful elements of this package can be repurposed for existing software packages. However, as released, it produces high-quality crystal structures and is therefore likely to be also useful to experienced users of X-ray free-electron laser (XFEL) software who wish to maximize the information extracted from a limited number of XFEL images.

On the release of cppxfel for processing X-ray free-electron laser images

DOE PAGES

Ginn, Helen Mary; Evans, Gwyndaf; Sauter, Nicholas K.; ...

2016-05-11

As serial femtosecond crystallography expands towards a variety of delivery methods, including chip-based methods, and smaller collected data sets, the requirement to optimize the data analysis to produce maximum structure quality is becoming increasingly pressing. Herecppxfel, a software package primarily written in C++, which showcases several data analysis techniques, is released. This software package presently indexes images using DIALS (diffraction integration for advanced light sources) and performs an initial orientation matrix refinement, followed by post-refinement of individual images against a reference data set.Cppxfelis released with the hope that the unique and useful elements of this package can be repurposed formore » existing software packages. However, as released, it produces high-quality crystal structures and is therefore likely to be also useful to experienced users of X-ray free-electron laser (XFEL) software who wish to maximize the information extracted from a limited number of XFEL images.« less

Testing and evaluation of tactical electro-optical sensors

NASA Astrophysics Data System (ADS)

Middlebrook, Christopher T.; Smith, John G.

2002-07-01

As integrated electro-optical sensor payloads (multi- sensors) comprised of infrared imagers, visible imagers, and lasers advance in performance, the tests and testing methods must also advance in order to fully evaluate them. Future operational requirements will require integrated sensor payloads to perform missions at further ranges and with increased targeting accuracy. In order to meet these requirements sensors will require advanced imaging algorithms, advanced tracking capability, high-powered lasers, and high-resolution imagers. To meet the U.S. Navy's testing requirements of such multi-sensors, the test and evaluation group in the Night Vision and Chemical Biological Warfare Department at NAVSEA Crane is developing automated testing methods, and improved tests to evaluate imaging algorithms, and procuring advanced testing hardware to measure high resolution imagers and line of sight stabilization of targeting systems. This paper addresses: descriptions of the multi-sensor payloads tested, testing methods used and under development, and the different types of testing hardware and specific payload tests that are being developed and used at NAVSEA Crane.

Advances in Imaging in Prostate and Bladder Cancer.

PubMed

Srivastava, Abhishek; Douglass, Laura M; Chernyak, Victoria; Watts, Kara L

2017-09-01

Recent advancements in urologic imaging techniques aim to improve the initial detection of urologic malignancies and subsequent recurrence and to more accurately stage disease. This allows the urologist to make better informed treatment decisions. In particular, exciting advances in the imaging of prostate cancer and bladder cancer have recently emerged including the use of dynamic, functional imaging with MRI and PET. In this review, we will explore these imaging modalities, in addition to new sonography techniques and CT, and how they hope to improve the diagnosis and management of prostate and bladder cancer.

Collaborating and sharing data in epilepsy research.

PubMed

Wagenaar, Joost B; Worrell, Gregory A; Ives, Zachary; Dümpelmann, Matthias; Matthias, Dümpelmann; Litt, Brian; Schulze-Bonhage, Andreas

2015-06-01

Technological advances are dramatically advancing translational research in Epilepsy. Neurophysiology, imaging, and metadata are now recorded digitally in most centers, enabling quantitative analysis. Basic and translational research opportunities to use these data are exploding, but academic and funding cultures prevent this potential from being realized. Research on epileptogenic networks, antiepileptic devices, and biomarkers could progress rapidly if collaborative efforts to digest this "big neuro data" could be organized. Higher temporal and spatial resolution data are driving the need for novel multidimensional visualization and analysis tools. Crowd-sourced science, the same that drives innovation in computer science, could easily be mobilized for these tasks, were it not for competition for funding, attribution, and lack of standard data formats and platforms. As these efforts mature, there is a great opportunity to advance Epilepsy research through data sharing and increase collaboration between the international research community.

The Open Microscopy Environment: open image informatics for the biological sciences

NASA Astrophysics Data System (ADS)

Blackburn, Colin; Allan, Chris; Besson, Sébastien; Burel, Jean-Marie; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gault, David; Gillen, Kenneth; Leigh, Roger; Leo, Simone; Li, Simon; Lindner, Dominik; Linkert, Melissa; Moore, Josh; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Swedlow, Jason R.

2016-07-01

Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. While the open FITS file format is ubiquitous in astronomy, astronomical imaging shares many challenges with biological imaging, including the need to share large image sets using secure, cross-platform APIs, and the need for scalable applications for processing and visualization. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME tools include: an open data model for multidimensional imaging (OME Data Model); an open file format (OME-TIFF) and library (Bio-Formats) enabling free access to images (5D+) written in more than 145 formats from many imaging domains, including FITS; and a data management server (OMERO). The Java-based OMERO client-server platform comprises an image metadata store, an image repository, visualization and analysis by remote access, allowing sharing and publishing of image data. OMERO provides a means to manage the data through a multi-platform API. OMERO's model-based architecture has enabled its extension into a range of imaging domains, including light and electron microscopy, high content screening, digital pathology and recently into applications using non-image data from clinical and genomic studies. This is made possible using the Bio-Formats library. The current release includes a single mechanism for accessing image data of all types, regardless of original file format, via Java, C/C++ and Python and a variety of applications and environments (e.g. ImageJ, Matlab and R).

A priori collaboration in population imaging: The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement consortium.

PubMed

Adams, Hieab H H; Hilal, Saima; Schwingenschuh, Petra; Wittfeld, Katharina; van der Lee, Sven J; DeCarli, Charles; Vernooij, Meike W; Katschnig-Winter, Petra; Habes, Mohamad; Chen, Christopher; Seshadri, Sudha; van Duijn, Cornelia M; Ikram, M Kamran; Grabe, Hans J; Schmidt, Reinhold; Ikram, M Arfan

2015-12-01

Virchow-Robin spaces (VRS), or perivascular spaces, are compartments of interstitial fluid enclosing cerebral blood vessels and are potential imaging markers of various underlying brain pathologies. Despite a growing interest in the study of enlarged VRS, the heterogeneity in rating and quantification methods combined with small sample sizes have so far hampered advancement in the field. The Uniform Neuro-Imaging of Virchow-Robin Spaces Enlargement (UNIVRSE) consortium was established with primary aims to harmonize rating and analysis (www.uconsortium.org). The UNIVRSE consortium brings together 13 (sub)cohorts from five countries, totaling 16,000 subjects and over 25,000 scans. Eight different magnetic resonance imaging protocols were used in the consortium. VRS rating was harmonized using a validated protocol that was developed by the two founding members, with high reliability independent of scanner type, rater experience, or concomitant brain pathology. Initial analyses revealed risk factors for enlarged VRS including increased age, sex, high blood pressure, brain infarcts, and white matter lesions, but this varied by brain region. Early collaborative efforts between cohort studies with respect to data harmonization and joint analyses can advance the field of population (neuro)imaging. The UNIVRSE consortium will focus efforts on other potential correlates of enlarged VRS, including genetics, cognition, stroke, and dementia.

Image detection and compression for memory efficient system analysis

NASA Astrophysics Data System (ADS)

Bayraktar, Mustafa

2015-02-01

The advances in digital signal processing have been progressing towards efficient use of memory and processing. Both of these factors can be utilized efficiently by using feasible techniques of image storage by computing the minimum information of image which will enhance computation in later processes. Scale Invariant Feature Transform (SIFT) can be utilized to estimate and retrieve of an image. In computer vision, SIFT can be implemented to recognize the image by comparing its key features from SIFT saved key point descriptors. The main advantage of SIFT is that it doesn't only remove the redundant information from an image but also reduces the key points by matching their orientation and adding them together in different windows of image [1]. Another key property of this approach is that it works on highly contrasted images more efficiently because it`s design is based on collecting key points from the contrast shades of image.

Advances in computer imaging/applications in facial plastic surgery.

PubMed

Papel, I D; Jiannetto, D F

1999-01-01

Rapidly progressing computer technology, ever-increasing expectations of patients, and a confusing medicolegal environment requires a clarification of the role of computer imaging/applications. Advances in computer technology and its applications are reviewed. A brief historical discussion is included for perspective. Improvements in both hardware and software with the advent of digital imaging have allowed great increases in speed and accuracy in patient imaging. This facilitates doctor-patient communication and possibly realistic patient expectations. Patients seeking cosmetic surgery now often expect preoperative imaging. Although society in general has become more litigious, a literature search up to 1998 reveals no lawsuits directly involving computer imaging. It appears that conservative utilization of computer imaging by the facial plastic surgeon may actually reduce liability and promote communication. Recent advances have significantly enhanced the value of computer imaging in the practice of facial plastic surgery. These technological advances in computer imaging appear to contribute a useful technique for the practice of facial plastic surgery. Inclusion of computer imaging should be given serious consideration as an adjunct to clinical practice.

Imaging evidence and recommendations for traumatic brain injury: advanced neuro- and neurovascular imaging techniques.

PubMed

Wintermark, M; Sanelli, P C; Anzai, Y; Tsiouris, A J; Whitlow, C T

2015-02-01

Neuroimaging plays a critical role in the evaluation of patients with traumatic brain injury, with NCCT as the first-line of imaging for patients with traumatic brain injury and MR imaging being recommended in specific settings. Advanced neuroimaging techniques, including MR imaging DTI, blood oxygen level-dependent fMRI, MR spectroscopy, perfusion imaging, PET/SPECT, and magnetoencephalography, are of particular interest in identifying further injury in patients with traumatic brain injury when conventional NCCT and MR imaging findings are normal, as well as for prognostication in patients with persistent symptoms. These advanced neuroimaging techniques are currently under investigation in an attempt to optimize them and substantiate their clinical relevance in individual patients. However, the data currently available confine their use to the research arena for group comparisons, and there remains insufficient evidence at the time of this writing to conclude that these advanced techniques can be used for routine clinical use at the individual patient level. TBI imaging is a rapidly evolving field, and a number of the recommendations presented will be updated in the future to reflect the advances in medical knowledge. © 2015 by American Journal of Neuroradiology.

Coherent Raman Scattering Microscopy in Biology and Medicine.

PubMed

Zhang, Chi; Zhang, Delong; Cheng, Ji-Xin

2015-01-01

Advancements in coherent Raman scattering (CRS) microscopy have enabled label-free visualization and analysis of functional, endogenous biomolecules in living systems. When compared with spontaneous Raman microscopy, a key advantage of CRS microscopy is the dramatic improvement in imaging speed, which gives rise to real-time vibrational imaging of live biological samples. Using molecular vibrational signatures, recently developed hyperspectral CRS microscopy has improved the readout of chemical information available from CRS images. In this article, we review recent achievements in CRS microscopy, focusing on the theory of the CRS signal-to-noise ratio, imaging speed, technical developments, and applications of CRS imaging in bioscience and clinical settings. In addition, we present possible future directions that the use of this technology may take.

Coherent Raman Scattering Microscopy in Biology and Medicine

PubMed Central

Zhang, Chi; Zhang, Delong; Cheng, Ji-Xin

2016-01-01

Advancements in coherent Raman scattering (CRS) microscopy have enabled label-free visualization and analysis of functional, endogenous biomolecules in living systems. When compared with spontaneous Raman microscopy, a key advantage of CRS microscopy is the dramatic improvement in imaging speed, which gives rise to real-time vibrational imaging of live biological samples. Using molecular vibrational signatures, recently developed hyperspectral CRS microscopy has improved the readout of chemical information available from CRS images. In this article, we review recent achievements in CRS microscopy, focusing on the theory of the CRS signal-to-noise ratio, imaging speed, technical developments, and applications of CRS imaging in bioscience and clinical settings. In addition, we present possible future directions that the use of this technology may take. PMID:26514285

A neotropical Miocene pollen database employing image-based search and semantic modeling.

PubMed

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W; Jaramillo, Carlos; Shyu, Chi-Ren

2014-08-01

Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery.

Design of a normal incidence multilayer imaging X-ray microscope

NASA Astrophysics Data System (ADS)

Shealy, David L.; Gabardi, David R.; Hoover, Richard B.; Walker, Arthur B. C., Jr.; Lindblom, Joakim F.

Normal incidence multilayer Cassegrain X-ray telescopes were flown on the Stanford/MSFC Rocket X-ray Spectroheliograph. These instruments produced high spatial resolution images of the sun and conclusively demonstrated that doubly reflecting multilayer X-ray optical systems are feasible. The images indicated that aplanatic imaging soft X-ray/EUV microscopes should be achievable using multilayer optics technology. A doubly reflecting normal incidence multilayer imaging X-ray microscope based on the Schwarzschild configuration has been designed. The design of the microscope and the results of the optical system ray trace analysis are discussed. High resolution aplanatic imaging X-ray microscopes using normal incidence multilayer X-ray mirrors should have many important applications in advanced X-ray astronomical instrumentation, X-ray lithography, biological, biomedical, metallurgical, and laser fusion research.

An automated and universal method for measuring mean grain size from a digital image of sediment

USGS Publications Warehouse

Buscombe, Daniel D.; Rubin, David M.; Warrick, Jonathan A.

2010-01-01

Existing methods for estimating mean grain size of sediment in an image require either complicated sequences of image processing (filtering, edge detection, segmentation, etc.) or statistical procedures involving calibration. We present a new approach which uses Fourier methods to calculate grain size directly from the image without requiring calibration. Based on analysis of over 450 images, we found the accuracy to be within approximately 16% across the full range from silt to pebbles. Accuracy is comparable to, or better than, existing digital methods. The new method, in conjunction with recent advances in technology for taking appropriate images of sediment in a range of natural environments, promises to revolutionize the logistics and speed at which grain-size data may be obtained from the field.

ADP of multispectral scanner data for land use mapping

NASA Technical Reports Server (NTRS)

Hoffer, R. M.

1971-01-01

The advantages and disadvantages of various remote sensing instrumentation and analysis techniques are reviewed. The use of multispectral scanner data and the automatic data processing techniques are considered. A computer-aided analysis system for remote sensor data is described with emphasis on the image display, statistics processor, wavelength band selection, classification processor, and results display. Advanced techniques in using spectral and temporal data are also considered.

Tropical Cyclone Intensity and Position Analysis Using Passive Microwave Imager and Sounder Data

DTIC Science & Technology

2015-03-26

NPP) Advanced Technology Microwave Sounder (ATMS) for a sample of 28 North Atlantic storms from the 2011 through 2013 TC seasons . Using a stepwise...58 27. NOAA NHC 2011 TC Season Tracks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61 28...per Season and TCs with Aircraft Reconnaissance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Making the Most of MASINT and Advanced Geospatial Intelligence

DTIC Science & Technology

2012-04-10

mining contracts and new job creation that ultimately supports economic development. This 22 type of forensic level analysis can make MASINT an...and Technology, ed. John D. Bossler (London: Taylor and Francis, 2002), 305 17 Jian Guo Liu and Philippa J. Mason, Essential Image Processing and

Automated sample area definition for high-throughput microscopy.

PubMed

Zeder, M; Ellrott, A; Amann, R

2011-04-01

High-throughput screening platforms based on epifluorescence microscopy are powerful tools in a variety of scientific fields. Although some applications are based on imaging geometrically defined samples such as microtiter plates, multiwell slides, or spotted gene arrays, others need to cope with inhomogeneously located samples on glass slides. The analysis of microbial communities in aquatic systems by sample filtration on membrane filters followed by multiple fluorescent staining, or the investigation of tissue sections are examples. Therefore, we developed a strategy for flexible and fast definition of sample locations by the acquisition of whole slide overview images and automated sample recognition by image analysis. Our approach was tested on different microscopes and the computer programs are freely available (http://www.technobiology.ch). Copyright © 2011 International Society for Advancement of Cytometry.

Advanced imaging techniques in brain tumors

PubMed Central

2009-01-01

Abstract Perfusion, permeability and magnetic resonance spectroscopy (MRS) are now widely used in the research and clinical settings. In the clinical setting, qualitative, semi-quantitative and quantitative approaches such as review of color-coded maps to region of interest analysis and analysis of signal intensity curves are being applied in practice. There are several pitfalls with all of these approaches. Some of these shortcomings are reviewed, such as the relative low sensitivity of metabolite ratios from MRS and the effect of leakage on the appearance of color-coded maps from dynamic susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging and what correction and normalization methods can be applied. Combining and applying these different imaging techniques in a multi-parametric algorithmic fashion in the clinical setting can be shown to increase diagnostic specificity and confidence. PMID:19965287

Large-Scale Quantitative Analysis of Painting Arts

PubMed Central

Kim, Daniel; Son, Seung-Woo; Jeong, Hawoong

2014-01-01

Scientists have made efforts to understand the beauty of painting art in their own languages. As digital image acquisition of painting arts has made rapid progress, researchers have come to a point where it is possible to perform statistical analysis of a large-scale database of artistic paints to make a bridge between art and science. Using digital image processing techniques, we investigate three quantitative measures of images – the usage of individual colors, the variety of colors, and the roughness of the brightness. We found a difference in color usage between classical paintings and photographs, and a significantly low color variety of the medieval period. Interestingly, moreover, the increment of roughness exponent as painting techniques such as chiaroscuro and sfumato have advanced is consistent with historical circumstances. PMID:25501877

Quantitative analysis of image quality for acceptance and commissioning of an MRI simulator with a semiautomatic method.

PubMed

Chen, Xinyuan; Dai, Jianrong

2018-05-01

Magnetic Resonance Imaging (MRI) simulation differs from diagnostic MRI in purpose, technical requirements, and implementation. We propose a semiautomatic method for image acceptance and commissioning for the scanner, the radiofrequency (RF) coils, and pulse sequences for an MRI simulator. The ACR MRI accreditation large phantom was used for image quality analysis with seven parameters. Standard ACR sequences with a split head coil were adopted to examine the scanner's basic performance. The performance of simulation RF coils were measured and compared using the standard sequence with different clinical diagnostic coils. We used simulation sequences with simulation coils to test the quality of image and advanced performance of the scanner. Codes and procedures were developed for semiautomatic image quality analysis. When using standard ACR sequences with a split head coil, image quality passed all ACR recommended criteria. The image intensity uniformity with a simulation RF coil decreased about 34% compared with the eight-channel diagnostic head coil, while the other six image quality parameters were acceptable. Those two image quality parameters could be improved to more than 85% by built-in intensity calibration methods. In the simulation sequences test, the contrast resolution was sensitive to the FOV and matrix settings. The geometric distortion of simulation sequences such as T1-weighted and T2-weighted images was well-controlled in the isocenter and 10 cm off-center within a range of ±1% (2 mm). We developed a semiautomatic image quality analysis method for quantitative evaluation of images and commissioning of an MRI simulator. The baseline performances of simulation RF coils and pulse sequences have been established for routine QA. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Efficient processing of fluorescence images using directional multiscale representations.

PubMed

Labate, D; Laezza, F; Negi, P; Ozcan, B; Papadakis, M

2014-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data.

Efficient processing of fluorescence images using directional multiscale representations

PubMed Central

Labate, D.; Laezza, F.; Negi, P.; Ozcan, B.; Papadakis, M.

2017-01-01

Recent advances in high-resolution fluorescence microscopy have enabled the systematic study of morphological changes in large populations of cells induced by chemical and genetic perturbations, facilitating the discovery of signaling pathways underlying diseases and the development of new pharmacological treatments. In these studies, though, due to the complexity of the data, quantification and analysis of morphological features are for the vast majority handled manually, slowing significantly data processing and limiting often the information gained to a descriptive level. Thus, there is an urgent need for developing highly efficient automated analysis and processing tools for fluorescent images. In this paper, we present the application of a method based on the shearlet representation for confocal image analysis of neurons. The shearlet representation is a newly emerged method designed to combine multiscale data analysis with superior directional sensitivity, making this approach particularly effective for the representation of objects defined over a wide range of scales and with highly anisotropic features. Here, we apply the shearlet representation to problems of soma detection of neurons in culture and extraction of geometrical features of neuronal processes in brain tissue, and propose it as a new framework for large-scale fluorescent image analysis of biomedical data. PMID:28804225

Cloud solution for histopathological image analysis using region of interest based compression.

PubMed

Kanakatte, Aparna; Subramanya, Rakshith; Delampady, Ashik; Nayak, Rajarama; Purushothaman, Balamuralidhar; Gubbi, Jayavardhana

2017-07-01

Recent technological gains have led to the adoption of innovative cloud based solutions in medical imaging field. Once the medical image is acquired, it can be viewed, modified, annotated and shared on many devices. This advancement is mainly due to the introduction of Cloud computing in medical domain. Tissue pathology images are complex and are normally collected at different focal lengths using a microscope. The single whole slide image contains many multi resolution images stored in a pyramidal structure with the highest resolution image at the base and the smallest thumbnail image at the top of the pyramid. Highest resolution image will be used for tissue pathology diagnosis and analysis. Transferring and storing such huge images is a big challenge. Compression is a very useful and effective technique to reduce the size of these images. As pathology images are used for diagnosis, no information can be lost during compression (lossless compression). A novel method of extracting the tissue region and applying lossless compression on this region and lossy compression on the empty regions has been proposed in this paper. The resulting compression ratio along with lossless compression on tissue region is in acceptable range allowing efficient storage and transmission to and from the Cloud.

Multispectral laser imaging for advanced food analysis

NASA Astrophysics Data System (ADS)

Senni, L.; Burrascano, P.; Ricci, M.

2016-07-01

A hardware-software apparatus for food inspection capable of realizing multispectral NIR laser imaging at four different wavelengths is herein discussed. The system was designed to operate in a through-transmission configuration to detect the presence of unwanted foreign bodies inside samples, whether packed or unpacked. A modified Lock-In technique was employed to counterbalance the significant signal intensity attenuation due to transmission across the sample and to extract the multispectral information more efficiently. The NIR laser wavelengths used to acquire the multispectral images can be varied to deal with different materials and to focus on specific aspects. In the present work the wavelengths were selected after a preliminary analysis to enhance the image contrast between foreign bodies and food in the sample, thus identifying the location and nature of the defects. Experimental results obtained from several specimens, with and without packaging, are presented and the multispectral image processing as well as the achievable spatial resolution of the system are discussed.

