Image segmentation for biomedical applications based on alternating sequential filtering and watershed transformation

NASA Astrophysics Data System (ADS)

Gorpas, D.; Yova, D.

2009-07-01

One of the major challenges in biomedical imaging is the extraction of quantified information from the acquired images. Light and tissue interaction leads to the acquisition of images that present inconsistent intensity profiles and thus the accurate identification of the regions of interest is a rather complicated process. On the other hand, the complex geometries and the tangent objects that very often are present in the acquired images, lead to either false detections or to the merging, shrinkage or expansion of the regions of interest. In this paper an algorithm, which is based on alternating sequential filtering and watershed transformation, is proposed for the segmentation of biomedical images. This algorithm has been tested over two applications, each one based on different acquisition system, and the results illustrate its accuracy in segmenting the regions of interest.

Finding and accessing diagrams in biomedical publications.

PubMed

Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael

2012-01-01

Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar and line charts by the shape and relative location of the different image elements that make up the charts. With recall and precisions of close to 90% for the detection of relevant figures, we discuss the use of this technology in an existing biomedical image search engine, and outline how it enables new forms of literature queries over biomedical relationships that are represented in these charts.

Finding and Accessing Diagrams in Biomedical Publications

PubMed Central

Kuhn, Tobias; Luong, ThaiBinh; Krauthammer, Michael

2012-01-01

Complex relationships in biomedical publications are often communicated by diagrams such as bar and line charts, which are a very effective way of summarizing and communicating multi-faceted data sets. Given the ever-increasing amount of published data, we argue that the precise retrieval of such diagrams is of great value for answering specific and otherwise hard-to-meet information needs. To this end, we demonstrate the use of advanced image processing and classification for identifying bar and line charts by the shape and relative location of the different image elements that make up the charts. With recall and precisions of close to 90% for the detection of relevant figures, we discuss the use of this technology in an existing biomedical image search engine, and outline how it enables new forms of literature queries over biomedical relationships that are represented in these charts. PMID:23304318

A fast discrete S-transform for biomedical signal processing.

PubMed

Brown, Robert A; Frayne, Richard

2008-01-01

Determining the frequency content of a signal is a basic operation in signal and image processing. The S-transform provides both the true frequency and globally referenced phase measurements characteristic of the Fourier transform and also generates local spectra, as does the wavelet transform. Due to this combination, the S-transform has been successfully demonstrated in a variety of biomedical signal and image processing tasks. However, the computational demands of the S-transform have limited its application in medicine to this point in time. This abstract introduces the fast S-transform, a more efficient discrete implementation of the classic S-transform with dramatically reduced computational requirements.

Review of spectral imaging technology in biomedical engineering: achievements and challenges.

PubMed

Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

2013-10-01

Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

New frontiers in biomedical science and engineering during 2014-2015.

PubMed

Liu, Feng; Lee, Dong-Hoon; Lagoa, Ricardo; Kumar, Sandeep

2015-01-01

The International Conference on Biomedical Engineering and Biotechnology (ICBEB) is an international meeting held once a year. This, the fourth International Conference on Biomedical Engineering and Biotechnology (ICBEB2015), will be held in Shanghai, China, during August 18th-21st, 2015. This annual conference intends to provide an opportunity for researchers and practitioners at home and abroad to present the most recent frontiers and future challenges in the fields of biomedical science, biomedical engineering, biomaterials, bioinformatics and computational biology, biomedical imaging and signal processing, biomechanical engineering and biotechnology, etc. The papers published in this issue are selected from this Conference, which witness the advances in biomedical engineering and biotechnology during 2014-2015.

Liquid Crystals, PIV and IR-Photography in Selected Technical and Biomedical Applications

NASA Astrophysics Data System (ADS)

Stasiek, Jan; Jewartowski, Marcin

2017-10-01

Thermochromic liquid crystals (TLC), Particle Image Velocimetry (PIV), Infrared Imaging Themography (IR) and True-Colour Digital Image Processing (TDIP) have been successfully used in non-intrusive technical, industrial and biomedical studies and applications. These four tools (based on the desktop computers) have come together during the past two decades to produce a powerful advanced experimental technique as a judgment of quality of information that cannot be obtained from any other imaging procedure. The brief summary of the history of this technique is reviewed, principal methods and tools are described and some examples are presented. With this objective, a new experimental technique have been developed and applied to the study of heat and mass transfer and for biomedical diagnosis. Automated evaluation allows determining the heat and flow visualisation and locate the area of suspicious tissue of human body.

Signal and image processing for early detection of coronary artery diseases: A review

NASA Astrophysics Data System (ADS)

Mobssite, Youness; Samir, B. Belhaouari; Mohamad Hani, Ahmed Fadzil B.

2012-09-01

Today biomedical signals and image based detection are a basic step to diagnose heart diseases, in particular, coronary artery diseases. The goal of this work is to provide non-invasive early detection of Coronary Artery Diseases relying on analyzing images and ECG signals as a combined approach to extract features, further classify and quantify the severity of DCAD by using B-splines method. In an aim of creating a prototype of screening biomedical imaging for coronary arteries to help cardiologists to decide the kind of treatment needed to reduce or control the risk of heart attack.

Advances in biomedical engineering and biotechnology during 2013-2014.

PubMed

Liu, Feng; Wang, Ying; Burkhart, Timothy A; González Penedo, Manuel Francisco; Ma, Shaodong

2014-01-01

The 3rd International Conference on Biomedical Engineering and Biotechnology (iCBEB 2014), held in Beijing from the 25th to the 28th of September 2014, is an annual conference that intends to provide an opportunity for researchers and practitioners around the world to present the most recent advances and future challenges in the fields of biomedical engineering, biomaterials, bioinformatics and computational biology, biomedical imaging and signal processing, biomechanical engineering and biotechnology, amongst others. The papers published in this issue are selected from this conference, which witnesses the advances in biomedical engineering and biotechnology during 2013-2014.

Biomedical signal and image processing.

PubMed

Cerutti, Sergio; Baselli, Giuseppe; Bianchi, Anna; Caiani, Enrico; Contini, Davide; Cubeddu, Rinaldo; Dercole, Fabio; Rienzo, Luca; Liberati, Diego; Mainardi, Luca; Ravazzani, Paolo; Rinaldi, Sergio; Signorini, Maria; Torricelli, Alessandro

2011-01-01

Generally, physiological modeling and biomedical signal processing constitute two important paradigms of biomedical engineering (BME): their fundamental concepts are taught starting from undergraduate studies and are more completely dealt with in the last years of graduate curricula, as well as in Ph.D. courses. Traditionally, these two cultural aspects were separated, with the first one more oriented to physiological issues and how to model them and the second one more dedicated to the development of processing tools or algorithms to enhance useful information from clinical data. A practical consequence was that those who did models did not do signal processing and vice versa. However, in recent years,the need for closer integration between signal processing and modeling of the relevant biological systems emerged very clearly [1], [2]. This is not only true for training purposes(i.e., to properly prepare the new professional members of BME) but also for the development of newly conceived research projects in which the integration between biomedical signal and image processing (BSIP) and modeling plays a crucial role. Just to give simple examples, topics such as brain–computer machine or interfaces,neuroengineering, nonlinear dynamical analysis of the cardiovascular (CV) system,integration of sensory-motor characteristics aimed at the building of advanced prostheses and rehabilitation tools, and wearable devices for vital sign monitoring and others do require an intelligent fusion of modeling and signal processing competences that are certainly peculiar of our discipline of BME.

Biomedical applications of a real-time terahertz color scanner

PubMed Central

Schirmer, Markus; Fujio, Makoto; Minami, Masaaki; Miura, Jiro; Araki, Tsutomu; Yasui, Takeshi

2010-01-01

A real-time THz color scanner has the potential to further expand the application scope of THz spectral imaging based on its rapid image acquisition rate. We demonstrated three possible applications of a THz color scanner in the biomedical field: imaging of pharmaceutical tablets, human teeth, and human hair. The first application showed the scanner’s potential in total inspection for rapid quality control of pharmaceutical tablets moving on a conveyor belt. The second application demonstrated that the scanner can be used to identify a potential indicator for crystallinity of dental tissue. In the third application, the scanner was successfully used to visualize the drying process of wet hairs. These demonstrations indicated the high potential of the THz color scanner for practical applications in the biomedical field. PMID:21258472

Liquid crystal thermography and true-colour digital image processing

NASA Astrophysics Data System (ADS)

Stasiek, J.; Stasiek, A.; Jewartowski, M.; Collins, M. W.

2006-06-01

In the last decade thermochromic liquid crystals (TLC) and true-colour digital image processing have been successfully used in non-intrusive technical, industrial and biomedical studies and applications. Thin coatings of TLCs at surfaces are utilized to obtain detailed temperature distributions and heat transfer rates for steady or transient processes. Liquid crystals also can be used to make visible the temperature and velocity fields in liquids by the simple expedient of directly mixing the liquid crystal material into the liquid (water, glycerol, glycol, and silicone oils) in very small quantities to use as thermal and hydrodynamic tracers. In biomedical situations e.g., skin diseases, breast cancer, blood circulation and other medical application, TLC and image processing are successfully used as an additional non-invasive diagnostic method especially useful for screening large groups of potential patients. The history of this technique is reviewed, principal methods and tools are described and some examples are also presented.

Reconstruction of Mammary Gland Structure Using Three-Dimensional Computer-Based Microscopy

DTIC Science & Technology

2004-08-01

for image analysis in cytology" Ortiz de Solorzano C., R . Malladi , Lockett S. In: Geometric methods in bio-medical image processing. Ravikanth Malladi ...Deschamps T., Idica A.K., Malladi R ., Ortiz de Solorzano C. Journal of Biomedical Optics 9(3):445-453, 2004.. Manuscripts (in preparation): "* "Three...Deschamps T., Idica A.K., 16 Malladi R ., Ortiz de Solorzano C., Proceedings of Photonics West 2003, Vol. 4964, 2003 "* "Automatic and segmentation

Bioinspired Polarization Imaging Sensors: From Circuits and Optics to Signal Processing Algorithms and Biomedical Applications

PubMed Central

York, Timothy; Powell, Samuel B.; Gao, Shengkui; Kahan, Lindsey; Charanya, Tauseef; Saha, Debajit; Roberts, Nicholas W.; Cronin, Thomas W.; Marshall, Justin; Achilefu, Samuel; Lake, Spencer P.; Raman, Baranidharan; Gruev, Viktor

2015-01-01

In this paper, we present recent work on bioinspired polarization imaging sensors and their applications in biomedicine. In particular, we focus on three different aspects of these sensors. First, we describe the electro–optical challenges in realizing a bioinspired polarization imager, and in particular, we provide a detailed description of a recent low-power complementary metal–oxide–semiconductor (CMOS) polarization imager. Second, we focus on signal processing algorithms tailored for this new class of bioinspired polarization imaging sensors, such as calibration and interpolation. Third, the emergence of these sensors has enabled rapid progress in characterizing polarization signals and environmental parameters in nature, as well as several biomedical areas, such as label-free optical neural recording, dynamic tissue strength analysis, and early diagnosis of flat cancerous lesions in a murine colorectal tumor model. We highlight results obtained from these three areas and discuss future applications for these sensors. PMID:26538682

78 FR 107 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

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2013-01-02

... Biomedical Imaging and Bioengineering; Notice of Closed Meeting Pursuant to section 10(d) of the Federal... Biomedical Imaging and Bioengineering Special Emphasis Panel, 2013-05 ZEB1 OSR-D(M1)S/Low- Dose CT Imaging..., National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, 6707 Democracy...

A midas plugin to enable construction of reproducible web-based image processing pipelines

PubMed Central

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A.; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline. PMID:24416016

A midas plugin to enable construction of reproducible web-based image processing pipelines.

PubMed

Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

2013-01-01

Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

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Image-Processing Program

NASA Technical Reports Server (NTRS)

Roth, D. J.; Hull, D. R.

1994-01-01

IMAGEP manipulates digital image data to effect various processing, analysis, and enhancement functions. It is keyboard-driven program organized into nine subroutines. Within subroutines are sub-subroutines also selected via keyboard. Algorithm has possible scientific, industrial, and biomedical applications in study of flows in materials, analysis of steels and ores, and pathology, respectively.

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

NASA Astrophysics Data System (ADS)

Maragos, Petros

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

A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.

PubMed

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

2017-03-01

Highly accurate classification of biomedical images is an essential task in the clinical diagnosis of numerous medical diseases identified from those images. Traditional image classification methods combined with hand-crafted image feature descriptors and various classifiers are not able to effectively improve the accuracy rate and meet the high requirements of classification of biomedical images. The same also holds true for artificial neural network models directly trained with limited biomedical images used as training data or directly used as a black box to extract the deep features based on another distant dataset. In this study, we propose a highly reliable and accurate end-to-end classifier for all kinds of biomedical images via deep learning and transfer learning. We first apply domain transferred deep convolutional neural network for building a deep model; and then develop an overall deep learning architecture based on the raw pixels of original biomedical images using supervised training. In our model, we do not need the manual design of the feature space, seek an effective feature vector classifier or segment specific detection object and image patches, which are the main technological difficulties in the adoption of traditional image classification methods. Moreover, we do not need to be concerned with whether there are large training sets of annotated biomedical images, affordable parallel computing resources featuring GPUs or long times to wait for training a perfect deep model, which are the main problems to train deep neural networks for biomedical image classification as observed in recent works. With the utilization of a simple data augmentation method and fast convergence speed, our algorithm can achieve the best accuracy rate and outstanding classification ability for biomedical images. We have evaluated our classifier on several well-known public biomedical datasets and compared it with several state-of-the-art approaches. We propose a robust automated end-to-end classifier for biomedical images based on a domain transferred deep convolutional neural network model that shows a highly reliable and accurate performance which has been confirmed on several public biomedical image datasets. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

A New Pivoting and Iterative Text Detection Algorithm for Biomedical Images

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

Xu, Songhua; Krauthammer, Prof. Michael

2010-01-01

There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper's key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manuallymore » labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. We demonstrate that our projection histogram-based text detection approach is well suited for text detection in biomedical images, and that the iterative application of the algorithm boosts performance to an F score of .60. We provide a C++ implementation of our algorithm freely available for academic use.« less

Extraction and labeling high-resolution images from PDF documents

NASA Astrophysics Data System (ADS)

Chachra, Suchet K.; Xue, Zhiyun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-12-01

Accuracy of content-based image retrieval is affected by image resolution among other factors. Higher resolution images enable extraction of image features that more accurately represent the image content. In order to improve the relevance of search results for our biomedical image search engine, Open-I, we have developed techniques to extract and label high-resolution versions of figures from biomedical articles supplied in the PDF format. Open-I uses the open-access subset of biomedical articles from the PubMed Central repository hosted by the National Library of Medicine. Articles are available in XML and in publisher supplied PDF formats. As these PDF documents contain little or no meta-data to identify the embedded images, the task includes labeling images according to their figure number in the article after they have been successfully extracted. For this purpose we use the labeled small size images provided with the XML web version of the article. This paper describes the image extraction process and two alternative approaches to perform image labeling that measure the similarity between two images based upon the image intensity projection on the coordinate axes and similarity based upon the normalized cross-correlation between the intensities of two images. Using image identification based on image intensity projection, we were able to achieve a precision of 92.84% and a recall of 82.18% in labeling of the extracted images.

77 FR 19675 - National Institute of Biomedical Imaging and Bioengineering; Notice of Meeting

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2012-04-02

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Realistic tissue visualization using photoacoustic image

NASA Astrophysics Data System (ADS)

Cho, Seonghee; Managuli, Ravi; Jeon, Seungwan; Kim, Jeesu; Kim, Chulhong

2018-02-01

Visualization methods are very important in biomedical imaging. As a technology that understands life, biomedical imaging has the unique advantage of providing the most intuitive information in the image. This advantage of biomedical imaging can be greatly improved by choosing a special visualization method. This is more complicated in volumetric data. Volume data has the advantage of containing 3D spatial information. Unfortunately, the data itself cannot directly represent the potential value. Because images are always displayed in 2D space, visualization is the key and creates the real value of volume data. However, image processing of 3D data requires complicated algorithms for visualization and high computational burden. Therefore, specialized algorithms and computing optimization are important issues in volume data. Photoacoustic-imaging is a unique imaging modality that can visualize the optical properties of deep tissue. Because the color of the organism is mainly determined by its light absorbing component, photoacoustic data can provide color information of tissue, which is closer to real tissue color. In this research, we developed realistic tissue visualization using acoustic-resolution photoacoustic volume data. To achieve realistic visualization, we designed specialized color transfer function, which depends on the depth of the tissue from the skin. We used direct ray casting method and processed color during computing shader parameter. In the rendering results, we succeeded in obtaining similar texture results from photoacoustic data. The surface reflected rays were visualized in white, and the reflected color from the deep tissue was visualized red like skin tissue. We also implemented the CUDA algorithm in an OpenGL environment for real-time interactive imaging.

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Biomedical Applications of Nanodiamonds: An Overview.

PubMed

Passeri, D; Rinaldi, F; Ingallina, C; Carafa, M; Rossi, M; Terranova, M L; Marianecci, C

2015-02-01

Nanodiamonds are a novel class of nanomaterials which have raised much attention for application in biomedical field, as they combine the possibility of being produced on large scale using relatively inexpensive synthetic processes, of being fluorescent as a consequence of the presence of nitrogen vacancies, of having their surfaces functionalized, and of having good biocompatibility. Among other applications, we mainly focus on drug delivery, including cell interaction, targeting, cancer therapy, gene and protein delivery. In addition, nanodiamonds for bone and dental implants and for antibacterial use is discussed. Techniques for detection and imaging of nanodiamonds in biological tissues are also reviewed, including electron microscopy, fluorescence microscopy, Raman mapping, atomic force microscopy, thermal imaging, magnetic resonance imaging, and positron emission tomography, either in vitro, in vivo, or ex vivo. Toxicological aspects related to the use of nanodiamonds are also discussed. Finally, patents, preclinical and clinical trials based on the use of nanodiamonds for biomedical applications are reviewed.

Multidimensional Processing and Visual Rendering of Complex 3D Biomedical Images

NASA Technical Reports Server (NTRS)

Sams, Clarence F.

2016-01-01

The proposed technology uses advanced image analysis techniques to maximize the resolution and utility of medical imaging methods being used during spaceflight. We utilize COTS technology for medical imaging, but our applications require higher resolution assessment of the medical images than is routinely applied with nominal system software. By leveraging advanced data reduction and multidimensional imaging techniques utilized in analysis of Planetary Sciences and Cell Biology imaging, it is possible to significantly increase the information extracted from the onboard biomedical imaging systems. Year 1 focused on application of these techniques to the ocular images collected on ground test subjects and ISS crewmembers. Focus was on the choroidal vasculature and the structure of the optic disc. Methods allowed for increased resolution and quantitation of structural changes enabling detailed assessment of progression over time. These techniques enhance the monitoring and evaluation of crew vision issues during space flight.

Camera systems in human motion analysis for biomedical applications

NASA Astrophysics Data System (ADS)

Chin, Lim Chee; Basah, Shafriza Nisha; Yaacob, Sazali; Juan, Yeap Ewe; Kadir, Aida Khairunnisaa Ab.

2015-05-01

Human Motion Analysis (HMA) system has been one of the major interests among researchers in the field of computer vision, artificial intelligence and biomedical engineering and sciences. This is due to its wide and promising biomedical applications, namely, bio-instrumentation for human computer interfacing and surveillance system for monitoring human behaviour as well as analysis of biomedical signal and image processing for diagnosis and rehabilitation applications. This paper provides an extensive review of the camera system of HMA, its taxonomy, including camera types, camera calibration and camera configuration. The review focused on evaluating the camera system consideration of the HMA system specifically for biomedical applications. This review is important as it provides guidelines and recommendation for researchers and practitioners in selecting a camera system of the HMA system for biomedical applications.

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A new pivoting and iterative text detection algorithm for biomedical images.

PubMed

Xu, Songhua; Krauthammer, Michael

2010-12-01

There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper's key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manually labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. We demonstrate that our projection histogram-based text detection approach is well suited for text detection in biomedical images, and that the iterative application of the algorithm boosts performance to an F score of .60. We provide a C++ implementation of our algorithm freely available for academic use. Copyright © 2010 Elsevier Inc. All rights reserved.

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

PubMed

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

1999-01-01

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

Micro/Nanostructured Films and Adhesives for Biomedical Applications.

PubMed

Lee, Jungkyu K; Kang, Sung Min; Yang, Sung Ho; Cho, Woo Kyung

2015-12-01

The advanced technologies available for micro/nanofabrication have opened new avenues for interdisciplinary approaches to solve the unmet medical needs of regenerative medicine and biomedical devices. This review highlights the recent developments in micro/nanostructured adhesives and films for biomedical applications, including waterproof seals for wounds or surgery sites, drug delivery, sensing human body signals, and optical imaging of human tissues. We describe in detail the fabrication processes required to prepare the adhesives and films, such as tape-based adhesives, nanofilms, and flexible and stretchable film-based electronic devices. We also discuss their biomedical functions, performance in vitro and in vivo, and the future research needed to improve the current systems.

77 FR 74675 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meetings

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2012-12-17

... Person: Ruth Grossman, DDS, Scientific Review Officer, National Institute of Biomedical Imaging and... Person: Ruth Grossman, DDS, Scientific Review Officer, National Institute of Biomedical Imaging and...

Processing of Fine-Scale Piezoelectric Ceramic/Polymer Composites for Sensors and Actuators

NASA Technical Reports Server (NTRS)

Janas, V. F.; Safari, A.

1996-01-01

The objective of the research effort at Rutgers is the development of lead zirconate titanate (PZT) ceramic/polymer composites with different designs for transducer applications including hydrophones, biomedical imaging, non-destructive testing, and air imaging. In this review, methods for processing both large area and multifunctional ceramic/polymer composites for acoustic transducers were discussed.

Mathematical models used in segmentation and fractal methods of 2-D ultrasound images

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Moraru, Luminita; Bibicu, Dorin

2012-11-01

Mathematical models are widely used in biomedical computing. The extracted data from images using the mathematical techniques are the "pillar" achieving scientific progress in experimental, clinical, biomedical, and behavioural researches. This article deals with the representation of 2-D images and highlights the mathematical support for the segmentation operation and fractal analysis in ultrasound images. A large number of mathematical techniques are suitable to be applied during the image processing stage. The addressed topics cover the edge-based segmentation, more precisely the gradient-based edge detection and active contour model, and the region-based segmentation namely Otsu method. Another interesting mathematical approach consists of analyzing the images using the Box Counting Method (BCM) to compute the fractal dimension. The results of the paper provide explicit samples performed by various combination of methods.

Application of the 4-D XCAT Phantoms in Biomedical Imaging and Beyond.