From microscopy to whole slide digital images: a century and a half of image analysis.

PubMed

Taylor, Clive R

2011-12-01

In the year 1850, microscopes had evolved in quality to the point that the "first pathologists emerged from the treacherous swamps of medieval practice onto the relatively firm ground that histopathology seemed to offer." These early pathologists began to practice the art of image analysis, and diagnostic surgical pathology was born. Today the traditional microscope, in the hands of an experienced pathologist, is established as the gold standard for diagnosis of cancer and other diseases. Nonetheless, it is a tool and a technology that is more than 150 years old. Rapid advances in the capabilities of digital imaging hardware and software now offer the real possibility of moving to a new level of practice, using whole slide digital images for diagnosis, education, and research in morphologic pathology. Potential efficiencies in work flow and diagnostic integration, coupled with the use of powerful new analytic methods, promise radically to change the future shape of surgical pathology.

High-resolution measurements of the multilayer ultra-structure of articular cartilage and their translational potential

PubMed Central

2014-01-01

Current musculoskeletal imaging techniques usually target the macro-morphology of articular cartilage or use histological analysis. These techniques are able to reveal advanced osteoarthritic changes in articular cartilage but fail to give detailed information to distinguish early osteoarthritis from healthy cartilage, and this necessitates high-resolution imaging techniques measuring cells and the extracellular matrix within the multilayer structure of articular cartilage. This review provides a comprehensive exploration of the cellular components and extracellular matrix of articular cartilage as well as high-resolution imaging techniques, including magnetic resonance image, electron microscopy, confocal laser scanning microscopy, second harmonic generation microscopy, and laser scanning confocal arthroscopy, in the measurement of multilayer ultra-structures of articular cartilage. This review also provides an overview for micro-structural analysis of the main components of normal or osteoarthritic cartilage and discusses the potential and challenges associated with developing non-invasive high-resolution imaging techniques for both research and clinical diagnosis of early to late osteoarthritis. PMID:24946278

Genotype-phenotype association study via new multi-task learning model

PubMed Central

Huo, Zhouyuan; Shen, Dinggang

2018-01-01

Research on the associations between genetic variations and imaging phenotypes is developing with the advance in high-throughput genotype and brain image techniques. Regression analysis of single nucleotide polymorphisms (SNPs) and imaging measures as quantitative traits (QTs) has been proposed to identify the quantitative trait loci (QTL) via multi-task learning models. Recent studies consider the interlinked structures within SNPs and imaging QTs through group lasso, e.g. ℓ2,1-norm, leading to better predictive results and insights of SNPs. However, group sparsity is not enough for representing the correlation between multiple tasks and ℓ2,1-norm regularization is not robust either. In this paper, we propose a new multi-task learning model to analyze the associations between SNPs and QTs. We suppose that low-rank structure is also beneficial to uncover the correlation between genetic variations and imaging phenotypes. Finally, we conduct regression analysis of SNPs and QTs. Experimental results show that our model is more accurate in prediction than compared methods and presents new insights of SNPs. PMID:29218896

Breast MRI radiogenomics: Current status and research implications.

PubMed

Grimm, Lars J

2016-06-01

Breast magnetic resonance imaging (MRI) radiogenomics is an emerging area of research that has the potential to directly influence clinical practice. Clinical MRI scanners today are capable of providing excellent temporal and spatial resolution, which allows extraction of numerous imaging features via human extraction approaches or complex computer vision algorithms. Meanwhile, advances in breast cancer genetics research has resulted in the identification of promising genes associated with cancer outcomes. In addition, validated genomic signatures have been developed that allow categorization of breast cancers into distinct molecular subtypes as well as predict the risk of cancer recurrence and response to therapy. Current radiogenomics research has been directed towards exploratory analysis of individual genes, understanding tumor biology, and developing imaging surrogates to genetic analysis with the long-term goal of developing a meaningful tool for clinical care. The background of breast MRI radiogenomics research, image feature extraction techniques, approaches to radiogenomics research, and promising areas of investigation are reviewed. J. Magn. Reson. Imaging 2016;43:1269-1278. © 2015 Wiley Periodicals, Inc.

Introduction to the GEOBIA 2010 special issue: From pixels to geographic objects in remote sensing image analysis

NASA Astrophysics Data System (ADS)

Addink, Elisabeth A.; Van Coillie, Frieke M. B.; De Jong, Steven M.

2012-04-01

Traditional image analysis methods are mostly pixel-based and use the spectral differences of landscape elements at the Earth surface to classify these elements or to extract element properties from the Earth Observation image. Geographic object-based image analysis (GEOBIA) has received considerable attention over the past 15 years for analyzing and interpreting remote sensing imagery. In contrast to traditional image analysis, GEOBIA works more like the human eye-brain combination does. The latter uses the object's color (spectral information), size, texture, shape and occurrence to other image objects to interpret and analyze what we see. GEOBIA starts by segmenting the image grouping together pixels into objects and next uses a wide range of object properties to classify the objects or to extract object's properties from the image. Significant advances and improvements in image analysis and interpretation are made thanks to GEOBIA. In June 2010 the third conference on GEOBIA took place at the Ghent University after successful previous meetings in Calgary (2008) and Salzburg (2006). This special issue presents a selection of the 2010 conference papers that are worked out as full research papers for JAG. The papers cover GEOBIA applications as well as innovative methods and techniques. The topics range from vegetation mapping, forest parameter estimation, tree crown identification, urban mapping, land cover change, feature selection methods and the effects of image compression on segmentation. From the original 94 conference papers, 26 full research manuscripts were submitted; nine papers were selected and are presented in this special issue. Selection was done on the basis of quality and topic of the studies. The next GEOBIA conference will take place in Rio de Janeiro from 7 to 9 May 2012 where we hope to welcome even more scientists working in the field of GEOBIA.

A new set of wavelet- and fractals-based features for Gleason grading of prostate cancer histopathology images

NASA Astrophysics Data System (ADS)

Mosquera Lopez, Clara; Agaian, Sos

2013-02-01

Prostate cancer detection and staging is an important step towards patient treatment selection. Advancements in digital pathology allow the application of new quantitative image analysis algorithms for computer-assisted diagnosis (CAD) on digitized histopathology images. In this paper, we introduce a new set of features to automatically grade pathological images using the well-known Gleason grading system. The goal of this study is to classify biopsy images belonging to Gleason patterns 3, 4, and 5 by using a combination of wavelet and fractal features. For image classification we use pairwise coupling Support Vector Machine (SVM) classifiers. The accuracy of the system, which is close to 97%, is estimated through three different cross-validation schemes. The proposed system offers the potential for automating classification of histological images and supporting prostate cancer diagnosis.

Energy and Technology Review

NASA Astrophysics Data System (ADS)

Poggio, Andrew J.

1988-10-01

This issue of Energy and Technology Review contains: Neutron Penumbral Imaging of Laser-Fusion Targets--using our new penumbral-imaging diagnostic, we have obtained the first images that can be used to measure directly the deuterium-tritium burn region in laser-driven fusion targets; Computed Tomography for Nondestructive Evaluation--various computed tomography systems and computational techniques are used in nondestructive evaluation; Three-Dimensional Image Analysis for Studying Nuclear Chromatin Structure--we have developed an optic-electronic system for acquiring cross-sectional views of cell nuclei, and computer codes to analyze these images and reconstruct the three-dimensional structures they represent; Imaging in the Nuclear Test Program--advanced techniques produce images of unprecedented detail and resolution from Nevada Test Site data; and Computational X-Ray Holography--visible-light experiments and numerically simulated holograms test our ideas about an X-ray microscope for biological research.

TH-E-9A-01: Medical Physics 1.0 to 2.0, Session 4: Computed Tomography, Ultrasound and Nuclear Medicine

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

Samei, E; Nelson, J; Hangiandreou, N

Medical Physics 2.0 is a bold vision for an existential transition of clinical imaging physics in face of the new realities of value-based and evidencebased medicine, comparative effectiveness, and meaningful use. It speaks to how clinical imaging physics can expand beyond traditional insular models of inspection and acceptance testing, oriented toward compliance, towards team-based models of operational engagement, prospective definition and assurance of effective use, and retrospective evaluation of clinical performance. Organized into four sessions of the AAPM, this particular session focuses on three specific modalities as outlined below. CT 2.0: CT has been undergoing a dramatic transition in themore » last few decades. While the changes in the technology merits discussions of their own, an important question is how clinical medical physicists are expected to effectively engage with the new realities of CT technology and practice. Consistent with the upcoming paradigm of Medical Physics 2.0, this CT presentation aims to provide definitions and demonstration of the components of the new clinical medical physics practice pertaining CT. The topics covered include physics metrics and analytics that aim to provide higher order clinicallyrelevant quantification of system performance as pertains to new (and not so new) technologies. That will include the new radiation and dose metrics (SSDE, organ dose, risk indices), image quality metrology (MTF/NPS/d’), task-based phantoms, and the effect of patient size. That will follow with a discussion of the testing implication of new CT hardware (detectors, tubes), acquisition methods (innovative helical geometries, AEC, wide beam CT, dual energy, inverse geometry, application specialties), and image processing and analysis (iterative reconstructions, quantitative CT, advanced renditions). The presentation will conclude with a discussion of clinical and operational aspects of Medical Physics 2.0 including training and communication, use optimization (dose and technique factors), automated analysis and data management (automated QC methods, protocol tracking, dose monitoring, issue tracking), and meaningful QC considerations. US 2.0: Ultrasound imaging is evolving at a rapid pace, adding new imaging functions and modes that continue to enhance its clinical utility and benefits to patients. The ultrasound talk will look ahead 10–15 years and consider how medical physicists can bring maximal value to the clinical ultrasound practices of the future. The roles of physics in accreditation and regulatory compliance, image quality and exam optimization, clinical innovation, and education of staff and trainees will all be considered. A detailed examination of expected technology evolution and impact on image quality metrics will be presented. Clinical implementation of comprehensive physics services will also be discussed. Nuclear Medicine 2.0: Although the basic science of nuclear imaging has remained relatively unchanged since its inception, advances in instrumentation continue to advance the field into new territories. With a great number of these advances occurring over the past decade, the role and testing strategies of clinical nuclear medicine physicists must evolve in parallel. The Nuclear Medicine 2.0 presentation is designed to highlight some of the recent advances from a clinical medical physicist perspective and provide ideas and motivation for designing better evaluation strategies. Topics include improvement of traditional physics metrics and analytics, testing implications of hybrid imaging and advanced detector technologies, and strategies for effective implementation into the clinic. Learning Objectives: Become familiar with new physics metrics and analytics in nuclear medicine, CT, and ultrasound. To become familiar with the major new developments of clinical physics support. To understand the physics testing implications of new technologies, hardware, software, and applications. Identify approaches for implementing comprehensive medical physics services in future imaging practices.« less

MSL: Facilitating automatic and physical analysis of published scientific literature in PDF format

PubMed Central

Ahmed, Zeeshan; Dandekar, Thomas

2018-01-01

Published scientific literature contains millions of figures, including information about the results obtained from different scientific experiments e.g. PCR-ELISA data, microarray analysis, gel electrophoresis, mass spectrometry data, DNA/RNA sequencing, diagnostic imaging (CT/MRI and ultrasound scans), and medicinal imaging like electroencephalography (EEG), magnetoencephalography (MEG), echocardiography  (ECG), positron-emission tomography (PET) images. The importance of biomedical figures has been widely recognized in scientific and medicine communities, as they play a vital role in providing major original data, experimental and computational results in concise form. One major challenge for implementing a system for scientific literature analysis is extracting and analyzing text and figures from published PDF files by physical and logical document analysis. Here we present a product line architecture based bioinformatics tool ‘Mining Scientific Literature (MSL)’, which supports the extraction of text and images by interpreting all kinds of published PDF files using advanced data mining and image processing techniques. It provides modules for the marginalization of extracted text based on different coordinates and keywords, visualization of extracted figures and extraction of embedded text from all kinds of biological and biomedical figures using applied Optimal Character Recognition (OCR). Moreover, for further analysis and usage, it generates the system’s output in different formats including text, PDF, XML and images files. Hence, MSL is an easy to install and use analysis tool to interpret published scientific literature in PDF format. PMID:29721305

Roles of universal three-dimensional image analysis devices that assist surgical operations.

PubMed

Sakamoto, Tsuyoshi

2014-04-01

The circumstances surrounding medical image analysis have undergone rapid evolution. In such a situation, it can be said that "imaging" obtained through medical imaging modality and the "analysis" that we employ have become amalgamated. Recently, we feel the distance between "imaging" and "analysis" has become closer regarding the imaging analysis of any organ system, as if both terms mentioned above have become integrated. The history of medical image analysis started with the appearance of the computer. The invention of multi-planar reconstruction (MPR) used in the helical scan had a significant impact and became the basis for recent image analysis. Subsequently, curbed MPR (CPR) and other methods were developed, and the 3D diagnostic imaging and image analysis of the human body have started on a full scale. Volume rendering: the development of a new rendering algorithm and the significant improvement of memory and CPUs contributed to the development of "volume rendering," which allows 3D views with retained internal information. A new value was created by this development; computed tomography (CT) images that used to be for "diagnosis" before that time have become "applicable to treatment." In the past, before the development of volume rendering, a clinician had to mentally reconstruct an image reconfigured for diagnosis into a 3D image, but these developments have allowed the depiction of a 3D image on a monitor. Current technology: Currently, in Japan, the estimation of the liver volume and the perfusion area of the portal vein and hepatic vein are vigorously being adopted during preoperative planning for hepatectomy. Such a circumstance seems to be brought by the substantial improvement of said basic techniques and by upgrading the user interface, allowing doctors easy manipulation by themselves. The following describes the specific techniques. Future of post-processing technology: It is expected, in terms of the role of image analysis, for better or worse, that computer-aided diagnosis (CAD) will develop to a highly advanced level in every diagnostic field. Further, it is also expected in the treatment field that a technique coordinating various devices will be strongly required as a surgery navigator. Actually, surgery using an image navigator is being widely studied, and coordination with hardware, including robots, will also be developed. © 2014 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

Neural networks: Application to medical imaging

NASA Technical Reports Server (NTRS)

Clarke, Laurence P.

1994-01-01

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

Multispectral image analysis for object recognition and classification

NASA Astrophysics Data System (ADS)

Viau, C. R.; Payeur, P.; Cretu, A.-M.

2016-05-01

Computer and machine vision applications are used in numerous fields to analyze static and dynamic imagery in order to assist or automate decision-making processes. Advancements in sensor technologies now make it possible to capture and visualize imagery at various wavelengths (or bands) of the electromagnetic spectrum. Multispectral imaging has countless applications in various fields including (but not limited to) security, defense, space, medical, manufacturing and archeology. The development of advanced algorithms to process and extract salient information from the imagery is a critical component of the overall system performance. The fundamental objective of this research project was to investigate the benefits of combining imagery from the visual and thermal bands of the electromagnetic spectrum to improve the recognition rates and accuracy of commonly found objects in an office setting. A multispectral dataset (visual and thermal) was captured and features from the visual and thermal images were extracted and used to train support vector machine (SVM) classifiers. The SVM's class prediction ability was evaluated separately on the visual, thermal and multispectral testing datasets.

High angular resolution at LBT

NASA Astrophysics Data System (ADS)

Conrad, A.; Arcidiacono, C.; Bertero, M.; Boccacci, P.; Davies, A. G.; Defrere, D.; de Kleer, K.; De Pater, I.; Hinz, P.; Hofmann, K. H.; La Camera, A.; Leisenring, J.; Kürster, M.; Rathbun, J. A.; Schertl, D.; Skemer, A.; Skrutskie, M.; Spencer, J. R.; Veillet, C.; Weigelt, G.; Woodward, C. E.

2015-12-01

High angular resolution from ground-based observatories stands as a key technology for advancing planetary science. In the window between the angular resolution achievable with 8-10 meter class telescopes, and the 23-to-40 meter giants of the future, LBT provides a glimpse of what the next generation of instruments providing higher angular resolution will provide. We present first ever resolved images of an Io eruption site taken from the ground, images of Io's Loki Patera taken with Fizeau imaging at the 22.8 meter LBT [Conrad, et al., AJ, 2015]. We will also present preliminary analysis of two data sets acquired during the 2015 opposition: L-band fringes at Kurdalagon and an occultation of Loki and Pele by Europa (see figure). The light curves from this occultation will yield an order of magnitude improvement in spatial resolution along the path of ingress and egress. We will conclude by providing an overview of the overall benefit of recent and future advances in angular resolution for planetary science.

Advances in laser technology for the atmospheric sciences; Proceedings of the Seminar, San Diego, Calif., August 25, 26, 1977

NASA Technical Reports Server (NTRS)

Trolinger, J. D. (Editor); Moore, W. W.

1977-01-01

These papers deal with recent research, developments, and applications in laser and electrooptics technology, particularly with regard to atmospheric effects in imaging and propagation, laser instrumentation and measurements, and particle measurement. Specific topics include advanced imaging techniques, image resolution through atmospheric turbulence over the ocean, an efficient method for calculating transmittance profiles, a comparison of a corner-cube reflector and a plane mirror in folded-path and direct transmission through atmospheric turbulence, line-spread instrumentation for propagation measurements, scaling laws for thermal fluctuations in the layer adjacent to ocean waves, particle sizing by laser photography, and an optical Fourier transform analysis of satellite cloud imagery. Other papers discuss a subnanosecond photomultiplier tube for laser application, holography of solid propellant combustion, diagnostics of turbulence by holography, a camera for in situ photography of cloud particles from a hail research aircraft, and field testing of a long-path laser transmissometer designed for atmospheric visibility measurements.

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

NASA Technical Reports Server (NTRS)

Fang, Wai-Chi

1997-01-01

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

Advances in basic science methodologies for clinical diagnosis in female stress urinary incontinence.

PubMed

Abdulaziz, Marwa; Deegan, Emily G; Kavanagh, Alex; Stothers, Lynn; Pugash, Denise; Macnab, Andrew

2017-06-01

We provide an overview of advanced imaging techniques currently being explored to gain greater understanding of the complexity of stress urinary incontinence (SUI) through better definition of structural anatomic data. Two methods of imaging and analysis are detailed for SUI with or without prolapse: 1) open magnetic resonance imaging (MRI) with or without the use of reference lines; and 2) 3D reconstruction of the pelvis using MRI. An additional innovative method of assessment includes the use of near infrared spectroscopy (NIRS), which uses non-invasive photonics in a vaginal speculum to objectively evaluate pelvic floor muscle (PFM) function as it relates to SUI pathology. Advantages and disadvantages of these techniques are described. The recent innovation of open-configuration magnetic resonance imaging (MRO) allows images to be captured in sitting and standing positions, which better simulates states that correlate with urinary leakage and can be further enhanced with 3D reconstruction. By detecting direct changes in oxygenated muscle tissue, the NIRS vaginal speculum is able to provide insight into how the oxidative capacity of the PFM influences SUI. The small number of units able to provide patient evaluation using these techniques and their cost and relative complexity are major considerations, but if such imaging can optimize diagnosis, treatment allocation, and selection for surgery enhanced imaging techniques may prove to be a worthwhile and cost-effective strategy for assessing and treating SUI.

Tularosa Basin Play Fairway Analysis: Weights of Evidence; Mineralogy, and Temperature Anomaly Maps

DOE Data Explorer

Adam Brandt

2015-11-15

This submission has two shapefiles and a tiff image. The weights of evidence analysis was applied to data representing heat of the earth and fracture permeability using training sites around the Southwest; this is shown in the tiff image. A shapefile of surface temperature anomalies was derived from the statistical analysis of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) thermal infrared data which had been converted to surface temperatures; these anomalies have not been field checked. The second shapefile shows outcrop mineralogy which originally mapped by the New Mexico Bureau of Geology and Mineral Resources, and supplemented with mineralogic information related to rock fracability risk for EGS. Further metadata can be found within each file.

Challenges of microtome‐based serial block‐face scanning electron microscopy in neuroscience

PubMed Central

WANNER, A. A.; KIRSCHMANN, M. A.

2015-01-01

Summary Serial block‐face scanning electron microscopy (SBEM) is becoming increasingly popular for a wide range of applications in many disciplines from biology to material sciences. This review focuses on applications for circuit reconstruction in neuroscience, which is one of the major driving forces advancing SBEM. Neuronal circuit reconstruction poses exceptional challenges to volume EM in terms of resolution, field of view, acquisition time and sample preparation. Mapping the connections between neurons in the brain is crucial for understanding information flow and information processing in the brain. However, information on the connectivity between hundreds or even thousands of neurons densely packed in neuronal microcircuits is still largely missing. Volume EM techniques such as serial section TEM, automated tape‐collecting ultramicrotome, focused ion‐beam scanning electron microscopy and SBEM (microtome serial block‐face scanning electron microscopy) are the techniques that provide sufficient resolution to resolve ultrastructural details such as synapses and provides sufficient field of view for dense reconstruction of neuronal circuits. While volume EM techniques are advancing, they are generating large data sets on the terabyte scale that require new image processing workflows and analysis tools. In this review, we present the recent advances in SBEM for circuit reconstruction in neuroscience and an overview of existing image processing and analysis pipelines. PMID:25907464

Availability of Advanced Breast Imaging at Screening Facilities Serving Vulnerable Populations.

PubMed

Lee, Christoph I; Bogart, Andy; Germino, Jessica C; Goldman, L Elizabeth; Hubbard, Rebecca A; Haas, Jennifer S; Hill, Deirdre A; Tosteson, Anna Na; Alford-Teaster, Jennifer A; DeMartini, Wendy B; Lehman, Constance D; Onega, Tracy L

2016-03-01

Among vulnerable women, unequal access to advanced breast imaging modalities beyond screening mammography may lead to delays in cancer diagnosis and unfavourable outcomes. We aimed to compare on-site availability of advanced breast imaging services (ultrasound, magnetic resonance imaging [MRI], and image-guided biopsy) between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations. 73 imaging facilities across five Breast Cancer Surveillance Consortium regional registries in the United States during 2011 and 2012. We examined facility and patient characteristics across a large, national sample of imaging facilities and patients served. We characterized facilities as serving vulnerable populations based on the proportion of mammograms performed on women with lower educational attainment, lower median income, racial/ethnic minority status, and rural residence.We performed multivariable logistic regression to determine relative risks of on-site availability of advanced imaging at facilities serving vulnerable women versus facilities serving non-vulnerable women. Facilities serving vulnerable populations were as likely (Relative risk [RR] for MRI = 0.71, 95% Confidence Interval [CI] 0.42, 1.19; RR for MRI-guided biopsy = 1.07 [0.61, 1.90]; RR for stereotactic biopsy = 1.18 [0.75, 1.85]) or more likely (RR for ultrasound = 1.38 [95% CI 1.09, 1.74]; RR for ultrasound-guided biopsy = 1.67 [1.30, 2.14]) to offer advanced breast imaging services as those serving non-vulnerable populations. Advanced breast imaging services are physically available on-site for vulnerable women in the United States, but it is unknown whether factors such as insurance coverage or out-of-pocket costs might limit their use. © The Author(s) 2015.

Availability of Advanced Breast Imaging at Screening Facilities Serving Vulnerable Populations

PubMed Central

Lee, Christoph I.; Bogart, Andy; Germino, Jessica C.; Goldman, L. Elizabeth; Hubbard, Rebecca A.; Haas, Jennifer S.; Hill, Deirdre A.; Tosteson, Anna N.A.; Alford-Teaster, Jennifer A.; DeMartini, Wendy B.; Lehman, Constance D.; Onega, Tracy L.

2015-01-01

Objective Among vulnerable women, unequal access to advanced breast imaging modalities beyond screening mammography may lead to delays in cancer diagnosis and unfavorable outcomes. We aimed to compare on-site availability of advanced breast imaging services (ultrasound (US), magnetic resonance imaging (MRI), and image-guided biopsy) between imaging facilities serving vulnerable patient populations and those serving non-vulnerable populations. Setting 73 United States imaging facilities across five Breast Cancer Surveillance Consortium regional registries during calendar years 2011–2012. Methods We examined facility and patient characteristics across a large, national sample of imaging facilities and patients served. We characterized facilities as serving vulnerable populations based on the proportion of mammograms performed on women with lower educational attainment, lower median income, racial/ethnic minority status, and rural residence. We performed multivariable logistic regression to determine relative risks of on-site availability of advanced imaging at facilities serving vulnerable women versus facilities serving non-vulnerable women. Results Facilities serving vulnerable populations were as likely (RR for MRI = 0.71 [95% CI 0.42, 1.19]; RR for MRI-guided biopsy = 1.07 [0.61, 1.90]; RR for stereotactic biopsy = 1.18 [0.75, 1.85]) or more likely (RR for US = 1.38 [95% CI 1.09, 1.74]; RR for US-guided biopsy = 1.67 [1.30, 2.14]) to offer advanced breast imaging services as those serving non-vulnerable populations. Conclusions Advanced breast imaging services are physically available on-site for vulnerable women in the United States, but it is unknown whether factors such as insurance coverage or out-of-pocket costs might limit their use. PMID:26078275

MO-DE-202-00: Image-Guided Interventions: Advances in Intraoperative Imaging, Guidance, and An Emerging Role for Medical Physics in Surgery

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

NONE

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-03: Image-Guided Surgery and Interventions in the Advanced Multimodality Image-Guided Operating (AMIGO) Suite

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

Kapur, T.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-02: Advances in Image Registration and Reconstruction for Image-Guided Neurosurgery

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

Siewerdsen, J.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

Advanced endoscopic imaging in gastric neoplasia and preneoplasia

PubMed Central

Lee, Jonathan W J; Lim, Lee Guan; Yeoh, Khay Guan

2017-01-01

Conventional white light endoscopy remains the current standard in routine clinical practice for early detection of gastric cancer. However, it may not accurately diagnose preneoplastic gastric lesions. The technological advancements in the field of endoscopic imaging for gastric lesions are fast growing. This article reviews currently available advanced endoscopic imaging modalities, in particular chromoendoscopy, narrow band imaging and confocal laser endomicroscopy, and their corresponding evidence shown to improve diagnosis of preneoplastic gastric lesions. Raman spectrometry and polarimetry are also introduced as promising emerging technologies. PMID:28176895

Deep Learning in Nuclear Medicine and Molecular Imaging: Current Perspectives and Future Directions.

PubMed

Choi, Hongyoon

2018-04-01

Recent advances in deep learning have impacted various scientific and industrial fields. Due to the rapid application of deep learning in biomedical data, molecular imaging has also started to adopt this technique. In this regard, it is expected that deep learning will potentially affect the roles of molecular imaging experts as well as clinical decision making. This review firstly offers a basic overview of deep learning particularly for image data analysis to give knowledge to nuclear medicine physicians and researchers. Because of the unique characteristics and distinctive aims of various types of molecular imaging, deep learning applications can be different from other fields. In this context, the review deals with current perspectives of deep learning in molecular imaging particularly in terms of development of biomarkers. Finally, future challenges of deep learning application for molecular imaging and future roles of experts in molecular imaging will be discussed.

Predictive images of postoperative levator resection outcome using image processing software.

PubMed

Mawatari, Yuki; Fukushima, Mikiko

2016-01-01

This study aims to evaluate the efficacy of processed images to predict postoperative appearance following levator resection. Analysis involved 109 eyes from 65 patients with blepharoptosis who underwent advancement of levator aponeurosis and Müller's muscle complex (levator resection). Predictive images were prepared from preoperative photographs using the image processing software (Adobe Photoshop ® ). Images of selected eyes were digitally enlarged in an appropriate manner and shown to patients prior to surgery. Approximately 1 month postoperatively, we surveyed our patients using questionnaires. Fifty-six patients (89.2%) were satisfied with their postoperative appearances, and 55 patients (84.8%) positively responded to the usefulness of processed images to predict postoperative appearance. Showing processed images that predict postoperative appearance to patients prior to blepharoptosis surgery can be useful for those patients concerned with their postoperative appearance. This approach may serve as a useful tool to simulate blepharoptosis surgery.

Predictive images of postoperative levator resection outcome using image processing software

PubMed Central

Mawatari, Yuki; Fukushima, Mikiko

2016-01-01

Purpose This study aims to evaluate the efficacy of processed images to predict postoperative appearance following levator resection. Methods Analysis involved 109 eyes from 65 patients with blepharoptosis who underwent advancement of levator aponeurosis and Müller’s muscle complex (levator resection). Predictive images were prepared from preoperative photographs using the image processing software (Adobe Photoshop®). Images of selected eyes were digitally enlarged in an appropriate manner and shown to patients prior to surgery. Results Approximately 1 month postoperatively, we surveyed our patients using questionnaires. Fifty-six patients (89.2%) were satisfied with their postoperative appearances, and 55 patients (84.8%) positively responded to the usefulness of processed images to predict postoperative appearance. Conclusion Showing processed images that predict postoperative appearance to patients prior to blepharoptosis surgery can be useful for those patients concerned with their postoperative appearance. This approach may serve as a useful tool to simulate blepharoptosis surgery. PMID:27757008

Harvey Mudd College: Technology Integration Offers Unique Opportunities for Undergraduates.

ERIC Educational Resources Information Center

Barna, John; Winstead, Jim

1993-01-01

Describes undergraduate projects at Harvey Mudd College (California) that use advanced laboratory equipment and procedures normally reserved for graduate students. Examples are given in experimental biology (e.g., digital imaging and DNA analysis), in physics (e.g., using satellites to study earthquake faults), and in mathematics (e.g., teaching…

High pressure single-crystal micro X-ray diffraction analysis with GSE_ADA/RSV software

NASA Astrophysics Data System (ADS)

Dera, Przemyslaw; Zhuravlev, Kirill; Prakapenka, Vitali; Rivers, Mark L.; Finkelstein, Gregory J.; Grubor-Urosevic, Ognjen; Tschauner, Oliver; Clark, Simon M.; Downs, Robert T.

2013-08-01

GSE_ADA/RSV is a free software package for custom analysis of single-crystal micro X-ray diffraction (SCμXRD) data, developed with particular emphasis on data from samples enclosed in diamond anvil cells and subject to high pressure conditions. The package has been in extensive use at the high pressure beamlines of Advanced Photon Source (APS), Argonne National Laboratory and Advanced Light Source (ALS), Lawrence Berkeley National Laboratory. The software is optimized for processing of wide-rotation images and includes a variety of peak intensity corrections and peak filtering features, which are custom-designed to make processing of high pressure SCμXRD easier and more reliable.

Textural features of pretreatment 18F-FDG PET/CT images: prognostic significance in patients with advanced T-stage oropharyngeal squamous cell carcinoma.

PubMed

Cheng, Nai-Ming; Fang, Yu-Hua Dean; Chang, Joseph Tung-Chieh; Huang, Chung-Guei; Tsan, Din-Li; Ng, Shu-Hang; Wang, Hung-Ming; Lin, Chien-Yu; Liao, Chun-Ta; Yen, Tzu-Chen

2013-10-01

Previous studies have shown that total lesion glycolysis (TLG) may serve as a prognostic indicator in oropharyngeal squamous cell carcinoma (OPSCC). We sought to investigate whether the textural features of pretreatment (18)F-FDG PET/CT images can provide any additional prognostic information over TLG and clinical staging in patients with advanced T-stage OPSCC. We retrospectively analyzed the pretreatment (18)F-FDG PET/CT images of 70 patients with advanced T-stage OPSCC who had completed concurrent chemoradiotherapy, bioradiotherapy, or radiotherapy with curative intent. All of the patients had data on human papillomavirus (HPV) infection and were followed up for at least 24 mo or until death. A standardized uptake value (SUV) of 2.5 was taken as a cutoff for tumor boundary. The textural features of pretreatment (18)F-FDG PET/CT images were extracted from histogram analysis (SUV variance and SUV entropy), normalized gray-level cooccurrence matrix (uniformity, entropy, dissimilarity, contrast, homogeneity, inverse different moment, and correlation), and neighborhood gray-tone difference matrix (coarseness, contrast, busyness, complexity, and strength). Receiver-operating-characteristic curves were used to identify the optimal cutoff values for the textural features and TLG. Thirteen patients were HPV-positive. Multivariate Cox regression analysis showed that age, tumor TLG, and uniformity were independently associated with progression-free survival (PFS) and disease-specific survival (DSS). TLG, uniformity, and HPV positivity were significantly associated with overall survival (OS). A prognostic scoring system based on TLG and uniformity was derived. Patients who presented with TLG > 121.9 g and uniformity ≤ 0.138 experienced significantly worse PFS, DSS, and OS rates than those without (P < 0.001, < 0.001, and 0.002, respectively). Patients with TLG > 121.9 g or uniformity ≤ 0.138 were further divided according to age, and different PFS and DSS were observed. Uniformity extracted from the normalized gray-level cooccurrence matrix represents an independent prognostic predictor in patients with advanced T-stage OPSCC. A scoring system was developed and may serve as a risk-stratification strategy for guiding therapy.

Design of multifunctional nanoparticles for combined in-vivo imaging and advanced drug delivery

NASA Astrophysics Data System (ADS)

Leary, James F.

2018-02-01

Design of multifunctional nanoparticles for multimodal in-vivo imaging and advanced targeting to diseased single cells for massive parallel processing nanomedicine approaches requires careful overall design and a multilayered approach. Initial core materials can include non-toxic metals which not only serve as an x-ray contrast agent for CAT scan imaging, but can contain T1 or T2 contrast agents for MRI imaging. One choice is superparamagnetic iron oxide NPs which also allow for convenient magnetic manipulation during manufacturing but also for re-positioning inside the body and for single cell hyperthermia therapies. To permit real-time fluorescence-guided surgery, fluorescence molecules can be included. Advanced targeting can be achieved by attaching antibodies, peptides, aptamers, or other targeting molecules to the nanoparticle in a multilayered approach producing "programmable nanoparticles" whereby the "programming" means controlling a sequence of multi-step targeting methods. Addition of membrane permeating peptides can facilitate uptake by the cell. Addition of "stealth" molecules (e.g. PEG or chitosan) to the outer surfaces of the nanoparticles can permit greatly enhanced circulation times in-vivo which in turn lead to lower amounts of drug exposure to the patient which can reduce undesirable side effects. Nanoparticles with incomplete layers can be removed by affinity purification methods to minimize mistargeting events in-vivo. Nanoscale imaging of these manufactured, multifunctional nanoparticles can be achieved either directly through superresolution microscopy or indirectly through single nanoparticle zeta-sizing or x-ray correlation microscopy. Since these multifunctional nanoparticles are best analyzed by technologies permitting analysis in aqueous environments, superresolution microscopy is, in most cases, the preferred method.

Radiomics: Images Are More than Pictures, They Are Data

PubMed Central

Kinahan, Paul E.; Hricak, Hedvig

2016-01-01

In the past decade, the field of medical image analysis has grown exponentially, with an increased number of pattern recognition tools and an increase in data set sizes. These advances have facilitated the development of processes for high-throughput extraction of quantitative features that result in the conversion of images into mineable data and the subsequent analysis of these data for decision support; this practice is termed radiomics. This is in contrast to the traditional practice of treating medical images as pictures intended solely for visual interpretation. Radiomic data contain first-, second-, and higher-order statistics. These data are combined with other patient data and are mined with sophisticated bioinformatics tools to develop models that may potentially improve diagnostic, prognostic, and predictive accuracy. Because radiomics analyses are intended to be conducted with standard of care images, it is conceivable that conversion of digital images to mineable data will eventually become routine practice. This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer. PMID:26579733

Development of a prediction model for residual disease in newly diagnosed advanced ovarian cancer.

PubMed

Janco, Jo Marie Tran; Glaser, Gretchen; Kim, Bohyun; McGree, Michaela E; Weaver, Amy L; Cliby, William A; Dowdy, Sean C; Bakkum-Gamez, Jamie N

2015-07-01

To construct a tool, using computed tomography (CT) imaging and preoperative clinical variables, to estimate successful primary cytoreduction for advanced epithelial ovarian cancer (EOC). Women who underwent primary cytoreductive surgery for stage IIIC/IV EOC at Mayo Clinic between 1/2/2003 and 12/30/2011 and had preoperative CT images of the abdomen and pelvis within 90days prior to their surgery available for review were included. CT images were reviewed for large-volume ascites, diffuse peritoneal thickening (DPT), omental cake, lymphadenopathy (LP), and spleen or liver involvement. Preoperative factors included age, body mass index (BMI), Eastern Cooperative Oncology Group performance status (ECOG PS), American Society of Anesthesiologists (ASA) score, albumin, CA-125, and thrombocytosis. Two prediction models were developed to estimate the probability of (i) complete and (ii) suboptimal cytoreduction (residual disease (RD) >1cm) using multivariable logistic analysis with backward and stepwise variable selection methods. Internal validation was assessed using bootstrap resampling to derive an optimism-corrected estimate of the c-index. 279 patients met inclusion criteria: 143 had complete cytoreduction, 26 had suboptimal cytoreduction (RD>1cm), and 110 had measurable RD ≤1cm. On multivariable analysis, age, absence of ascites, omental cake, and DPT on CT imaging independently predicted complete cytoreduction (c-index=0.748). Conversely, predictors of suboptimal cytoreduction were ECOG PS, DPT, and LP on preoperative CT imaging (c-index=0.685). The generated models serve as preoperative evaluation tools that may improve counseling and selection for primary surgery, but need to be externally validated. Copyright © 2015 Elsevier Inc. All rights reserved.

Latest advances in molecular imaging instrumentation.

PubMed

Pichler, Bernd J; Wehrl, Hans F; Judenhofer, Martin S

2008-06-01

This review concentrates on the latest advances in molecular imaging technology, including PET, MRI, and optical imaging. In PET, significant improvements in tumor detection and image resolution have been achieved by introducing new scintillation materials, iterative image reconstruction, and correction methods. These advances enabled the first clinical scanners capable of time-of-flight detection and incorporating point-spread-function reconstruction to compensate for depth-of-interaction effects. In the field of MRI, the most important developments in recent years have mainly been MRI systems with higher field strengths and improved radiofrequency coil technology. Hyperpolarized imaging, functional MRI, and MR spectroscopy provide molecular information in vivo. A special focus of this review article is multimodality imaging and, in particular, the emerging field of combined PET/MRI.

Virtual medicine: Utilization of the advanced cardiac imaging patient avatar for procedural planning and facilitation.

PubMed

Shinbane, Jerold S; Saxon, Leslie A

Advances in imaging technology have led to a paradigm shift from planning of cardiovascular procedures and surgeries requiring the actual patient in a "brick and mortar" hospital to utilization of the digitalized patient in the virtual hospital. Cardiovascular computed tomographic angiography (CCTA) and cardiovascular magnetic resonance (CMR) digitalized 3-D patient representation of individual patient anatomy and physiology serves as an avatar allowing for virtual delineation of the most optimal approaches to cardiovascular procedures and surgeries prior to actual hospitalization. Pre-hospitalization reconstruction and analysis of anatomy and pathophysiology previously only accessible during the actual procedure could potentially limit the intrinsic risks related to time in the operating room, cardiac procedural laboratory and overall hospital environment. Although applications are specific to areas of cardiovascular specialty focus, there are unifying themes related to the utilization of technologies. The virtual patient avatar computer can also be used for procedural planning, computational modeling of anatomy, simulation of predicted therapeutic result, printing of 3-D models, and augmentation of real time procedural performance. Examples of the above techniques are at various stages of development for application to the spectrum of cardiovascular disease processes, including percutaneous, surgical and hybrid minimally invasive interventions. A multidisciplinary approach within medicine and engineering is necessary for creation of robust algorithms for maximal utilization of the virtual patient avatar in the digital medical center. Utilization of the virtual advanced cardiac imaging patient avatar will play an important role in the virtual health care system. Although there has been a rapid proliferation of early data, advanced imaging applications require further assessment and validation of accuracy, reproducibility, standardization, safety, efficacy, quality, cost effectiveness, and overall value to medical care. Copyright © 2018 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

High content analysis of differentiation and cell death in human adipocytes.

PubMed

Doan-Xuan, Quang Minh; Sarvari, Anitta K; Fischer-Posovszky, Pamela; Wabitsch, Martin; Balajthy, Zoltan; Fesus, Laszlo; Bacso, Zsolt

2013-10-01

Understanding adipocyte biology and its homeostasis is in the focus of current obesity research. We aimed to introduce a high-content analysis procedure for directly visualizing and quantifying adipogenesis and adipoapoptosis by laser scanning cytometry (LSC) in a large population of cell. Slide-based image cytometry and image processing algorithms were used and optimized for high-throughput analysis of differentiating cells and apoptotic processes in cell culture at high confluence. Both preadipocytes and adipocytes were simultaneously scrutinized for lipid accumulation, texture properties, nuclear condensation, and DNA fragmentation. Adipocyte commitment was found after incubation in adipogenic medium for 3 days identified by lipid droplet formation and increased light absorption, while terminal differentiation of adipocytes occurred throughout day 9-14 with characteristic nuclear shrinkage, eccentric nuclei localization, chromatin condensation, and massive lipid deposition. Preadipocytes were shown to be more prone to tumor necrosis factor alpha (TNFα)-induced apoptosis compared to mature adipocytes. Importantly, spontaneous DNA fragmentation was observed at early stage when adipocyte commitment occurs. This DNA damage was independent from either spontaneous or induced apoptosis and probably was part of the differentiation program. © 2013 International Society for Advancement of Cytometry. Copyright © 2013 International Society for Advancement of Cytometry.

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

PubMed

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

2013-09-01

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

Advanced Tomographic Imaging Methods for the Analysis of Materials

DTIC Science & Technology

1991-08-01

used in composite manufacture: aluminum, silicon carbide, and titanium aluminide . Also depicted in Fig. 2 are the energy intervals which can...SiC-fiber (SCS6) in a titanium - aluminide matrix. The contrast between SiC and AtIis only 10% over a broad eiaergy range. Therefore, distinguishing the...borehole logging, orrodent detection on turbine blades , kerogen analysis of shale, and contents of coals (sulfur, minerals, and btu). APSTNG

Recent advances in 3D computed tomography techniques for simulation and navigation in hepatobiliary pancreatic surgery.

PubMed

Uchida, Masafumi

2014-04-01

A few years ago it could take several hours to complete a 3D image using a 3D workstation. Thanks to advances in computer science, obtaining results of interest now requires only a few minutes. Many recent 3D workstations or multimedia computers are equipped with onboard 3D virtual patient modeling software, which enables patient-specific preoperative assessment and virtual planning, navigation, and tool positioning. Although medical 3D imaging can now be conducted using various modalities, including computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and ultrasonography (US) among others, the highest quality images are obtained using CT data, and CT images are now the most commonly used source of data for 3D simulation and navigation image. If the 2D source image is bad, no amount of 3D image manipulation in software will provide a quality 3D image. In this exhibition, the recent advances in CT imaging technique and 3D visualization of the hepatobiliary and pancreatic abnormalities are featured, including scan and image reconstruction technique, contrast-enhanced techniques, new application of advanced CT scan techniques, and new virtual reality simulation and navigation imaging. © 2014 Japanese Society of Hepato-Biliary-Pancreatic Surgery.

WE-E-17A-02: Predictive Modeling of Outcome Following SABR for NSCLC Based On Radiomics of FDG-PET Images

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

Li, R; Aguilera, T; Shultz, D

2014-06-15

Purpose: This study aims to develop predictive models of patient outcome by extracting advanced imaging features (i.e., Radiomics) from FDG-PET images. Methods: We acquired pre-treatment PET scans for 51 stage I NSCLC patients treated with SABR. We calculated 139 quantitative features from each patient PET image, including 5 morphological features, 8 statistical features, 27 texture features, and 100 features from the intensity-volume histogram. Based on the imaging features, we aim to distinguish between 2 risk groups of patients: those with regional failure or distant metastasis versus those without. We investigated 3 pattern classification algorithms: linear discriminant analysis (LDA), naive Bayesmore » (NB), and logistic regression (LR). To avoid the curse of dimensionality, we performed feature selection by first removing redundant features and then applying sequential forward selection using the wrapper approach. To evaluate the predictive performance, we performed 10-fold cross validation with 1000 random splits of the data and calculated the area under the ROC curve (AUC). Results: Feature selection identified 2 texture features (homogeneity and/or wavelet decompositions) for NB and LR, while for LDA SUVmax and one texture feature (correlation) were identified. All 3 classifiers achieved statistically significant improvements over conventional PET imaging metrics such as tumor volume (AUC = 0.668) and SUVmax (AUC = 0.737). Overall, NB achieved the best predictive performance (AUC = 0.806). This also compares favorably with MTV using the best threshold at an SUV of 11.6 (AUC = 0.746). At a sensitivity of 80%, NB achieved 69% specificity, while SUVmax and tumor volume only had 36% and 47% specificity. Conclusion: Through a systematic analysis of advanced PET imaging features, we are able to build models with improved predictive value over conventional imaging metrics. If validated in a large independent cohort, the proposed techniques could potentially aid in identifying patients who might benefit from adjuvant therapy.« less

Three-dimensional ray-tracing model for the study of advanced refractive errors in keratoconus.