PubMed

Segars, W Paul; Tsui, B M W; Cai, Jing; Yin, Fang-Fang; Fung, George S K; Samei, Ehsan

2018-03-01

The four-dimensional (4-D) eXtended CArdiac-Torso (XCAT) series of phantoms was developed to provide accurate computerized models of the human anatomy and physiology. The XCAT series encompasses a vast population of phantoms of varying ages from newborn to adult, each including parameterized models for the cardiac and respiratory motions. With great flexibility in the XCAT's design, any number of body sizes, different anatomies, cardiac or respiratory motions or patterns, patient positions and orientations, and spatial resolutions can be simulated. As such, the XCAT phantoms are gaining a wide use in biomedical imaging research. There they can provide a virtual patient base from which to quantitatively evaluate and improve imaging instrumentation, data acquisition, techniques, and image reconstruction and processing methods which can lead to improved image quality and more accurate clinical diagnoses. The phantoms have also found great use in radiation dosimetry, radiation therapy, medical device design, and even the security and defense industry. This review paper highlights some specific areas in which the XCAT phantoms have found use within biomedical imaging and other fields. From these examples, we illustrate the increasingly important role that computerized phantoms and computer simulation are playing in the research community.

Biomedical informatics and translational medicine.

PubMed

Sarkar, Indra Neil

2010-02-26

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams.

A New Pivoting and Iterative Text Detection Algorithm for Biomedical Images

PubMed Central

Xu, Songhua; Krauthammer, Michael

2010-01-01

There is interest to expand the reach of literature mining to include the analysis of biomedical images, which often contain a paper’s key findings. Examples include recent studies that use Optical Character Recognition (OCR) to extract image text, which is used to boost biomedical image retrieval and classification. Such studies rely on the robust identification of text elements in biomedical images, which is a non-trivial task. In this work, we introduce a new text detection algorithm for biomedical images based on iterative projection histograms. We study the effectiveness of our algorithm by evaluating the performance on a set of manually labeled random biomedical images, and compare the performance against other state-of-the-art text detection algorithms. In this paper, we demonstrate that a projection histogram-based text detection approach is well suited for text detection in biomedical images, with a performance of F score of .60. The approach performs better than comparable approaches for text detection. Further, we show that the iterative application of the algorithm is boosting overall detection performance. A C++ implementation of our algorithm is freely available through email request for academic use. PMID:20887803

From Mars to man - Biomedical research at the Jet Propulsion Laboratory

NASA Technical Reports Server (NTRS)

Beckenbach, E. S.

1984-01-01

In the course of the unmanned exploration of the solar system, which the California Institute of Technology's Jet Propulsion Laboratory has managed for NASA, major advances in computerized image processing, materials research, and miniature electronics design have been accomplished. This presentation shows some of the imaging results from space exploration missions, as well as biomedical research tasks based in these technologies. Among other topics, the use of polymeric microspheres in cancer therapy is discussed. Also included are ceramic applications to prosthesis development, laser applications in the treatment of coronary artery disease, multispectral imaging as used in the diagnosis of thermal burn injury, and some examples of telemetry systems as they can be involved in biological systems.

e-Science platform for translational biomedical imaging research: running, statistics, and analysis

NASA Astrophysics Data System (ADS)

Wang, Tusheng; Yang, Yuanyuan; Zhang, Kai; Wang, Mingqing; Zhao, Jun; Xu, Lisa; Zhang, Jianguo

2015-03-01

In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. In past the two-years, we implemented a biomedical image chain including communication, storage, cooperation and computing based on this e-Science platform. In this presentation, we presented the operating status of this system in supporting biomedical imaging research, analyzed and discussed results of this system in supporting multi-disciplines collaboration cross-multiple institutions.

Nanoparticles for Biomedical Imaging

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

Nune, Satish K.; Gunda, Padmaja; Thallapally, Praveen K.

2009-11-01

Background: Synthetic nanoparticles are emerging as versatile tools in biomedical applications, particularly in the area of biomedical imaging. Nanoparticles 1 to 100 nm in diameter possess dimensions comparable to biological functional units. Diverse surface chemistries, unique magnetic properties, tunable absorption and emission properties, and recent advances in the synthesis and engineering of various nanoparticles suggest their potential as probes for early detection of diseases such as cancer. Surface functionalization has further expanded the potential of nanoparticles as probes for molecular imaging. Objective: To summarize emerging research of nanoparticles for biomedical imaging with increased selectivity and reduced non-specific uptake with increasedmore » spatial resolution containing stabilizers conjugated with targeting ligands. Methods: This review summarizes recent technological advances in the synthesis of various nanoparticle probes, and surveys methods to improve the targeting of nanoparticles for their applications in biomedical imaging. Conclusion: Structural design of nanomaterials for biomedical imaging continues to expand and diversify. Synthetic methods have aimed to control the size and surface characteristics of nanoparticles to control distribution, half-life and elimination. Although molecular imaging applications using nanoparticles are advancing into clinical applications, challenges such as storage stability and long-term toxicology should continue to be addressed. Keywords: nanoparticle synthesis, surface modification, targeting, molecular imaging, and biomedical imaging.« less

Biomedical imaging graduate curricula and courses: report from the 2005 Whitaker Biomedical Engineering Educational Summit.

PubMed

Louie, Angelique; Izatt, Joseph; Ferrara, Katherine

2006-02-01

We present an overview of graduate programs in biomedical imaging that are currently available in the US. Special attention is given to the emerging technologies of molecular imaging and biophotonics. Discussions from the workshop on Graduate Imaging at the 2005 Whitaker Educational Summit meeting are summarized.

Translational research of optical molecular imaging for personalized medicine.

PubMed

Qin, C; Ma, X; Tian, J

2013-12-01

In the medical imaging field, molecular imaging is a rapidly developing discipline and forms many imaging modalities, providing us effective tools to visualize, characterize, and measure molecular and cellular mechanisms in complex biological processes of living organisms, which can deepen our understanding of biology and accelerate preclinical research including cancer study and medicine discovery. Among many molecular imaging modalities, although the penetration depth of optical imaging and the approved optical probes used for clinics are limited, it has evolved considerably and has seen spectacular advances in basic biomedical research and new drug development. With the completion of human genome sequencing and the emergence of personalized medicine, the specific drug should be matched to not only the right disease but also to the right person, and optical molecular imaging should serve as a strong adjunct to develop personalized medicine by finding the optimal drug based on an individual's proteome and genome. In this process, the computational methodology and imaging system as well as the biomedical application regarding optical molecular imaging will play a crucial role. This review will focus on recent typical translational studies of optical molecular imaging for personalized medicine followed by a concise introduction. Finally, the current challenges and the future development of optical molecular imaging are given according to the understanding of the authors, and the review is then concluded.

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

Bernstein, Dr. Ira

This grant was awarded in support of Phase 2 of the University of Vermont Center for Biomedical Imaging. Phase 2 outlined several specific aims including: The development of expertise in MRI and fMRI imaging and their applications The acquisition of peer reviewed extramural funding in support of the Center The development of a Core Imaging Advisory Board, fee structure and protocol review and approval process.

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving (SSLE) of Glass Crystals.

PubMed

Betts, Aislinn M; McGoldrick, Matthew T; Dethlefs, Christopher R; Piotrowicz, Justin; Van Avermaete, Tony; Maki, Jeff; Gerstler, Steve; Leevy, W M

2017-04-25

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings.

Laser Speckle Imaging to Monitor Microvascular Blood Flow: A Review.

PubMed

Vaz, Pedro G; Humeau-Heurtier, Anne; Figueiras, Edite; Correia, Carlos; Cardoso, Joao

2016-01-01

Laser speckle is a complex interference phenomenon that can easily be understood, in concept, but is difficult to predict mathematically, because it is a stochastic process. The use of laser speckle to produce images, which can carry many types of information, is called laser speckle imaging (LSI). The biomedical applications of LSI started in 1981 and, since then, many scientists have improved the laser speckle theory and developed different imaging techniques. During this process, some inconsistencies have been propagated up to now. These inconsistencies should be clarified in order to avoid errors in future works. This review presents a review of the laser speckle theory used in biomedical applications. Moreover, we also make a review of the practical concepts that are useful in the construction of laser speckle imagers. This study is not only an exposition of the concepts that can be found in the literature but also a critical analysis of the investigations presented so far. Concepts like scatterers velocity distribution, effect of static scatterers, optimal speckle size, light penetration angle, and contrast computation algorithms are discussed in detail.

Software and Algorithms for Biomedical Image Data Processing and Visualization

NASA Technical Reports Server (NTRS)

Talukder, Ashit; Lambert, James; Lam, Raymond

2004-01-01

A new software equipped with novel image processing algorithms and graphical-user-interface (GUI) tools has been designed for automated analysis and processing of large amounts of biomedical image data. The software, called PlaqTrak, has been specifically used for analysis of plaque on teeth of patients. New algorithms have been developed and implemented to segment teeth of interest from surrounding gum, and a real-time image-based morphing procedure is used to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The PlaqTrak system integrates these components into a single software suite with an easy-to-use GUI (see Figure 1) that allows users to do an end-to-end run of a patient s record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image. The automated and accurate processing of the captured images to segment each tooth [see Figure 2(a)] and then detect plaque on a tooth-by-tooth basis is a critical component of the PlaqTrak system to do clinical trials and analysis with minimal human intervention. These features offer distinct advantages over other competing systems that analyze groups of teeth or synthetic teeth. PlaqTrak divides each segmented tooth into eight regions using an advanced graphics morphing procedure [see results on a chipped tooth in Figure 2(b)], and a pattern recognition classifier is then used to locate plaque [red regions in Figure 2(d)] and enamel regions. The morphing allows analysis within regions of teeth, thereby facilitating detailed statistical analysis such as the amount of plaque present on the biting surfaces on teeth. This software system is applicable to a host of biomedical applications, such as cell analysis and life detection, or robotic applications, such as product inspection or assembly of parts in space and industry.

77 FR 50516 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

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2012-08-21

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78 FR 67375 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

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2013-11-12

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78 FR 67373 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

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2013-11-12

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78 FR 54259 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

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2013-09-03

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Fully automated rodent brain MR image processing pipeline on a Midas server: from acquired images to region-based statistics.

PubMed

Budin, Francois; Hoogstoel, Marion; Reynolds, Patrick; Grauer, Michael; O'Leary-Moore, Shonagh K; Oguz, Ipek

2013-01-01

Magnetic resonance imaging (MRI) of rodent brains enables study of the development and the integrity of the brain under certain conditions (alcohol, drugs etc.). However, these images are difficult to analyze for biomedical researchers with limited image processing experience. In this paper we present an image processing pipeline running on a Midas server, a web-based data storage system. It is composed of the following steps: rigid registration, skull-stripping, average computation, average parcellation, parcellation propagation to individual subjects, and computation of region-based statistics on each image. The pipeline is easy to configure and requires very little image processing knowledge. We present results obtained by processing a data set using this pipeline and demonstrate how this pipeline can be used to find differences between populations.

78 FR 64519 - National Institute of Biomedical Imaging and Bioengineering; Amended Notice of Meeting

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2013-10-29

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health National Institute of Biomedical Imaging and Bioengineering; Amended Notice of Meeting Notice is hereby given of a change in the meeting of the National Institute of Biomedical Imaging and Bioengineering Special Emphasis Panel, October...

78 FR 64506 - National Institute of Biomedical Imaging and Bioengineering; Amended Notice of Meeting

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2013-10-29

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78 FR 78982 - National Institute of Biomedical Imaging and Bioengineering; Amended Notice of Meeting

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2013-12-27

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2011-10-11

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78 FR 55268 - National Institute of Biomedical Imaging and Bioengineering Amended; Notice of Meeting

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2013-09-10

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2011-01-28

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2013-11-06

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2013-10-30

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Role of Kinetic Modeling in Biomedical Imaging

PubMed Central

Huang, Sung-Cheng

2009-01-01

Biomedical imaging can reveal clear 3-dimensional body morphology non-invasively with high spatial resolution. Its efficacy, in both clinical and pre-clinical settings, is enhanced with its capability to provide in vivo functional/biological information in tissue. The role of kinetic modeling in providing biological/functional information in biomedical imaging is described. General characteristics and limitations in extracting biological information are addressed and practical approaches to solve the problems are discussed and illustrated with examples. Some future challenges and opportunities for kinetic modeling to expand the capability of biomedical imaging are also presented. PMID:20640185

A theoretical-experimental methodology for assessing the sensitivity of biomedical spectral imaging platforms, assays, and analysis methods.

PubMed

Leavesley, Silas J; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter; Rich, Thomas C

2018-01-01

Spectral imaging technologies have been used for many years by the remote sensing community. More recently, these approaches have been applied to biomedical problems, where they have shown great promise. However, biomedical spectral imaging has been complicated by the high variance of biological data and the reduced ability to construct test scenarios with fixed ground truths. Hence, it has been difficult to objectively assess and compare biomedical spectral imaging assays and technologies. Here, we present a standardized methodology that allows assessment of the performance of biomedical spectral imaging equipment, assays, and analysis algorithms. This methodology incorporates real experimental data and a theoretical sensitivity analysis, preserving the variability present in biomedical image data. We demonstrate that this approach can be applied in several ways: to compare the effectiveness of spectral analysis algorithms, to compare the response of different imaging platforms, and to assess the level of target signature required to achieve a desired performance. Results indicate that it is possible to compare even very different hardware platforms using this methodology. Future applications could include a range of optimization tasks, such as maximizing detection sensitivity or acquisition speed, providing high utility for investigators ranging from design engineers to biomedical scientists. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The ImageJ ecosystem: an open platform for biomedical image analysis

PubMed Central

Schindelin, Johannes; Rueden, Curtis T.; Hiner, Mark C.; Eliceiri, Kevin W.

2015-01-01

Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available – from commercial to academic, special-purpose to Swiss army knife, small to large–but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts life science, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. PMID:26153368

The ImageJ ecosystem: An open platform for biomedical image analysis.

PubMed

Schindelin, Johannes; Rueden, Curtis T; Hiner, Mark C; Eliceiri, Kevin W

2015-01-01

Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available-from commercial to academic, special-purpose to Swiss army knife, small to large-but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. © 2015 Wiley Periodicals, Inc.

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.

Rudiments of curvelet with applications

NASA Astrophysics Data System (ADS)

Zahra, Noor e.

2012-07-01

Curvelet transform is now a days a favored tool for image processing. Edges are an important part of an image and usually they are not straight lines. Curvelet prove to be very efficient in representing curve like edges. In this chapter application of curvelet is shown with some examples like seismic wave analysis, oil exploration, fingerprint identification and biomedical images like mammography and MRI.

Diagnostic imaging applications; Proceedings of the Meeting, Amsterdam, Netherlands, October 8, 9, 1984

NASA Technical Reports Server (NTRS)

Beckenbach, E. S. (Editor)

1984-01-01

It is more important than ever that engineers have an understanding of the future needs of clinical and research medicine, and that physicians know somthing about probable future developments in instrumentation capabilities. Only by maintaining such a dialog can the most effective application of technological advances to medicine be achieved. This workshop attempted to provide this kind of information transfer in the limited field of diagnostic imaging. Biomedical research at the Jet Propulsion Laboratory is discussed, taking into account imaging results from space exploration missions, as well as biomedical research tasks based in these technologies. Attention is also given to current and future indications for magnetic resonance in medicine, high speed quantitative digital microscopy, computer processing of radiographic images, computed tomography and its modern applications, position emission tomography, and developments related to medical ultrasound.

77 FR 54584 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

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2012-09-05

... Biomedical Imaging and Bioengineering; Notice of Closed Meeting Pursuant to section 10(d) of the Federal... clearly unwarranted invasion of personal privacy. Name of Committee: National Institute of Biomedical Imaging and Bioengineering Special Emphasis Panel, ZEB1 OSR-D(J2) P Tissue Engineering Resource Center...

77 FR 25488 - National Institute of Biomedical Imaging and Bioengineering; Amended Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-30

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health National Institute of Biomedical Imaging and Bioengineering; Amended Notice of Meeting Notice is hereby given a change in the meeting of the National Advisory Council for Biomedical Imaging and Bioengineering, May 21, 2012, 9:00 a.m...

Scaled Anatomical Model Creation of Biomedical Tomographic Imaging Data and Associated Labels for Subsequent Sub-surface Laser Engraving (SSLE) of Glass Crystals

PubMed Central

Dethlefs, Christopher R.; Piotrowicz, Justin; Van Avermaete, Tony; Maki, Jeff; Gerstler, Steve; Leevy, W. M.

2017-01-01

Biomedical imaging modalities like computed tomography (CT) and magnetic resonance (MR) provide excellent platforms for collecting three-dimensional data sets of patient or specimen anatomy in clinical or preclinical settings. However, the use of a virtual, on-screen display limits the ability of these tomographic images to fully convey the anatomical information embedded within. One solution is to interface a biomedical imaging data set with 3D printing technology to generate a physical replica. Here we detail a complementary method to visualize tomographic imaging data with a hand-held model: Sub Surface Laser Engraving (SSLE) of crystal glass. SSLE offers several unique benefits including: the facile ability to include anatomical labels, as well as a scale bar; streamlined multipart assembly of complex structures in one medium; high resolution in the X, Y, and Z planes; and semi-transparent shells for visualization of internal anatomical substructures. Here we demonstrate the process of SSLE with CT data sets derived from pre-clinical and clinical sources. This protocol will serve as a powerful and inexpensive new tool with which to visualize complex anatomical structures for scientists and students in a number of educational and research settings. PMID:28518066

Potential medical applications of TAE

NASA Technical Reports Server (NTRS)

Fahy, J. Ben; Kaucic, Robert; Kim, Yongmin

1986-01-01

In cooperation with scientists in the University of Washington Medical School, a microcomputer-based image processing system for quantitative microscopy, called DMD1 (Digital Microdensitometer 1) was constructed. In order to make DMD1 transportable to different hosts and image processors, we have been investigating the possibility of rewriting the lower level portions of DMD1 software using Transportable Applications Executive (TAE) libraries and subsystems. If successful, we hope to produce a newer version of DMD1, called DMD2, running on an IBM PC/AT under the SCO XENIX System 5 operating system, using any of seven target image processors available in our laboratory. Following this implementation, copies of the system will be transferred to other laboratories with biomedical imaging applications. By integrating those applications into DMD2, we hope to eventually expand our system into a low-cost general purpose biomedical imaging workstation. This workstation will be useful not only as a self-contained instrument for clinical or research applications, but also as part of a large scale Digital Imaging Network and Picture Archiving and Communication System, (DIN/PACS). Widespread application of these TAE-based image processing and analysis systems should facilitate software exchange and scientific cooperation not only within the medical community, but between the medical and remote sensing communities as well.

Modern technologies for retinal scanning and imaging: an introduction for the biomedical engineer

PubMed Central

2014-01-01

This review article is meant to help biomedical engineers and nonphysical scientists better understand the principles of, and the main trends in modern scanning and imaging modalities used in ophthalmology. It is intended to ease the communication between physicists, medical doctors and engineers, and hopefully encourage “classical” biomedical engineers to generate new ideas and to initiate projects in an area which has traditionally been dominated by optical physics. Most of the methods involved are applicable to other areas of biomedical optics and optoelectronics, such as microscopic imaging, spectroscopy, spectral imaging, opto-acoustic tomography, fluorescence imaging etc., all of which are with potential biomedical application. Although all described methods are novel and important, the emphasis of this review has been placed on three technologies introduced in the 1990’s and still undergoing vigorous development: Confocal Scanning Laser Ophthalmoscopy, Optical Coherence Tomography, and polarization-sensitive retinal scanning. PMID:24779618

Nanodiamonds of Laser Synthesis for Biomedical Applications.

PubMed

Perevedentseva, E; Peer, D; Uvarov, V; Zousman, B; Levinson, O

2015-02-01

In recent decade detonation nanodiamonds (DND), discovered 50 years ago and used in diverse technological processes, have been actively applied in biomedical research as a drug and gene delivery carrier, a contrast agent for bio-imaging and diagnostics and an adsorbent for protein separation and purification. In this work we report about nanodiamonds of high purity produced by laser assisted technique, compare them with DND and consider the prospect and advantages of their use in the said applications.

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

PubMed

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

2010-12-01

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

Viruses, Artificial Viruses and Virus-Based Structures for Biomedical Applications.

PubMed

van Rijn, Patrick; Schirhagl, Romana

2016-06-01

Nanobiomaterials such as virus particles and artificial virus particles offer tremendous opportunities to develop new biomedical applications such as drug- or gene-delivery, imaging and sensing but also improve understanding of biological mechanisms. Recent advances within the field of virus-based systems give insights in how to mimic viral structures and virus assembly processes as well as understanding biodistribution, cell/tissue targeting, controlled and triggered disassembly or release and circulation times. All these factors are of high importance for virus-based functional systems. This review illustrates advances in mimicking and enhancing or controlling these aspects to a high degree toward delivery and imaging applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Supervised restoration of degraded medical images using multiple-point geostatistics.

PubMed

Pham, Tuan D

2012-06-01

Reducing noise in medical images has been an important issue of research and development for medical diagnosis, patient treatment, and validation of biomedical hypotheses. Noise inherently exists in medical and biological images due to the acquisition and transmission in any imaging devices. Being different from image enhancement, the purpose of image restoration is the process of removing noise from a degraded image in order to recover as much as possible its original version. This paper presents a statistically supervised approach for medical image restoration using the concept of multiple-point geostatistics. Experimental results have shown the effectiveness of the proposed technique which has potential as a new methodology for medical and biological image processing. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2005-03-09

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

Image processing applications: From particle physics to society

NASA Astrophysics Data System (ADS)

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

2017-01-01

We present an embedded system for extremely efficient real-time pattern recognition execution, enabling technological advancements with both scientific and social impact. It is a compact, fast, low consumption processing unit (PU) based on a combination of Field Programmable Gate Arrays (FPGAs) and the full custom associative memory chip. The PU has been developed for real time tracking in particle physics experiments, but delivers flexible features for potential application in a wide range of fields. It has been proposed to be used in accelerated pattern matching execution for Magnetic Resonance Fingerprinting (biomedical applications), in real time detection of space debris trails in astronomical images (space applications) and in brain emulation for image processing (cognitive image processing). We illustrate the potentiality of the PU for the new applications.

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval.

PubMed

Rahman, Md Mahmudur; Antani, Sameer K; Demner-Fushman, Dina; Thoma, George R

2015-10-01

This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term "concept" refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature.

Biomedical image representation approach using visualness and spatial information in a concept feature space for interactive region-of-interest-based retrieval

PubMed Central

Rahman, Md. Mahmudur; Antani, Sameer K.; Demner-Fushman, Dina; Thoma, George R.