PubMed

Schedin, Staffan; Hallberg, Per; Behndig, Anders

2016-01-20

We propose a numerical three-dimensional (3D) ray-tracing model for the analysis of advanced corneal refractive errors. The 3D modeling was based on measured corneal elevation data by means of Scheimpflug photography. A mathematical description of the measured corneal surfaces from a keratoconus (KC) patient was used for the 3D ray tracing, based on Snell's law of refraction. A model of a commercial intraocular lens (IOL) was included in the analysis. By modifying the posterior IOL surface, it was shown that the imaging quality could be significantly improved. The RMS values were reduced by approximately 50% close to the retina, both for on- and off-axis geometries. The 3D ray-tracing model can constitute a basis for simulation of customized IOLs that are able to correct the advanced, irregular refractive errors in KC.

An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

PubMed

Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

2016-01-01

The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

The role of Imaging and Radiation Oncology Core for precision medicine era of clinical trial

PubMed Central

Rosen, Mark

2017-01-01

Imaging and Radiation Oncology Core (IROC) services have been established for the quality assurance (QA) of imaging and radiotherapy (RT) for NCI’s Clinical Trial Network (NCTN) for any trials that contain imaging or RT. The randomized clinical trial is the gold standard for evidence-based medicine. QA ensures data quality, preventing noise from inferior treatments obscuring clinical trial outcome. QA is also found to be cost-effective. IROC has made great progress in multi-institution standardization and is expected to lead QA standardization, QA science in imaging and RT and to advance quality data analysis with big data in the future. The QA in the era of precision medicine is of paramount importance, when individualized decision making may depend on the quality and accuracy of RT and imaging. PMID:29218265

Current and future trends in marine image annotation software

NASA Astrophysics Data System (ADS)

Gomes-Pereira, Jose Nuno; Auger, Vincent; Beisiegel, Kolja; Benjamin, Robert; Bergmann, Melanie; Bowden, David; Buhl-Mortensen, Pal; De Leo, Fabio C.; Dionísio, Gisela; Durden, Jennifer M.; Edwards, Luke; Friedman, Ariell; Greinert, Jens; Jacobsen-Stout, Nancy; Lerner, Steve; Leslie, Murray; Nattkemper, Tim W.; Sameoto, Jessica A.; Schoening, Timm; Schouten, Ronald; Seager, James; Singh, Hanumant; Soubigou, Olivier; Tojeira, Inês; van den Beld, Inge; Dias, Frederico; Tempera, Fernando; Santos, Ricardo S.

2016-12-01

Given the need to describe, analyze and index large quantities of marine imagery data for exploration and monitoring activities, a range of specialized image annotation tools have been developed worldwide. Image annotation - the process of transposing objects or events represented in a video or still image to the semantic level, may involve human interactions and computer-assisted solutions. Marine image annotation software (MIAS) have enabled over 500 publications to date. We review the functioning, application trends and developments, by comparing general and advanced features of 23 different tools utilized in underwater image analysis. MIAS requiring human input are basically a graphical user interface, with a video player or image browser that recognizes a specific time code or image code, allowing to log events in a time-stamped (and/or geo-referenced) manner. MIAS differ from similar software by the capability of integrating data associated to video collection, the most simple being the position coordinates of the video recording platform. MIAS have three main characteristics: annotating events in real time, posteriorly to annotation and interact with a database. These range from simple annotation interfaces, to full onboard data management systems, with a variety of toolboxes. Advanced packages allow to input and display data from multiple sensors or multiple annotators via intranet or internet. Posterior human-mediated annotation often include tools for data display and image analysis, e.g. length, area, image segmentation, point count; and in a few cases the possibility of browsing and editing previous dive logs or to analyze the annotations. The interaction with a database allows the automatic integration of annotations from different surveys, repeated annotation and collaborative annotation of shared datasets, browsing and querying of data. Progress in the field of automated annotation is mostly in post processing, for stable platforms or still images. Integration into available MIAS is currently limited to semi-automated processes of pixel recognition through computer-vision modules that compile expert-based knowledge. Important topics aiding the choice of a specific software are outlined, the ideal software is discussed and future trends are presented.

Single molecule imaging of conformational dynamics in sodium-coupled transporters

NASA Astrophysics Data System (ADS)

Terry, Daniel S.

Neurotransmitter:sodium symporter (NSS) proteins remove neurotransmitters released into the synapse through a transport process driven by the physiological sodium ion (Na+) gradient. NSSs for dopamine, noradrenaline, and serotonin are targeted by the psychostimulants cocaine and amphetamines, as well as by antidepressants. The crystal structure of LeuT, a prokaryotic NSS homologue, revealed the NSS molecular architecture and has been the basis for extensive structural, biochemical, and computational investigations of the mechanism of transporter proteins with a LeuT-like fold. In this dissertation, the conformational states sampled by LeuT are explored using single-molecule fluorescence resonance energy transfer imaging methods, with special focus on the motions of transmembrane helix 1a that lead to inward release of substrate. We also explored how dynamics are modulated by substrate, Na+, and protons to produce efficient transport. These advances represent a first of a kind study of the dynamics of an integral membrane protein at a truly single-molecule scale. Advances in instrumentation, analysis tools, and organic fluorophores were all required to achieve these goals, and such advances are also described. While these experiments were performed with detergent-solubilized protein, preliminary work suggests that imaging of LeuT in proteoliposomes is feasible and a fluorescence sensor assay could be used to simultaneously detect conformational dynamics and transport function.

Alterations of the cytoskeleton in human cells in space proved by life-cell imaging.

PubMed

Corydon, Thomas J; Kopp, Sascha; Wehland, Markus; Braun, Markus; Schütte, Andreas; Mayer, Tobias; Hülsing, Thomas; Oltmann, Hergen; Schmitz, Burkhard; Hemmersbach, Ruth; Grimm, Daniela

2016-01-28

Microgravity induces changes in the cytoskeleton. This might have an impact on cells and organs of humans in space. Unfortunately, studies of cytoskeletal changes in microgravity reported so far are obligatorily based on the analysis of fixed cells exposed to microgravity during a parabolic flight campaign (PFC). This study focuses on the development of a compact fluorescence microscope (FLUMIAS) for fast live-cell imaging under real microgravity. It demonstrates the application of the instrument for on-board analysis of cytoskeletal changes in FTC-133 cancer cells expressing the Lifeact-GFP marker protein for the visualization of F-actin during the 24(th) DLR PFC and TEXUS 52 rocket mission. Although vibration is an inevitable part of parabolic flight maneuvers, we successfully for the first time report life-cell cytoskeleton imaging during microgravity, and gene expression analysis after the 31(st) parabola showing a clear up-regulation of cytoskeletal genes. Notably, during the rocket flight the FLUMIAS microscope reveals significant alterations of the cytoskeleton related to microgravity. Our findings clearly demonstrate the applicability of the FLUMIAS microscope for life-cell imaging during microgravity, rendering it an important technological advance in live-cell imaging when dissecting protein localization.

Alterations of the cytoskeleton in human cells in space proved by life-cell imaging

PubMed Central

Corydon, Thomas J.; Kopp, Sascha; Wehland, Markus; Braun, Markus; Schütte, Andreas; Mayer, Tobias; Hülsing, Thomas; Oltmann, Hergen; Schmitz, Burkhard; Hemmersbach, Ruth; Grimm, Daniela

2016-01-01

Microgravity induces changes in the cytoskeleton. This might have an impact on cells and organs of humans in space. Unfortunately, studies of cytoskeletal changes in microgravity reported so far are obligatorily based on the analysis of fixed cells exposed to microgravity during a parabolic flight campaign (PFC). This study focuses on the development of a compact fluorescence microscope (FLUMIAS) for fast live-cell imaging under real microgravity. It demonstrates the application of the instrument for on-board analysis of cytoskeletal changes in FTC-133 cancer cells expressing the Lifeact-GFP marker protein for the visualization of F-actin during the 24th DLR PFC and TEXUS 52 rocket mission. Although vibration is an inevitable part of parabolic flight maneuvers, we successfully for the first time report life-cell cytoskeleton imaging during microgravity, and gene expression analysis after the 31st parabola showing a clear up-regulation of cytoskeletal genes. Notably, during the rocket flight the FLUMIAS microscope reveals significant alterations of the cytoskeleton related to microgravity. Our findings clearly demonstrate the applicability of the FLUMIAS microscope for life-cell imaging during microgravity, rendering it an important technological advance in live-cell imaging when dissecting protein localization. PMID:26818711

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.

Advanced imaging research and development at DARPA

NASA Astrophysics Data System (ADS)

Dhar, Nibir K.; Dat, Ravi

2012-06-01

Advances in imaging technology have huge impact on our daily lives. Innovations in optics, focal plane arrays (FPA), microelectronics and computation have revolutionized camera design. As a result, new approaches to camera design and low cost manufacturing is now possible. These advances are clearly evident in visible wavelength band due to pixel scaling, improvements in silicon material and CMOS technology. CMOS cameras are available in cell phones and many other consumer products. Advances in infrared imaging technology have been slow due to market volume and many technological barriers in detector materials, optics and fundamental limits imposed by the scaling laws of optics. There is of course much room for improvements in both, visible and infrared imaging technology. This paper highlights various technology development projects at DARPA to advance the imaging technology for both, visible and infrared. Challenges and potentials solutions are highlighted in areas related to wide field-of-view camera design, small pitch pixel, broadband and multiband detectors and focal plane arrays.

Multifunctional Polymer Microbubbles for Advanced Sentinel Lymph Node Imaging and Mapping

DTIC Science & Technology

2012-06-01

of thiolated poly(acrylic acid) with fluorescein attached. (b) Bright field image of large bubbles stabilized by polymer and phospholipid...Page 1 of 6 AD_________________ Award Number: W81XWH-11-1-0215 TITLE:   Multifunctional Polymer Microbubbles for Advanced... Polymer Microbubbles for Advanced Sentinel Lymph Node Imaging and Mapping 5b. GRANT NUMBER W81XWH-11-1-0215   5c. PROGRAM ELEMENT NUMBER 6

Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer

PubMed Central

Gutman, David A.; Dunn, William D.; Cobb, Jake; Stoner, Richard M.; Kalpathy-Cramer, Jayashree; Erickson, Bradley

2014-01-01

Advances in web technologies now allow direct visualization of imaging data sets without necessitating the download of large file sets or the installation of software. This allows centralization of file storage and facilitates image review and analysis. XNATView is a light framework recently developed in our lab to visualize DICOM images stored in The Extensible Neuroimaging Archive Toolkit (XNAT). It consists of a PyXNAT-based framework to wrap around the REST application programming interface (API) and query the data in XNAT. XNATView was developed to simplify quality assurance, help organize imaging data, and facilitate data sharing for intra- and inter-laboratory collaborations. Its zero-footprint design allows the user to connect to XNAT from a web browser, navigate through projects, experiments, and subjects, and view DICOM images with accompanying metadata all within a single viewing instance. PMID:24904399

[Imaging Mass Spectrometry in Histopathologic Analysis].

PubMed

Yamazaki, Fumiyoshi; Seto, Mitsutoshi

2015-04-01

Matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry (IMS) enables visualization of the distribution of a range of biomolecules by integrating biochemical information from mass spectrometry with positional information from microscopy. IMS identifies a target molecule. In addition, IMS enables global analysis of biomolecules containing unknown molecules by detecting the ratio of the molecular weight to electric charge without any target, which makes it possible to identify novel molecules. IMS generates data on the distribution of lipids and small molecules in tissues, which is difficult to visualize with either conventional counter-staining or immunohistochemistry. In this review, we firstly introduce the principle of imaging mass spectrometry and recent advances in the sample preparation method. Secondly, we present findings regarding biological samples, especially pathological ones. Finally, we discuss the limitations and problems of the IMS technique and clinical application, such as in drug development.

REVIEWS OF TOPICAL PROBLEMS: Recent advances in X-ray refractive optics

NASA Astrophysics Data System (ADS)

Aristov, V. V.; Shabel'nikov, L. G.

2008-01-01

X-ray refractive optics has made rapid strides to a large degree due to the work of Russian scientists, and has now become one of the most rapidly advancing areas in modern physical optics. This review outlines the results of investigation of refractive devices and analysis of their properties. The conception of planar lenses made of silicon and other materials is set forth. We discuss the applications of refractive lenses to the transformation of X-ray images, photonic crystal research, and the development of focusing devices in high-energy X-ray telescopes.

Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging.

PubMed

Falahati, Farshad; Westman, Eric; Simmons, Andrew

2014-01-01

Machine learning algorithms and multivariate data analysis methods have been widely utilized in the field of Alzheimer's disease (AD) research in recent years. Advances in medical imaging and medical image analysis have provided a means to generate and extract valuable neuroimaging information. Automatic classification techniques provide tools to analyze this information and observe inherent disease-related patterns in the data. In particular, these classifiers have been used to discriminate AD patients from healthy control subjects and to predict conversion from mild cognitive impairment to AD. In this paper, recent studies are reviewed that have used machine learning and multivariate analysis in the field of AD research. The main focus is on studies that used structural magnetic resonance imaging (MRI), but studies that included positron emission tomography and cerebrospinal fluid biomarkers in addition to MRI are also considered. A wide variety of materials and methods has been employed in different studies, resulting in a range of different outcomes. Influential factors such as classifiers, feature extraction algorithms, feature selection methods, validation approaches, and cohort properties are reviewed, as well as key MRI-based and multi-modal based studies. Current and future trends are discussed.

The Advanced Gamma-ray Imaging System (AGIS): A Nanosecond Time Scale Stereoscopic Array Trigger System.

NASA Astrophysics Data System (ADS)

Krennrich, Frank; Buckley, J.; Byrum, K.; Dawson, J.; Drake, G.; Horan, D.; Krawzcynski, H.; Schroedter, M.

2008-04-01

Imaging atmospheric Cherenkov telescope arrays (VERITAS, HESS) have shown unprecedented background suppression capabilities for reducing cosmic-ray induced air showers, muons and night sky background fluctuations. Next-generation arrays with on the order of 100 telescopes offer larger collection areas, provide the possibility to see the air shower from more view points on the ground, have the potential to improve the sensitivity and give additional background suppression. Here we discuss the design of a fast array trigger system that has the potential to perform a real time image analysis allowing substantially improved background rate suppression at the trigger level.

Digital transplantation pathology: combining whole slide imaging, multiplex staining and automated image analysis.

PubMed

Isse, K; Lesniak, A; Grama, K; Roysam, B; Minervini, M I; Demetris, A J

2012-01-01

Conventional histopathology is the gold standard for allograft monitoring, but its value proposition is increasingly questioned. "-Omics" analysis of tissues, peripheral blood and fluids and targeted serologic studies provide mechanistic insights into allograft injury not currently provided by conventional histology. Microscopic biopsy analysis, however, provides valuable and unique information: (a) spatial-temporal relationships; (b) rare events/cells; (c) complex structural context; and (d) integration into a "systems" model. Nevertheless, except for immunostaining, no transformative advancements have "modernized" routine microscopy in over 100 years. Pathologists now team with hardware and software engineers to exploit remarkable developments in digital imaging, nanoparticle multiplex staining, and computational image analysis software to bridge the traditional histology-global "-omic" analyses gap. Included are side-by-side comparisons, objective biopsy finding quantification, multiplexing, automated image analysis, and electronic data and resource sharing. Current utilization for teaching, quality assurance, conferencing, consultations, research and clinical trials is evolving toward implementation for low-volume, high-complexity clinical services like transplantation pathology. Cost, complexities of implementation, fluid/evolving standards, and unsettled medical/legal and regulatory issues remain as challenges. Regardless, challenges will be overcome and these technologies will enable transplant pathologists to increase information extraction from tissue specimens and contribute to cross-platform biomarker discovery for improved outcomes. ©Copyright 2011 The American Society of Transplantation and the American Society of Transplant Surgeons.

In-situ Isotopic Analysis at Nanoscale using Parallel Ion Electron Spectrometry: A Powerful New Paradigm for Correlative Microscopy

NASA Astrophysics Data System (ADS)

Yedra, Lluís; Eswara, Santhana; Dowsett, David; Wirtz, Tom

2016-06-01

Isotopic analysis is of paramount importance across the entire gamut of scientific research. To advance the frontiers of knowledge, a technique for nanoscale isotopic analysis is indispensable. Secondary Ion Mass Spectrometry (SIMS) is a well-established technique for analyzing isotopes, but its spatial-resolution is fundamentally limited. Transmission Electron Microscopy (TEM) is a well-known method for high-resolution imaging down to the atomic scale. However, isotopic analysis in TEM is not possible. Here, we introduce a powerful new paradigm for in-situ correlative microscopy called the Parallel Ion Electron Spectrometry by synergizing SIMS with TEM. We demonstrate this technique by distinguishing lithium carbonate nanoparticles according to the isotopic label of lithium, viz. 6Li and 7Li and imaging them at high-resolution by TEM, adding a new dimension to correlative microscopy.

Advanced magneto-optical microscopy: Imaging from picoseconds to centimeters - imaging spin waves and temperature distributions (invited)

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

Urs, Necdet Onur; Mozooni, Babak; Kustov, Mikhail

2016-05-15

Recent developments in the observation of magnetic domains and domain walls by wide-field optical microscopy based on the magneto-optical Kerr, Faraday, Voigt, and Gradient effect are reviewed. Emphasis is given to the existence of higher order magneto-optical effects for advanced magnetic imaging. Fundamental concepts and advances in methodology are discussed that allow for imaging of magnetic domains on various length and time scales. Time-resolved imaging of electric field induced domain wall rotation is shown. Visualization of magnetization dynamics down to picosecond temporal resolution for the imaging of spin-waves and magneto-optical multi-effect domain imaging techniques for obtaining vectorial information are demonstrated.more » Beyond conventional domain imaging, the use of a magneto-optical indicator technique for local temperature sensing is shown.« less

Quantum image processing: A review of advances in its security technologies

NASA Astrophysics Data System (ADS)

Yan, Fei; Iliyasu, Abdullah M.; Le, Phuc Q.

In this review, we present an overview of the advances made in quantum image processing (QIP) comprising of the image representations, the operations realizable on them, and the likely protocols and algorithms for their applications. In particular, we focus on recent progresses on QIP-based security technologies including quantum watermarking, quantum image encryption, and quantum image steganography. This review is aimed at providing readers with a succinct, yet adequate compendium of the progresses made in the QIP sub-area. Hopefully, this effort will stimulate further interest aimed at the pursuit of more advanced algorithms and experimental validations for available technologies and extensions to other domains.

Progressive data transmission for anatomical landmark detection in a cloud.

PubMed

Sofka, M; Ralovich, K; Zhang, J; Zhou, S K; Comaniciu, D

2012-01-01

In the concept of cloud-computing-based systems, various authorized users have secure access to patient records from a number of care delivery organizations from any location. This creates a growing need for remote visualization, advanced image processing, state-of-the-art image analysis, and computer aided diagnosis. This paper proposes a system of algorithms for automatic detection of anatomical landmarks in 3D volumes in the cloud computing environment. The system addresses the inherent problem of limited bandwidth between a (thin) client, data center, and data analysis server. The problem of limited bandwidth is solved by a hierarchical sequential detection algorithm that obtains data by progressively transmitting only image regions required for processing. The client sends a request to detect a set of landmarks for region visualization or further analysis. The algorithm running on the data analysis server obtains a coarse level image from the data center and generates landmark location candidates. The candidates are then used to obtain image neighborhood regions at a finer resolution level for further detection. This way, the landmark locations are hierarchically and sequentially detected and refined. Only image regions surrounding landmark location candidates need to be trans- mitted during detection. Furthermore, the image regions are lossy compressed with JPEG 2000. Together, these properties amount to at least 30 times bandwidth reduction while achieving similar accuracy when compared to an algorithm using the original data. The hierarchical sequential algorithm with progressive data transmission considerably reduces bandwidth requirements in cloud-based detection systems.

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

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-03-01

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

Optical coherence tomography – current and future applications

PubMed Central

Adhi, Mehreen; Duker, Jay S.

2013-01-01

Purpose of review Optical coherence tomography (OCT) has revolutionized the clinical practice of ophthalmology. It is a noninvasive imaging technique that provides high-resolution, cross-sectional images of the retina, retinal nerve fiber layer and the optic nerve head. This review discusses the present applications of the commercially available spectral-domain OCT (SD-OCT) systems in the diagnosis and management of retinal diseases, with particular emphasis on choroidal imaging. Future directions of OCT technology and their potential clinical uses are discussed. Recent findings Analysis of the choroidal thickness in healthy eyes and disease states such as age-related macular degeneration, central serous chorioretinopathy, diabetic retinopathy and inherited retinal dystrophies has been successfully achieved using SD-OCT devices with software improvements. Future OCT innovations such as longer-wavelength OCT systems including the swept-source technology, along with Doppler OCT and en-face imaging, may improve the detection of subtle microstructural changes in chorioretinal diseases by improving imaging of the choroid. Summary Advances in OCT technology provide for better understanding of pathogenesis, improved monitoring of progression and assistance in quantifying response to treatment modalities in diseases of the posterior segment of the eye. Further improvements in both hardware and software technologies should further advance the clinician’s ability to assess and manage chorioretinal diseases. PMID:23429598

New public dataset for spotting patterns in medieval document images

NASA Astrophysics Data System (ADS)

En, Sovann; Nicolas, Stéphane; Petitjean, Caroline; Jurie, Frédéric; Heutte, Laurent

2017-01-01

With advances in technology, a large part of our cultural heritage is becoming digitally available. In particular, in the field of historical document image analysis, there is now a growing need for indexing and data mining tools, thus allowing us to spot and retrieve the occurrences of an object of interest, called a pattern, in a large database of document images. Patterns may present some variability in terms of color, shape, or context, making the spotting of patterns a challenging task. Pattern spotting is a relatively new field of research, still hampered by the lack of available annotated resources. We present a new publicly available dataset named DocExplore dedicated to spotting patterns in historical document images. The dataset contains 1500 images and 1464 queries, and allows the evaluation of two tasks: image retrieval and pattern localization. A standardized benchmark protocol along with ad hoc metrics is provided for a fair comparison of the submitted approaches. We also provide some first results obtained with our baseline system on this new dataset, which show that there is room for improvement and that should encourage researchers of the document image analysis community to design new systems and submit improved results.

Molecular spectral imaging system for quantitative immunohistochemical analysis of early diabetic retinopathy.

PubMed

Li, Qingli; Zhang, Jingfa; Wang, Yiting; Xu, Guoteng

2009-12-01

A molecular spectral imaging system has been developed based on microscopy and spectral imaging technology. The system is capable of acquiring molecular spectral images from 400 nm to 800 nm with 2 nm wavelength increments. The basic principles, instrumental systems, and system calibration method as well as its applications for the calculation of the stain-uptake by tissues are introduced. As a case study, the system is used for determining the pathogenesis of diabetic retinopathy and evaluating the therapeutic effects of erythropoietin. Some molecular spectral images of retinal sections of normal, diabetic, and treated rats were collected and analyzed. The typical transmittance curves of positive spots stained for albumin and advanced glycation end products are retrieved from molecular spectral data with the spectral response calibration algorithm. To explore and evaluate the protective effect of erythropoietin (EPO) on retinal albumin leakage of streptozotocin-induced diabetic rats, an algorithm based on Beer-Lambert's law is presented. The algorithm can assess the uptake by histologic retinal sections of stains used in quantitative pathology to label albumin leakage and advanced glycation end products formation. Experimental results show that the system is helpful for the ophthalmologist to reveal the pathogenesis of diabetic retinopathy and explore the protective effect of erythropoietin on retinal cells of diabetic rats. It also highlights the potential of molecular spectral imaging technology to provide more effective and reliable diagnostic criteria in pathology.

Prospective comparison of magnetic resonance imaging to transient elastography and serum markers for liver fibrosis detection.

PubMed

Dyvorne, Hadrien A; Jajamovich, Guido H; Bane, Octavia; Fiel, M Isabel; Chou, Hsin; Schiano, Thomas D; Dieterich, Douglas; Babb, James S; Friedman, Scott L; Taouli, Bachir

2016-05-01

Establishing accurate non-invasive methods of liver fibrosis quantification remains a major unmet need. Here, we assessed the diagnostic value of a multiparametric magnetic resonance imaging (MRI) protocol including diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI and magnetic resonance elastography (MRE) in comparison with transient elastography (TE) and blood tests [including ELF (Enhanced Liver Fibrosis) and APRI] for liver fibrosis detection. In this single centre cross-sectional study, we prospectively enrolled 60 subjects with liver disease who underwent multiparametric MRI (DWI, DCE-MRI and MRE), TE and blood tests. Correlation was assessed between non-invasive modalities and histopathologic findings including stage, grade and collagen content, while accounting for covariates such as age, sex, BMI, HCV status and MRI-derived fat and iron content. ROC curve analysis evaluated the performance of each technique for detection of moderate-to-advanced liver fibrosis (F2-F4) and advanced fibrosis (F3-F4). Magnetic resonance elastography provided the strongest correlation with fibrosis stage (r = 0.66, P < 0.001), inflammation grade (r = 0.52, P < 0.001) and collagen content (r = 0.53, P = 0.036). For detection of moderate-to-advanced fibrosis (F2-F4), AUCs were 0.78, 0.82, 0.72, 0.79, 0.71 for MRE, TE, DCE-MRI, DWI and APRI, respectively. For detection of advanced fibrosis (F3-F4), AUCs were 0.94, 0.77, 0.79, 0.79 and 0.70, respectively. Magnetic resonance elastography provides the highest correlation with histopathologic markers and yields high diagnostic performance for detection of advanced liver fibrosis and cirrhosis, compared to DWI, DCE-MRI, TE and serum markers. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Towards advanced OCT clinical applications

NASA Astrophysics Data System (ADS)

Kirillin, Mikhail; Panteleeva, Olga; Agrba, Pavel; Pasukhin, Mikhail; Sergeeva, Ekaterina; Plankina, Elena; Dudenkova, Varvara; Gubarkova, Ekaterina; Kiseleva, Elena; Gladkova, Natalia; Shakhova, Natalia; Vitkin, Alex

2015-07-01

In this paper we report on our recent achievement in application of conventional and cross-polarization OCT (CP OCT) modalities for in vivo clinical diagnostics in different medical areas including gynecology, dermatology, and stomatology. In gynecology, CP OCT was employed for diagnosing fallopian tubes and cervix; in dermatology OCT for monitoring of treatment of psoriasis, scleroderma and atopic dermatitis; and in stomatology for diagnosis of oral diseases. For all considered application, we propose and develop different image processing methods which enhance the diagnostic value of the technique. In particular, we use histogram analysis, Fourier analysis and neural networks, thus calculating different tissue characteristics as revealed by OCT's polarization evolution. These approaches enable improved OCT image quantification and increase its resultant diagnostic accuracy.

Different methods of image segmentation in the process of meat marbling evaluation

NASA Astrophysics Data System (ADS)

Ludwiczak, A.; Ślósarz, P.; Lisiak, D.; Przybylak, A.; Boniecki, P.; Stanisz, M.; Koszela, K.; Zaborowicz, M.; Przybył, K.; Wojcieszak, D.; Janczak, D.; Bykowska, M.

2015-07-01

The level of marbling in meat assessment based on digital images is very popular, as computer vision tools are becoming more and more advanced. However considering muscle cross sections as the data source for marbling level evaluation, there are still a few problems to cope with. There is a need for an accurate method which would facilitate this evaluation procedure and increase its accuracy. The presented research was conducted in order to compare the effect of different image segmentation tools considering their usefulness in meat marbling evaluation on the muscle anatomical cross - sections. However this study is considered to be an initial trial in the presented field of research and an introduction to ultrasonic images processing and analysis.

Development of methods for the analysis of multi-mode TFM images

NASA Astrophysics Data System (ADS)

Sy, K.; Bredif, P.; Iakovleva, E.; Roy, O.; Lesselier, D.

2018-05-01

TFM (Total Focusing Method) is an advanced post-processing imaging algorithm of ultrasonic array data that shows good potential in defect detection and characterization. It can be employed using an infinite number of paths between transducer and focusing point. Depending upon the geometry and the characteristics of the defect in a given part, there are not the same modes that are appropriate for the defect reconstruction. Furthermore, non-physical indications can be observed, prone to misinterpretation. These imaging artifacts are due to the coexistence of several contributions involving several modes of propagation and interactions with possible defects and/or the geometry of the part. Two methods for filtering artifacts and reducing the number of TFM images are developed and illustrated.

A neotropical Miocene pollen database employing image-based search and semantic modeling1

PubMed Central

Han, Jing Ginger; Cao, Hongfei; Barb, Adrian; Punyasena, Surangi W.; Jaramillo, Carlos; Shyu, Chi-Ren

2014-01-01

• Premise of the study: Digital microscopic pollen images are being generated with increasing speed and volume, producing opportunities to develop new computational methods that increase the consistency and efficiency of pollen analysis and provide the palynological community a computational framework for information sharing and knowledge transfer. • Methods: Mathematical methods were used to assign trait semantics (abstract morphological representations) of the images of neotropical Miocene pollen and spores. Advanced database-indexing structures were built to compare and retrieve similar images based on their visual content. A Web-based system was developed to provide novel tools for automatic trait semantic annotation and image retrieval by trait semantics and visual content. • Results: Mathematical models that map visual features to trait semantics can be used to annotate images with morphology semantics and to search image databases with improved reliability and productivity. Images can also be searched by visual content, providing users with customized emphases on traits such as color, shape, and texture. • Discussion: Content- and semantic-based image searches provide a powerful computational platform for pollen and spore identification. The infrastructure outlined provides a framework for building a community-wide palynological resource, streamlining the process of manual identification, analysis, and species discovery. PMID:25202648

"Anatomy and imaging": 10 years of experience with an interdisciplinary teaching project in preclinical medical education - from an elective to a curricular course.

PubMed

Schober, A; Pieper, C C; Schmidt, R; Wittkowski, W

2014-05-01

Presentation of an interdisciplinary, interactive, tutor-based preclinical teaching project called "Anatomy and Imaging". Experience report, analysis of evaluation results and selective literature review. From 2001 to 2012, 618 students took the basic course (4 periods per week throughout the semester) and 316 took the advanced course (2 periods per week). We reviewed 557 (return rate 90.1 %) and 292 (92.4 %) completed evaluation forms of the basic and the advanced course. Results showed overall high satisfaction with the courses (1.33 and 1.56, respectively, on a 5-point Likert scale). The recognizability of the relevance of the course content for medical training, the promotion of the interest in medicine and the quality of the student tutors were evaluated especially positively. The "Anatomy and Imaging" teaching project is a successful concept for integrating medical imaging into the preclinical stage of medical education. The course was offered as part of the curriculum in 2013 for the first time. "Anatomia in mortuis" and "Anatomia in vivo" are not regarded as rivaling entities in the delivery of knowledge, but as complementary methods. © Georg Thieme Verlag KG Stuttgart · New York.

Studies in Leading and Organizing Schools. A Volume in Research and Theory in Educational Administration.

ERIC Educational Resources Information Center

Hoy, Wayne, Ed.; Miskel, Cecil, Ed.

This collection of research reports is intended to advance the understanding of schools through empirical study and theoretical analysis. The reports are as follows: "The Punctuated Equilibrium of National Reading Policy: Literacy's Changing Images and Venues" (Celia Sims and Cecil Miskel); "Productive Campus Leadership Responses to…

37 CFR 201.22 - Advance notices of potential infringement of works consisting of sounds, images, or both.

Code of Federal Regulations, 2012 CFR

2012-07-01

... infringement of works consisting of sounds, images, or both. 201.22 Section 201.22 Patents, Trademarks, and... Advance notices of potential infringement of works consisting of sounds, images, or both. (a) Definitions... after the first fixation of a work consisting of sounds, images, or both that is first fixed...

37 CFR 201.22 - Advance notices of potential infringement of works consisting of sounds, images, or both.

Code of Federal Regulations, 2013 CFR

2013-07-01

... infringement of works consisting of sounds, images, or both. 201.22 Section 201.22 Patents, Trademarks, and... Advance notices of potential infringement of works consisting of sounds, images, or both. (a) Definitions... after the first fixation of a work consisting of sounds, images, or both that is first fixed...

37 CFR 201.22 - Advance notices of potential infringement of works consisting of sounds, images, or both.

Code of Federal Regulations, 2011 CFR

2011-07-01

... infringement of works consisting of sounds, images, or both. 201.22 Section 201.22 Patents, Trademarks, and... Advance notices of potential infringement of works consisting of sounds, images, or both. (a) Definitions... after the first fixation of a work consisting of sounds, images, or both that is first fixed...

Experiments in electron microscopy: from metals to nerves

NASA Astrophysics Data System (ADS)

Unwin, Nigel

2015-04-01

Electron microscopy has advanced remarkably as a tool for biological structure research since the development of methods to examine radiation-sensitive unstained specimens and the introduction of cryo-techniques. Structures of biological molecules at near-atomic resolution can now be obtained from images of single particles as well as crystalline arrays. It has also become possible to analyze structures of molecules in their functional context, i.e. in their natural membrane or cellular setting, and in an ionic environment like that in living tissue. Electron microscopy is thus opening ways to answer definitively questions about physiological mechanisms. Here I recall a number of experiments contributing to, and benefiting from the technical advances that have taken place. I begin—in the spirit of this crystallography series—with some biographical background, and then sketch the path to an analysis by time-resolved microscopy of the opening mechanism of an ion channel (nicotinic acetylcholine receptor). This analysis illustrates how electron imaging can be combined with freeze-trapping to illuminate a transient biological event: in our case, chemical-to-electrical transduction at the nerve-muscle synapse.

Utility of high-altitude infrared spectral data in mineral exploration: Application to Northern Patagonia Mountains, Arizona

USGS Publications Warehouse

Berger, B.R.; King, T.V.V.; Morath, L.C.; Phillips, J.D.

2003-01-01

Synoptic views of hydrothermal alteration assemblages are of considerable utility in regional-scale minerals exploration. Recent advances in data acquisition and analysis technologies have greatly enhanced the usefulness of remotely sensed imaging spectroscopy for reliable alteration mineral assemblages mapping. Using NASA's Airborne Visible Infrared Imaging Spectrometer (AVIRIS) sensor, this study mapped large areas of advanced argillic and phyllic-argillic alteration assemblages in the southeastern Santa Rita and northern Patagonia mountains, Arizona. Two concealed porphyry copper deposits have been identified during past exploration, the Red Mountain and Sunnyside deposits, and related published hydrothermal alteration zoning studies allow the comparison of the results obtained from AVIRIS data to the more traditional field mapping approaches. The AVIRIS mapping compares favorably with field-based studies. An analysis of iron-bearing oxide minerals above a concealed supergene chalcocite deposit at Red Mountain also indicates that remotely sensed data can be of value in the interpretation of leached caps above porphyry copper deposits. In conjunction with other types of geophysical data, AVIRIS mineral maps can be used to discriminate different exploration targets within a region.

Soft X-ray and cathodoluminescence measurement, optimisation and analysis at liquid nitrogen temperatures

NASA Astrophysics Data System (ADS)

MacRae, C. M.; Wilson, N. C.; Torpy, A.; Delle Piane, C.

2018-01-01

Advances in field emission gun electron microprobes have led to significant gains in the beam power density and when analysis at high resolution is required then low voltages are often selected. The resulting beam power can lead to damage and this can be minimised by cooling the sample down to cryogenic temperatures allowing sub-micrometre imaging using a variety of spectrometers. Recent advances in soft X-ray emission spectrometers (SXES) offer a spectral tool to measure both chemistry and bonding and when combined with spectral cathodoluminescence the complementary techniques enable new knowledge to be gained from both mineral and materials. Magnesium and aluminium metals have been examined at both room and liquid nitrogen temperatures by SXES and the L-emission Fermi-edge has been observed to sharpen at the lower temperatures directly confirming thermal broadening of the X-ray spectra. Gains in emission intensity and resolution have been observed in cathodoluminescence for liquid nitrogen cooled quartz grains compared to ambient temperature quartz. This has enabled subtle growth features at quartz to quartz-cement boundaries to be imaged for the first time.

Forensic Science Research and Development at the National Institute of Justice: Opportunities in Applied Physics

NASA Astrophysics Data System (ADS)

Dutton, Gregory

Forensic science is a collection of applied disciplines that draws from all branches of science. A key question in forensic analysis is: to what degree do a piece of evidence and a known reference sample share characteristics? Quantification of similarity, estimation of uncertainty, and determination of relevant population statistics are of current concern. A 2016 PCAST report questioned the foundational validity and the validity in practice of several forensic disciplines, including latent fingerprints, firearms comparisons and DNA mixture interpretation. One recommendation was the advancement of objective, automated comparison methods based on image analysis and machine learning. These concerns parallel the National Institute of Justice's ongoing R&D investments in applied chemistry, biology and physics. NIJ maintains a funding program spanning fundamental research with potential for forensic application to the validation of novel instruments and methods. Since 2009, NIJ has funded over 179M in external research to support the advancement of accuracy, validity and efficiency in the forensic sciences. An overview of NIJ's programs will be presented, with examples of relevant projects from fluid dynamics, 3D imaging, acoustics, and materials science.

Instant electronic imaging systems are superior to Polaroid at detecting sight-threatening diabetic retinopathy.

PubMed

Ryder, R E; Kong, N; Bates, A S; Sim, J; Welch, J; Kritzinger, E E

1998-03-01

Polaroid photography in diabetic retinopathy screening allows instant image availability to enhance the results of ophthalmoscopy. Retinal cameras are now being developed which use video/digital imaging techniques to produce an instant enlarged retinal image on a computer monitor screen. We aimed to compare one such electronic imaging system, attached to a Canon CR5 45NM, with standard Polaroid retinal photography. Two hundred and thirteen eyes from 107 diabetic patients were photographed through dilated pupils by both systems in random order and the images were analysed blind. Diabetic retinopathy was present in 58 eyes of which 55/58 (95%) were detected on the electronic image and only 49/58 (84%) on the Polaroid. Of 34 eyes requiring ophthalmologist referral according to standard European criteria, 34/34 (100%) were detected on the electronic image and only 24/34 (71%) on the Polaroid. Side by side comparisons showed electronic imaging to be superior to Polaroid at lesion detection. Using linear analogue scales, the patients assessed the electronic imaging photographic flash as less uncomfortable than the Polaroid equivalent (p < 0.0001). Other advantages of electronic imaging include: ready storage of the images with other patient clinical data on the diabetes computerized register/database; potential for image enhancement and analysis using image analysis software and electronic transfer of images to ophthalmologist or general practitioner. Electronic imaging systems represent a potential major advance for the improvement of diabetic retinopathy screening.

Real-time MRI guidance of cardiac interventions.

PubMed

Campbell-Washburn, Adrienne E; Tavallaei, Mohammad A; Pop, Mihaela; Grant, Elena K; Chubb, Henry; Rhode, Kawal; Wright, Graham A

2017-10-01

Cardiac magnetic resonance imaging (MRI) is appealing to guide complex cardiac procedures because it is ionizing radiation-free and offers flexible soft-tissue contrast. Interventional cardiac MR promises to improve existing procedures and enable new ones for complex arrhythmias, as well as congenital and structural heart disease. Guiding invasive procedures demands faster image acquisition, reconstruction and analysis, as well as intuitive intraprocedural display of imaging data. Standard cardiac MR techniques such as 3D anatomical imaging, cardiac function and flow, parameter mapping, and late-gadolinium enhancement can be used to gather valuable clinical data at various procedural stages. Rapid intraprocedural image analysis can extract and highlight critical information about interventional targets and outcomes. In some cases, real-time interactive imaging is used to provide a continuous stream of images displayed to interventionalists for dynamic device navigation. Alternatively, devices are navigated relative to a roadmap of major cardiac structures generated through fast segmentation and registration. Interventional devices can be visualized and tracked throughout a procedure with specialized imaging methods. In a clinical setting, advanced imaging must be integrated with other clinical tools and patient data. In order to perform these complex procedures, interventional cardiac MR relies on customized equipment, such as interactive imaging environments, in-room image display, audio communication, hemodynamic monitoring and recording systems, and electroanatomical mapping and ablation systems. Operating in this sophisticated environment requires coordination and planning. This review provides an overview of the imaging technology used in MRI-guided cardiac interventions. Specifically, this review outlines clinical targets, standard image acquisition and analysis tools, and the integration of these tools into clinical workflow. 1 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2017;46:935-950. © 2017 International Society for Magnetic Resonance in Medicine.

A PC-based multispectral scanner data evaluation workstation: Application to Daedalus scanners

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; James, Mark W.; Smith, Matthew R.; Atkinson, Robert J.

1991-01-01

In late 1989, a personal computer (PC)-based data evaluation workstation was developed to support post flight processing of Multispectral Atmospheric Mapping Sensor (MAMS) data. The MAMS Quick View System (QVS) is an image analysis and display system designed to provide the capability to evaluate Daedalus scanner data immediately after an aircraft flight. Even in its original form, the QVS offered the portability of a personal computer with the advanced analysis and display features of a mainframe image analysis system. It was recognized, however, that the original QVS had its limitations, both in speed and processing of MAMS data. Recent efforts are presented that focus on overcoming earlier limitations and adapting the system to a new data tape structure. In doing so, the enhanced Quick View System (QVS2) will accommodate data from any of the four spectrometers used with the Daedalus scanner on the NASA ER2 platform. The QVS2 is designed around the AST 486/33 MHz CPU personal computer and comes with 10 EISA expansion slots, keyboard, and 4.0 mbytes of memory. Specialized PC-McIDAS software provides the main image analysis and display capability for the system. Image analysis and display of the digital scanner data is accomplished with PC-McIDAS software.

Updated MDRIZTAB Parameters for ACS/WFC

NASA Astrophysics Data System (ADS)

Hoffman, S. L.; Avila, R. J.

2017-03-01

The Mikulski Archive for Space Telescopes (MAST) pipeline performs geometric distortion corrections, associated image combinations, and cosmic ray rejections with AstroDrizzle. The MDRIZTAB reference table contains a list of relevant parameters that controls this program. This document details our photometric analysis of Advanced Camera for Surveys Wide Field Channel (ACS/WFC) data processed by AstroDrizzle. Based on this analysis, we update the MDRIZTAB table to improve the quality of the drizzled products delivered by MAST.

VERAView

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

Lee, Ronald W.; Collins, Benjamin S.; Godfrey, Andrew T.

2016-12-09

In order to support engineering analysis of Virtual Environment for Reactor Analysis (VERA) model results, the Consortium for Advanced Simulation of Light Water Reactors (CASL) needs a tool that provides visualizations of HDF5 files that adhere to the VERAOUT specification. VERAView provides an interactive graphical interface for the visualization and engineering analyses of output data from VERA. The Python-based software provides instantaneous 2D and 3D images, 1D plots, and alphanumeric data from VERA multi-physics simulations.

Advanced Spectroscopic and Thermal Imaging Instrumentation for Shock Tube and Ballistic Range Facilities

DTIC Science & Technology

2010-04-01

the development process, increase its quality and reduce development time through automation of synthesis, analysis or verification. For this purpose...made of time-non-deterministic systems, improving efficiency and reducing complexity of formal analysis . We also show how our theory relates to, and...of the most recent investigations for Earth and Mars atmospheres will be discussed in the following sections. 2.4.1 Earth: lunar return NASA’s

[Three-dimensional finite element study on the change of glossopharyngeum in patient with obstructive sleep apnea hypopnea syndrome during titrated mandible advancement].