2015-01-01

Abstract. This article presents an approach to biomedical image retrieval by mapping image regions to local concepts where images are represented in a weighted entropy-based concept feature space. The term “concept” refers to perceptually distinguishable visual patches that are identified locally in image regions and can be mapped to a glossary of imaging terms. Further, the visual significance (e.g., visualness) of concepts is measured as the Shannon entropy of pixel values in image patches and is used to refine the feature vector. Moreover, the system can assist the user in interactively selecting a region-of-interest (ROI) and searching for similar image ROIs. Further, a spatial verification step is used as a postprocessing step to improve retrieval results based on location information. The hypothesis that such approaches would improve biomedical image retrieval is validated through experiments on two different data sets, which are collected from open access biomedical literature. PMID:26730398

Optical Tecnology Developments in Biomedicine: History, Current and Future

PubMed Central

Nioka, Shoko; Chen, Yu

2011-01-01

Biomedical optics is a rapidly emerging field for medical imaging and diagnostics. This paper reviews several biomedical optical technologies that have been developed and translated for either clinical or pre-clinical applications. Specifically, we focus on the following technologies: 1) near-infrared spectroscopy and tomography, 2) optical coherence tomography, 3) fluorescence spectroscopy and imaging, and 4) optical molecular imaging. There representative biomedical applications are also discussed here. PMID:23905030

78 FR 58547 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

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2013-12-19

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Spatiotemporal integration of molecular and anatomical data in virtual reality using semantic mapping.

PubMed

Soh, Jung; Turinsky, Andrei L; Trinh, Quang M; Chang, Jasmine; Sabhaney, Ajay; Dong, Xiaoli; Gordon, Paul Mk; Janzen, Ryan Pw; Hau, David; Xia, Jianguo; Wishart, David S; Sensen, Christoph W

2009-01-01

We have developed a computational framework for spatiotemporal integration of molecular and anatomical datasets in a virtual reality environment. Using two case studies involving gene expression data and pharmacokinetic data, respectively, we demonstrate how existing knowledge bases for molecular data can be semantically mapped onto a standardized anatomical context of human body. Our data mapping methodology uses ontological representations of heterogeneous biomedical datasets and an ontology reasoner to create complex semantic descriptions of biomedical processes. This framework provides a means to systematically combine an increasing amount of biomedical imaging and numerical data into spatiotemporally coherent graphical representations. Our work enables medical researchers with different expertise to simulate complex phenomena visually and to develop insights through the use of shared data, thus paving the way for pathological inference, developmental pattern discovery and biomedical hypothesis testing.

Multi-Atlas Segmentation of Biomedical Images: A Survey

PubMed Central

Iglesias, Juan Eugenio; Sabuncu, Mert R.

2015-01-01

Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering work of Rohlfing, Brandt, Menzel and Maurer Jr (2004), Klein, Mensh, Ghosh, Tourville and Hirsch (2005), and Heckemann, Hajnal, Aljabar, Rueckert and Hammers (2006), is becoming one of the most widely-used and successful image segmentation techniques in biomedical applications. By manipulating and utilizing the entire dataset of “atlases” (training images that have been previously labeled, e.g., manually by an expert), rather than some model-based average representation, MAS has the flexibility to better capture anatomical variation, thus offering superior segmentation accuracy. This benefit, however, typically comes at a high computational cost. Recent advancements in computer hardware and image processing software have been instrumental in addressing this challenge and facilitated the wide adoption of MAS. Today, MAS has come a long way and the approach includes a wide array of sophisticated algorithms that employ ideas from machine learning, probabilistic modeling, optimization, and computer vision, among other fields. This paper presents a survey of published MAS algorithms and studies that have applied these methods to various biomedical problems. In writing this survey, we have three distinct aims. Our primary goal is to document how MAS was originally conceived, later evolved, and now relates to alternative methods. Second, this paper is intended to be a detailed reference of past research activity in MAS, which now spans over a decade (2003 – 2014) and entails novel methodological developments and application-specific solutions. Finally, our goal is to also present a perspective on the future of MAS, which, we believe, will be one of the dominant approaches in biomedical image segmentation. PMID:26201875

Publication ethics in biomedical journals from countries in Central and Eastern Europe.

PubMed

Broga, Mindaugas; Mijaljica, Goran; Waligora, Marcin; Keis, Aime; Marusic, Ana

2014-03-01

Publication ethics is an important aspect of both the research and publication enterprises. It is particularly important in the field of biomedical science because published data may directly affect human health. In this article, we examine publication ethics policies in biomedical journals published in Central and Eastern Europe. We were interested in possible differences between East European countries that are members of the European Union (Eastern EU) and South-East European countries (South-East Europe) that are not members of the European Union. The most common ethical issues addressed by all journals in the region were redundant publication, peer review process, and copyright or licensing details. Image manipulation, editors' conflicts of interest and registration of clinical trials were the least common ethical policies. Three aspects were significantly more common in journals published outside the EU: statements on the endorsement of international editorial standards, contributorship policy, and image manipulation. On the other hand, copyright or licensing information were more prevalent in journals published in the Eastern EU. The existence of significant differences among biomedical journals' ethical policies calls for further research and active measures to harmonize policies across journals.

[Scientometrics and bibliometrics of biomedical engineering periodicals and papers].

PubMed

Zhao, Ping; Xu, Ping; Li, Bingyan; Wang, Zhengrong

2003-09-01

This investigation was made to reveal the current status, research trend and research level of biomedical engineering in Chinese mainland by means of scientometrics and to assess the quality of the four domestic publications by bibliometrics. We identified all articles of four related publications by searching Chinese and foreign databases from 1997 to 2001. All articles collected or cited by these databases were searched and statistically analyzed for finding out the relevant distributions, including databases, years, authors, institutions, subject headings and subheadings. The source of sustentation funds and the related articles were analyzed too. The results showed that two journals were cited by two foreign databases and five Chinese databases simultaneously. The output of Journal of Biomedical Engineering was the highest. Its quantity of original papers cited by EI, CA and the totality of papers sponsored by funds were higher than those of the others, but the quantity and percentage per year of biomedical articles cited by EI were decreased in all. Inland core authors and institutions had come into being in the field of biomedical engineering. Their research topics were mainly concentrated on ten subject headings which included biocompatible materials, computer-assisted signal processing, electrocardiography, computer-assisted image processing, biomechanics, algorithms, electroencephalography, automatic data processing, mechanical stress, hemodynamics, mathematical computing, microcomputers, theoretical models, etc. The main subheadings were concentrated on instrumentation, physiopathology, diagnosis, therapy, ultrasonography, physiology, analysis, surgery, pathology, method, etc.

Securing quality of camera-based biomedical optics

NASA Astrophysics Data System (ADS)

Guse, Frank; Kasper, Axel; Zinter, Bob

2009-02-01

As sophisticated optical imaging technologies move into clinical applications, manufacturers need to guarantee their products meet required performance criteria over long lifetimes and in very different environmental conditions. A consistent quality management marks critical components features derived from end-users requirements in a top-down approach. Careful risk analysis in the design phase defines the sample sizes for production tests, whereas first article inspection assures the reliability of the production processes. We demonstrate the application of these basic quality principles to camera-based biomedical optics for a variety of examples including molecular diagnostics, dental imaging, ophthalmology and digital radiography, covering a wide range of CCD/CMOS chip sizes and resolutions. Novel concepts in fluorescence detection and structured illumination are also highlighted.

Cerenkov luminescence imaging: physics principles and potential applications in biomedical sciences.

PubMed

Ciarrocchi, Esther; Belcari, Nicola

2017-12-01

Cerenkov luminescence imaging (CLI) is a novel imaging modality to study charged particles with optical methods by detecting the Cerenkov luminescence produced in tissue. This paper first describes the physical processes that govern the production and transport in tissue of Cerenkov luminescence. The detectors used for CLI and their most relevant specifications to optimize the acquisition of the Cerenkov signal are then presented, and CLI is compared with the other optical imaging modalities sharing the same data acquisition and processing methods. Finally, the scientific work related to CLI and the applications for which CLI has been proposed are reviewed. The paper ends with some considerations about further perspectives for this novel imaging modality.

Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip.

PubMed

Heo, Young Jin; Lee, Donghyeon; Kang, Junsu; Lee, Keondo; Chung, Wan Kyun

2017-09-14

Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.

Population-based imaging biobanks as source of big data.

PubMed

Gatidis, Sergios; Heber, Sophia D; Storz, Corinna; Bamberg, Fabian

2017-06-01

Advances of computational sciences over the last decades have enabled the introduction of novel methodological approaches in biomedical research. Acquiring extensive and comprehensive data about a research subject and subsequently extracting significant information has opened new possibilities in gaining insight into biological and medical processes. This so-called big data approach has recently found entrance into medical imaging and numerous epidemiological studies have been implementing advanced imaging to identify imaging biomarkers that provide information about physiological processes, including normal development and aging but also on the development of pathological disease states. The purpose of this article is to present existing epidemiological imaging studies and to discuss opportunities, methodological and organizational aspects, and challenges that population imaging poses to the field of big data research.

Research-oriented image registry for multimodal image integration.

PubMed

Tanaka, M; Sadato, N; Ishimori, Y; Yonekura, Y; Yamashita, Y; Komuro, H; Hayahsi, N; Ishii, Y

1998-01-01

To provide multimodal biomedical images automatically, we constructed the research-oriented image registry, Data Delivery System (DDS). DDS was constructed on the campus local area network. Machines which generate images (imagers: DSA, ultrasound, PET, MRI, SPECT and CT) were connected to the campus LAN. Once a patient is registered, all his images are automatically picked up by DDS as they are generated, transferred through the gateway server to the intermediate server, and copied into the directory of the user who registered the patient. DDS informs the user through e-mail that new data have been generated and transferred. Data format is automatically converted into one which is chosen by the user. Data inactive for a certain period in the intermediate server are automatically achieved into the final and permanent data server based on compact disk. As a soft link is automatically generated through this step, a user has access to all (old or new) image data of the patient of his interest. As DDS runs with minimal maintenance, cost and time for data transfer are significantly saved. By making the complex process of data transfer and conversion invisible, DDS has made it easy for naive-to-computer researchers to concentrate on their biomedical interest.

Biomedical imaging with THz waves

NASA Astrophysics Data System (ADS)

Nguyen, Andrew

2010-03-01

We discuss biomedical imaging using radio waves operating in the terahertz (THz) range between 300 GHz to 3 THz. Particularly, we present the concept for two THz imaging systems. One system employs single antenna, transmitter and receiver operating over multi-THz-frequency simultaneously for sensing and imaging small areas of the human body or biological samples. Another system consists of multiple antennas, a transmitter, and multiple receivers operating over multi-THz-frequency capable of sensing and imaging simultaneously the whole body or large biological samples. Using THz waves for biomedical imaging promises unique and substantial medical benefits including extremely small medical devices, extraordinarily fine spatial resolution, and excellent contrast between images of diseased and healthy tissues. THz imaging is extremely attractive for detection of cancer in the early stages, sensing and imaging of tissues near the skin, and study of disease and its growth versus time.

WebMedSA: a web-based framework for segmenting and annotating medical images using biomedical ontologies

NASA Astrophysics Data System (ADS)

Vega, Francisco; Pérez, Wilson; Tello, Andrés.; Saquicela, Victor; Espinoza, Mauricio; Solano-Quinde, Lizandro; Vidal, Maria-Esther; La Cruz, Alexandra

2015-12-01

Advances in medical imaging have fostered medical diagnosis based on digital images. Consequently, the number of studies by medical images diagnosis increases, thus, collaborative work and tele-radiology systems are required to effectively scale up to this diagnosis trend. We tackle the problem of the collaborative access of medical images, and present WebMedSA, a framework to manage large datasets of medical images. WebMedSA relies on a PACS and supports the ontological annotation, as well as segmentation and visualization of the images based on their semantic description. Ontological annotations can be performed directly on the volumetric image or at different image planes (e.g., axial, coronal, or sagittal); furthermore, annotations can be complemented after applying a segmentation technique. WebMedSA is based on three main steps: (1) RDF-ization process for extracting, anonymizing, and serializing metadata comprised in DICOM medical images into RDF/XML; (2) Integration of different biomedical ontologies (using L-MOM library), making this approach ontology independent; and (3) segmentation and visualization of annotated data which is further used to generate new annotations according to expert knowledge, and validation. Initial user evaluations suggest that WebMedSA facilitates the exchange of knowledge between radiologists, and provides the basis for collaborative work among them.

Image cloning beyond diffraction based on coherent population trapping in a hot rubidium vapor.

PubMed

Ding, Dong-Sheng; Zhou, Zhi-Yuan; Shi, Bao-Sen

2014-01-15

Following recent theoretical predictions, we report on an experimental realization of image cloning beyond usual diffraction, through the coherent population trapping (CPT) effect in a hot rubidium vapor. In our experiment, an alphabet letter image was transferred from a coupling field to a probe field, based on the CPT effect. Furthermore, we demonstrate that the cloned probe field carrying the image is transmitted without the usual diffraction. To our best knowledge, this is the first experimental report about image cloning beyond diffraction. We believe this mechanism, based on CPT, has definite and important applications in image metrology, image processing, and biomedical imaging.

AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images.

PubMed

Albarqouni, Shadi; Baur, Christoph; Achilles, Felix; Belagiannis, Vasileios; Demirci, Stefanie; Navab, Nassir

2016-05-01

The lack of publicly available ground-truth data has been identified as the major challenge for transferring recent developments in deep learning to the biomedical imaging domain. Though crowdsourcing has enabled annotation of large scale databases for real world images, its application for biomedical purposes requires a deeper understanding and hence, more precise definition of the actual annotation task. The fact that expert tasks are being outsourced to non-expert users may lead to noisy annotations introducing disagreement between users. Despite being a valuable resource for learning annotation models from crowdsourcing, conventional machine-learning methods may have difficulties dealing with noisy annotations during training. In this manuscript, we present a new concept for learning from crowds that handle data aggregation directly as part of the learning process of the convolutional neural network (CNN) via additional crowdsourcing layer (AggNet). Besides, we present an experimental study on learning from crowds designed to answer the following questions. 1) Can deep CNN be trained with data collected from crowdsourcing? 2) How to adapt the CNN to train on multiple types of annotation datasets (ground truth and crowd-based)? 3) How does the choice of annotation and aggregation affect the accuracy? Our experimental setup involved Annot8, a self-implemented web-platform based on Crowdflower API realizing image annotation tasks for a publicly available biomedical image database. Our results give valuable insights into the functionality of deep CNN learning from crowd annotations and prove the necessity of data aggregation integration.

Three-dimensional Imaging and Scanning: Current and Future Applications for Pathology

PubMed Central

Farahani, Navid; Braun, Alex; Jutt, Dylan; Huffman, Todd; Reder, Nick; Liu, Zheng; Yagi, Yukako; Pantanowitz, Liron

2017-01-01

Imaging is vital for the assessment of physiologic and phenotypic details. In the past, biomedical imaging was heavily reliant on analog, low-throughput methods, which would produce two-dimensional images. However, newer, digital, and high-throughput three-dimensional (3D) imaging methods, which rely on computer vision and computer graphics, are transforming the way biomedical professionals practice. 3D imaging has been useful in diagnostic, prognostic, and therapeutic decision-making for the medical and biomedical professions. Herein, we summarize current imaging methods that enable optimal 3D histopathologic reconstruction: Scanning, 3D scanning, and whole slide imaging. Briefly mentioned are emerging platforms, which combine robotics, sectioning, and imaging in their pursuit to digitize and automate the entire microscopy workflow. Finally, both current and emerging 3D imaging methods are discussed in relation to current and future applications within the context of pathology. PMID:28966836

78 FR 3903 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meetings

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-17

... Hilton Hotel Tarrytown, 455 South Broadway, Tarrytown, NY 10591. Contact Person: Ruth Grossman, DDS.... Contact Person: Ruth Grossman, DDS, Scientific Review Officer, National Institute of Biomedical Imaging...

Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging.

PubMed

Esposito, M; Anaxagoras, T; Konstantinidis, A C; Zheng, Y; Speller, R D; Evans, P M; Allinson, N M; Wells, K

2014-07-07

Recently CMOS active pixels sensors (APSs) have become a valuable alternative to amorphous silicon and selenium flat panel imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However, despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ⩽1.9%. The uniformity of the image quality performance has been further investigated in a typical x-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practice. Finally, in order to compare the detection capability of this novel APS with the technology currently used (i.e. FPIs), theoretical evaluation of the detection quantum efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this detector compared to FPIs. Optical characterization, x-ray contrast measurements and theoretical DQE evaluation suggest that a trade off can be found between the need of a large imaging area and the requirement of a uniform imaging performance, making the DynAMITe large area CMOS APS suitable for a range of bio-medical applications.

Design of e-Science platform for biomedical imaging research cross multiple academic institutions and hospitals

NASA Astrophysics Data System (ADS)

Zhang, Jianguo; Zhang, Kai; Yang, Yuanyuan; Ling, Tonghui; Wang, Tusheng; Wang, Mingqing; Hu, Haibo; Xu, Xuemin

2012-02-01

More and more image informatics researchers and engineers are considering to re-construct imaging and informatics infrastructure or to build new framework to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment. In this presentation, we show an outline and our preliminary design work of building an e-Science platform for biomedical imaging and informatics research and application in Shanghai. We will present our consideration and strategy on designing this platform, and preliminary results. We also will discuss some challenges and solutions in building this platform.

Simplified generation of biomedical 3D surface model data for embedding into 3D portable document format (PDF) files for publication and education.

PubMed

Newe, Axel; Ganslandt, Thomas

2013-01-01

The usefulness of the 3D Portable Document Format (PDF) for clinical, educational, and research purposes has recently been shown. However, the lack of a simple tool for converting biomedical data into the model data in the necessary Universal 3D (U3D) file format is a drawback for the broad acceptance of this new technology. A new module for the image processing and rapid prototyping framework MeVisLab does not only provide a platform-independent possibility to create surface meshes out of biomedical/DICOM and other data and to export them into U3D--it also lets the user add meta data to these meshes to predefine colors and names that can be processed by a PDF authoring software while generating 3D PDF files. Furthermore, the source code of the respective module is available and well documented so that it can easily be modified for own purposes.

Image BOSS: a biomedical object storage system

NASA Astrophysics Data System (ADS)

Stacy, Mahlon C.; Augustine, Kurt E.; Robb, Richard A.

1997-05-01

Researchers using biomedical images have data management needs which are oriented perpendicular to clinical PACS. The image BOSS system is designed to permit researchers to organize and select images based on research topic, image metadata, and a thumbnail of the image. Image information is captured from existing images in a Unix based filesystem, stored in an object oriented database, and presented to the user in a familiar laboratory notebook metaphor. In addition, the ImageBOSS is designed to provide an extensible infrastructure for future content-based queries directly on the images.

Multiscale Integration of -Omic, Imaging, and Clinical Data in Biomedical Informatics

PubMed Central

Phan, John H.; Quo, Chang F.; Cheng, Chihwen; Wang, May Dongmei

2016-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data. PMID:23231990

Multiscale integration of -omic, imaging, and clinical data in biomedical informatics.

PubMed

Phan, John H; Quo, Chang F; Cheng, Chihwen; Wang, May Dongmei

2012-01-01

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

Functional requirements for a central research imaging data repository.

PubMed

Franke, Thomas; Gruetz, Romanus; Dickmann, Frank

2013-01-01

The current situation at many university medical centers regarding the management of biomedical research imaging data leaves much to be desired. In contrast to the recommendations of the German Research Foundation (DFG) and the German Council of Sciences and Humanities regarding the professional management of research data, there are commonly many individual data pools for research data in each institute and the management remains the responsibility of the researcher. A possible solution for this situation would be to install local central repositories for biomedical research imaging data. In this paper, we developed a scenario based on abstracted use-cases for institutional research undertakings as well as collaborative biomedical research projects and analyzed the functional requirements that a local repository would have to fulfill. We determined eight generic categories of functional requirements, which can be viewed as a basic guideline for the minimum functionality of a central repository for biomedical research imaging data.

Physics of fractional imaging in biomedicine.

PubMed

Sohail, Ayesha; Bég, O A; Li, Zhiwu; Celik, Sebahattin

2018-03-12

The mathematics of imaging is a growing field of research and is evolving rapidly parallel to evolution in the field of imaging. Imaging, which is a sub-field of biomedical engineering, considers novel approaches to visualize biological tissues with the general goal of improving health. "Medical imaging research provides improved diagnostic tools in clinical settings and supports the development of drugs and other therapies. The data acquisition and diagnostic interpretation with minimum error are the important technical aspects of medical imaging. The image quality and resolution are really important in portraying the internal aspects of patient's body. Although there are several user friendly resources for processing image features, such as enhancement, colour manipulation and compression, the development of new processing methods is still worthy of efforts. In this article we aim to present the role of fractional calculus in imaging with the aid of practical examples. Copyright © 2018 Elsevier Ltd. All rights reserved.

On-Chip Biomedical Imaging

PubMed Central

Göröcs, Zoltán; Ozcan, Aydogan

2012-01-01

Lab-on-a-chip systems have been rapidly emerging to pave the way toward ultra-compact, efficient, mass producible and cost-effective biomedical research and diagnostic tools. Although such microfluidic and micro electromechanical systems achieved high levels of integration, and are capable of performing various important tasks on the same chip, such as cell culturing, sorting and staining, they still rely on conventional microscopes for their imaging needs. Recently several alternative on-chip optical imaging techniques have been introduced, which have the potential to substitute conventional microscopes for various lab-on-a-chip applications. Here we present a critical review of these recently emerging on-chip biomedical imaging modalities, including contact shadow imaging, lensfree holographic microscopy, fluorescent on-chip microscopy and lensfree optical tomography. PMID:23558399

New Windows based Color Morphological Operators for Biomedical Image Processing

NASA Astrophysics Data System (ADS)

Pastore, Juan; Bouchet, Agustina; Brun, Marcel; Ballarin, Virginia

2016-04-01

Morphological image processing is well known as an efficient methodology for image processing and computer vision. With the wide use of color in many areas, the interest on the color perception and processing has been growing rapidly. Many models have been proposed to extend morphological operators to the field of color images, dealing with some new problems not present previously in the binary and gray level contexts. These solutions usually deal with the lattice structure of the color space, or provide it with total orders, to be able to define basic operators with required properties. In this work we propose a new locally defined ordering, in the context of window based morphological operators, for the definition of erosions-like and dilation-like operators, which provides the same desired properties expected from color morphology, avoiding some of the drawbacks of the prior approaches. Experimental results show that the proposed color operators can be efficiently used for color image processing.