PubMed

Yang, Suixing; Feng, Jing; Zhang, Zuo; Qu, Aili; Gong, Miao; Tang, Jie; Fan, Junheng; Li, Songqing; Zhao, Yanling

2013-04-01

To construct a three-dimensional finite element model of the upper airway and adjacent structure of an obstructive sleep apnea hypopnea syndrome (OSAHS) patient for biomechanical analysis. And to study the influence of glossopharyngeum of an OSAHS patient with three-dimensional finite element model during titrated mandible advancement. DICOM format image information of an OSAHS patient's upper airway was obtained by thin-section CT scanning and digital image processing were utilized to construct a three-dimensional finite element model by Mimics 10.0, Imageware 10.0 and Ansys software. The changes and the law of glossopharyngeum were observed by biomechanics and morphology after loading with titrated mandible advancement. A three-dimensional finite element model of the adjacent upper airway structure of OSAHS was established successfully. After loading, the transverse diameter of epiglottis tip of glossopharyngeum increased significantly, although the sagittal diameter decreased correspondingly. The principal stress was mainly distributed in anterior wall of the upper airway. The location of principal stress concentration did not change significantly with the increasing of distance. The stress of glossopharyngeum increased during titrated mandible advancement. A more precise three-dimensional finite model of upper airway and adjacent structure of an OSAHS patient is established and improved efficiency by Mimics, Imageware and Ansys software. The glossopharyngeum of finite element model of OSAHS is analyzed by titrated mandible advancement and can effectively show the relationship between mandible advancement and the glossopharyngeum.

Advanced imaging in acute stroke management-Part I: Computed tomographic.

PubMed

Saini, Monica; Butcher, Ken

2009-01-01

Neuroimaging is fundamental to stroke diagnosis and management. Non-contrast computed tomography (NCCT) has been the primary imaging modality utilized for this purpose for almost four decades. Although NCCT does permit identification of intracranial hemorrhage and parenchymal ischemic changes, insights into blood vessel patency and cerebral perfusion are limited. Advances in reperfusion strategies have made identification of potentially salvageable brain tissue a more practical concern. Advances in CT technology now permit identification of acute and chronic arterial lesions, as well as cerebral blood flow deficits. This review outlines principles of advanced CT image acquisition and its utility in acute stroke management.

Systematic Review on the Accuracy of Positron Emission Tomography/Computed Tomography and Positron Emission Tomography/Magnetic Resonance Imaging in the Management of Ovarian Cancer: Is Functional Information Really Needed?

PubMed Central

Suppiah, Subapriya; Chang, Wing Liong; Hassan, Hasyma Abu; Kaewput, Chalermrat; Asri, Andi Anggeriana Andi; Saad, Fathinul Fikri Ahmad; Nordin, Abdul Jalil; Vinjamuri, Sobhan

2017-01-01

Ovarian cancer (OC) often presents at an advanced stage with frequent relapses despite optimal treatment; thus, accurate staging and restaging are required for improving treatment outcomes and prognostication. Conventionally, staging of OC is performed using contrast-enhanced computed tomography (CT). Nevertheless, recent advances in the field of hybrid imaging have made positron emission tomography/CT (PET/CT) and PET/magnetic resonance imaging (PET/MRI) as emerging potential noninvasive imaging tools for improved management of OC. Several studies have championed the role of PET/CT for the detection of recurrence and prognostication of OC. We provide a systematic review and meta-analysis of the latest publications regarding the role of molecular imaging in the management of OC. We retrieved 57 original research articles with one article having overlap in both diagnosis and staging; 10 articles (734 patients) regarding the role of PET/CT in diagnosis of OC; 12 articles (604 patients) regarding staging of OC; 22 studies (1429 patients) for detection of recurrence; and 13 articles for prognostication and assessment of treatment response. We calculated pooled sensitivity and specificity of PET/CT performance in various aspects of imaging of OC. We also discussed the emerging role of PET/MRI in the management of OC. We aim to give the readers and objective overview on the role of molecular imaging in the management of OC. PMID:28670174

A comparison of diagnostic imaging ordering patterns between advanced practice clinicians and primary care physicians following office-based evaluation and management visits.

PubMed

Hughes, Danny R; Jiang, Miao; Duszak, Richard

2015-01-01

Little is known about the use of diagnostic testing, such as medical imaging, by advanced practice clinicians (APCs), specifically, nurse practitioners and physician assistants. To examine the use of diagnostic imaging ordered by APCs relative to that of primary care physicians (PCPs) following office-based encounters. Using 2010-2011 Medicare claims for a 5% sample of beneficiaries, we compared diagnostic imaging ordering between APC and PCP episodes of care, controlling for geographic variation, patient demographics, and Charlson Comorbidity Index scores. Provider specialty codes were used to identify PCPs and APCs (general practice, family practice, or internal medicine for PCP; nurse practitioner or physician assistant for APC). Episodes were constructed using evaluation and management (E&M) office visits without any claims 30 days prior to the index visit and (1) no claims at all within the subsequent 30 days; (2) no claims within the subsequent 30 days other than a single imaging event; or (3) claims for any nonimaging services in that subsequent 30-day period. The primary outcome was whether an imaging event followed a qualifying E&M visit. Advanced practice clinicians and PCPs ordered imaging in 2.8% and 1.9% episodes of care, respectively. In adjusted estimates and across all patient groups and imaging services, APCs were associated with more imaging than PCPs (odds ratio [OR], 1.34 [95% CI, 1.27-1.42]), ordering 0.3% more images per episode. Advanced practice clinicians were associated with increased radiography orders on both new (OR, 1.36 [95% CI, 1.13-1.66]) and established (OR, 1.33 [95% CI, 1.24-1.43]) patients, ordering 0.3% and 0.2% more images per episode of care, respectively. For advanced imaging, APCs were associated with increased imaging on established patients (OR, 1.28 [95% CI, 1.14-1.44]), ordering 0.1% more images, but were not significantly different from PCPs ordering imaging on new patients. Advanced practice clinicians are associated with more imaging services than PCPs for similar patients during E&M office visits. Expanding the use of APCs may alleviate PCP shortages. While increased use of imaging appears modest for individual patients, this increase may have ramifications on care and overall costs at the population level.

Hepatocellular carcinoma: Advances in diagnostic imaging.

PubMed

Sun, Haoran; Song, Tianqiang

2015-10-01

Thanks to the growing knowledge on biological behaviors of hepatocellular carcinomas (HCC), as well as continuous improvement in imaging techniques and experienced interpretation of imaging features of the nodules in cirrhotic liver, the detection and characterization of HCC has improved in the past decade. A number of practice guidelines for imaging diagnosis have been developed to reduce interpretation variability and standardize management of HCC, and they are constantly updated with advances in imaging techniques and evidence based data from clinical series. In this article, we strive to review the imaging techniques and the characteristic features of hepatocellular carcinoma associated with cirrhotic liver, with emphasis on the diagnostic value of advanced magnetic resonance imaging (MRI) techniques and utilization of hepatocyte-specific MRI contrast agents. We also briefly describe the concept of liver imaging reporting and data systems and discuss the consensus and controversy of major practice guidelines.

Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks.

PubMed

Islam, Jyoti; Zhang, Yanqing

2018-05-31

Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier detection of Alzheimer's disease can help with proper treatment and prevent brain tissue damage. Several statistical and machine learning models have been exploited by researchers for Alzheimer's disease diagnosis. Analyzing magnetic resonance imaging (MRI) is a common practice for Alzheimer's disease diagnosis in clinical research. Detection of Alzheimer's disease is exacting due to the similarity in Alzheimer's disease MRI data and standard healthy MRI data of older people. Recently, advanced deep learning techniques have successfully demonstrated human-level performance in numerous fields including medical image analysis. We propose a deep convolutional neural network for Alzheimer's disease diagnosis using brain MRI data analysis. While most of the existing approaches perform binary classification, our model can identify different stages of Alzheimer's disease and obtains superior performance for early-stage diagnosis. We conducted ample experiments to demonstrate that our proposed model outperformed comparative baselines on the Open Access Series of Imaging Studies dataset.

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

Recent Advances in Cardiac Computed Tomography: Dual Energy, Spectral and Molecular CT Imaging

PubMed Central

Danad, Ibrahim; Fayad, Zahi A.; Willemink, Martin J.; Min, James K.

2015-01-01

Computed tomography (CT) evolved into a powerful diagnostic tool and it is impossible to imagine current clinical practice without CT imaging. Due to its widespread availability, ease of clinical application, superb sensitivity for detection of CAD, and non-invasive nature, CT has become a valuable tool within the armamentarium of the cardiologist. In the last few years, numerous technological advances in CT have occurred—including dual energy CT (DECT), spectral CT and CT-based molecular imaging. By harnessing the advances in technology, cardiac CT has advanced beyond the mere evaluation of coronary stenosis to an imaging modality tool that permits accurate plaque characterization, assessment of myocardial perfusion and even probing of molecular processes that are involved in coronary atherosclerosis. Novel innovations in CT contrast agents and pre-clinical spectral CT devices have paved the way for CT-based molecular imaging. PMID:26068288

LLIMAS: Revolutionizing integrating modeling and analysis at MIT Lincoln Laboratory

NASA Astrophysics Data System (ADS)

Doyle, Keith B.; Stoeckel, Gerhard P.; Rey, Justin J.; Bury, Mark E.

2017-08-01

MIT Lincoln Laboratory's Integrated Modeling and Analysis Software (LLIMAS) enables the development of novel engineering solutions for advanced prototype systems through unique insights into engineering performance and interdisciplinary behavior to meet challenging size, weight, power, environmental, and performance requirements. LLIMAS is a multidisciplinary design optimization tool that wraps numerical optimization algorithms around an integrated framework of structural, thermal, optical, stray light, and computational fluid dynamics analysis capabilities. LLIMAS software is highly extensible and has developed organically across a variety of technologies including laser communications, directed energy, photometric detectors, chemical sensing, laser radar, and imaging systems. The custom software architecture leverages the capabilities of existing industry standard commercial software and supports the incorporation of internally developed tools. Recent advances in LLIMAS's Structural-Thermal-Optical Performance (STOP), aeromechanical, and aero-optical capabilities as applied to Lincoln prototypes are presented.

Adipose Tissue Quantification by Imaging Methods: A Proposed Classification

PubMed Central

Shen, Wei; Wang, ZiMian; Punyanita, Mark; Lei, Jianbo; Sinav, Ahmet; Kral, John G.; Imielinska, Celina; Ross, Robert; Heymsfield, Steven B.

2007-01-01

Recent advances in imaging techniques and understanding of differences in the molecular biology of adipose tissue has rendered classical anatomy obsolete, requiring a new classification of the topography of adipose tissue. Adipose tissue is one of the largest body compartments, yet a classification that defines specific adipose tissue depots based on their anatomic location and related functions is lacking. The absence of an accepted taxonomy poses problems for investigators studying adipose tissue topography and its functional correlates. The aim of this review was to critically examine the literature on imaging of whole body and regional adipose tissue and to create the first systematic classification of adipose tissue topography. Adipose tissue terminology was examined in over 100 original publications. Our analysis revealed inconsistencies in the use of specific definitions, especially for the compartment termed “visceral” adipose tissue. This analysis leads us to propose an updated classification of total body and regional adipose tissue, providing a well-defined basis for correlating imaging studies of specific adipose tissue depots with molecular processes. PMID:12529479

Advances in fMRI Real-Time Neurofeedback.

PubMed

Watanabe, Takeo; Sasaki, Yuka; Shibata, Kazuhisa; Kawato, Mitsuo

2017-12-01

Functional magnetic resonance imaging (fMRI) neurofeedback is a type of biofeedback in which real-time online fMRI signals are used to self-regulate brain function. Since its advent in 2003 significant progress has been made in fMRI neurofeedback techniques. Specifically, the use of implicit protocols, external rewards, multivariate analysis, and connectivity analysis has allowed neuroscientists to explore a possible causal involvement of modified brain activity in modified behavior. These techniques have also been integrated into groundbreaking new neurofeedback technologies, specifically decoded neurofeedback (DecNef) and functional connectivity-based neurofeedback (FCNef). By modulating neural activity and behavior, DecNef and FCNef have substantially advanced both basic and clinical research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Treatment of developmental stress disorder: mind, body and brain - analysis and pharmacology coupled.

PubMed

McFadden, Joseph

2017-11-01

The schism between psychiatry, psychology and analysis, while long present, has widened even more in the past half-century with the advances in psychopharmacology. With the advances in electronic brain imaging, particularly in developmental and post-traumatic stress disorders, there has emerged both an understanding of brain changes resulting from severe, chronic stress and an ability to target brain chemistry in ways that can relieve clinical symptomatology. The use of alpha-1 adrenergic brain receptor antagonists decreases many of the manifestations of PTSD. Additionally, this paper discusses the ways in which dreaming, thinking and the analytic process are facilitated with this concomitant treatment and hypervigilence and hyper-arousal states are signficiantly decreased. © 2017, The Society of Analytical Psychology.

Advanced astigmatism-corrected Czerny-Turner imaging spectrometer in spectral broadband

NASA Astrophysics Data System (ADS)

Cong, Hai-fang

2014-12-01

This paper reports an advanced Czerny-Turner optical structure which is used for the application in imaging spectrometers. To obtain the excellent imaging quality, a cylindrical lens with a wedge angle is used between the focusing mirror and the imaging plane to remove astigmatism in broadband. It makes the advanced optical system presents high resolution over the full bandwidth and decreases the cost. An example of the imaging spectrometer in the waveband of 260nm~520nm has been designed to prove our theory. It yields the excellent modulation transfer functions (MTF) of all fields of view which are more than 0.75 over the broadband under the required Nyquist frequency (20lp/mm).

Age, Sex, and Racial Differences in Neuroimaging Use in Acute Stroke: A Population-Based Study.

PubMed

Vagal, A; Sanelli, P; Sucharew, H; Alwell, K A; Khoury, J C; Khatri, P; Woo, D; Flaherty, M; Kissela, B M; Adeoye, O; Ferioli, S; De Los Rios La Rosa, F; Martini, S; Mackey, J; Kleindorfer, D

2017-10-01

Limited information is available regarding differences in neuroimaging use for acute stroke work-up. Our objective was to assess whether race, sex, or age differences exist in neuroimaging use and whether these differences depend on the care center type in a population-based study. Patients with stroke (ischemic and hemorrhagic) and transient ischemic attack were identified in a metropolitan, biracial population using the Greater Cincinnati/Northern Kentucky Stroke Study in 2005 and 2010. Multivariable regression was used to determine the odds of advanced imaging use (CT angiography/MR imaging/MR angiography) for race, sex, and age. In 2005 and 2010, there were 3471 and 3431 stroke/TIA events, respectively. If one adjusted for covariates, the odds of advanced imaging were higher for younger (55 years or younger) compared with older patients, blacks compared with whites, and patients presenting to an academic center and those seen by a stroke team or neurologist. The observed association between race and advanced imaging depended on age; in the older age group, blacks had higher odds of advanced imaging compared with whites (odds ratio, 1.34; 95% CI, 1.12-1.61; P < .01), and in the younger group, the association between race and advanced imaging was not statistically significant. Age by race interaction persisted in the academic center subgroup ( P < .01), but not in the nonacademic center subgroup ( P = .58). No significant association was found between sex and advanced imaging. Within a large, biracial stroke/TIA population, there is variation in the use of advanced neuroimaging by age and race, depending on the care center type. © 2017 by American Journal of Neuroradiology.

Advanced imaging programs: maximizing a multislice CT investment.

PubMed

Falk, Robert

2008-01-01

Advanced image processing has moved from a luxury to a necessity in the practice of medicine. A hospital's adoption of sophisticated 3D imaging entails several important steps with many factors to consider in order to be successful. Like any new hospital program, 3D post-processing should be introduced through a strategic planning process that includes administrators, physicians, and technologists to design, implement, and market a program that is scalable-one that minimizes up front costs while providing top level service. This article outlines the steps for planning, implementation, and growth of an advanced imaging program.

Objects Grouping for Segmentation of Roads Network in High Resolution Images of Urban Areas

NASA Astrophysics Data System (ADS)

Maboudi, M.; Amini, J.; Hahn, M.

2016-06-01

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors - as the main source of large scale mapping applications - was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of "Object-based Image Analysis (OBIA)" as an alternative to pixel-based image analysis methods. Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

Collaborative classification of hyperspectral and visible images with convolutional neural network

NASA Astrophysics Data System (ADS)

Zhang, Mengmeng; Li, Wei; Du, Qian

2017-10-01

Recent advances in remote sensing technology have made multisensor data available for the same area, and it is well-known that remote sensing data processing and analysis often benefit from multisource data fusion. Specifically, low spatial resolution of hyperspectral imagery (HSI) degrades the quality of the subsequent classification task while using visible (VIS) images with high spatial resolution enables high-fidelity spatial analysis. A collaborative classification framework is proposed to fuse HSI and VIS images for finer classification. First, the convolutional neural network model is employed to extract deep spectral features for HSI classification. Second, effective binarized statistical image features are learned as contextual basis vectors for the high-resolution VIS image, followed by a classifier. The proposed approach employs diversified data in a decision fusion, leading to an integration of the rich spectral information, spatial information, and statistical representation information. In particular, the proposed approach eliminates the potential problems of the curse of dimensionality and excessive computation time. The experiments evaluated on two standard data sets demonstrate better classification performance offered by this framework.

Perceptual security of encrypted images based on wavelet scaling analysis

NASA Astrophysics Data System (ADS)

Vargas-Olmos, C.; Murguía, J. S.; Ramírez-Torres, M. T.; Mejía Carlos, M.; Rosu, H. C.; González-Aguilar, H.

2016-08-01

The scaling behavior of the pixel fluctuations of encrypted images is evaluated by using the detrended fluctuation analysis based on wavelets, a modern technique that has been successfully used recently for a wide range of natural phenomena and technological processes. As encryption algorithms, we use the Advanced Encryption System (AES) in RBT mode and two versions of a cryptosystem based on cellular automata, with the encryption process applied both fully and partially by selecting different bitplanes. In all cases, the results show that the encrypted images in which no understandable information can be visually appreciated and whose pixels look totally random present a persistent scaling behavior with the scaling exponent α close to 0.5, implying no correlation between pixels when the DFA with wavelets is applied. This suggests that the scaling exponents of the encrypted images can be used as a perceptual security criterion in the sense that when their values are close to 0.5 (the white noise value) the encrypted images are more secure also from the perceptual point of view.

Noncontact optical motion sensing for real-time analysis

NASA Astrophysics Data System (ADS)

Fetzer, Bradley R.; Imai, Hiromichi

1990-08-01

The adaptation of an image dissector tube (IDT) within the OPTFOLLOW system provides high resolution displacement measurement of a light discontinuity. Due to the high speed response of the IDT and the advanced servo loop circuitry, the system is capable of real time analysis of the object under test. The image of the discontinuity may be contoured by direct or reflected light and ranges spectrally within the field of visible light. The image is monitored to 500 kHz through a lens configuration which transposes the optical image upon the photocathode of the IDT. The photoelectric effect accelerates the resultant electrons through a photomultiplier and an enhanced current is emitted from the anode. A servo loop controls the electron beam, continually centering it within the IDT using magnetic focusing of deflection coils. The output analog voltage from the servo amplifier is thereby proportional to the displacement of the target. The system is controlled by a microprocessor with a 32kbyte memory and provides a digital display as well as instructional readout on a color monitor allowing for offset image tracking and automatic system calibration.

Classification of river water pollution using Hyperion data

NASA Astrophysics Data System (ADS)

Kar, Soumyashree; Rathore, V. S.; Champati ray, P. K.; Sharma, Richa; Swain, S. K.

2016-06-01

A novel attempt is made to use hyperspectral remote sensing to identify the spatial variability of metal pollutants present in river water. It was also attempted to classify the hyperspectral image - Earth Observation-1 (EO-1) Hyperion data of an 8 km stretch of the river Yamuna, near Allahabad city in India depending on its chemical composition. For validating image analysis results, a total of 10 water samples were collected and chemically analyzed using Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Two different spectral libraries from field and image data were generated for the 10 sample locations. Advanced per-pixel supervised classifications such as Spectral Angle Mapper (SAM), SAM target finder using BandMax and Support Vector Machine (SVM) were carried out along with the unsupervised clustering procedure - Iterative Self-Organizing Data Analysis Technique (ISODATA). The results were compared and assessed with respect to ground data. Analytical Spectral Devices (ASD), Inc. spectroradiometer, FieldSpec 4 was used to generate the spectra of the water samples which were compiled into a spectral library and used for Spectral Absorption Depth (SAD) analysis. The spectral depth pattern of image and field spectral libraries was found to be highly correlated (correlation coefficient, R2 = 0.99) which validated the image analysis results with respect to the ground data. Further, we carried out a multivariate regression analysis to assess the varying concentrations of metal ions present in water based on the spectral depth of the corresponding absorption feature. Spectral Absorption Depth (SAD) analysis along with metal analysis of field data revealed the order in which the metals affected the river pollution, which was in conformity with the findings of Central Pollution Control Board (CPCB). Therefore, it is concluded that hyperspectral imaging provides opportunity that can be used for satellite based remote monitoring of water quality from space.

Analysis of S-box in Image Encryption Using Root Mean Square Error Method

NASA Astrophysics Data System (ADS)

Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan

2012-07-01

The use of substitution boxes (S-boxes) in encryption applications has proven to be an effective nonlinear component in creating confusion and randomness. The S-box is evolving and many variants appear in literature, which include advanced encryption standard (AES) S-box, affine power affine (APA) S-box, Skipjack S-box, Gray S-box, Lui J S-box, residue prime number S-box, Xyi S-box, and S8 S-box. These S-boxes have algebraic and statistical properties which distinguish them from each other in terms of encryption strength. In some circumstances, the parameters from algebraic and statistical analysis yield results which do not provide clear evidence in distinguishing an S-box for an application to a particular set of data. In image encryption applications, the use of S-boxes needs special care because the visual analysis and perception of a viewer can sometimes identify artifacts embedded in the image. In addition to existing algebraic and statistical analysis already used for image encryption applications, we propose an application of root mean square error technique, which further elaborates the results and enables the analyst to vividly distinguish between the performances of various S-boxes. While the use of the root mean square error analysis in statistics has proven to be effective in determining the difference in original data and the processed data, its use in image encryption has shown promising results in estimating the strength of the encryption method. In this paper, we show the application of the root mean square error analysis to S-box image encryption. The parameters from this analysis are used in determining the strength of S-boxes

Spatial information technologies for remote sensing today and tomorrow; Proceedings of the Ninth Pecora Symposium, Sioux Falls, SD, October 2-4, 1984

NASA Technical Reports Server (NTRS)

1984-01-01

Topics discussed at the symposium include hardware, geographic information system (GIS) implementation, processing remotely sensed data, spatial data structures, and NASA programs in remote sensing information systems. Attention is also given GIS applications, advanced techniques, artificial intelligence, graphics, spatial navigation, and classification. Papers are included on the design of computer software for geographic image processing, concepts for a global resource information system, algorithm development for spatial operators, and an application of expert systems technology to remotely sensed image analysis.

Improved automatic adjustment of density and contrast in FCR system using neural network

NASA Astrophysics Data System (ADS)

Takeo, Hideya; Nakajima, Nobuyoshi; Ishida, Masamitsu; Kato, Hisatoyo

1994-05-01

FCR system has an automatic adjustment of image density and contrast by analyzing the histogram of image data in the radiation field. Advanced image recognition methods proposed in this paper can improve the automatic adjustment performance, in which neural network technology is used. There are two methods. Both methods are basically used 3-layer neural network with back propagation. The image data are directly input to the input-layer in one method and the histogram data is input in the other method. The former is effective to the imaging menu such as shoulder joint in which the position of interest region occupied on the histogram changes by difference of positioning and the latter is effective to the imaging menu such as chest-pediatrics in which the histogram shape changes by difference of positioning. We experimentally confirm the validity of these methods (about the automatic adjustment performance) as compared with the conventional histogram analysis methods.

Technologies for imaging neural activity in large volumes

PubMed Central

Ji, Na; Freeman, Jeremy; Smith, Spencer L.

2017-01-01

Neural circuitry has evolved to form distributed networks that act dynamically across large volumes. Collecting data from individual planes, conventional microscopy cannot sample circuitry across large volumes at the temporal resolution relevant to neural circuit function and behaviors. Here, we review emerging technologies for rapid volume imaging of neural circuitry. We focus on two critical challenges: the inertia of optical systems, which limits image speed, and aberrations, which restrict the image volume. Optical sampling time must be long enough to ensure high-fidelity measurements, but optimized sampling strategies and point spread function engineering can facilitate rapid volume imaging of neural activity within this constraint. We also discuss new computational strategies for the processing and analysis of volume imaging data of increasing size and complexity. Together, optical and computational advances are providing a broader view of neural circuit dynamics, and help elucidate how brain regions work in concert to support behavior. PMID:27571194

Slice-to-volume medical image registration: A survey.

PubMed

Ferrante, Enzo; Paragios, Nikos

2017-07-01

During the last decades, the research community of medical imaging has witnessed continuous advances in image registration methods, which pushed the limits of the state-of-the-art and enabled the development of novel medical procedures. A particular type of image registration problem, known as slice-to-volume registration, played a fundamental role in areas like image guided surgeries and volumetric image reconstruction. However, to date, and despite the extensive literature available on this topic, no survey has been written to discuss this challenging problem. This paper introduces the first comprehensive survey of the literature about slice-to-volume registration, presenting a categorical study of the algorithms according to an ad-hoc taxonomy and analyzing advantages and disadvantages of every category. We draw some general conclusions from this analysis and present our perspectives on the future of the field. Copyright © 2017 Elsevier B.V. All rights reserved.

Image understanding and the man-machine interface II; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

NASA Technical Reports Server (NTRS)

Barrett, Eamon B. (Editor); Pearson, James J. (Editor)

1989-01-01

Image understanding concepts and models, image understanding systems and applications, advanced digital processors and software tools, and advanced man-machine interfaces are among the topics discussed. Particular papers are presented on such topics as neural networks for computer vision, object-based segmentation and color recognition in multispectral images, the application of image algebra to image measurement and feature extraction, and the integration of modeling and graphics to create an infrared signal processing test bed.

Quantifying and visualizing variations in sets of images using continuous linear optimal transport

NASA Astrophysics Data System (ADS)

Kolouri, Soheil; Rohde, Gustavo K.

2014-03-01

Modern advancements in imaging devices have enabled us to explore the subcellular structure of living organisms and extract vast amounts of information. However, interpreting the biological information mined in the captured images is not a trivial task. Utilizing predetermined numerical features is usually the only hope for quantifying this information. Nonetheless, direct visual or biological interpretation of results obtained from these selected features is non-intuitive and difficult. In this paper, we describe an automatic method for modeling visual variations in a set of images, which allows for direct visual interpretation of the most significant differences, without the need for predefined features. The method is based on a linearized version of the continuous optimal transport (OT) metric, which provides a natural linear embedding for the image data set, in which linear combination of images leads to a visually meaningful image. This enables us to apply linear geometric data analysis techniques such as principal component analysis and linear discriminant analysis in the linearly embedded space and visualize the most prominent modes, as well as the most discriminant modes of variations, in the dataset. Using the continuous OT framework, we are able to analyze variations in shape and texture in a set of images utilizing each image at full resolution, that otherwise cannot be done by existing methods. The proposed method is applied to a set of nuclei images segmented from Feulgen stained liver tissues in order to investigate the major visual differences in chromatin distribution of Fetal-Type Hepatoblastoma (FHB) cells compared to the normal cells.

Digital Rocks Portal: a sustainable platform for imaged dataset sharing, translation and automated analysis

NASA Astrophysics Data System (ADS)

Prodanovic, M.; Esteva, M.; Hanlon, M.; Nanda, G.; Agarwal, P.

2015-12-01

Recent advances in imaging have provided a wealth of 3D datasets that reveal pore space microstructure (nm to cm length scale) and allow investigation of nonlinear flow and mechanical phenomena from first principles using numerical approaches. This framework has popularly been called "digital rock physics". Researchers, however, have trouble storing and sharing the datasets both due to their size and the lack of standardized image types and associated metadata for volumetric datasets. This impedes scientific cross-validation of the numerical approaches that characterize large scale porous media properties, as well as development of multiscale approaches required for correct upscaling. A single research group typically specializes in an imaging modality and/or related modeling on a single length scale, and lack of data-sharing infrastructure makes it difficult to integrate different length scales. We developed a sustainable, open and easy-to-use repository called the Digital Rocks Portal, that (1) organizes images and related experimental measurements of different porous materials, (2) improves access to them for a wider community of geosciences or engineering researchers not necessarily trained in computer science or data analysis. Once widely accepter, the repository will jumpstart productivity and enable scientific inquiry and engineering decisions founded on a data-driven basis. This is the first repository of its kind. We show initial results on incorporating essential software tools and pipelines that make it easier for researchers to store and reuse data, and for educators to quickly visualize and illustrate concepts to a wide audience. For data sustainability and continuous access, the portal is implemented within the reliable, 24/7 maintained High Performance Computing Infrastructure supported by the Texas Advanced Computing Center (TACC) at the University of Texas at Austin. Long-term storage is provided through the University of Texas System Research Cyber-infrastructure initiative.

3D Printing and Digital Rock Physics for Geomaterials

NASA Astrophysics Data System (ADS)

Martinez, M. J.; Yoon, H.; Dewers, T. A.

2015-12-01

Imaging techniques for the analysis of porous structures have revolutionized our ability to quantitatively characterize geomaterials. Digital representations of rock from CT images and physics modeling based on these pore structures provide the opportunity to further advance our quantitative understanding of fluid flow, geomechanics, and geochemistry, and the emergence of coupled behaviors. Additive manufacturing, commonly known as 3D printing, has revolutionized production of custom parts with complex internal geometries. For the geosciences, recent advances in 3D printing technology may be co-opted to print reproducible porous structures derived from CT-imaging of actual rocks for experimental testing. The use of 3D printed microstructure allows us to surmount typical problems associated with sample-to-sample heterogeneity that plague rock physics testing and to test material response independent from pore-structure variability. Together, imaging, digital rocks and 3D printing potentially enables a new workflow for understanding coupled geophysical processes in a real, but well-defined setting circumventing typical issues associated with reproducibility, enabling full characterization and thus connection of physical phenomena to structure. In this talk we will discuss the possibilities that these technologies can bring to geosciences and present early experiences with coupled multiscale experimental and numerical analysis using 3D printed fractured rock specimens. In particular, we discuss the processes of selection and printing of transparent fractured specimens based on 3D reconstruction of micro-fractured rock to study fluid flow characterization and manipulation. Micro-particle image velocimetry is used to directly visualize 3D single and multiphase flow velocity in 3D fracture networks. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Statistical performance of image cytometry for DNA, lipids, cytokeratin, & CD45 in a model system for circulation tumor cell detection.

PubMed

Futia, Gregory L; Schlaepfer, Isabel R; Qamar, Lubna; Behbakht, Kian; Gibson, Emily A

2017-07-01

Detection of circulating tumor cells (CTCs) in a blood sample is limited by the sensitivity and specificity of the biomarker panel used to identify CTCs over other blood cells. In this work, we present Bayesian theory that shows how test sensitivity and specificity set the rarity of cell that a test can detect. We perform our calculation of sensitivity and specificity on our image cytometry biomarker panel by testing on pure disease positive (D + ) populations (MCF7 cells) and pure disease negative populations (D - ) (leukocytes). In this system, we performed multi-channel confocal fluorescence microscopy to image biomarkers of DNA, lipids, CD45, and Cytokeratin. Using custom software, we segmented our confocal images into regions of interest consisting of individual cells and computed the image metrics of total signal, second spatial moment, spatial frequency second moment, and the product of the spatial-spatial frequency moments. We present our analysis of these 16 features. The best performing of the 16 features produced an average separation of three standard deviations between D + and D - and an average detectable rarity of ∼1 in 200. We performed multivariable regression and feature selection to combine multiple features for increased performance and showed an average separation of seven standard deviations between the D + and D - populations making our average detectable rarity of ∼1 in 480. Histograms and receiver operating characteristics (ROC) curves for these features and regressions are presented. We conclude that simple regression analysis holds promise to further improve the separation of rare cells in cytometry applications. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Optimisation of quantitative lung SPECT applied to mild COPD: a software phantom simulation study.

PubMed

Norberg, Pernilla; Olsson, Anna; Alm Carlsson, Gudrun; Sandborg, Michael; Gustafsson, Agnetha

2015-01-01

The amount of inhomogeneities in a (99m)Tc Technegas single-photon emission computed tomography (SPECT) lung image, caused by reduced ventilation in lung regions affected by chronic obstructive pulmonary disease (COPD), is correlated to disease advancement. A quantitative analysis method, the CVT method, measuring these inhomogeneities was proposed in earlier work. To detect mild COPD, which is a difficult task, optimised parameter values are needed. In this work, the CVT method was optimised with respect to the parameter values of acquisition, reconstruction and analysis. The ordered subset expectation maximisation (OSEM) algorithm was used for reconstructing the lung SPECT images. As a first step towards clinical application of the CVT method in detecting mild COPD, this study was based on simulated SPECT images of an advanced anthropomorphic lung software phantom including respiratory and cardiac motion, where the mild COPD lung had an overall ventilation reduction of 5%. The best separation between healthy and mild COPD lung images as determined using the CVT measure of ventilation inhomogeneity and 125 MBq (99m)Tc was obtained using a low-energy high-resolution collimator (LEHR) and a power 6 Butterworth post-filter with a cutoff frequency of 0.6 to 0.7 cm(-1). Sixty-four reconstruction updates and a small kernel size should be used when the whole lung is analysed, and for the reduced lung a greater number of updates and a larger kernel size are needed. A LEHR collimator and 125 (99m)Tc MBq together with an optimal combination of cutoff frequency, number of updates and kernel size, gave the best result. Suboptimal selections of either cutoff frequency, number of updates and kernel size will reduce the imaging system's ability to detect mild COPD in the lung phantom.

Thermal Characterization of Defects in Aircraft Structures Via Spatially Controlled Heat Application

NASA Technical Reports Server (NTRS)

Cramer, K. Elliott; Winfree, William P.

1997-01-01

Recent advances in thermal imaging technology have spawned a number of new thermal NDE techniques that provide quantitative information about flaws in aircraft structures. Thermography has a number of advantages as an inspection technique. It is a totally noncontacting, nondestructive, imaging technology capable of inspecting a large area in a matter of a few seconds. The development of fast, inexpensive image processors have aided in the attractiveness of thermography as an NDE technique. These image processors have increased the signal to noise ratio of thermography and facilitated significant advances in post-processing. The resulting digital images enable archival records for comparison with later inspections thus providing a means of monitoring the evolution of damage in a particular structure. The National Aeronautics and Space Administration's Langley Research Center has developed a thermal NDE technique designed to image a number of potential flaws in aircraft structures. The technique involves injecting a small, spatially controlled heat flux into the outer surface of an aircraft. Images of fatigue cracking, bond integrity and material loss due to corrosion are generated from measurements of the induced surface temperature variations. This paper will present a discussion of the development of the thermal imaging system as well as the techniques used to analyze the resulting thermal images. Spatial tailoring of the heat coupled with the analysis techniques represent a significant improvement in the delectability of flaws over conventional thermal imaging. Results of laboratory experiments on fabricated crack, disbond and material loss samples will be presented to demonstrate the capabilities of the technique. An integral part of the development of this technology is the use of analytic and computational modeling. The experimental results will be compared with these models to demonstrate the utility of such an approach.

Multi-channel pre-beamformed data acquisition system for research on advanced ultrasound imaging methods.

PubMed

Cheung, Chris C P; Yu, Alfred C H; Salimi, Nazila; Yiu, Billy Y S; Tsang, Ivan K H; Kerby, Benjamin; Azar, Reza Zahiri; Dickie, Kris

2012-02-01

The lack of open access to the pre-beamformed data of an ultrasound scanner has limited the research of novel imaging methods to a few privileged laboratories. To address this need, we have developed a pre-beamformed data acquisition (DAQ) system that can collect data over 128 array elements in parallel from the Ultrasonix series of research-purpose ultrasound scanners. Our DAQ system comprises three system-level blocks: 1) a connector board that interfaces with the array probe and the scanner through a probe connector port; 2) a main board that triggers DAQ and controls data transfer to a computer; and 3) four receiver boards that are each responsible for acquiring 32 channels of digitized raw data and storing them to the on-board memory. This system can acquire pre-beamformed data with 12-bit resolution when using a 40-MHz sampling rate. It houses a 16 GB RAM buffer that is sufficient to store 128 channels of pre-beamformed data for 8000 to 25 000 transmit firings, depending on imaging depth; corresponding to nearly a 2-s period in typical imaging setups. Following the acquisition, the data can be transferred through a USB 2.0 link to a computer for offline processing and analysis. To evaluate the feasibility of using the DAQ system for advanced imaging research, two proof-of-concept investigations have been conducted on beamforming and plane-wave B-flow imaging. Results show that adaptive beamforming algorithms such as the minimum variance approach can generate sharper images of a wire cross-section whose diameter is equal to the imaging wavelength (150 μm in our example). Also, planewave B-flow imaging can provide more consistent visualization of blood speckle movement given the higher temporal resolution of this imaging approach (2500 fps in our example).

Reliability analysis of the epidural spinal cord compression scale.

PubMed

Bilsky, Mark H; Laufer, Ilya; Fourney, Daryl R; Groff, Michael; Schmidt, Meic H; Varga, Peter Paul; Vrionis, Frank D; Yamada, Yoshiya; Gerszten, Peter C; Kuklo, Timothy R

2010-09-01

The evolution of imaging techniques, along with highly effective radiation options has changed the way metastatic epidural tumors are treated. While high-grade epidural spinal cord compression (ESCC) frequently serves as an indication for surgical decompression, no consensus exists in the literature about the precise definition of this term. The advancement of the treatment paradigms in patients with metastatic tumors for the spine requires a clear grading scheme of ESCC. The degree of ESCC often serves as a major determinant in the decision to operate or irradiate. The purpose of this study was to determine the reliability and validity of a 6-point, MR imaging-based grading system for ESCC. To determine the reliability of the grading scale, a survey was distributed to 7 spine surgeons who participate in the Spine Oncology Study Group. The MR images of 25 cervical or thoracic spinal tumors were distributed consisting of 1 sagittal image and 3 axial images at the identical level including T1-weighted, T2-weighted, and Gd-enhanced T1-weighted images. The survey was administered 3 times at 2-week intervals. The inter- and intrarater reliability was assessed. The inter- and intrarater reliability ranged from good to excellent when surgeons were asked to rate the degree of spinal cord compression using T2-weighted axial images. The T2-weighted images were superior indicators of ESCC compared with T1-weighted images with and without Gd. The ESCC scale provides a valid and reliable instrument that may be used to describe the degree of ESCC based on T2-weighted MR images. This scale accounts for recent advances in the treatment of spinal metastases and may be used to provide an ESCC classification scheme for multicenter clinical trial and outcome studies.

Wavelet Analysis of SAR Images for Coastal Monitoring

NASA Technical Reports Server (NTRS)

Liu, Antony K.; Wu, Sunny Y.; Tseng, William Y.; Pichel, William G.

1998-01-01

The mapping of mesoscale ocean features in the coastal zone is a major potential application for satellite data. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ice edge can be tracked by the wavelet analysis using satellite data from repeating paths. The wavelet transform has been applied to satellite images, such as those from Synthetic Aperture Radar (SAR), Advanced Very High-Resolution Radiometer (AVHRR), and ocean color sensor for feature extraction. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite SAR imagery employing wavelet analysis have been developed. Case studies on two major coastal oil spills have been investigated using wavelet analysis for tracking along the coast of Uruguay (February 1997), and near Point Barrow, Alaska (November 1997). Comparison of SAR images with SeaWiFS (Sea-viewing Wide Field-of-view Sensor) data for coccolithophore bloom in the East Bering Sea during the fall of 1997 shows a good match on bloom boundary. This paper demonstrates that this technique is a useful and promising tool for monitoring of coastal waters.

An atlas of the (near) future: cognitive computing applications for medical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

LeGrand, Anne

2017-02-01

The role of medical imaging in global health systems is literally fundamental. Like labs, medical images are used at one point or another in almost every high cost, high value episode of care. CT scans, mammograms, and x-rays, for example, "atlas" the body and help chart a course forward for a patient's care team. Imaging precision has improved as a result of technological advancements and breakthroughs in related medical research. Those advancements also bring with them exponential growth in medical imaging data. As IBM trains Watson to "see" medical images, Ms. Le Grand will discuss recent advances made by Watson Health and explore the potential value of "augmented intelligence" to assist healthcare providers like radiologists and cardiologists, as well as the patients they serve.

Nanoparticles and Radiotracers: Advances toward Radio-Nanomedicine

PubMed Central

Pratt, Edwin C.; Shaffer, Travis M.; Grimm, Jan

2016-01-01

Here, we cover the convergence of radiochemistry for imaging and therapy with advances in nanoparticle (NP) design for biomedical applications. We first explore NP properties relevant for therapy and theranostics and emphasize the need for biocompatibility. We then explore radionuclide-imaging modalities such as Positron Emission Tomography (PET), Single Photon Emission Computed Tomography (SPECT), and Cerenkov Luminescence (CL) with examples utilizing radiolabeled NP for imaging. PET and SPECT have served as diagnostic workhorses in the clinic, while preclinical NP design examples of multimodal imaging with radiotracers show promise in imaging and therapy. CL expands the types of radionuclides beyond PET and SPECT tracers to include high-energy electrons (β−) for imaging purposes. These advances in radionanomedicine will be discussed, showing the potential for radiolabeled NPs as theranostic agents. PMID:27006133

Carnegie Mellon University bioimaging day 2014: Challenges and opportunities in digital pathology

PubMed Central

Rohde, Gustavo K.; Ozolek, John A.; Parwani, Anil V.; Pantanowitz, Liron

2014-01-01

Recent advances in digital imaging is impacting the practice of pathology. One of the key enabling technologies that is leading the way towards this transformation is the use of whole slide imaging (WSI) which allows glass slides to be converted into large image files that can be shared, stored, and analyzed rapidly. Many applications around this novel technology have evolved in the last decade including education, research and clinical applications. This publication highlights a collection of abstracts, each corresponding to a talk given at Carnegie Mellon University's (CMU) Bioimaging Day 2014 co-sponsored by the Biomedical Engineering and Lane Center for Computational Biology Departments at CMU. Topics related specifically to digital pathology are presented in this collection of abstracts. These include topics related to digital workflow implementation, imaging and artifacts, storage demands, and automated image analysis algorithms. PMID:25250190

Carnegie Mellon University bioimaging day 2014: Challenges and opportunities in digital pathology.

PubMed

Rohde, Gustavo K; Ozolek, John A; Parwani, Anil V; Pantanowitz, Liron

2014-01-01

Recent advances in digital imaging is impacting the practice of pathology. One of the key enabling technologies that is leading the way towards this transformation is the use of whole slide imaging (WSI) which allows glass slides to be converted into large image files that can be shared, stored, and analyzed rapidly. Many applications around this novel technology have evolved in the last decade including education, research and clinical applications. This publication highlights a collection of abstracts, each corresponding to a talk given at Carnegie Mellon University's (CMU) Bioimaging Day 2014 co-sponsored by the Biomedical Engineering and Lane Center for Computational Biology Departments at CMU. Topics related specifically to digital pathology are presented in this collection of abstracts. These include topics related to digital workflow implementation, imaging and artifacts, storage demands, and automated image analysis algorithms.