Measurement of OH, NO, O and N atoms in helium plasma jet for ROS/RNS controlled biomedical processes

NASA Astrophysics Data System (ADS)

Yonemori, Seiya; Kamakura, Taku; Ono, Ryo

2014-10-01

Atmospheric-pressure plasmas are of emerging interest for new plasma applications such as cancer treatment, cell activation and sterilization. In those biomedical processes, reactive oxygen/nitrogen species (ROS/RNS) are said that they play significant role. It is though that active species give oxidative stress and induce biomedical reactions. In this study, we measured OH, NO, O and N atoms using laser induced fluorescence (LIF) measurement and found that voltage polarity affect particular ROS. When negative high voltage was applied to the plasma jet, O atom density was tripled compared to the case of positive applied voltage. In that case, O atom density was around 3 × 1015 [cm-3] at maximum. In contrast, OH and NO density did not change their density depending on the polarity of applied voltage, measured as in order of 1013 and 1014 [cm-3] at maximum, respectively. From ICCD imaging measurement, it could be seen that negative high voltage enhanced secondary emission in plasma bullet propagation and it can affect the effective production of particular ROS. Since ROS/RNS dose can be a quantitative criterion to control plasma biomedical application, those measurement results is able to be applied for in vivo and in vitro plasma biomedical experiments. This study is supported by the Grant-in-Aid for Science Research by the Ministry of Education, Culture, Sport, Science and Technology.

Hypericin-mediated selective photomodification of connective tissues

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

Hovhannisyan, V., E-mail: hovv@phys.ntu.edu.tw; Guo, H. W.; Chen, Y. F., E-mail: yfchen@phys.ntu.edu.tw

2014-12-29

Controllable modification of biological molecules and supramolecular components of connective tissue are important for biophysical and biomedical applications. Through the use of second harmonic generation imaging, two-photon fluorescence microscopy, and spectrofluorimetry, we found that hypericin, a natural pigment, induces photosensitized destruction of collagen fibers but does not affect elastic fibers and lipids in chicken tendon, skin, and blood vessels. We demonstrated the dynamics and efficiency of collagen photomodification and investigated mechanisms of this processes. Our results suggest that hypericin–mediated photoprocesses in biological tissues may be useful in biomedical applications that require selective modification of connective tissues.

MATHEMATICAL METHODS IN MEDICAL IMAGE PROCESSING

PubMed Central

ANGENENT, SIGURD; PICHON, ERIC; TANNENBAUM, ALLEN

2013-01-01

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

Extraction of endoscopic images for biomedical figure classification

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; You, Daekeun; Chachra, Suchet; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.

2015-03-01

Modality filtering is an important feature in biomedical image searching systems and may significantly improve the retrieval performance of the system. This paper presents a new method for extracting endoscopic image figures from photograph images in biomedical literature, which are found to have highly diverse content and large variability in appearance. Our proposed method consists of three main stages: tissue image extraction, endoscopic image candidate extraction, and ophthalmic image filtering. For tissue image extraction we use image patch level clustering and MRF relabeling to detect images containing skin/tissue regions. Next, we find candidate endoscopic images by exploiting the round shape characteristics that commonly appear in these images. However, this step needs to compensate for images where endoscopic regions are not entirely round. In the third step we filter out the ophthalmic images which have shape characteristics very similar to the endoscopic images. We do this by using text information, specifically, anatomy terms, extracted from the figure caption. We tested and evaluated our method on a dataset of 115,370 photograph figures, and achieved promising precision and recall rates of 87% and 84%, respectively.

Integration of instrumentation and processing software of a laser speckle contrast imaging system

NASA Astrophysics Data System (ADS)

Carrick, Jacob J.

Laser speckle contrast imaging (LSCI) has the potential to be a powerful tool in medicine, but more research in the field is required so it can be used properly. To help in the progression of Michigan Tech's research in the field, a graphical user interface (GUI) was designed in Matlab to control the instrumentation of the experiments as well as process the raw speckle images into contrast images while they are being acquired. The design of the system was successful and is currently being used by Michigan Tech's Biomedical Engineering department. This thesis describes the development of the LSCI GUI as well as offering a full introduction into the history, theory and applications of LSCI.

A portable low-cost long-term live-cell imaging platform for biomedical research and education.

PubMed

Walzik, Maria P; Vollmar, Verena; Lachnit, Theresa; Dietz, Helmut; Haug, Susanne; Bachmann, Holger; Fath, Moritz; Aschenbrenner, Daniel; Abolpour Mofrad, Sepideh; Friedrich, Oliver; Gilbert, Daniel F

2015-02-15

Time-resolved visualization and analysis of slow dynamic processes in living cells has revolutionized many aspects of in vitro cellular studies. However, existing technology applied to time-resolved live-cell microscopy is often immobile, costly and requires a high level of skill to use and maintain. These factors limit its utility to field research and educational purposes. The recent availability of rapid prototyping technology makes it possible to quickly and easily engineer purpose-built alternatives to conventional research infrastructure which are low-cost and user-friendly. In this paper we describe the prototype of a fully automated low-cost, portable live-cell imaging system for time-resolved label-free visualization of dynamic processes in living cells. The device is light-weight (3.6 kg), small (22 × 22 × 22 cm) and extremely low-cost (<€1250). We demonstrate its potential for biomedical use by long-term imaging of recombinant HEK293 cells at varying culture conditions and validate its ability to generate time-resolved data of high quality allowing for analysis of time-dependent processes in living cells. While this work focuses on long-term imaging of mammalian cells, the presented technology could also be adapted for use with other biological specimen and provides a general example of rapidly prototyped low-cost biosensor technology for application in life sciences and education. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

[A web-based biomedical image mosaicing system].

PubMed

Zhang, Meng; Yan, Zhuang-zhi; Pan, Zhi-jun; Shao, Shi-jie

2006-11-01

This paper describes a web service for biomedical image mosaicing. A web site based on CGI (Common Gateway Interface) is implemented. The system is based on Browser/Server model and is tested in www. Finally implementation examples and experiment results are provided.

Window classification of brain CT images in biomedical articles.

PubMed

Xue, Zhiyun; Antani, Sameer; Long, L Rodney; Demner-Fushman, Dina; Thoma, George R

2012-01-01

Effective capability to search biomedical articles based on visual properties of article images may significantly augment information retrieval in the future. In this paper, we present a new method to classify the window setting types of brain CT images. Windowing is a technique frequently used in the evaluation of CT scans, and is used to enhance contrast for the particular tissue or abnormality type being evaluated. In particular, it provides radiologists with an enhanced view of certain types of cranial abnormalities, such as the skull lesions and bone dysplasia which are usually examined using the " bone window" setting and illustrated in biomedical articles using "bone window images". Due to the inherent large variations of images among articles, it is important that the proposed method is robust. Our algorithm attained 90% accuracy in classifying images as bone window or non-bone window in a 210 image data set.

Comparing methods for analysis of biomedical hyperspectral image data

NASA Astrophysics Data System (ADS)

Leavesley, Silas J.; Sweat, Brenner; Abbott, Caitlyn; Favreau, Peter F.; Annamdevula, Naga S.; Rich, Thomas C.

2017-02-01

Over the past 2 decades, hyperspectral imaging technologies have been adapted to address the need for molecule-specific identification in the biomedical imaging field. Applications have ranged from single-cell microscopy to whole-animal in vivo imaging and from basic research to clinical systems. Enabling this growth has been the availability of faster, more effective hyperspectral filtering technologies and more sensitive detectors. Hence, the potential for growth of biomedical hyperspectral imaging is high, and many hyperspectral imaging options are already commercially available. However, despite the growth in hyperspectral technologies for biomedical imaging, little work has been done to aid users of hyperspectral imaging instruments in selecting appropriate analysis algorithms. Here, we present an approach for comparing the effectiveness of spectral analysis algorithms by combining experimental image data with a theoretical "what if" scenario. This approach allows us to quantify several key outcomes that characterize a hyperspectral imaging study: linearity of sensitivity, positive detection cut-off slope, dynamic range, and false positive events. We present results of using this approach for comparing the effectiveness of several common spectral analysis algorithms for detecting weak fluorescent protein emission in the midst of strong tissue autofluorescence. Results indicate that this approach should be applicable to a very wide range of applications, allowing a quantitative assessment of the effectiveness of the combined biology, hardware, and computational analysis for detecting a specific molecular signature.

To boldly glow ... applications of laser scanning confocal microscopy in developmental biology.

PubMed

Paddock, S W

1994-05-01

The laser scanning confocal microscope (LSCM) is now established as an invaluable tool in developmental biology for improved light microscope imaging of fluorescently labelled eggs, embryos and developing tissues. The universal application of the LSCM in biomedical research has stimulated improvements to the microscopes themselves and the synthesis of novel probes for imaging biological structures and physiological processes. Moreover the ability of the LSCM to produce an optical series in perfect register has made computer 3-D reconstruction and analysis of light microscope images a practical option.

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

PubMed

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

2017-04-10

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

The development of biomedical engineering as experienced by one biomedical engineer

PubMed Central

2012-01-01

This personal essay described the development of the field of Biomedical Engineering from its early days, from the perspective of one who lived through that development. It describes the making of a major invention using data that had been rejected by other scientists, the re-discovery of an obscure fact of physiology and its use in developing a major medical instrument, the development of a new medical imaging modality, and the near-death rescue of a research project. The essay concludes with comments about the development and present status of impedance imaging, and recent changes in the evolution of biomedical engineering as a field. PMID:23234267

The development of biomedical engineering as experienced by one biomedical engineer.

PubMed

Newell, Jonathan C

2012-12-12

This personal essay described the development of the field of Biomedical Engineering from its early days, from the perspective of one who lived through that development. It describes the making of a major invention using data that had been rejected by other scientists, the re-discovery of an obscure fact of physiology and its use in developing a major medical instrument, the development of a new medical imaging modality, and the near-death rescue of a research project. The essay concludes with comments about the development and present status of impedance imaging, and recent changes in the evolution of biomedical engineering as a field.

Quantum Cascade Lasers in Biomedical Infrared Imaging.

PubMed

Bird, Benjamin; Baker, Matthew J

2015-10-01

Technological advances, namely the integration of quantum cascade lasers (QCLs) within an infrared (IR) microscope, are enabling the development of valuable label-free biomedical-imaging tools capable of targeting and detecting salient chemical species within practical clinical timeframes. Copyright © 2015 Elsevier Ltd. All rights reserved.

A robust pointer segmentation in biomedical images toward building a visual ontology for biomedical article retrieval

NASA Astrophysics Data System (ADS)

You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-01-01

Pointers (arrows and symbols) are frequently used in biomedical images to highlight specific image regions of interest (ROIs) that are mentioned in figure captions and/or text discussion. Detection of pointers is the first step toward extracting relevant visual features from ROIs and combining them with textual descriptions for a multimodal (text and image) biomedical article retrieval system. Recently we developed a pointer recognition algorithm based on an edge-based pointer segmentation method, and subsequently reported improvements made on our initial approach involving the use of Active Shape Models (ASM) for pointer recognition and region growing-based method for pointer segmentation. These methods contributed to improving the recall of pointer recognition but not much to the precision. The method discussed in this article is our recent effort to improve the precision rate. Evaluation performed on two datasets and compared with other pointer segmentation methods show significantly improved precision and the highest F1 score.

Validation of Clay Modeling as a Learning Tool for the Periventricular Structures of the Human Brain

ERIC Educational Resources Information Center

Akle, Veronica; Peña-Silva, Ricardo A.; Valencia, Diego M.; Rincón-Perez, Carlos W.

2018-01-01

Visualizing anatomical structures and functional processes in three dimensions (3D) are important skills for medical students. However, contemplating 3D structures mentally and interpreting biomedical images can be challenging. This study examines the impact of a new pedagogical approach to teaching neuroanatomy, specifically how building a…

Biomedical photoacoustics: fundamentals, instrumentation and perspectives on nanomedicine

PubMed Central

Zou, Chunpeng; Wu, Beibei; Dong, Yanyan; Song, Zhangwei; Zhao, Yaping; Ni, Xianwei; Yang, Yan; Liu, Zhe

2017-01-01

Photoacoustic imaging (PAI) is an integrated biomedical imaging modality which combines the advantages of acoustic deep penetration and optical high sensitivity. It can provide functional and structural images with satisfactory resolution and contrast which could provide abundant pathological information for disease-oriented diagnosis. Therefore, it has found vast applications so far and become a powerful tool of precision nanomedicine. However, the investigation of PAI-based imaging nanomaterials is still in its infancy. This perspective article aims to summarize the developments in photoacoustic technologies and instrumentations in the past years, and more importantly, present a bright outlook for advanced PAI-based imaging nanomaterials as well as their emerging biomedical applications in nanomedicine. Current challenges and bottleneck issues have also been discussed and elucidated in this article to bring them to the attention of the readership. PMID:28053532

Towards an easier creation of three-dimensional data for embedding into scholarly 3D PDF (Portable Document Format) files

PubMed Central

2015-01-01

The Portable Document Format (PDF) allows for embedding three-dimensional (3D) models and is therefore particularly suitable to communicate respective data, especially as regards scholarly articles. The generation of the necessary model data, however, is still challenging, especially for inexperienced users. This prevents an unrestrained proliferation of 3D PDF usage in scholarly communication. This article introduces a new solution for the creation of three of types of 3D geometry (point clouds, polylines and triangle meshes), that is based on MeVisLab, a framework for biomedical image processing. This solution enables even novice users to generate the model data files without requiring programming skills and without the need for an intensive training by simply using it as a conversion tool. Advanced users can benefit from the full capability of MeVisLab to generate and export the model data as part of an overall processing chain. Although MeVisLab is primarily designed for handling biomedical image data, the new module is not restricted to this domain. It can be used for all scientific disciplines. PMID:25780759

Towards an easier creation of three-dimensional data for embedding into scholarly 3D PDF (Portable Document Format) files.

PubMed

Newe, Axel

2015-01-01

The Portable Document Format (PDF) allows for embedding three-dimensional (3D) models and is therefore particularly suitable to communicate respective data, especially as regards scholarly articles. The generation of the necessary model data, however, is still challenging, especially for inexperienced users. This prevents an unrestrained proliferation of 3D PDF usage in scholarly communication. This article introduces a new solution for the creation of three of types of 3D geometry (point clouds, polylines and triangle meshes), that is based on MeVisLab, a framework for biomedical image processing. This solution enables even novice users to generate the model data files without requiring programming skills and without the need for an intensive training by simply using it as a conversion tool. Advanced users can benefit from the full capability of MeVisLab to generate and export the model data as part of an overall processing chain. Although MeVisLab is primarily designed for handling biomedical image data, the new module is not restricted to this domain. It can be used for all scientific disciplines.

78 FR 76634 - National Institute of Biomedical Imaging and Bioengineering; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-18

... such as patentable material, and personal information concerning individuals associated with the grant... of personal privacy. Name of Committee: National Advisory Council for Biomedical Imaging and..., Bethesda, MD 20892. Any interested person may file written comments with the committee by forwarding the...

75 FR 76019 - National Institute of Biomedical Imaging and Bioengineering; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-07

... strategic plan. Place: Bethesda Marriott Suites, 6711 Democracy Boulevard, Independence Room (2nd Level... proposals. Place: Bethesda Marriott Suites, 6711 Democracy Boulevard, Independence Room (2nd Level), Bethesda, MD 20817. Contact Person: Anthony Demsey, PhD, Director, National Institute of Biomedical Imaging...

Plasmonic nanoparticle-generated photothermal bubbles and their biomedical applications

PubMed Central

Lapotko, Dmitri

2009-01-01

This article is focused on the optical generation and detection of photothermal vapor bubbles around plasmonic nanoparticles. We report physical properties of such plasmonic nanobubbles and their biomedical applications as cellular probes. Our experimental studies of gold nanoparticle-generated photothermal bubbles demonstrated the selectivity of photothermal bubble generation, amplification of optical scattering and thermal insulation effect, all realized at the nanoscale. The generation and imaging of photothermal bubbles in living cells (leukemia and carcinoma culture and primary cancerous cells), and tissues (atherosclerotic plaque and solid tumor in animal) demonstrated a noninvasive highly sensitive imaging of target cells by small photothermal bubbles and a selective mechanical, nonthermal damage to the individual target cells by bigger photothermal bubbles due to a rapid disruption of cellular membranes. The analysis of the plasmonic nanobubbles suggests them as theranostic probes, which can be tuned and optically guided at cell level from diagnosis to delivery and therapy during one fast process. PMID:19839816

Seeing through walls at the nanoscale: Microwave microscopy of enclosed objects and processes in liquids

DOE PAGES

Velmurugan, Jeyavel; Kalinin, Sergei V.; Kolmakov, Andrei; ...

2016-02-11

Here, noninvasive in situ nanoscale imaging in liquid environments is a current imperative in the analysis of delicate biomedical objects and electrochemical processes at reactive liquid–solid interfaces. Microwaves of a few gigahertz frequencies offer photons with energies of ≈10 μeV, which can affect neither electronic states nor chemical bonds in condensed matter. Here, we describe an implementation of scanning near-field microwave microscopy for imaging in liquids using ultrathin molecular impermeable membranes separating scanning probes from samples enclosed in environmental cells. We imaged a model electroplating reaction as well as individual live cells. Through a side-by-side comparison of the microwave imagingmore » with scanning electron microscopy, we demonstrate the advantage of microwaves for artifact-free imaging.« less

Big Data Application in Biomedical Research and Health Care: A Literature Review.

PubMed

Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

2016-01-01

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care.

Big Data Application in Biomedical Research and Health Care: A Literature Review

PubMed Central

Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

2016-01-01

Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care. PMID:26843812

Structure-Preserving Smoothing of Biomedical Images

NASA Astrophysics Data System (ADS)

Gil, Debora; Hernàndez-Sabaté, Aura; Burnat, Mireia; Jansen, Steven; Martínez-Villalta, Jordi

Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood.

Non-Contact Optical Ultrasound Concept for Biomedical Imaging

DTIC Science & Technology

2016-11-03

Non -Contact Optical Ultrasound Concept for Biomedical Imaging Robert Haupt1, Charles Wynn1, Jonathan Fincke2, Shawn Zhang2, Brian Anthony2...results. Lastly, we present imaging capabilities using a non -contact laser ultrasound proof-of-concept system. Two and three dimensional time... non -contact, standoff optical ultrasound has the potential to provide a fixed reference measurement capability that minimizes operator variability as

Biomedical terahertz imaging with a quantum cascade laser

NASA Astrophysics Data System (ADS)

Kim, Seongsin M.; Hatami, Fariba; Harris, James S.; Kurian, Allison W.; Ford, James; King, Douglas; Scalari, Giacomo; Giovannini, Marcella; Hoyler, Nicolas; Faist, Jerome; Harris, Geoff

2006-04-01

We present biomedical imaging using a single frequency terahertz imaging system based on a low threshold quantum cascade laser emitting at 3.7THz (λ=81μm). With a peak output power of 4mW, coherent terahertz radiation and detection provide a relatively large dynamic range and high spatial resolution. We study image contrast based on water/fat content ratios in different tissues. Terahertz transmission imaging demonstrates a distinct anatomy in a rat brain slice. We also demonstrate malignant tissue contrast in an image of a mouse liver with developed tumors, indicating potential use of terahertz imaging for probing cancerous tissues.

Synthesis and Ligand-Exchange Reactions of a Tri-Tungsten Cluster with Applications in Biomedical Imaging

ERIC Educational Resources Information Center

Noey, Elizabeth; Curtis, Jeff C.; Tam, Sylvia; Pham, David M.; Jones, Ella F.

2011-01-01

In this experiment students are exposed to concepts in inorganic synthesis and various spectroscopies as applied to a tri-tungsten cluster with applications in biomedical imaging. The tungsten-acetate cluster, Na[W[superscript 3](mu-O)[subscript 2](CH[superscript 3]COO)[superscript 9

Biomedical imaging and sensing using flatbed scanners.

PubMed

Göröcs, Zoltán; Ozcan, Aydogan

2014-09-07

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600-700 cm(2)) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings.

Biomedical Imaging and Sensing using Flatbed Scanners

PubMed Central

Göröcs, Zoltán; Ozcan, Aydogan

2014-01-01

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g., ~600–700 cm2) of these devices coupled with their cost-effectiveness provide unique opportunities for digital imaging of samples that are too large for regular optical microscopes, and for collection of large amounts of statistical data in various automated imaging or sensing tasks. Here we give a short introduction to the basic features of flatbed scanners also highlighting the key parameters for designing scientific experiments using these devices, followed by a discussion of some of the significant examples, where scanner-based systems were constructed to conduct various biomedical imaging and/or sensing experiments. Along with mobile phones and other emerging consumer electronics devices, flatbed scanners and their use in advanced imaging and sensing experiments might help us transform current practices of medicine, engineering and sciences through democratization of measurement science and empowerment of citizen scientists, science educators and researchers in resource limited settings. PMID:24965011

Biomedical Applications of Carbon Nanotubes: A Critical Review.

PubMed

Sharma, Priyanka; Mehra, Neelesh Kumar; Jain, Keerti; Jain, N K

2016-08-01

The convergence of nano and biotechnology is enabling scientific and technical knowledge for improving human well being. Carbon nanotubes have become most fascinating material to be studied and unveil new avenues in the field of nanobiotechnology. The nanometer size and high aspect ratio of the CNTs are the two distinct features, which have contributed to diverse biomedical applications. They have captured the attention as nanoscale materials due to their nanometric structure and remarkable list of superlative and extravagant properties that encouraged their exploitation for promising applications. Significant progress has been made in order to overcome some of the major hurdles towards biomedical application of nanomaterials, especially on issues regarding the aqueous solubility/dispersion and safety of CNTs. Functionalized CNTs have been used in drug targeting, imaging, and in the efficient delivery of gene and nucleic acids. CNTs have also demonstrated great potential in diverse biomedical uses like drug targeting, imaging, cancer treatment, tissue regeneration, diagnostics, biosensing, genetic engineering and so forth. The present review highlights the possible potential of CNTs in diagnostics, imaging and targeted delivery of bioactives and also outlines the future opportunities for biomedical applications.

Molecular Imaging in Synthetic Biology, and Synthetic Biology in Molecular Imaging.

PubMed

Gilad, Assaf A; Shapiro, Mikhail G

2017-06-01

Biomedical synthetic biology is an emerging field in which cells are engineered at the genetic level to carry out novel functions with relevance to biomedical and industrial applications. This approach promises new treatments, imaging tools, and diagnostics for diseases ranging from gastrointestinal inflammatory syndromes to cancer, diabetes, and neurodegeneration. As these cellular technologies undergo pre-clinical and clinical development, it is becoming essential to monitor their location and function in vivo, necessitating appropriate molecular imaging strategies, and therefore, we have created an interest group within the World Molecular Imaging Society focusing on synthetic biology and reporter gene technologies. Here, we highlight recent advances in biomedical synthetic biology, including bacterial therapy, immunotherapy, and regenerative medicine. We then discuss emerging molecular imaging approaches to facilitate in vivo applications, focusing on reporter genes for noninvasive modalities such as magnetic resonance, ultrasound, photoacoustic imaging, bioluminescence, and radionuclear imaging. Because reporter genes can be incorporated directly into engineered genetic circuits, they are particularly well suited to imaging synthetic biological constructs, and developing them provides opportunities for creative molecular and genetic engineering.

Ultrasound tissue analysis and characterization

NASA Astrophysics Data System (ADS)

Kaufhold, John; Chan, Ray C.; Karl, William C.; Castanon, David A.

1999-07-01

On the battlefield of the future, it may become feasible for medics to perform, via application of new biomedical technologies, more sophisticated diagnoses and surgery than is currently practiced. Emerging biomedical technology may enable the medic to perform laparoscopic surgical procedures to remove, for example, shrapnel from injured soldiers. Battlefield conditions constrain the types of medical image acquisition and interpretation which can be performed. Ultrasound is the only viable biomedical imaging modality appropriate for deployment on the battlefield -- which leads to image interpretation issues because of the poor quality of ultrasound imagery. To help overcome these issues, we develop and implement a method of image enhancement which could aid non-experts in the rapid interpretation and use of ultrasound imagery. We describe an energy minimization approach to finding boundaries in medical images and show how prior information on edge orientation can be incorporated into this framework to detect tissue boundaries oriented at a known angle.

Annotating image ROIs with text descriptions for multimodal biomedical document retrieval

NASA Astrophysics Data System (ADS)

You, Daekeun; Simpson, Matthew; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-01-01

Regions of interest (ROIs) that are pointed to by overlaid markers (arrows, asterisks, etc.) in biomedical images are expected to contain more important and relevant information than other regions for biomedical article indexing and retrieval. We have developed several algorithms that localize and extract the ROIs by recognizing markers on images. Cropped ROIs then need to be annotated with contents describing them best. In most cases accurate textual descriptions of the ROIs can be found from figure captions, and these need to be combined with image ROIs for annotation. The annotated ROIs can then be used to, for example, train classifiers that separate ROIs into known categories (medical concepts), or to build visual ontologies, for indexing and retrieval of biomedical articles. We propose an algorithm that pairs visual and textual ROIs that are extracted from images and figure captions, respectively. This algorithm based on dynamic time warping (DTW) clusters recognized pointers into groups, each of which contains pointers with identical visual properties (shape, size, color, etc.). Then a rule-based matching algorithm finds the best matching group for each textual ROI mention. Our method yields a precision and recall of 96% and 79%, respectively, when ground truth textual ROI data is used.

Use of commercial off-the-shelf digital cameras for scientific data acquisition and scene-specific color calibration

PubMed Central

Akkaynak, Derya; Treibitz, Tali; Xiao, Bei; Gürkan, Umut A.; Allen, Justine J.; Demirci, Utkan; Hanlon, Roger T.

2014-01-01

Commercial off-the-shelf digital cameras are inexpensive and easy-to-use instruments that can be used for quantitative scientific data acquisition if images are captured in raw format and processed so that they maintain a linear relationship with scene radiance. Here we describe the image-processing steps required for consistent data acquisition with color cameras. In addition, we present a method for scene-specific color calibration that increases the accuracy of color capture when a scene contains colors that are not well represented in the gamut of a standard color-calibration target. We demonstrate applications of the proposed methodology in the fields of biomedical engineering, artwork photography, perception science, marine biology, and underwater imaging. PMID:24562030

Microbubble Compositions, Properties and Biomedical Applications

PubMed Central

Sirsi, Shashank

2010-01-01

Over the last decade, there has been significant progress towards the development of microbubbles as theranostics for a wide variety of biomedical applications. The unique ability of microbubbles to respond to ultrasound makes them useful agents for contrast ultrasound imaging, molecular imaging, and targeted drug and gene delivery. The general composition of a microbubble is a gas core stabilized by a shell comprised of proteins, lipids or polymers. Each type of microbubble has its own unique advantages and can be tailored for specialized functions. In this review, different microbubbles compositions and physiochemical properties are discussed in the context of current progress towards developing novel constructs for biomedical applications, with specific emphasis on molecular imaging and targeted drug/gene delivery. PMID:20574549

Advances in Clinical and Biomedical Applications of Photoacoustic Imaging

PubMed Central

Su, Jimmy L.; Wang, Bo; Wilson, Katheryne E.; Bayer, Carolyn L.; Chen, Yun-Sheng; Kim, Seungsoo; Homan, Kimberly A.; Emelianov, Stanislav Y.

2010-01-01

Importance of the field Photoacoustic imaging is an imaging modality that derives image contrast from the optical absorption coefficient of the tissue being imaged. The imaging technique is able to differentiate between healthy and diseased tissue with either deeper penetration or higher resolution than other functional imaging modalities currently available. From a clinical standpoint, photoacoustic imaging has demonstrated safety and effectiveness in diagnosing diseased tissue regions using either endogenous tissue contrast or exogenous contrast agents. Furthermore, the potential of photoacoustic imaging has been demonstrated in various therapeutic interventions ranging from drug delivery and release to image-guided therapy and monitoring. Areas covered in this review This article reviews the current state of photoacoustic imaging in biomedicine from a technological perspective, highlights various biomedical and clinical applications of photoacoustic imaging, and gives insights on future directions. What the reader will gain Readers will learn about the various applications of photoacoustic imaging, as well as the various contrast agents that can be used to assist photoacoustic imaging. This review will highlight both pre-clinical and clinical uses for photoacoustic imaging, as well as discuss some of the challenges that must be addressed to move photoacoustic imaging into the clinical realm. Take home message Photoacoustic imaging offers unique advantages over existing imaging modalities. The imaging field is broad with many exciting applications for detecting and diagnosing diseased tissue or processes. Photoacoustics is also used in therapeutic applications to identify and characterize the pathology and then to monitor the treatment. Although the technology is still in its infancy, much work has been done in the pre-clinical arena, and photoacoustic imaging is fast approaching the clinical setting. PMID:21344060

Automated segmentation of synchrotron radiation micro-computed tomography biomedical images using Graph Cuts and neural networks

NASA Astrophysics Data System (ADS)

Alvarenga de Moura Meneses, Anderson; Giusti, Alessandro; de Almeida, André Pereira; Parreira Nogueira, Liebert; Braz, Delson; Cely Barroso, Regina; deAlmeida, Carlos Eduardo

2011-12-01

Synchrotron Radiation (SR) X-ray micro-Computed Tomography (μCT) enables magnified images to be used as a non-invasive and non-destructive technique with a high space resolution for the qualitative and quantitative analyses of biomedical samples. The research on applications of segmentation algorithms to SR-μCT is an open problem, due to the interesting and well-known characteristics of SR images for visualization, such as the high resolution and the phase contrast effect. In this article, we describe and assess the application of the Energy Minimization via Graph Cuts (EMvGC) algorithm for the segmentation of SR-μCT biomedical images acquired at the Synchrotron Radiation for MEdical Physics (SYRMEP) beam line at the Elettra Laboratory (Trieste, Italy). We also propose a method using EMvGC with Artificial Neural Networks (EMANNs) for correcting misclassifications due to intensity variation of phase contrast, which are important effects and sometimes indispensable in certain biomedical applications, although they impair the segmentation provided by conventional techniques. Results demonstrate considerable success in the segmentation of SR-μCT biomedical images, with average Dice Similarity Coefficient 99.88% for bony tissue in Wistar Rats rib samples (EMvGC), as well as 98.95% and 98.02% for scans of Rhodnius prolixus insect samples (Chagas's disease vector) with EMANNs, in relation to manual segmentation. The techniques EMvGC and EMANNs cope with the task of performing segmentation in images with the intensity variation due to phase contrast effects, presenting a superior performance in comparison to conventional segmentation techniques based on thresholding and linear/nonlinear image filtering, which is also discussed in the present article.

The Function Biomedical Informatics Research Network Data Repository

PubMed Central

Keator, David B.; van Erp, Theo G.M.; Turner, Jessica A.; Glover, Gary H.; Mueller, Bryon A.; Liu, Thomas T.; Voyvodic, James T.; Rasmussen, Jerod; Calhoun, Vince D.; Lee, Hyo Jong; Toga, Arthur W.; McEwen, Sarah; Ford, Judith M.; Mathalon, Daniel H.; Diaz, Michele; O’Leary, Daniel S.; Bockholt, H. Jeremy; Gadde, Syam; Preda, Adrian; Wible, Cynthia G.; Stern, Hal S.; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G.

2015-01-01

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical datasets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 dataset consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 Tesla scanners. The FBIRN Phase 2 and Phase 3 datasets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN’s multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data. PMID:26364863

75 FR 35820 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-23

... Imaging and Bioengineering Special Emphasis Panel Decision Support Systems and Comparative Effectiveness Research (ARRA). Date: July 23, 2010. Time: 12 p.m. to 5 p.m. Agenda: To review and evaluate grant... Assistance Program Nos. 93.701, ARRA Related Biomedical Research and Research Support Awards, National...

Characterization of Acoustic Droplet Vaporization Using MRI

NASA Astrophysics Data System (ADS)

Li, David; Allen, Steven; Hernandez-Garcia, Luis; Bull, Joseph

2013-11-01

Acoustic droplet vaporization (ADV) is the selective vaporization of liquid droplets to form larger gas bubbles. The ADV process is currently being researched for biomedical applications such as gas embolotherapy, drug delivery, and phase-change contrast agents. In this study an albumin encapsulated dodecafluoropentane (DDFP, CAS: 678-26-2) microdroplet suspension was vaporized using a single element focused (f/2, D = 19 mm) 3.5 MHz transducer (Panametrics A321S, Olympus, Waltham, MA). The resulting DDFP bubble clouds were imaged using both bright field microscopy and MRI (Varian 7T, Agilent Technologies Inc., Santa Clara, CA). Field distortions due to DDFP bubble generation were characterized against the bright field images as a function of acoustic power and bubble cloud size. Experimentally a direct correlation between bubble cloud dimensions generated and field distortions seen in the MRI was observed. Additionally, MR velocimetry was used to measure the flow field resulting from ADV. The field distortions due to the bubbles were further characterized by modeling Maxwell's equations using COMSOL (COMSOL Inc., Burlington, MA). The ability to characterize ADV with alternative imaging modalities may prove useful in further development of ADV based biomedical therapies.

Development of image mappers for hyperspectral biomedical imaging applications

PubMed Central

Kester, Robert T.; Gao, Liang; Tkaczyk, Tomasz S.

2010-01-01

A new design and fabrication method is presented for creating large-format (>100 mirror facets) image mappers for a snapshot hyperspectral biomedical imaging system called an image mapping spectrometer (IMS). To verify this approach a 250 facet image mapper with 25 multiple-tilt angles is designed for a compact IMS that groups the 25 subpupils in a 5 × 5 matrix residing within a single collecting objective's pupil. The image mapper is fabricated by precision diamond raster fly cutting using surface-shaped tools. The individual mirror facets have minimal edge eating, tilt errors of <1 mrad, and an average roughness of 5.4 nm. PMID:20357875

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.

76 FR 66735 - Announcement of Requirements and Registration for the NIBIB DEsign by Biomedical Undergraduate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-27

...., implants, biomaterials, surgical tools, tissue engineering, drug and gene delivery; (c) Technology to Aid... health information, and other programs with respect to biomedical imaging and engineering and associated... ceremony: October 2012, Biomedical Engineering Society Conference (exact date to be determined). FOR...

Planning a new library in an age of transition: the Washington University School of Medicine Library and Biomedical Communications Center.

PubMed Central

Crawford, S; Halbrook, B

1990-01-01

In an era of great technological and socioeconomic changes, the Washington University School of Medicine conceptualized and built its first Library and Biomedical Communications Center in seventy-eight years. The planning process, evolution of the electronic library, and translation of functions into operating spaces are discussed. Since 1983, when the project was approved, a whole range of information technologies and services have emerged. The authors consider the kind of library that would operate in a setting where people can do their own searches, order data and materials through an electronic network, analyze and manage information, and use software to create their own publications. Images PMID:2393757

Endovascular Device Testing with Particle Image Velocimetry Enhances Undergraduate Biomedical Engineering Education

ERIC Educational Resources Information Center

Nair, Priya; Ankeny, Casey J.; Ryan, Justin; Okcay, Murat; Frakes, David H.

2016-01-01

We investigated the use of a new system, HemoFlow™, which utilizes state of the art technologies such as particle image velocimetry to test endovascular devices as part of an undergraduate biomedical engineering curriculum. Students deployed an endovascular stent into an anatomical model of a cerebral aneurysm and measured intra-aneurysmal flow…

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.

Time of flight imaging through scattering environments (Conference Presentation)

NASA Astrophysics Data System (ADS)

Le, Toan H.; Breitbach, Eric C.; Jackson, Jonathan A.; Velten, Andreas

2017-02-01

Light scattering is a primary obstacle to imaging in many environments. On small scales in biomedical microscopy and diffuse tomography scenarios scattering is caused by tissue. On larger scales scattering from dust and fog provide challenges to vision systems for self driving cars and naval remote imaging systems. We are developing scale models for scattering environments and investigation methods for improved imaging particularly using time of flight transient information. With the emergence of Single Photon Avalanche Diode detectors and fast semiconductor lasers, illumination and capture on picosecond timescales are becoming possible in inexpensive, compact, and robust devices. This opens up opportunities for new computational imaging techniques that make use of photon time of flight. Time of flight or range information is used in remote imaging scenarios in gated viewing and in biomedical imaging in time resolved diffuse tomography. In addition spatial filtering is popular in biomedical scenarios with structured illumination and confocal microscopy. We are presenting a combination analytical, computational, and experimental models that allow us develop and test imaging methods across scattering scenarios and scales. This framework will be used for proof of concept experiments to evaluate new computational imaging methods.

Melanin-Based Contrast Agents for Biomedical Optoacoustic Imaging and Theranostic Applications.

PubMed

Longo, Dario Livio; Stefania, Rachele; Aime, Silvio; Oraevsky, Alexander

2017-08-07

Optoacoustic imaging emerged in early 1990s as a new biomedical imaging technology that generates images by illuminating tissues with short laser pulses and detecting resulting ultrasound waves. This technique takes advantage of the spectroscopic approach to molecular imaging, and delivers high-resolution images in the depth of tissue. Resolution of the optoacoustic imaging is scalable, so that biomedical systems from cellular organelles to large organs can be visualized and, more importantly, characterized based on their optical absorption coefficient, which is proportional to the concentration of absorbing chromophores. Optoacoustic imaging was shown to be useful in both preclinical research using small animal models and in clinical applications. Applications in the field of molecular imaging offer abundant opportunities for the development of highly specific and effective contrast agents for quantitative optoacoustic imaging. Recent efforts are being made in the direction of nontoxic biodegradable contrast agents (such as nanoparticles made of melanin) that are potentially applicable in clinical optoacoustic imaging. In order to increase the efficiency and specificity of contrast agents and probes, they need to be made smart and capable of controlled accumulation in the target cells. This review was written in recognition of the potential breakthroughs in medical optoacoustic imaging that can be enabled by efficient and nontoxic melanin-based optoacoustic contrast agents.

Melanin-Based Contrast Agents for Biomedical Optoacoustic Imaging and Theranostic Applications

PubMed Central

Longo, Dario Livio; Aime, Silvio

2017-01-01

Optoacoustic imaging emerged in early 1990s as a new biomedical imaging technology that generates images by illuminating tissues with short laser pulses and detecting resulting ultrasound waves. This technique takes advantage of the spectroscopic approach to molecular imaging, and delivers high-resolution images in the depth of tissue. Resolution of the optoacoustic imaging is scalable, so that biomedical systems from cellular organelles to large organs can be visualized and, more importantly, characterized based on their optical absorption coefficient, which is proportional to the concentration of absorbing chromophores. Optoacoustic imaging was shown to be useful in both preclinical research using small animal models and in clinical applications. Applications in the field of molecular imaging offer abundant opportunities for the development of highly specific and effective contrast agents for quantitative optoacoustic imaging. Recent efforts are being made in the direction of nontoxic biodegradable contrast agents (such as nanoparticles made of melanin) that are potentially applicable in clinical optoacoustic imaging. In order to increase the efficiency and specificity of contrast agents and probes, they need to be made smart and capable of controlled accumulation in the target cells. This review was written in recognition of the potential breakthroughs in medical optoacoustic imaging that can be enabled by efficient and nontoxic melanin-based optoacoustic contrast agents. PMID:28783106

3D correlative light and electron microscopy of cultured cells using serial blockface scanning electron microscopy

PubMed Central

Lerner, Thomas R.; Burden, Jemima J.; Nkwe, David O.; Pelchen-Matthews, Annegret; Domart, Marie-Charlotte; Durgan, Joanne; Weston, Anne; Jones, Martin L.; Peddie, Christopher J.; Carzaniga, Raffaella; Florey, Oliver; Marsh, Mark; Gutierrez, Maximiliano G.

2017-01-01

ABSTRACT The processes of life take place in multiple dimensions, but imaging these processes in even three dimensions is challenging. Here, we describe a workflow for 3D correlative light and electron microscopy (CLEM) of cell monolayers using fluorescence microscopy to identify and follow biological events, combined with serial blockface scanning electron microscopy to analyse the underlying ultrastructure. The workflow encompasses all steps from cell culture to sample processing, imaging strategy, and 3D image processing and analysis. We demonstrate successful application of the workflow to three studies, each aiming to better understand complex and dynamic biological processes, including bacterial and viral infections of cultured cells and formation of entotic cell-in-cell structures commonly observed in tumours. Our workflow revealed new insight into the replicative niche of Mycobacterium tuberculosis in primary human lymphatic endothelial cells, HIV-1 in human monocyte-derived macrophages, and the composition of the entotic vacuole. The broad application of this 3D CLEM technique will make it a useful addition to the correlative imaging toolbox for biomedical research. PMID:27445312

Using image mapping towards biomedical and biological data sharing

PubMed Central

2013-01-01

Image-based data integration in eHealth and life sciences is typically concerned with the method used for anatomical space mapping, needed to retrieve, compare and analyse large volumes of biomedical data. In mapping one image onto another image, a mechanism is used to match and find the corresponding spatial regions which have the same meaning between the source and the matching image. Image-based data integration is useful for integrating data of various information structures. Here we discuss a broad range of issues related to data integration of various information structures, review exemplary work on image representation and mapping, and discuss the challenges that these techniques may bring. PMID:24059352

Recent Development of Inorganic Nanoparticles for Biomedical Imaging

PubMed Central

2018-01-01

Inorganic nanoparticle-based biomedical imaging probes have been studied extensively as a potential alternative to conventional molecular imaging probes. Not only can they provide better imaging performance but they can also offer greater versatility of multimodal, stimuli-responsive, and targeted imaging. However, inorganic nanoparticle-based probes are still far from practical use in clinics due to safety concerns and less-optimized efficiency. In this context, it would be valuable to look over the underlying issues. This outlook highlights the recent advances in the development of inorganic nanoparticle-based probes for MRI, CT, and anti-Stokes shift-based optical imaging. Various issues and possibilities regarding the construction of imaging probes are discussed, and future research directions are suggested. PMID:29632878

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

NASA Astrophysics Data System (ADS)

Möller, Manuel; Tuot, Christopher; Sintek, Michael

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

Magnetic particle imaging for radiation-free, sensitive and high-contrast vascular imaging and cell tracking.

PubMed

Zhou, Xinyi Y; Tay, Zhi Wei; Chandrasekharan, Prashant; Yu, Elaine Y; Hensley, Daniel W; Orendorff, Ryan; Jeffris, Kenneth E; Mai, David; Zheng, Bo; Goodwill, Patrick W; Conolly, Steven M

2018-05-10

Magnetic particle imaging (MPI) is an emerging ionizing radiation-free biomedical tracer imaging technique that directly images the intense magnetization of superparamagnetic iron oxide nanoparticles (SPIOs). MPI offers ideal image contrast because MPI shows zero signal from background tissues. Moreover, there is zero attenuation of the signal with depth in tissue, allowing for imaging deep inside the body quantitatively at any location. Recent work has demonstrated the potential of MPI for robust, sensitive vascular imaging and cell tracking with high contrast and dose-limited sensitivity comparable to nuclear medicine. To foster future applications in MPI, this new biomedical imaging field is welcoming researchers with expertise in imaging physics, magnetic nanoparticle synthesis and functionalization, nanoscale physics, and small animal imaging applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

Biomedical Imaging

DTIC Science & Technology

1994-04-01

distribution unlimited. United States Army Aeromedical Research Laboratory Fort Rucker, Alabama 36362-0577 Qualified recuesters Qualified requesters may...FUNDING NUMBER5 I PROGRAM zfJECT TASK WORK UNIT ELEMENT NO. NO. ACCESSION NO. 62787A 30162787A87$ EA 138 Biomedical Imaging 12. PERSONAL AUTHOR(S...times larger. Usually they are expensive with commercially available units starting at around $100,000. Triangulation sensors are capable of range

Characterizing microstructural features of biomedical samples by statistical analysis of Mueller matrix images

NASA Astrophysics Data System (ADS)

He, Honghui; Dong, Yang; Zhou, Jialing; Ma, Hui

2017-03-01

As one of the salient features of light, polarization contains abundant structural and optical information of media. Recently, as a comprehensive description of polarization property, the Mueller matrix polarimetry has been applied to various biomedical studies such as cancerous tissues detections. In previous works, it has been found that the structural information encoded in the 2D Mueller matrix images can be presented by other transformed parameters with more explicit relationship to certain microstructural features. In this paper, we present a statistical analyzing method to transform the 2D Mueller matrix images into frequency distribution histograms (FDHs) and their central moments to reveal the dominant structural features of samples quantitatively. The experimental results of porcine heart, intestine, stomach, and liver tissues demonstrate that the transformation parameters and central moments based on the statistical analysis of Mueller matrix elements have simple relationships to the dominant microstructural properties of biomedical samples, including the density and orientation of fibrous structures, the depolarization power, diattenuation and absorption abilities. It is shown in this paper that the statistical analysis of 2D images of Mueller matrix elements may provide quantitative or semi-quantitative criteria for biomedical diagnosis.