3D GeoWall Analysis System for Shuttle External Tank Foreign Object Debris Events

NASA Technical Reports Server (NTRS)

Brown, Richard; Navard, Andrew; Spruce, Joseph

2010-01-01

An analytical, advanced imaging method has been developed for the initial monitoring and identification of foam debris and similar anomalies that occur post-launch in reference to the space shuttle s external tank (ET). Remote sensing technologies have been used to perform image enhancement and analysis on high-resolution, true-color images collected with the DCS 760 Kodak digital camera located in the right umbilical well of the space shuttle. Improvements to the camera, using filters, have added sharpness/definition to the image sets; however, image review/analysis of the ET has been limited by the fact that the images acquired by umbilical cameras during launch are two-dimensional, and are usually nonreferenceable between frames due to rotation translation of the ET as it falls away from the space shuttle. Use of stereo pairs of these images can enable strong visual indicators that can immediately portray depth perception of damaged areas or movement of fragments between frames is not perceivable in two-dimensional images. A stereoscopic image visualization system has been developed to allow 3D depth perception of stereo-aligned image pairs taken from in-flight umbilical and handheld digital shuttle cameras. This new system has been developed to augment and optimize existing 2D monitoring capabilities. Using this system, candidate sequential image pairs are identified for transformation into stereo viewing pairs. Image orientation is corrected using control points (similar points) between frames to place the two images in proper X-Y viewing perspective. The images are then imported into the WallView stereo viewing software package. The collected control points are used to generate a transformation equation that is used to re-project one image and effectively co-register it to the other image. The co-registered, oriented image pairs are imported into a WallView image set and are used as a 3D stereo analysis slide show. Multiple sequential image pairs can be used to allow forensic review of temporal phenomena between pairs. The observer, while wearing linear polarized glasses, is able to review image pairs in passive 3D stereo.

Advanced Image Search: A Strategy for Creating Presentation Boards

ERIC Educational Resources Information Center

Frey, Diane K.; Hines, Jean D.; Swinker, Mary E.

2008-01-01

Finding relevant digital images to create presentation boards requires advanced search skills. This article describes a course assignment involving a technique designed to develop students' literacy skills with respect to locating images of desired quality and content from Internet databases. The assignment was applied in a collegiate apparel…

Kinetic Simulation and Energetic Neutral Atom Imaging of the Magnetosphere

NASA Technical Reports Server (NTRS)

Fok, Mei-Ching H.

2011-01-01

Advanced simulation tools and measurement techniques have been developed to study the dynamic magnetosphere and its response to drivers in the solar wind. The Comprehensive Ring Current Model (CRCM) is a kinetic code that solves the 3D distribution in space, energy and pitch-angle information of energetic ions and electrons. Energetic Neutral Atom (ENA) imagers have been carried in past and current satellite missions. Global morphology of energetic ions were revealed by the observed ENA images. We have combined simulation and ENA analysis techniques to study the development of ring current ions during magnetic storms and substorms. We identify the timing and location of particle injection and loss. We examine the evolution of ion energy and pitch-angle distribution during different phases of a storm. In this talk we will discuss the findings from our ring current studies and how our simulation and ENA analysis tools can be applied to the upcoming TRIO-CINAMA mission.

European health telematics networks for positron emission tomography

NASA Astrophysics Data System (ADS)

Kontaxakis, George; Pozo, Miguel Angel; Ohl, Roland; Visvikis, Dimitris; Sachpazidis, Ilias; Ortega, Fernando; Guerra, Pedro; Cheze-Le Rest, Catherine; Selby, Peter; Pan, Leyun; Diaz, Javier; Dimitrakopoulou-Strauss, Antonia; Santos, Andres; Strauss, Ludwig; Sakas, Georgios

2006-12-01

A pilot network of positron emission tomography centers across Europe has been setup employing telemedicine services. The primary aim is to bring all PET centers in Europe (and beyond) closer, by integrating advanced medical imaging technology and health telematics networks applications into a single, easy to operate health telematics platform, which allows secure transmission of medical data via a variety of telecommunications channels and fosters the cooperation between professionals in the field. The platform runs on PCs with Windows 2000/XP and incorporates advanced techniques for image visualization, analysis and fusion. The communication between two connected workstations is based on a TCP/IP connection secured by secure socket layers and virtual private network or jabber protocols. A teleconsultation can be online (with both physicians physically present) or offline (via transmission of messages which contain image data and other information). An interface sharing protocol enables online teleconsultations even over low bandwidth connections. This initiative promotes the cooperation and improved communication between nuclear medicine professionals, offering options for second opinion and training. It permits physicians to remotely consult patient data, even if they are away from the physical examination site.

Advances in Surface Plasmon Resonance Imaging enable quantitative measurement of laterally heterogeneous coatings of nanoscale thickness

NASA Astrophysics Data System (ADS)

Raegen, Adam; Reiter, Kyle; Clarke, Anthony; Lipkowski, Jacek; Dutcher, John

2013-03-01

The Surface Plasmon Resonance (SPR) phenomenon is routinely exploited to qualitatively probe changes to the optical properties of nanoscale coatings on thin metallic surfaces, for use in probes and sensors. Unfortunately, extracting truly quantitative information is usually limited to a select few cases - uniform absorption/desorption of small biomolecules and films, in which a continuous ``slab'' model is a good approximation. We present advancements in the SPR technique that expand the number of cases for which the technique can provide meaningful results. Use of a custom, angle-scanning SPR imaging system, together with a refined data analysis method, allow for quantitative kinetic measurements of laterally heterogeneous systems. We first demonstrate the directionally heterogeneous nature of the SPR phenomenon using a directionally ordered sample, then show how this allows for the calculation of the average coverage of a heterogeneous sample. Finally, the degradation of cellulose microfibrils and bundles of microfibrils due to the action of cellulolytic enzymes will be presented as an excellent example of the capabilities of the SPR imaging system.

Recent Advances in Conjugated Polymer Materials for Disease Diagnosis.

PubMed

Lv, Fengting; Qiu, Tian; Liu, Libing; Ying, Jianming; Wang, Shu

2016-02-10

The extraordinary optical amplification and light-harvesting properties of conjugated polymers impart sensing systems with higher sensitivity, which meets the primary demands of early cancer diagnosis. Recent advances in the detection of DNA methylation and mutation with polyfluorene derivatives based fluorescence resonance energy transfer (FRET) as a means to modulate fluorescent responses attest to the great promise of conjugated polymers as powerful tools for the clinical diagnosis of diseases. To facilitate the ever-changing needs of diagnosis, the development of detection approaches and FRET signal analysis are highlighted in this review. Due to their exceptional brightness, excellent photostability, and low or absent toxicity, conjugated polymers are verified as superior materials for in-vivo imaging, and provide feasibility for future clinical molecular-imaging applications. The integration of conjugated polymers with clinical research has shown profound effects on diagnosis for the early detection of disease-related biomarkers, as well as in-vivo imaging, which leads to a multidisciplinary scientific field with perspectives in both basic research and application issues. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

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

PubMed

Needham, J A; Sharp, J S

2016-02-16

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

An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization

NASA Astrophysics Data System (ADS)

Li, Shuo; Jin, Weiqi; Li, Li; Li, Yiyang

2018-05-01

Infrared thermal images can reflect the thermal-radiation distribution of a particular scene. However, the contrast of the infrared images is usually low. Hence, it is generally necessary to enhance the contrast of infrared images in advance to facilitate subsequent recognition and analysis. Based on the adaptive double plateaus histogram equalization, this paper presents an improved contrast enhancement algorithm for infrared thermal images. In the proposed algorithm, the normalized coefficient of variation of the histogram, which characterizes the level of contrast enhancement, is introduced as feedback information to adjust the upper and lower plateau thresholds. The experiments on actual infrared images show that compared to the three typical contrast-enhancement algorithms, the proposed algorithm has better scene adaptability and yields better contrast-enhancement results for infrared images with more dark areas or a higher dynamic range. Hence, it has high application value in contrast enhancement, dynamic range compression, and digital detail enhancement for infrared thermal images.

Molecular imaging for theranostics in gastroenterology: one stone to kill two birds.

PubMed

Ko, Kwang Hyun; Kown, Chang-Il; Park, Jong Min; Lee, Hoo Geun; Han, Na Young; Hahm, Ki Baik

2014-09-01

Molecular imaging in gastroenterology has become more feasible with recent advances in imaging technology, molecular genetics, and next-generation biochemistry, in addition to advances in endoscopic imaging techniques including magnified high-resolution endoscopy, narrow band imaging or autofluorescence imaging, flexible spectral imaging color enhancement, and confocal laser endomicroscopy. These developments have the potential to serve as "red flag" techniques enabling the earlier and accurate detection of mucosal abnormalities (such as precancerous lesions) beyond biomarkers, virtual histology of detected lesions, and molecular targeted therapy-the strategy of "one stone to kill two or three birds"; however, more effort should be done to be "blue ocean" benefit. This review deals with the introduction of Raman spectroscopy endoscopy, imaging mass spectroscopy, and nanomolecule development for theranostics. Imaging of molecular pathological changes in cells/tissues/organs might open the "royal road" to either convincing diagnosis of diseases that otherwise would only be detected in the advanced stages or novel therapeutic methods targeted to personalized medicine.

Perspectives on Current Training Guidelines for Cardiac Imaging and Recommendations for the Future.

PubMed

Arrighi, James A; Kilic, Sena; Haines, Philip G

2018-04-23

To summarize current training guidelines for cardiac imaging and provide recommendations for future guidelines. The current structure of training in cardiac imaging is largely dictated by modality-specific guidelines. While there has been debate on how to define the advanced cardiac imager for over a decade, a uniform consensus has not emerged. We report the perspectives of three key stakeholders in this debate: a senior faculty member-former fellowship program director, a cardiology fellow, and an academic junior faculty imaging expert. The observations of these stakeholders suggest that there is no consensus on the definition of advanced cardiac imaging, leading to ambiguity in training guidelines. This may have negative impact on recruitment of fellows into cardiac imaging careers. Based on the current status of training in cardiac imaging, the authors suggest that the relevant professional groups reconvene to form a consensus in defining advanced cardiac imaging, in order to guide future revisions of training guidelines.

Advanced GPR imaging of sedimentary features: integrated attribute analysis applied to sand dunes

NASA Astrophysics Data System (ADS)

Zhao, Wenke; Forte, Emanuele; Fontolan, Giorgio; Pipan, Michele

2018-04-01

We evaluate the applicability and the effectiveness of integrated GPR attribute analysis to image the internal sedimentary features of the Piscinas Dunes, SW Sardinia, Italy. The main objective is to explore the limits of GPR techniques to study sediment-bodies geometry and to provide a non-invasive high-resolution characterization of the different subsurface domains of dune architecture. On such purpose, we exploit the high-quality Piscinas data-set to extract and test different attributes of the GPR trace. Composite displays of multi-attributes related to amplitude, frequency, similarity and textural features are displayed with overlays and RGB mixed models. A multi-attribute comparative analysis is used to characterize different radar facies to better understand the characteristics of internal reflection patterns. The results demonstrate that the proposed integrated GPR attribute analysis can provide enhanced information about the spatial distribution of sediment bodies, allowing an enhanced and more constrained data interpretation.

Recent advances in parametric neuroreceptor mapping with dynamic PET: basic concepts and graphical analyses.

PubMed

Seo, Seongho; Kim, Su Jin; Lee, Dong Soo; Lee, Jae Sung

2014-10-01

Tracer kinetic modeling in dynamic positron emission tomography (PET) has been widely used to investigate the characteristic distribution patterns or dysfunctions of neuroreceptors in brain diseases. Its practical goal has progressed from regional data quantification to parametric mapping that produces images of kinetic-model parameters by fully exploiting the spatiotemporal information in dynamic PET data. Graphical analysis (GA) is a major parametric mapping technique that is independent on any compartmental model configuration, robust to noise, and computationally efficient. In this paper, we provide an overview of recent advances in the parametric mapping of neuroreceptor binding based on GA methods. The associated basic concepts in tracer kinetic modeling are presented, including commonly-used compartment models and major parameters of interest. Technical details of GA approaches for reversible and irreversible radioligands are described, considering both plasma input and reference tissue input models. Their statistical properties are discussed in view of parametric imaging.

The future of space imaging. Report of a community-based study of an advanced camera for the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Brown, Robert A. (Editor)

1993-01-01

The scientific and technical basis for an Advanced Camera (AC) for the Hubble Space Telescope (HST) is discussed. In March 1992, the NASA Program Scientist for HST invited the Space Telescope Science Institute to conduct a community-based study of an AC, which would be installed on a scheduled HST servicing mission in 1999. The study had three phases: a broad community survey of views on candidate science program and required performance of the AC, an analysis of technical issues relating to its implementation, and a panel of experts to formulate conclusions and prioritize recommendations. From the assessment of the imaging tasks astronomers have proposed for or desired from HST, we believe the most valuable 1999 instrument would be a camera with both near ultraviolet/optical (NUVO) and far ultraviolet (FUV) sensitivity, and with both wide field and high resolution options.

Mission science value-cost savings from the Advanced Imaging Communication System (AICS)

NASA Technical Reports Server (NTRS)

Rice, R. F.

1984-01-01

An Advanced Imaging Communication System (AICS) was proposed in the mid-1970s as an alternative to the Voyager data/communication system architecture. The AICS achieved virtually error free communication with little loss in the downlink data rate by concatenating a powerful Reed-Solomon block code with the Voyager convolutionally coded, Viterbi decoded downlink channel. The clean channel allowed AICS sophisticated adaptive data compression techniques. Both Voyager and the Galileo mission have implemented AICS components, and the concatenated channel itself is heading for international standardization. An analysis that assigns a dollar value/cost savings to AICS mission performance gains is presented. A conservative value or savings of $3 million for Voyager, $4.5 million for Galileo, and as much as $7 to 9.5 million per mission for future projects such as the proposed Mariner Mar 2 series is shown.

Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation.

PubMed

Asner, G P; Martin, R E; Knapp, D E; Tupayachi, R; Anderson, C B; Sinca, F; Vaughn, N R; Llactayo, W

2017-01-27

Functional biogeography may bridge a gap between field-based biodiversity information and satellite-based Earth system studies, thereby supporting conservation plans to protect more species and their contributions to ecosystem functioning. We used airborne laser-guided imaging spectroscopy with environmental modeling to derive large-scale, multivariate forest canopy functional trait maps of the Peruvian Andes-to-Amazon biodiversity hotspot. Seven mapped canopy traits revealed functional variation in a geospatial pattern explained by geology, topography, hydrology, and climate. Clustering of canopy traits yielded a map of forest beta functional diversity for land-use analysis. Up to 53% of each mapped, functionally distinct forest presents an opportunity for new conservation action. Mapping functional diversity advances our understanding of the biosphere to conserve more biodiversity in the face of land use and climate change. Copyright © 2017, American Association for the Advancement of Science.

Atom Probe Tomographic Analysis of Biological Systems Enabled by Advanced Specimen Preparation Approaches

NASA Astrophysics Data System (ADS)

Perea, D. E.; Evans, J. E.

2017-12-01

The ability to image biointerfaces over nanometer to micrometer length scales is fundamental to correlating biological composition and structure to physiological function, and is aided by a multimodal approach using advanced complementary microscopic and spectroscopic characterization techniques. Atom Probe Tomography (APT) is a rapidly expanding technique for atomic-scale three-dimensional structural and chemical analysis. However, the regular application of APT to soft biological materials is lacking in large part due to difficulties in specimen preparation and inabilities to yield meaningful tomographic reconstructions that produce atomic scale compositional distributions as no other technique currently can. Here we describe the atomic-scale tomographic analysis of biological materials using APT that is facilitated by an advanced focused ion beam based approach. A novel specimen preparation strategy is used in the analysis of horse spleen ferritin protein embedded in an organic polymer resin which provides chemical contrast to distinguish the inorganic-organic interface of the ferrihydrite mineral core and protein shell of the ferritin protein. One-dimensional composition profiles directly reveal an enhanced concentration of P and Na at the surface of the ferrihydrite mineral core. We will also describe the development of a unique multifunctional environmental transfer hub allowing controlled cryogenic transfer of specimens under vacuum pressure conditions between an Atom Probe and cryo-FIB/SEM. The utility of the environmental transfer hub is demonstrated through the acquisition of previously unavailable mass spectral analysis of an intact organometallic molecule made possible via controlled cryogenic transfer. The results demonstrate a viable application of APT analysis to study complex biological organic/inorganic interfaces relevant to energy and the environment. References D.E. Perea et al. An environmental transfer hub for multimodal atom probe tomography, Adv. Struct. Chem. Imag, 2017, 3:12 The research was performed at the Environmental Molecular Sciences Laboratory; a national scientific user facility sponsored by the Department of Energy's Office of Biological and Environmental Research located at Pacific Northwest National Laboratory.

Observing hydrological processes: recent advancements in surface flow monitoring through image analysis

NASA Astrophysics Data System (ADS)

Tauro, Flavia; Grimaldi, Salvatore

2017-04-01

Recently, several efforts have been devoted to the design and development of innovative, and often unintended, approaches for the acquisition of hydrological data. Among such pioneering techniques, this presentation reports recent advancements towards the establishment of a novel noninvasive and potentially continuous methodology based on the acquisition and analysis of images for spatially distributed observations of the kinematics of surface waters. The approach aims at enabling rapid, affordable, and accurate surface flow monitoring of natural streams. Flow monitoring is an integral part of hydrological sciences and is essential for disaster risk reduction and the comprehension of natural phenomena. However, water processes are inherently complex to observe: they are characterized by multiscale and highly heterogeneous phenomena which have traditionally demanded sophisticated and costly measurement techniques. Challenges in the implementation of such techniques have also resulted in lack of hydrological data during extreme events, in difficult-to-access environments, and at high temporal resolution. By combining low-cost yet high-resolution images and several velocimetry algorithms, noninvasive flow monitoring has been successfully conducted at highly heterogeneous scales, spanning from rills to highly turbulent streams, and medium-scale rivers, with minimal supervision by external users. Noninvasive image data acquisition has also afforded observations in high flow conditions. Latest novelties towards continuous flow monitoring at the catchment scale have entailed the development of a remote gauge-cam station on the Tiber River and integration of flow monitoring through image analysis with unmanned aerial systems (UASs) technology. The gauge-cam station and the UAS platform both afford noninvasive image acquisition and calibration through an innovative laser-based setup. Compared to traditional point-based instrumentation, images allow for generating surface flow velocity maps which fully describe the kinematics of the velocity field in natural streams. Also, continuous observations provide a close picture of the evolving dynamics of natural water bodies. Despite such promising achievements, dealing with images also involves coping with adverse illumination, massive data handling and storage, and data-intensive computing. Most importantly, establishing a novel observational technique requires estimation of the uncertainty associated to measurements and thorough comparison to existing benchmark approaches. In this presentation, we provide answers to some of these issues and perspectives for future research.

PLUS: open-source toolkit for ultrasound-guided intervention systems.

PubMed

Lasso, Andras; Heffter, Tamas; Rankin, Adam; Pinter, Csaba; Ungi, Tamas; Fichtinger, Gabor

2014-10-01

A variety of advanced image analysis methods have been under the development for ultrasound-guided interventions. Unfortunately, the transition from an image analysis algorithm to clinical feasibility trials as part of an intervention system requires integration of many components, such as imaging and tracking devices, data processing algorithms, and visualization software. The objective of our paper is to provide a freely available open-source software platform-PLUS: Public software Library for Ultrasound-to facilitate rapid prototyping of ultrasound-guided intervention systems for translational clinical research. PLUS provides a variety of methods for interventional tool pose and ultrasound image acquisition from a wide range of tracking and imaging devices, spatial and temporal calibration, volume reconstruction, simulated image generation, and recording and live streaming of the acquired data. This paper introduces PLUS, explains its functionality and architecture, and presents typical uses and performance in ultrasound-guided intervention systems. PLUS fulfills the essential requirements for the development of ultrasound-guided intervention systems and it aspires to become a widely used translational research prototyping platform. PLUS is freely available as open source software under BSD license and can be downloaded from http://www.plustoolkit.org.

Advances in targeting strategies for nanoparticles in cancer imaging and therapy.

PubMed

Yhee, Ji Young; Lee, Sangmin; Kim, Kwangmeyung

2014-11-21

In the last decade, nanoparticles have offered great advances in diagnostic imaging and targeted drug delivery. In particular, nanoparticles have provided remarkable progress in cancer imaging and therapy based on materials science and biochemical engineering technology. Researchers constantly attempted to develop the nanoparticles which can deliver drugs more specifically to cancer cells, and these efforts brought the advances in the targeting strategy of nanoparticles. This minireview will discuss the progress in targeting strategies for nanoparticles focused on the recent innovative work for nanomedicine.

Automated digital image analysis of islet cell mass using Nikon's inverted eclipse Ti microscope and software to improve engraftment may help to advance the therapeutic efficacy and accessibility of islet transplantation across centers.

PubMed

Gmyr, Valery; Bonner, Caroline; Lukowiak, Bruno; Pawlowski, Valerie; Dellaleau, Nathalie; Belaich, Sandrine; Aluka, Isanga; Moermann, Ericka; Thevenet, Julien; Ezzouaoui, Rimed; Queniat, Gurvan; Pattou, Francois; Kerr-Conte, Julie

2015-01-01

Reliable assessment of islet viability, mass, and purity must be met prior to transplanting an islet preparation into patients with type 1 diabetes. The standard method for quantifying human islet preparations is by direct microscopic analysis of dithizone-stained islet samples, but this technique may be susceptible to inter-/intraobserver variability, which may induce false positive/negative islet counts. Here we describe a simple, reliable, automated digital image analysis (ADIA) technique for accurately quantifying islets into total islet number, islet equivalent number (IEQ), and islet purity before islet transplantation. Islets were isolated and purified from n = 42 human pancreata according to the automated method of Ricordi et al. For each preparation, three islet samples were stained with dithizone and expressed as IEQ number. Islets were analyzed manually by microscopy or automatically quantified using Nikon's inverted Eclipse Ti microscope with built-in NIS-Elements Advanced Research (AR) software. The AIDA method significantly enhanced the number of islet preparations eligible for engraftment compared to the standard manual method (p < 0.001). Comparisons of individual methods showed good correlations between mean values of IEQ number (r(2) = 0.91) and total islet number (r(2) = 0.88) and thus increased to r(2) = 0.93 when islet surface area was estimated comparatively with IEQ number. The ADIA method showed very high intraobserver reproducibility compared to the standard manual method (p < 0.001). However, islet purity was routinely estimated as significantly higher with the manual method versus the ADIA method (p < 0.001). The ADIA method also detected small islets between 10 and 50 µm in size. Automated digital image analysis utilizing the Nikon Instruments software is an unbiased, simple, and reliable teaching tool to comprehensively assess the individual size of each islet cell preparation prior to transplantation. Implementation of this technology to improve engraftment may help to advance the therapeutic efficacy and accessibility of islet transplantation across centers.