Refraction-based X-ray Computed Tomography for Biomedical Purpose Using Dark Field Imaging Method

NASA Astrophysics Data System (ADS)

Sunaguchi, Naoki; Yuasa, Tetsuya; Huo, Qingkai; Ichihara, Shu; Ando, Masami

We have proposed a tomographic x-ray imaging system using DFI (dark field imaging) optics along with a data-processing method to extract information on refraction from the measured intensities, and a reconstruction algorithm to reconstruct a refractive-index field from the projections generated from the extracted refraction information. The DFI imaging system consists of a tandem optical system of Bragg- and Laue-case crystals, a positioning device system for a sample, and two CCD (charge coupled device) cameras. Then, we developed a software code to simulate the data-acquisition, data-processing, and reconstruction methods to investigate the feasibility of the proposed methods. Finally, in order to demonstrate its efficacy, we imaged a sample with DCIS (ductal carcinoma in situ) excised from a breast cancer patient using a system constructed at the vertical wiggler beamline BL-14C in KEK-PF. Its CT images depicted a variety of fine histological structures, such as milk ducts, duct walls, secretions, adipose and fibrous tissue. They correlate well with histological sections.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Book Review: Reiner Salzer and Heinz W. Siesler (Eds.): Infrared and Raman spectroscopic imaging, 2nd ed.

DOE PAGES

Moore, David Steven

2015-05-10

This second edition of "Infrared and Raman Spectroscopic Imaging" propels practitioners in that wide-ranging field, as well as other readers, to the current state of the art in a well-produced and full-color, completely revised and updated, volume. This new edition chronicles the expanded application of vibrational spectroscopic imaging from yesterday's time-consuming point-by-point buildup of a hyperspectral image cube, through the improvements afforded by the addition of focal plane arrays and line scan imaging, to methods applicable beyond the diffraction limit, instructs the reader on the improved instrumentation and image and data analysis methods, and expounds on their application to fundamentalmore » biomedical knowledge, food and agricultural surveys, materials science, process and quality control, and many others.« less

Progress toward automatic classification of human brown adipose tissue using biomedical imaging

NASA Astrophysics Data System (ADS)

Gifford, Aliya; Towse, Theodore F.; Walker, Ronald C.; Avison, Malcom J.; Welch, E. B.

2015-03-01

Brown adipose tissue (BAT) is a small but significant tissue, which may play an important role in obesity and the pathogenesis of metabolic syndrome. Interest in studying BAT in adult humans is increasing, but in order to quantify BAT volume in a single measurement or to detect changes in BAT over the time course of a longitudinal experiment, BAT needs to first be reliably differentiated from surrounding tissue. Although the uptake of the radiotracer 18F-Fluorodeoxyglucose (18F-FDG) in adipose tissue on positron emission tomography (PET) scans following cold exposure is accepted as an indication of BAT, it is not a definitive indicator, and to date there exists no standardized method for segmenting BAT. Consequently, there is a strong need for robust automatic classification of BAT based on properties measured with biomedical imaging. In this study we begin the process of developing an automated segmentation method based on properties obtained from fat-water MRI and PET-CT scans acquired on ten healthy adult subjects.

Fundamental and applied studies in nanoparticle biomedical imaging, stabilization, and processing

NASA Astrophysics Data System (ADS)

Pansare, Vikram J.

Nanoparticle carrier systems are gaining importance in the rapidly expanding field of biomedical whole animal imaging where they provide long circulating, real time imaging capability. This thesis presents a new paradigm in imaging whereby long wavelength fluorescent or photoacoustically active contrast agents are embedded in the hydrophobic core of nanocarriers formed by Flash NanoPrecipitation. The long wavelength allows for improved optical penetration depth. Compared to traditional contrast agents where fluorophores are placed on the surface, this allows for improved signal, increased stability, and molecular targeting capabilities. Several types of long wavelength hydrophobic dyes based on acene, cyanine, and bacteriochlorin scaffolds are utilized and animal results obtained for nanocarrier systems used in both fluorescent and photoacoustic imaging modes. Photoacoustic imaging is particularly promising due to its high resolution, excellent penetration depth, and ability to provide real-time functional information. Fundamental studies in nanoparticle stabilization are also presented for two systems: model alumina nanoparticles and charge stabilized polystyrene nanoparticles. Motivated by the need for stable suspensions of alumina-based nanocrystals for security printing applications, results are presented for the adsorption of various small molecule charged hydrophobes onto the surface of alumina nanoparticles. Results are also presented for the production of charge stabilized polystyrene nanoparticles via Flash NanoPrecipitation, allowing for the independent control of polymer molecular weight and nanoparticle size, which is not possible by traditional emulsion polymerization routes. Lastly, methods for processing nanoparticle systems are explored. The increasing use of nanoparticle therapeutics in the pharmaceutical industry has necessitated the development of scalable, industrially relevant processing methods. Ultrafiltration is particularly well suited for concentrating and purifying macromolecular suspensions. Processing parameters are defined and optimized for PEGylated nanoparticles, charge stabilized latices, and solutions of albumin. The fouling characteristics are compared and scale-up recommendations made. Finally, a pilot scale spray drying system to produce stable nanocrystalline powders of highly crystalline drugs which cannot be stably formulated by traditional spray drying methods is presented. To accomplish this, a novel mixing device was developed and implemented at pilot scale, demonstrating feasibility beyond the lab scale.

Low-Cost, High-Throughput 3D Pulmonary Imager Using Hyperpolarized Contrast Agents and Low-Field MRI

DTIC Science & Technology

2016-10-01

COMMUNITIES OF INTEREST? ................................................. 8 4. IMPACT...publicize the work performed and also for their exposure to biomedical science. How were the results disseminated to communities of interest? Nothing...biomedical community , expanding the utility of HP methods as a new tool for probing fundamental biomedical questions. Acknowledgments The authors thank

The Function Biomedical Informatics Research Network Data Repository.

PubMed

Keator, David B; van Erp, Theo G M; Turner, Jessica A; Glover, Gary H; Mueller, Bryon A; Liu, Thomas T; Voyvodic, James T; Rasmussen, Jerod; Calhoun, Vince D; Lee, Hyo Jong; Toga, Arthur W; McEwen, Sarah; Ford, Judith M; Mathalon, Daniel H; Diaz, Michele; O'Leary, Daniel S; Jeremy Bockholt, H; Gadde, Syam; Preda, Adrian; Wible, Cynthia G; Stern, Hal S; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G

2016-01-01

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data. Copyright © 2015 Elsevier Inc. All rights reserved.

Function Biomedical Informatics Research Network Recommendations for Prospective Multi-Center Functional Magnetic Resonance Imaging Studies

PubMed Central

Glover, Gary H.; Mueller, Bryon A.; Turner, Jessica A.; van Erp, Theo G.M.; Liu, Thomas T.; Greve, Douglas N.; Voyvodic, James T.; Rasmussen, Jerod; Brown, Gregory G.; Keator, David B.; Calhoun, Vince D.; Lee, Hyo Jong; Ford, Judith M.; Mathalon, Daniel H.; Diaz, Michele; O’Leary, Daniel S.; Gadde, Syam; Preda, Adrian; Lim, Kelvin O.; Wible, Cynthia G.; Stern, Hal S.; Belger, Aysenil; McCarthy, Gregory; Ozyurt, Burak; Potkin, Steven G.

2011-01-01

This report provides practical recommendations for the design and execution of Multi-Center functional Magnetic Resonance Imaging (MC-fMRI) studies based on the collective experience of the Function Biomedical Informatics Research Network (FBIRN). The paper was inspired by many requests from the fMRI community to FBIRN group members for advice on how to conduct MC-fMRI studies. The introduction briefly discusses the advantages and complexities of MC-fMRI studies. Prerequisites for MC-fMRI studies are addressed before delving into the practical aspects of carefully and efficiently setting up a MC-fMRI study. Practical multi-site aspects include: (1) establishing and verifying scan parameters including scanner types and magnetic fields, (2) establishing and monitoring of a scanner quality program, (3) developing task paradigms and scan session documentation, (4) establishing clinical and scanner training to ensure consistency over time, (5) developing means for uploading, storing, and monitoring of imaging and other data, (6) the use of a traveling fMRI expert and (7) collectively analyzing imaging data and disseminating results. We conclude that when MC-fMRI studies are organized well with careful attention to unification of hardware, software and procedural aspects, the process can be a highly effective means for accessing a desired participant demographics while accelerating scientific discovery. PMID:22314879

Mid-infrared (MIR) photonics: MIR passive and active fiberoptics chemical and biomedical, sensing and imaging

NASA Astrophysics Data System (ADS)

Seddon, Angela B.

2016-10-01

The case for new, portable, real-time mid-infrared (MIR) molecular sensing and imaging is discussed. We set a record in demonstrating extreme broad-band supercontinuum (SC) generated light 1.4-13.3 μm in a specially engineered, step-index MIR optical fiber of high numerical aperture. This was the first experimental demonstration truly to reveal the potential of MIR fibers to emit across the MIR molecular "fingerprint spectral region" and a key first step towards bright, portable, broadband MIR sources for chemical and biomedical, molecular sensing and imaging in real-time. Potential applications are in the healthcare, security, energy, environmental monitoring, chemical-processing, manufacturing and the agriculture sectors. MIR narrow-line fiber lasers are now required to pump the fiber MIR-SC for a compact all-fiber solution. Rare-earth-ion (RE-) doped MIR fiber lasers are not yet demonstrated >=4 μm wavelength. We have fabricated small-core RE-fiber with photoluminescence across 3.5-6 μm, and long excited-state lifetimes. MIR-RE-fiber lasers are also applicable as discrete MIR fiber sensors in their own right, for applications including: ship-to-ship free-space communications, aircraft counter-measures, coherent MIR imaging, MIR-optical coherent tomography, laser-cutting/ patterning of soft materials and new wavelengths for fiber laser medical surgery.

Human emotions detection based on a smart-thermal system of thermographic images

NASA Astrophysics Data System (ADS)

Cruz-Albarran, Irving A.; Benitez-Rangel, Juan P.; Osornio-Rios, Roque A.; Morales-Hernandez, Luis A.

2017-03-01

This work presents a noninvasive methodology to obtain biomedical thermal imaging which provide relevant information that may assist in the diagnosis of emotions. Biomedical thermal images of the facial expressions of 44 subjects were captured experiencing joy, disgust, anger, fear and sadness. The analysis of these thermograms was carried out through its thermal value not with its intensity value. Regions of interest were obtained through image processing techniques that allow to differentiate between the subject and the background, having only the subject, the centers of each region of interest were obtained in order to get the same region of the face for each subject. Through the thermal analysis a biomarker for each region of interest was obtained, these biomarkers can diagnose when an emotion takes place. Because each subject tends to react differently to the same stimuli, a self-calibration phase is proposed, its function is to have the same thermal trend for each subject in order to make a decision so that the five emotions can be correctly diagnosed through a top-down hierarchical classifier. As a final result, a smart-thermal system that diagnose emotions was obtained and it was tested on twenty-five subjects (625 thermograms). The results of this test were 89.9% successful.

Optimal processing for gel electrophoresis images: Applying Monte Carlo Tree Search in GelApp.

PubMed

Nguyen, Phi-Vu; Ghezal, Ali; Hsueh, Ya-Chih; Boudier, Thomas; Gan, Samuel Ken-En; Lee, Hwee Kuan

2016-08-01

In biomedical research, gel band size estimation in electrophoresis analysis is a routine process. To facilitate and automate this process, numerous software have been released, notably the GelApp mobile app. However, the band detection accuracy is limited due to a band detection algorithm that cannot adapt to the variations in input images. To address this, we used the Monte Carlo Tree Search with Upper Confidence Bound (MCTS-UCB) method to efficiently search for optimal image processing pipelines for the band detection task, thereby improving the segmentation algorithm. Incorporating this into GelApp, we report a significant enhancement of gel band detection accuracy by 55.9 ± 2.0% for protein polyacrylamide gels, and 35.9 ± 2.5% for DNA SYBR green agarose gels. This implementation is a proof-of-concept in demonstrating MCTS-UCB as a strategy to optimize general image segmentation. The improved version of GelApp-GelApp 2.0-is freely available on both Google Play Store (for Android platform), and Apple App Store (for iOS platform). © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recent advances in terahertz technology for biomedical applications.

PubMed

Sun, Qiushuo; He, Yuezhi; Liu, Kai; Fan, Shuting; Parrott, Edward P J; Pickwell-MacPherson, Emma

2017-06-01

Terahertz instrumentation has improved significantly in recent years such that THz imaging systems have become more affordable and easier to use. THz systems can now be operated by non-THz experts greatly facilitating research into many potential applications. Due to the non-ionising nature of THz light and its high sensitivity to soft tissues, there is an increasing interest in biomedical applications including both in vivo and ex vivo studies. Additionally, research continues into understanding the origin of contrast and how to interpret terahertz biomedical images. This short review highlights some of the recent work in these areas and suggests some future research directions.

Compact, Automated, Frequency-Agile Microspectrofluorimeter

NASA Technical Reports Server (NTRS)

Fernandez, Salvador M.; Guignon, Ernest F.

1995-01-01

Compact, reliable, rugged, automated cell-culture and frequency-agile microspectrofluorimetric apparatus developed to perform experiments involving photometric imaging observations of single live cells. In original application, apparatus operates mostly unattended aboard spacecraft; potential terrestrial applications include automated or semiautomated diagnosis of pathological tissues in clinical laboratories, biomedical instrumentation, monitoring of biological process streams, and portable instrumentation for testing biological conditions in various environments. Offers obvious advantages over present laboratory instrumentation.

Collaborative Initiative in Biomedical Imaging to Study Complex Diseases

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

Lin, Weili; Fiddy, Michael A.

2012-03-31

The work reported addressed these topics: Fluorescence imaging; Optical coherence tomography; X-ray interferometer/phase imaging system; Quantitative imaging from scattered fields, Terahertz imaging and spectroscopy; and Multiphoton and Raman microscopy.

An Algorithm to Detect the Retinal Region of Interest

NASA Astrophysics Data System (ADS)

Şehirli, E.; Turan, M. K.; Demiral, E.

2017-11-01

Retina is one of the important layers of the eyes, which includes sensitive cells to colour and light and nerve fibers. Retina can be displayed by using some medical devices such as fundus camera, ophthalmoscope. Hence, some lesions like microaneurysm, haemorrhage, exudate with many diseases of the eye can be detected by looking at the images taken by devices. In computer vision and biomedical areas, studies to detect lesions of the eyes automatically have been done for a long time. In order to make automated detections, the concept of ROI may be utilized. ROI which stands for region of interest generally serves the purpose of focusing on particular targets. The main concentration of this paper is the algorithm to automatically detect retinal region of interest belonging to different retinal images on a software application. The algorithm consists of three stages such as pre-processing stage, detecting ROI on processed images and overlapping between input image and obtained ROI of the image.

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

Managing biomedical image metadata for search and retrieval of similar images.

PubMed

Korenblum, Daniel; Rubin, Daniel; Napel, Sandy; Rodriguez, Cesar; Beaulieu, Chris

2011-08-01

Radiology images are generally disconnected from the metadata describing their contents, such as imaging observations ("semantic" metadata), which are usually described in text reports that are not directly linked to the images. We developed a system, the Biomedical Image Metadata Manager (BIMM) to (1) address the problem of managing biomedical image metadata and (2) facilitate the retrieval of similar images using semantic feature metadata. Our approach allows radiologists, researchers, and students to take advantage of the vast and growing repositories of medical image data by explicitly linking images to their associated metadata in a relational database that is globally accessible through a Web application. BIMM receives input in the form of standard-based metadata files using Web service and parses and stores the metadata in a relational database allowing efficient data query and maintenance capabilities. Upon querying BIMM for images, 2D regions of interest (ROIs) stored as metadata are automatically rendered onto preview images included in search results. The system's "match observations" function retrieves images with similar ROIs based on specific semantic features describing imaging observation characteristics (IOCs). We demonstrate that the system, using IOCs alone, can accurately retrieve images with diagnoses matching the query images, and we evaluate its performance on a set of annotated liver lesion images. BIMM has several potential applications, e.g., computer-aided detection and diagnosis, content-based image retrieval, automating medical analysis protocols, and gathering population statistics like disease prevalences. The system provides a framework for decision support systems, potentially improving their diagnostic accuracy and selection of appropriate therapies.

Novel snapshot hyperspectral imager for fluorescence imaging

NASA Astrophysics Data System (ADS)

Chandler, Lynn; Chandler, Andrea; Periasamy, Ammasi

2018-02-01

Hyperspectral imaging has emerged as a new technique for the identification and classification of biological tissue1. Benefitting recent developments in sensor technology, the new class of hyperspectral imagers can capture entire hypercubes with single shot operation and it shows great potential for real-time imaging in biomedical sciences. This paper explores the use of a SnapShot imager in fluorescence imaging via microscope for the very first time. Utilizing the latest imaging sensor, the Snapshot imager is both compact and attachable via C-mount to any commercially available light microscope. Using this setup, fluorescence hypercubes of several cells were generated, containing both spatial and spectral information. The fluorescence images were acquired with one shot operation for all the emission range from visible to near infrared (VIS-IR). The paper will present the hypercubes obtained images from example tissues (475-630nm). This study demonstrates the potential of application in cell biology or biomedical applications for real time monitoring.

Multiple energy synchrotron biomedical imaging system

NASA Astrophysics Data System (ADS)

Bassey, B.; Martinson, M.; Samadi, N.; Belev, G.; Karanfil, C.; Qi, P.; Chapman, D.

2016-12-01

A multiple energy imaging system that can extract multiple endogenous or induced contrast materials as well as water and bone images would be ideal for imaging of biological subjects. The continuous spectrum available from synchrotron light facilities provides a nearly perfect source for multiple energy x-ray imaging. A novel multiple energy x-ray imaging system, which prepares a horizontally focused polychromatic x-ray beam, has been developed at the BioMedical Imaging and Therapy bend magnet beamline at the Canadian Light Source. The imaging system is made up of a cylindrically bent Laue single silicon (5,1,1) crystal monochromator, scanning and positioning stages for the subjects, flat panel (area) detector, and a data acquisition and control system. Depending on the crystal’s bent radius, reflection type, and the horizontal beam width of the filtered synchrotron radiation (20-50 keV) used, the size and spectral energy range of the focused beam prepared varied. For example, with a bent radius of 95 cm, a (1,1,1) type reflection and a 50 mm wide beam, a 0.5 mm wide focused beam of spectral energy range 27 keV-43 keV was obtained. This spectral energy range covers the K-edges of iodine (33.17 keV), xenon (34.56 keV), cesium (35.99 keV), and barium (37.44 keV) some of these elements are used as biomedical and clinical contrast agents. Using the developed imaging system, a test subject composed of iodine, xenon, cesium, and barium along with water and bone were imaged and their projected concentrations successfully extracted. The estimated dose rate to test subjects imaged at a ring current of 200 mA is 8.7 mGy s-1, corresponding to a cumulative dose of 1.3 Gy and a dose of 26.1 mGy per image. Potential biomedical applications of the imaging system will include projection imaging that requires any of the extracted elements as a contrast agent and multi-contrast K-edge imaging.

Image Acquisition Context

PubMed Central

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

1999-01-01

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

Real-time biochemical sensor based on Raman scattering with CMOS contact imaging.

PubMed

Muyun Cao; Yuhua Li; Yadid-Pecht, Orly

2015-08-01

This work presents a biochemical sensor based on Raman scattering with Complementary metal-oxide-semiconductor (CMOS) contact imaging. This biochemical optical sensor is designed for detecting the concentration of solutions. The system is built with a laser diode, an optical filter, a sample holder and a commercial CMOS sensor. The output of the system is analyzed by an image processing program. The system provides instant measurements with a resolution of 0.2 to 0.4 Mol. This low cost and easy-operated small scale system is useful in chemical, biomedical and environmental labs for quantitative bio-chemical concentration detection with results reported comparable to a highly cost commercial spectrometer.

3D printed optical phantoms and deep tissue imaging for in vivo applications including oral surgery

NASA Astrophysics Data System (ADS)

Bentz, Brian Z.; Costas, Alfonso; Gaind, Vaibhav; Garcia, Jose M.; Webb, Kevin J.

2017-03-01

Progress in developing optical imaging for biomedical applications requires customizable and often complex objects known as "phantoms" for testing, evaluation, and calibration. This work demonstrates that 3D printing is an ideal method for fabricating such objects, allowing intricate inhomogeneities to be placed at exact locations in complex or anatomically realistic geometries, a process that is difficult or impossible using molds. We show printed mouse phantoms we have fabricated for developing deep tissue fluorescence imaging methods, and measurements of both their optical and mechanical properties. Additionally, we present a printed phantom of the human mouth that we use to develop an artery localization method to assist in oral surgery.

Synthesis of fluorescent carbon dots by a microwave heating process: structural characterization and cell imaging applications

NASA Astrophysics Data System (ADS)

Stefanakis, Dimitrios; Philippidis, Aggelos; Sygellou, Labrini; Filippidis, George; Ghanotakis, Demetrios; Anglos, Demetrios

2014-10-01

Two types of highly fluorescent carbon dots (C-dots) were prepared by a single-step procedure based on microwave heating citric acid and 6-aminocaproic acid or citric acid and urea in an aqueous solution. The small size of the isolated carbon dots along with their strong absorption in the UV and their excitation wavelength-dependent fluorescence render them ideal nanomaterials for biomedical applications (imaging and sensing). The structure and properties of the two types of C-dot materials were studied using a series of spectroscopic techniques. The ability of the C-dots to be internalized by HeLa cells was demonstrated via 3-photon fluorescence microscopy imaging.

Combined photoacoustic and magneto-acoustic imaging.

PubMed

Qu, Min; Mallidi, Srivalleesha; Mehrmohammadi, Mohammad; Ma, Li Leo; Johnston, Keith P; Sokolov, Konstantin; Emelianov, Stanislav

2009-01-01

Ultrasound is a widely used modality with excellent spatial resolution, low cost, portability, reliability and safety. In clinical practice and in the biomedical field, molecular ultrasound-based imaging techniques are desired to visualize tissue pathologies, such as cancer. In this paper, we present an advanced imaging technique - combined photoacoustic and magneto-acoustic imaging - capable of visualizing the anatomical, functional and biomechanical properties of tissues or organs. The experiments to test the combined imaging technique were performed using dual, nanoparticle-based contrast agents that exhibit the desired optical and magnetic properties. The results of our study demonstrate the feasibility of the combined photoacoustic and magneto-acoustic imaging that takes the advantages of each imaging techniques and provides high sensitivity, reliable contrast and good penetrating depth. Therefore, the developed imaging technique can be used in wide range of biomedical and clinical application.

High-energy proton imaging for biomedical applications

DOE PAGES

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

2016-06-10

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

High-energy proton imaging for biomedical applications

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

An efficient method for facial component detection in thermal images

NASA Astrophysics Data System (ADS)

Paul, Michael; Blanik, Nikolai; Blazek, Vladimir; Leonhardt, Steffen

2015-04-01

A method to detect certain regions in thermal images of human faces is presented. In this approach, the following steps are necessary to locate the periorbital and the nose regions: First, the face is segmented from the background by thresholding and morphological filtering. Subsequently, a search region within the face, around its center of mass, is evaluated. Automatically computed temperature thresholds are used per subject and image or image sequence to generate binary images, in which the periorbital regions are located by integral projections. Then, the located positions are used to approximate the nose position. It is possible to track features in the located regions. Therefore, these regions are interesting for different applications like human-machine interaction, biometrics and biomedical imaging. The method is easy to implement and does not rely on any training images or templates. Furthermore, the approach saves processing resources due to simple computations and restricted search regions.

High-energy proton imaging for biomedical applications

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

Prall, Matthias; Durante, Marco; Berger, Thomas

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

Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering.

PubMed

Nahid, Abdullah-Al; Mehrabi, Mohamad Ali; Kong, Yinan

2018-01-01

Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians. Analyzing histopathological images is a nontrivial task, and decisions from investigation of these kinds of images always require specialised knowledge. However, Computer Aided Diagnosis (CAD) techniques can help the doctor make more reliable decisions. The state-of-the-art Deep Neural Network (DNN) has been recently introduced for biomedical image analysis. Normally each image contains structural and statistical information. This paper classifies a set of biomedical breast cancer images (BreakHis dataset) using novel DNN techniques guided by structural and statistical information derived from the images. Specifically a Convolutional Neural Network (CNN), a Long-Short-Term-Memory (LSTM), and a combination of CNN and LSTM are proposed for breast cancer image classification. Softmax and Support Vector Machine (SVM) layers have been used for the decision-making stage after extracting features utilising the proposed novel DNN models. In this experiment the best Accuracy value of 91.00% is achieved on the 200x dataset, the best Precision value 96.00% is achieved on the 40x dataset, and the best F -Measure value is achieved on both the 40x and 100x datasets.

Toxicity of inorganic nanomaterials in biomedical imaging.

PubMed

Li, Jinxia; Chang, Xueling; Chen, Xiaoxia; Gu, Zhanjun; Zhao, Feng; Chai, Zhifang; Zhao, Yuliang

2014-01-01

Inorganic nanoparticles have shown promising potentials as novel biomedical imaging agents with high sensitivity, high spatial and temporal resolution. To translate the laboratory innovations into clinical applications, their potential toxicities are highly concerned and have to be evaluated comprehensively both in vitro and in vivo before their clinical applications. In this review, we first summarized the in vivo and in vitro toxicities of the representative inorganic nanoparticles used in biomedical imagings. Then we further discuss the origin of nanotoxicity of inorganic nanomaterials, including ROS generation and oxidative stress, chemical instability, chemical composition, the surface modification, dissolution of nanoparticles to release excess free ions of metals, metal redox state, and left-over chemicals from synthesis, etc. We intend to provide the readers a better understanding of the toxicology aspects of inorganic nanomaterials and knowledge for achieving optimized designs of safer inorganic nanomaterials for clinical applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Surface engineering of graphene-based nanomaterials for biomedical applications.

PubMed

Shi, Sixiang; Chen, Feng; Ehlerding, Emily B; Cai, Weibo

2014-09-17

Graphene-based nanomaterials have attracted tremendous interest over the past decade due to their unique electronic, optical, mechanical, and chemical properties. However, the biomedical applications of these intriguing nanomaterials are still limited due to their suboptimal solubility/biocompatibility, potential toxicity, and difficulties in achieving active tumor targeting, just to name a few. In this Topical Review, we will discuss in detail the important role of surface engineering (i.e., bioconjugation) in improving the in vitro/in vivo stability and enriching the functionality of graphene-based nanomaterials, which can enable single/multimodality imaging (e.g., optical imaging, positron emission tomography, magnetic resonance imaging) and therapy (e.g., photothermal therapy, photodynamic therapy, and drug/gene delivery) of cancer. Current challenges and future research directions are also discussed and we believe that graphene-based nanomaterials are attractive nanoplatforms for a broad array of future biomedical applications.

Surface Engineering of Graphene-Based Nanomaterials for Biomedical Applications

PubMed Central

2015-01-01

Graphene-based nanomaterials have attracted tremendous interest over the past decade due to their unique electronic, optical, mechanical, and chemical properties. However, the biomedical applications of these intriguing nanomaterials are still limited due to their suboptimal solubility/biocompatibility, potential toxicity, and difficulties in achieving active tumor targeting, just to name a few. In this Topical Review, we will discuss in detail the important role of surface engineering (i.e., bioconjugation) in improving the in vitro/in vivo stability and enriching the functionality of graphene-based nanomaterials, which can enable single/multimodality imaging (e.g., optical imaging, positron emission tomography, magnetic resonance imaging) and therapy (e.g., photothermal therapy, photodynamic therapy, and drug/gene delivery) of cancer. Current challenges and future research directions are also discussed and we believe that graphene-based nanomaterials are attractive nanoplatforms for a broad array of future biomedical applications. PMID:25117569

Self-assembled nanomaterials for photoacoustic imaging

NASA Astrophysics Data System (ADS)

Wang, Lei; Yang, Pei-Pei; Zhao, Xiao-Xiao; Wang, Hao

2016-01-01

In recent years, extensive endeavors have been paid to construct functional self-assembled nanomaterials for various applications such as catalysis, separation, energy and biomedicines. To date, different strategies have been developed for preparing nanomaterials with diversified structures and functionalities via fine tuning of self-assembled building blocks. In terms of biomedical applications, bioimaging technologies are urgently calling for high-efficient probes/contrast agents for high-performance bioimaging. Photoacoustic (PA) imaging is an emerging whole-body imaging modality offering high spatial resolution, deep penetration and high contrast in vivo. The self-assembled nanomaterials show high stability in vivo, specific tolerance to sterilization and prolonged half-life stability and desirable targeting properties, which is a kind of promising PA contrast agents for biomedical imaging. Herein, we focus on summarizing recent advances in smart self-assembled nanomaterials with NIR absorption as PA contrast agents for biomedical imaging. According to the preparation strategy of the contrast agents, the self-assembled nanomaterials are categorized into two groups, i.e., the ex situ and in situ self-assembled nanomaterials. The driving forces, assembly modes and regulation of PA properties of self-assembled nanomaterials and their applications for long-term imaging, enzyme activity detection and aggregation-induced retention (AIR) effect for diagnosis and therapy are emphasized. Finally, we conclude with an outlook towards future developments of self-assembled nanomaterials for PA imaging.

Self-assembled nanomaterials for photoacoustic imaging.

PubMed

Wang, Lei; Yang, Pei-Pei; Zhao, Xiao-Xiao; Wang, Hao

2016-02-07

In recent years, extensive endeavors have been paid to construct functional self-assembled nanomaterials for various applications such as catalysis, separation, energy and biomedicines. To date, different strategies have been developed for preparing nanomaterials with diversified structures and functionalities via fine tuning of self-assembled building blocks. In terms of biomedical applications, bioimaging technologies are urgently calling for high-efficient probes/contrast agents for high-performance bioimaging. Photoacoustic (PA) imaging is an emerging whole-body imaging modality offering high spatial resolution, deep penetration and high contrast in vivo. The self-assembled nanomaterials show high stability in vivo, specific tolerance to sterilization and prolonged half-life stability and desirable targeting properties, which is a kind of promising PA contrast agents for biomedical imaging. Herein, we focus on summarizing recent advances in smart self-assembled nanomaterials with NIR absorption as PA contrast agents for biomedical imaging. According to the preparation strategy of the contrast agents, the self-assembled nanomaterials are categorized into two groups, i.e., the ex situ and in situ self-assembled nanomaterials. The driving forces, assembly modes and regulation of PA properties of self-assembled nanomaterials and their applications for long-term imaging, enzyme activity detection and aggregation-induced retention (AIR) effect for diagnosis and therapy are emphasized. Finally, we conclude with an outlook towards future developments of self-assembled nanomaterials for PA imaging.

Fabrication of monodisperse magnetic nanoparticles released in solution using a block copolymer template

NASA Astrophysics Data System (ADS)

Morcrette, Mélissa; Ortiz, Guillermo; Tallegas, Salomé; Joisten, Hélène; Tiron, Raluca; Baron, Thierry; Hou, Yanxia; Lequien, Stéphane; Bsiesy, Ahmad; Dieny, Bernard

2017-07-01

This paper describes a fabrication process of monodisperse magnetic nanoparticles released in solution, based on combined ‘top-down’ and ‘bottom-up’ approaches. The process involves the use of a self-assembled PS-PMMA block copolymer formed on a sacrificial layer. Such an approach was so far mostly explored for the preparation of patterned magnetic media for ultrahigh density magnetic storage. It is here extended to the preparation of released monodisperse nanoparticles for biomedical applications. A special sacrificial layer had to be developed compatible with the copolymer self-organization. The resulting nanoparticles exhibit very narrow size dispersion (≈7%) and can be good candidates as contrast agents for medical imaging i.e. magnetic resonance imaging or magnetic particle imaging. The approach provides a great freedom in the choice of the particles shapes and compositions. In particular, they can be made of biocompatible magnetic material.

Adaptive photoacoustic imaging quality optimization with EMD and reconstruction

NASA Astrophysics Data System (ADS)

Guo, Chengwen; Ding, Yao; Yuan, Jie; Xu, Guan; Wang, Xueding; Carson, Paul L.

2016-10-01

Biomedical photoacoustic (PA) signal is characterized with extremely low signal to noise ratio which will yield significant artifacts in photoacoustic tomography (PAT) images. Since PA signals acquired by ultrasound transducers are non-linear and non-stationary, traditional data analysis methods such as Fourier and wavelet method cannot give useful information for further research. In this paper, we introduce an adaptive method to improve the quality of PA imaging based on empirical mode decomposition (EMD) and reconstruction. Data acquired by ultrasound transducers are adaptively decomposed into several intrinsic mode functions (IMFs) after a sifting pre-process. Since noise is randomly distributed in different IMFs, depressing IMFs with more noise while enhancing IMFs with less noise can effectively enhance the quality of reconstructed PAT images. However, searching optimal parameters by means of brute force searching algorithms will cost too much time, which prevent this method from practical use. To find parameters within reasonable time, heuristic algorithms, which are designed for finding good solutions more efficiently when traditional methods are too slow, are adopted in our method. Two of the heuristic algorithms, Simulated Annealing Algorithm, a probabilistic method to approximate the global optimal solution, and Artificial Bee Colony Algorithm, an optimization method inspired by the foraging behavior of bee swarm, are selected to search optimal parameters of IMFs in this paper. The effectiveness of our proposed method is proved both on simulated data and PA signals from real biomedical tissue, which might bear the potential for future clinical PA imaging de-noising.

The Mechanisms and Biomedical Applications of an NIR BODIPY-Based Switchable Fluorescent Probe

PubMed Central

Cheng, Bingbing; Bandi, Venugopal; Yu, Shuai; D’Souza, Francis; Nguyen, Kytai T.; Hong, Yi; Tang, Liping; Yuan, Baohong

2017-01-01

Highly environment-sensitive fluorophores have been desired for many biomedical applications. Because of the noninvasive operation, high sensitivity, and high specificity to the microenvironment change, they can be used as excellent probes for fluorescence sensing/imaging, cell tracking/imaging, molecular imaging for cancer, and so on (i.e., polarity, viscosity, temperature, or pH measurement). In this work, investigations of the switching mechanism of a recently reported near-infrared environment-sensitive fluorophore, ADP(CA)2, were conducted. Besides, multiple potential biomedical applications of this switchable fluorescent probe have been demonstrated, including wash-free live-cell fluorescence imaging, in vivo tissue fluorescence imaging, temperature sensing, and ultrasound-switchable fluorescence (USF) imaging. The fluorescence of the ADP(CA)2 is extremely sensitive to the microenvironment, especially polarity and viscosity. Our investigations showed that the fluorescence of ADP(CA)2 can be switched on by low polarity, high viscosity, or the presence of protein and surfactants. In wash-free live-cell imaging, the fluorescence of ADP(CA)2 inside cells was found much brighter than the dye-containing medium and was retained for at least two days. In all of the fluorescence imaging applications conducted in this study, high target-to-noise (>5-fold) was achieved. In addition, a high temperature sensitivity (73-fold per Celsius degree) of ADP(CA)2-based temperature probes was found in temperature sensing. PMID:28208666

Focus on: Washington Hospital Center, Biomedical Engineering Department.

PubMed

Hughes, J D

1995-01-01

The Biomedical Engineering Department of the Washington Hospital Center provides clinical engineering services to an urban 907-bed, tertiary care teaching hospital and a variety of associated healthcare facilities. With an annual budget of over $3,000,000, the 24-person department provides cradle-to-grave support for a host of sophisticated medical devices and imaging systems such as lasers, CT scanners, and linear accelerators as well as traditional patient care instrumentation. Hallmarks of the department include its commitment to customer service and patient care, close collaboration with clinicians and quality assurance teams throughout the hospital system, proactive involvement in all phases of the technology management process, and shared leadership in safety standards with the hospital's risk management group. Through this interactive process, the department has assisted the Center not only in the acquisition of 11,000 active devices with a value of more than $64 million, but also in becoming one of the leading providers of high technology healthcare in the Washington, DC metropolitan area.

Three-dimensional fuse deposition modeling of tissue-simulating phantom for biomedical optical imaging

NASA Astrophysics Data System (ADS)

Dong, Erbao; Zhao, Zuhua; Wang, Minjie; Xie, Yanjun; Li, Shidi; Shao, Pengfei; Cheng, Liuquan; Xu, Ronald X.

2015-12-01

Biomedical optical devices are widely used for clinical detection of various tissue anomalies. However, optical measurements have limited accuracy and traceability, partially owing to the lack of effective calibration methods that simulate the actual tissue conditions. To facilitate standardized calibration and performance evaluation of medical optical devices, we develop a three-dimensional fuse deposition modeling (FDM) technique for freeform fabrication of tissue-simulating phantoms. The FDM system uses transparent gel wax as the base material, titanium dioxide (TiO2) powder as the scattering ingredient, and graphite powder as the absorption ingredient. The ingredients are preheated, mixed, and deposited at the designated ratios layer-by-layer to simulate tissue structural and optical heterogeneities. By printing the sections of human brain model based on magnetic resonance images, we demonstrate the capability for simulating tissue structural heterogeneities. By measuring optical properties of multilayered phantoms and comparing with numerical simulation, we demonstrate the feasibility for simulating tissue optical properties. By creating a rat head phantom with embedded vasculature, we demonstrate the potential for mimicking physiologic processes of a living system.

Application of Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Imaging Mass Spectrometry (MALDI-TOF IMS) for Premalignant Gastrointestinal Lesions

PubMed Central

Ko, Kwang Hyun; Kwon, Chang Il; Park, So Hye; Han, Na Young; Lee, Hoo Keun; Kim, Eun Hee

2013-01-01

Imaging mass spectrometry (IMS) is currently receiving large attention from the mass spectrometric community, although its use is not yet well known in the clinic. As matrix-assisted laser desorption/ionization time-of-flight (MALDI)-IMS can show the biomolecular changes in cells as well as tissues, it can be an ideal tool for biomedical diagnostics as well as the molecular diagnosis of clinical specimens, especially aimed at the prompt detection of premalignant lesions much earlier before overt mass formation, or for obtaining histologic clues from endoscopic biopsy. Besides its use for pathologic diagnosis, MALDI-IMS is also a powerful tool for the detection and localization of drugs, proteins, and lipids in tissue. Measurement of parameters that define and control the implications, challenges, and opportunities associated with the application of IMS to biomedical tissue studies might be feasible through a deep understanding of mass spectrometry. In this focused review series, new insights into the molecular processes relevant to IMS as well as other field applications are introduced. PMID:24340253

HaloTag Technology: A Versatile Platform for Biomedical Applications

PubMed Central

2015-01-01

Exploration of protein function and interaction is critical for discovering links among genomics, proteomics, and disease state; yet, the immense complexity of proteomics found in biological systems currently limits our investigational capacity. Although affinity and autofluorescent tags are widely employed for protein analysis, these methods have been met with limited success because they lack specificity and require multiple fusion tags and genetic constructs. As an alternative approach, the innovative HaloTag protein fusion platform allows protein function and interaction to be comprehensively analyzed using a single genetic construct with multiple capabilities. This is accomplished using a simplified process, in which a variable HaloTag ligand binds rapidly to the HaloTag protein (usually linked to the protein of interest) with high affinity and specificity. In this review, we examine all current applications of the HaloTag technology platform for biomedical applications, such as the study of protein isolation and purification, protein function, protein–protein and protein–DNA interactions, biological assays, in vitro cellular imaging, and in vivo molecular imaging. In addition, novel uses of the HaloTag platform are briefly discussed along with potential future applications. PMID:25974629

A Workstation for Interactive Display and Quantitative Analysis of 3-D and 4-D Biomedical Images

PubMed Central

Robb, R.A.; Heffeman, P.B.; Camp, J.J.; Hanson, D.P.

1986-01-01

The capability to extract objective and quantitatively accurate information from 3-D radiographic biomedical images has not kept pace with the capabilities to produce the images themselves. This is rather an ironic paradox, since on the one hand the new 3-D and 4-D imaging capabilities promise significant potential for providing greater specificity and sensitivity (i.e., precise objective discrimination and accurate quantitative measurement of body tissue characteristics and function) in clinical diagnostic and basic investigative imaging procedures than ever possible before, but on the other hand, the momentous advances in computer and associated electronic imaging technology which have made these 3-D imaging capabilities possible have not been concomitantly developed for full exploitation of these capabilities. Therefore, we have developed a powerful new microcomputer-based system which permits detailed investigations and evaluation of 3-D and 4-D (dynamic 3-D) biomedical images. The system comprises a special workstation to which all the information in a large 3-D image data base is accessible for rapid display, manipulation, and measurement. The system provides important capabilities for simultaneously representing and analyzing both structural and functional data and their relationships in various organs of the body. This paper provides a detailed description of this system, as well as some of the rationale, background, theoretical concepts, and practical considerations related to system implementation. ImagesFigure 5Figure 7Figure 8Figure 9Figure 10Figure 11Figure 12Figure 13Figure 14Figure 15Figure 16

In vivo optical imaging and dynamic contrast methods for biomedical research

PubMed Central

Hillman, Elizabeth M. C.; Amoozegar, Cyrus B.; Wang, Tracy; McCaslin, Addason F. H.; Bouchard, Matthew B.; Mansfield, James; Levenson, Richard M.

2011-01-01

This paper provides an overview of optical imaging methods commonly applied to basic research applications. Optical imaging is well suited for non-clinical use, since it can exploit an enormous range of endogenous and exogenous forms of contrast that provide information about the structure and function of tissues ranging from single cells to entire organisms. An additional benefit of optical imaging that is often under-exploited is its ability to acquire data at high speeds; a feature that enables it to not only observe static distributions of contrast, but to probe and characterize dynamic events related to physiology, disease progression and acute interventions in real time. The benefits and limitations of in vivo optical imaging for biomedical research applications are described, followed by a perspective on future applications of optical imaging for basic research centred on a recently introduced real-time imaging technique called dynamic contrast-enhanced small animal molecular imaging (DyCE). PMID:22006910

Biochemical imaging of tissues by SIMS for biomedical applications

NASA Astrophysics Data System (ADS)

Lee, Tae Geol; Park, Ji-Won; Shon, Hyun Kyong; Moon, Dae Won; Choi, Won Woo; Li, Kapsok; Chung, Jin Ho

2008-12-01

With the development of optimal surface cleaning techniques by cluster ion beam sputtering, certain applications of SIMS for analyzing cells and tissues have been actively investigated. For this report, we collaborated with bio-medical scientists to study bio-SIMS analyses of skin and cancer tissues for biomedical diagnostics. We pay close attention to the setting up of a routine procedure for preparing tissue specimens and treating the surface before obtaining the bio-SIMS data. Bio-SIMS was used to study two biosystems, skin tissues for understanding the effects of photoaging and colon cancer tissues for insight into the development of new cancer diagnostics for cancer. Time-of-flight SIMS imaging measurements were taken after surface cleaning with cluster ion bombardment by Bi n or C 60 under varying conditions. The imaging capability of bio-SIMS with a spatial resolution of a few microns combined with principal component analysis reveal biologically meaningful information, but the lack of high molecular weight peaks even with cluster ion bombardment was a problem. This, among other problems, shows that discourse with biologists and medical doctors are critical to glean any meaningful information from SIMS mass spectrometric and imaging data. For SIMS to be accepted as a routine, daily analysis tool in biomedical laboratories, various practical sample handling methodology such as surface matrix treatment, including nano-metal particles and metal coating, in addition to cluster sputtering, should be studied.

[Application of Fourier transform profilometry in 3D-surface reconstruction].

PubMed

Shi, Bi'er; Lu, Kuan; Wang, Yingting; Li, Zhen'an; Bai, Jing

2011-08-01

With the improvement of system frame and reconstruction methods in fluorescent molecules tomography (FMT), the FMT technology has been widely used as an important experimental tool in biomedical research. It is necessary to get the 3D-surface profile of the experimental object as the boundary constraints of FMT reconstruction algorithms. We proposed a new 3D-surface reconstruction method based on Fourier transform profilometry (FTP) method under the blue-purple light condition. The slice images were reconstructed using proper image processing methods, frequency spectrum analysis and filtering. The results of experiment showed that the method properly reconstructed the 3D-surface of objects and has the mm-level accuracy. Compared to other methods, this one is simple and fast. Besides its well-reconstructed, the proposed method could help monitor the behavior of the object during the experiment to ensure the correspondence of the imaging process. Furthermore, the method chooses blue-purple light section as its light source to avoid the interference towards fluorescence imaging.

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

Advances in nano-scaled biosensors for biomedical applications.

PubMed

Wang, Jianling; Chen, Guihua; Jiang, Hui; Li, Zhiyong; Wang, Xuemei

2013-08-21

Recently, a growing amount of attention has been focused on the utility of biosensors for biomedical applications. Combined with nanomaterials and nanostructures, nano-scaled biosensors are installed for biomedical applications, such as pathogenic bacteria monitoring, virus recognition, disease biomarker detection, among others. These nano-biosensors offer a number of advantages and in many respects are ideally suited to biomedical applications, which could be made as extremely flexible devices, allowing biomedical analysis with speediness, excellent selectivity and high sensitivity. This minireview discusses the literature published in the latest years on the advances in biomedical applications of nano-scaled biosensors for disease bio-marking and detection, especially in bio-imaging and the diagnosis of pathological cells and viruses, monitoring pathogenic bacteria, thus providing insight into the future prospects of biosensors in relevant clinical applications.

What is nature capable of? Evidence, ontology and speculative medical humanities.

PubMed

Savransky, Martin; Rosengarten, Marsha

2016-09-01

Expanding on the recent call for a 'critical medical humanities' to intervene in questions of the ontology of health, this article develops a what we call a 'speculative' orientation to such interventions in relation to some of the ontological commitments on which contemporary biomedical cultures rest. We argue that crucial to this task is an approach to ontology that treats it not as a question of first principles, but as a matter of the consequences of the images of nature that contemporary biomedical research practices espouse when they make claims to evidence, as well as the possible consequences of imagining different worlds in which health and disease processes partake. By attending to the implicit ontological assumptions involved in the method par excellence of biomedical research, namely the randomised controlled trial (RCT), we argue that the mechanistic ontology that tacitly informs evidence-based biomedical research simultaneously authorises a series of problematic consequences for understanding and intervening practically in the concrete realities of health. As a response, we develop an alternative ontological proposition that regards processes of health and disease as always situated achievements. We show that, without disqualifying RCT-based evidence, such a situated ontology enables one to resist the reduction of the realities of health and disease to biomedicine's current forms of explanation. In so doing, we call for medical humanities scholars to actively engage in the speculative question of what nature may be capable of. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

3D digital image processing for biofilm quantification from confocal laser scanning microscopy: Multidimensional statistical analysis of biofilm modeling

NASA Astrophysics Data System (ADS)

Zielinski, Jerzy S.

The dramatic increase in number and volume of digital images produced in medical diagnostics, and the escalating demand for rapid access to these relevant medical data, along with the need for interpretation and retrieval has become of paramount importance to a modern healthcare system. Therefore, there is an ever growing need for processed, interpreted and saved images of various types. Due to the high cost and unreliability of human-dependent image analysis, it is necessary to develop an automated method for feature extraction, using sophisticated mathematical algorithms and reasoning. This work is focused on digital image signal processing of biological and biomedical data in one- two- and three-dimensional space. Methods and algorithms presented in this work were used to acquire data from genomic sequences, breast cancer, and biofilm images. One-dimensional analysis was applied to DNA sequences which were presented as a non-stationary sequence and modeled by a time-dependent autoregressive moving average (TD-ARMA) model. Two-dimensional analyses used 2D-ARMA model and applied it to detect breast cancer from x-ray mammograms or ultrasound images. Three-dimensional detection and classification techniques were applied to biofilm images acquired using confocal laser scanning microscopy. Modern medical images are geometrically arranged arrays of data. The broadening scope of imaging as a way to organize our observations of the biophysical world has led to a dramatic increase in our ability to apply new processing techniques and to combine multiple channels of data into sophisticated and complex mathematical models of physiological function and dysfunction. With explosion of the amount of data produced in a field of biomedicine, it is crucial to be able to construct accurate mathematical models of the data at hand. Two main purposes of signal modeling are: data size conservation and parameter extraction. Specifically, in biomedical imaging we have four key problems that were addressed in this work: (i) registration, i.e. automated methods of data acquisition and the ability to align multiple data sets with each other; (ii) visualization and reconstruction, i.e. the environment in which registered data sets can be displayed on a plane or in multidimensional space; (iii) segmentation, i.e. automated and semi-automated methods to create models of relevant anatomy from images; (iv) simulation and prediction, i.e. techniques that can be used to simulate growth end evolution of researched phenomenon. Mathematical models can not only be used to verify experimental findings, but also to make qualitative and quantitative predictions, that might serve as guidelines for the future development of technology and/or treatment.

KaBOB: ontology-based semantic integration of biomedical databases.

PubMed

Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

2015-04-23

The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for formal reasoning over a wealth of integrated biomedical data.

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

Recommending images of user interests from the biomedical literature

NASA Astrophysics Data System (ADS)

Clukey, Steven; Xu, Songhua

2013-03-01

Every year hundreds of thousands of biomedical images are published in journals and conferences. Consequently, finding images relevant to one's interests becomes an ever daunting task. This vast amount of literature creates a need for intelligent and easy-to-use tools that can help researchers effectively navigate through the content corpus and conveniently locate materials of their interests. Traditionally, literature search tools allow users to query content using topic keywords. However, manual query composition is often time and energy consuming. A better system would be one that can automatically deliver relevant content to a researcher without having the end user manually manifest one's search intent and interests via search queries. Such a computer-aided assistance for information access can be provided by a system that first determines a researcher's interests automatically and then recommends images relevant to the person's interests accordingly. The technology can greatly improve a researcher's ability to stay up to date in their fields of study by allowing them to efficiently browse images and documents matching their needs and interests among the vast amount of the biomedical literature. A prototype system implementation of the technology can be accessed via http://www.smartdataware.com.

Deep learning in bioinformatics.

PubMed

Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh

2017-09-01

In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Creating a classification of image types in the medical literature for visual categorization

NASA Astrophysics Data System (ADS)

Müller, Henning; Kalpathy-Cramer, Jayashree; Demner-Fushman, Dina; Antani, Sameer

2012-02-01

Content-based image retrieval (CBIR) from specialized collections has often been proposed for use in such areas as diagnostic aid, clinical decision support, and teaching. The visual retrieval from broad image collections such as teaching files, the medical literature or web images, by contrast, has not yet reached a high maturity level compared to textual information retrieval. Visual image classification into a relatively small number of classes (20-100) on the other hand, has shown to deliver good results in several benchmarks. It is, however, currently underused as a basic technology for retrieval tasks, for example, to limit the search space. Most classification schemes for medical images are focused on specific areas and consider mainly the medical image types (modalities), imaged anatomy, and view, and merge them into a single descriptor or classification hierarchy. Furthermore, they often ignore other important image types such as biological images, statistical figures, flowcharts, and diagrams that frequently occur in the biomedical literature. Most of the current classifications have also been created for radiology images, which are not the only types to be taken into account. With Open Access becoming increasingly widespread particularly in medicine, images from the biomedical literature are more easily available for use. Visual information from these images and knowledge that an image is of a specific type or medical modality could enrich retrieval. This enrichment is hampered by the lack of a commonly agreed image classification scheme. This paper presents a hierarchy for classification of biomedical illustrations with the goal of using it for visual classification and thus as a basis for retrieval. The proposed hierarchy is based on relevant parts of existing terminologies, such as the IRMA-code (Image Retrieval in Medical Applications), ad hoc classifications and hierarchies used in imageCLEF (Image retrieval task at the Cross-Language Evaluation Forum) and NLM's (National Library of Medicine) OpenI. Furtheron, mappings to NLM's MeSH (Medical Subject Headings), RSNA's RadLex (Radiological Society of North America, Radiology Lexicon), and the IRMA code are also attempted for relevant image types. Advantages derived from such hierarchical classification for medical image retrieval are being evaluated through benchmarks such as imageCLEF, and R&D systems such as NLM's OpenI. The goal is to extend this hierarchy progressively and (through adding image types occurring in the biomedical literature) to have a terminology for visual image classification based on image types distinguishable by visual means and occurring in the medical open access literature.

All-passive pixel super-resolution of time-stretch imaging

PubMed Central

Chan, Antony C. S.; Ng, Ho-Cheung; Bogaraju, Sharat C. V.; So, Hayden K. H.; Lam, Edmund Y.; Tsia, Kevin K.

2017-01-01

Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the-art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate — hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished without any active opto-mechanical subpixel-shift control or other additional hardware. Here, we present the experimental pixel-SR image reconstruction pipeline that restores high-resolution time-stretch images of microparticles and biological cells (phytoplankton) at a relaxed sampling rate (≈2–5 GSa/s)—more than four times lower than the originally required readout rate (20 GSa/s) — is thus effective for high-throughput label-free, morphology-based cellular classification down to single-cell precision. Upon integration with the high-throughput image processing technology, this pixel-SR time-stretch imaging technique represents a cost-effective and practical solution for large scale cell-based phenotypic screening in biomedical diagnosis and machine vision for quality control in manufacturing. PMID:28303936

The Impact Factor of Radiological Journals: Associations with Journal Content and Other Characteristics Over a Recent 12-Year Period.

PubMed

Rosenkrantz, Andrew B; Ayoola, Abimbola

2016-06-01

The aim of this study was to evaluate the trends in the impact factor (IF) of radiological journals over a recent 12-year period, including associations between IF and journal topic. Journal Citation Reports (JCR) was used to identify all biomedical journals and all radiological journals (assigned a JCR category of "Radiology, Nuclear Medicine, & Medical Imaging"), along with journal IF, in 2003 and 2014. Radiological journals were manually classified by topic. Trends in median IF (mIF) were assessed. The number of radiological journals increased from 83 (2003) to 125 (2014) (all biomedical journals: 5907 to 8718, respectively). mIF of radiological journals increased from 1.42 (2003) to 1.75 (2014) (all biomedical journals: 0.93 to 1.46, respectively). The most common topic among new radiological journals was general (nonspecialized) radiology (8). Five new radiological journals in 2014 were in topics (cancer imaging and molecular imaging) having no journals in 2003. mIF of general radiological journals was 1.49. Topics having highest mIF were cardiac imaging (2.94), optics (2.86), molecular imaging (2.77), radiation oncology (2.60), and neuroradiology (2.25). Topics with lowest mIF were ultrasound (1.19) and interventional radiology (1.44). Topics with the largest increase in mIF were cardiac imaging (from 1.17 to 2.94) and neuroradiology (from 1.07 to 2.25). Radiological journals exhibited higher mIF than biomedical journals overall. Among radiological journals, subspecialty journals had highest mIF. While a considerable number of new radiological journals since 2003 were general radiology journals having relatively low IF, there were also new journal topics representing emerging areas of subspecialized radiological research. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Minimizing the semantic gap in biomedical content-based image retrieval

NASA Astrophysics Data System (ADS)

Guan, Haiying; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2010-03-01

A major challenge in biomedical Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings that minimize the semantic gap between the high-level biomedical semantic concepts and the low-level visual features in images. This paper presents a comprehensive learning-based scheme toward meeting this challenge and improving retrieval quality. The article presents two algorithms: a learning-based feature selection and fusion algorithm and the Ranking Support Vector Machine (Ranking SVM) algorithm. The feature selection algorithm aims to select 'good' features and fuse them using different similarity measurements to provide a better representation of the high-level concepts with the low-level image features. Ranking SVM is applied to learn the retrieval rank function and associate the selected low-level features with query concepts, given the ground-truth ranking of the training samples. The proposed scheme addresses four major issues in CBIR to improve the retrieval accuracy: image feature extraction, selection and fusion, similarity measurements, the association of the low-level features with high-level concepts, and the generation of the rank function to support high-level semantic image retrieval. It models the relationship between semantic concepts and image features, and enables retrieval at the semantic level. We apply it to the problem of vertebra shape retrieval from a digitized spine x-ray image set collected by the second National Health and Nutrition Examination Survey (NHANES II). The experimental results show an improvement of up to 41.92% in the mean average precision (MAP) over conventional image similarity computation methods.

Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

PubMed

Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

2013-08-01

A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

Synthesis and size classification of metal oxide nanoparticles for biomedical applications

NASA Astrophysics Data System (ADS)

Atsumi, Takashi; Jeyadevan, Balachandran; Sato, Yoshinori; Tamura, Kazuchika; Aiba, Setsuya; Tohji, Kazuyuki

2004-12-01

Magnetic nanoparticles are considered for biomedical applications, such as the medium in magnetic resonance imaging, hyperthermia, drug delivery, and for the purification or classification of DNA or virus. The performance of magnetic nanoparticles in biomedical application such as hyperthermia depends very much on the magnetic properties, size and size distribution. We briefly described the basic idea behind their use in drug delivery, magnetic separation and hyperthermia and discussed the prerequisite properties magnetic particles for biomedical applications. Finally reported the synthesis and classification scheme to prepare magnetite (Fe3O4) nanoparticles with narrow size distribution for magnetic fluid hyperthermia.

Wireless image-data transmission from an implanted image sensor through a living mouse brain by intra body communication

NASA Astrophysics Data System (ADS)

Hayami, Hajime; Takehara, Hiroaki; Nagata, Kengo; Haruta, Makito; Noda, Toshihiko; Sasagawa, Kiyotaka; Tokuda, Takashi; Ohta, Jun

2016-04-01

Intra body communication technology allows the fabrication of compact implantable biomedical sensors compared with RF wireless technology. In this paper, we report the fabrication of an implantable image sensor of 625 µm width and 830 µm length and the demonstration of wireless image-data transmission through a brain tissue of a living mouse. The sensor was designed to transmit output signals of pixel values by pulse width modulation (PWM). The PWM signals from the sensor transmitted through a brain tissue were detected by a receiver electrode. Wireless data transmission of a two-dimensional image was successfully demonstrated in a living mouse brain. The technique reported here is expected to provide useful methods of data transmission using micro sized implantable biomedical sensors.

Measurements and analysis in imaging for biomedical applications

NASA Astrophysics Data System (ADS)

Hoeller, Timothy L.

2009-02-01

A Total Quality Management (TQM) approach can be used to analyze data from biomedical optical and imaging platforms of tissues. A shift from individuals to teams, partnerships, and total participation are necessary from health care groups for improved prognostics using measurement analysis. Proprietary measurement analysis software is available for calibrated, pixel-to-pixel measurements of angles and distances in digital images. Feature size, count, and color are determinable on an absolute and comparative basis. Although changes in images of histomics are based on complex and numerous factors, the variation of changes in imaging analysis to correlations of time, extent, and progression of illness can be derived. Statistical methods are preferred. Applications of the proprietary measurement software are available for any imaging platform. Quantification of results provides improved categorization of illness towards better health. As health care practitioners try to use quantified measurement data for patient diagnosis, the techniques reported can be used to track and isolate causes better. Comparisons, norms, and trends are available from processing of measurement data which is obtained easily and quickly from Scientific Software and methods. Example results for the class actions of Preventative and Corrective Care in Ophthalmology and Dermatology, respectively, are provided. Improved and quantified diagnosis can lead to better health and lower costs associated with health care. Systems support improvements towards Lean and Six Sigma affecting all branches of biology and medicine. As an example for use of statistics, the major types of variation involving a study of Bone Mineral Density (BMD) are examined. Typically, special causes in medicine relate to illness and activities; whereas, common causes are known to be associated with gender, race, size, and genetic make-up. Such a strategy of Continuous Process Improvement (CPI) involves comparison of patient results to baseline data using F-statistics. Self-parings over time are also useful. Special and common causes are identified apart from aging in applying the statistical methods. In the future, implementation of imaging measurement methods by research staff, doctors, and concerned patient partners result in improved health diagnosis, reporting, and cause determination. The long-term prospects for quantified measurements are better quality in imaging analysis with applications of higher utility for heath care providers.

A 3D ultrasound scanner: real time filtering and rendering algorithms.

PubMed

Cifarelli, D; Ruggiero, C; Brusacà, M; Mazzarella, M

1997-01-01

The work described here has been carried out within a collaborative project between DIST and ESAOTE BIOMEDICA aiming to set up a new ultrasonic scanner performing 3D reconstruction. A system is being set up to process and display 3D ultrasonic data in a fast, economical and user friendly way to help the physician during diagnosis. A comparison is presented among several algorithms for digital filtering, data segmentation and rendering for real time, PC based, three-dimensional reconstruction from B-mode ultrasonic biomedical images. Several algorithms for digital filtering have been compared as relates to processing time and to final image quality. Three-dimensional data segmentation techniques and rendering has been carried out with special reference to user friendly features for foreseeable applications and reconstruction speed.

Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy.

PubMed

Medyukhina, Anna; Meyer, Tobias; Schmitt, Michael; Romeike, Bernd F M; Dietzek, Benjamin; Popp, Jürgen

2012-11-01

Nonlinear optical (NLO) imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or two photon excited fluorescence (TPEF) show great potential for biomedical imaging. In order to facilitate the diagnostic process based on NLO imaging, there is need for an automated calculation of quantitative values such as cell density, nucleus-to-cytoplasm ratio, average nuclear size. Extraction of these parameters is helpful for the histological assessment in general and specifically e.g. for the determination of tumor grades. This requires an accurate image segmentation and detection of locations and boundaries of cells and nuclei. Here we present an image processing approach for the detection of nuclei and cells in co-registered TPEF and CARS images. The algorithm developed utilizes the gray-scale information for the detection of the nuclei locations and the gradient information for the delineation of the nuclear and cellular boundaries. The approach reported is capable for an automated segmentation of cells and nuclei in multimodal TPEF-CARS images of human brain tumor samples. The results are important for the development of NLO microscopy into a clinically relevant diagnostic tool. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Use of multidimensional, multimodal imaging and PACS to support neurological diagnoses

NASA Astrophysics Data System (ADS)

Wong, Stephen T. C.; Knowlton, Robert C.; Hoo, Kent S.; Huang, H. K.

1995-05-01

Technological advances in brain imaging have revolutionized diagnosis in neurology and neurological surgery. Major imaging techniques include magnetic resonance imaging (MRI) to visualize structural anatomy, positron emission tomography (PET) to image metabolic function and cerebral blood flow, magnetoencephalography (MEG) to visualize the location of physiologic current sources, and magnetic resonance spectroscopy (MRS) to measure specific biochemicals. Each of these techniques studies different biomedical aspects of the brain, but there lacks an effective means to quantify and correlate the disparate imaging datasets in order to improve clinical decision making processes. This paper describes several techniques developed in a UNIX-based neurodiagnostic workstation to aid the noninvasive presurgical evaluation of epilepsy patients. These techniques include online access to the picture archiving and communication systems (PACS) multimedia archive, coregistration of multimodality image datasets, and correlation and quantitation of structural and functional information contained in the registered images. For illustration, we describe the use of these techniques in a patient case of nonlesional neocortical epilepsy. We also present out future work based on preliminary studies.

Monitoring tumor growth and treatment in small animals with magnetic resonance and optical tomographic imaging

NASA Astrophysics Data System (ADS)

Masciotti, J.; Provenzano, F.; Papa, J.; Klose, A.; Hur, J.; Gu, X.; Yamashiro, D.; Kandel, J.; Hielscher, A. H.

2006-02-01

Small animal models are employed to simulate disease in humans and to study its progression, what factors are important to the disease process, and to study the disease treatment. Biomedical imaging modalities such as magnetic resonance imaging (MRI) and Optical Tomography make it possible to non-invasively monitor the progression of diseases in living small animals and study the efficacy of drugs and treatment protocols. MRI is an established imaging modality capable of obtaining high resolution anatomical images and along with contrast agents allow the studying of blood volume. Optical tomography, on the other hand, is an emerging imaging modality, which, while much lower in spatial resolution, can separate the effects of oxyhemoglobin, deoxyhemoglobin, and blood volume with high temporal resolution. In this study we apply these modalities to imaging the growth of kidney tumors and then there treatment by an anti-VEGF agent. We illustrate how these imaging modalities have their individual uses, but can still supplement each other and cross validation can be performed.

Lipid-polymer hybrid nanoparticle-mediated therapeutics delivery: advances and challenges.

PubMed

Bose, Rajendran J C; Ravikumar, Rramaswamy; Karuppagounder, Vengadeshprabu; Bennet, Devasier; Rangasamy, Sabarinathan; Thandavarayan, Rajarajan A

2017-08-01

With rapid advances in nanomedicine, lipid-polymer hybrid nanoparticles (LPHNPs) have emerged as promising nanocarriers for several biomedical applications, including therapeutics delivery and biomedical imaging. Significant research has been dedicated to biomimetic or targeting functionalization, as well as controlled and image-guided drug-release capabilities. Despite this research, the clinical translation of LPHNP-mediated therapeutics delivery has progressed incrementally. In this review, we discuss the recent advances in and challenges to the development and application of LPHNPs, present examples to demonstrate the advantages of LPHNPs in therapeutics delivery and imaging applications, and discuss the translational obstacles to LPHNP technology. Copyright © 2017. Published by Elsevier Ltd.

High-power THz to IR emission by femtosecond laser irradiation of random 2D metallic nanostructures.

PubMed

Zhang, Liangliang; Mu, Kaijun; Zhou, Yunsong; Wang, Hai; Zhang, Cunlin; Zhang, X-C

2015-07-24

Terahertz (THz) spectroscopic sensing and imaging has identified its potentials in a number of areas such as standoff security screening at portals, explosive detection at battle fields, bio-medical research, and so on. With these needs, the development of an intense and broadband THz source has been a focus of THz research. In this work, we report an intense (~10 mW) and ultra-broadband (~150 THz) THz to infrared (IR) source with a Gaussian wavefront, emitted from nano-pore-structured metallic thin films with femtosecond laser pulse excitation. The underlying mechanism has been proposed as thermal radiation. In addition, an intense coherent THz signal was generated through the optical rectification process simultaneously with the strong thermal signal. This unique feature opens up new avenues in biomedical research.

76 FR 69748 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-09

... Grossman, DDS, Scientific Review Officer, National Institute of Biomedical Imagin and Bioengineering... Bethesda Metro Station, Bethesda, MD 20814. Contact Person: Ruth Grossman, DDS, Scientific Review Officer...Continental Chicago, 505 North Michigan Avenue, Chicago, IL. Contact Person: Ruth Grossman, DDS, Scientific...

Design and implementation of a biomedical image database (BDIM).

PubMed

Aubry, F; Badaoui, S; Kaplan, H; Di Paola, R

1988-01-01

We developed a biomedical image database (BDIM) which proposes a standardized representation of value arrays such as images and curves, and of their associated parameters, independently of their acquisition mode to make their transmission and processing easier. It includes three kinds of interactions, oriented to the users. The network concept was kept as a constraint to incorporate the BDIM in a distributed structure and we maintained compatibility with the ACR/NEMA communication protocol. The management of arrays and their associated parameters includes two distinct bases of objects, linked together via a gateway. The first one manages arrays according to their storage mode: long term storage on optionally on-line mass storage devices, and, for consultations, partial copies of long term stored arrays on hard disk. The second one manages the associated parameters and the gateway by means of the relational DBMS ORACLE. Parameters are grouped into relations. Some of them are in agreement with groups defined by the ACR/NEMA. The other relations describe objects resulting from processed initial objects. These new objects are not described by the ACR/NEMA but they can be inserted as shadow groups of ACR/NEMA description. The relations describing the storage and their pathname constitute the gateway. ORACLE distributed tools and the two-level storage technique will allow the integration of the BDIM into a distributed structure, Queries and array (alone or in sequences) retrieval module has access to the relations via a level in which a dictionary managed by ORACLE is included. This dictionary translates ACR/NEMA objects into objects that can be handled by the DBMS.(ABSTRACT TRUNCATED AT 250 WORDS)

Using wavelet denoising and mathematical morphology in the segmentation technique applied to blood cells images.

PubMed

Boix, Macarena; Cantó, Begoña

2013-04-01

Accurate image segmentation is used in medical diagnosis since this technique is a noninvasive pre-processing step for biomedical treatment. In this work we present an efficient segmentation method for medical image analysis. In particular, with this method blood cells can be segmented. For that, we combine the wavelet transform with morphological operations. Moreover, the wavelet thresholding technique is used to eliminate the noise and prepare the image for suitable segmentation. In wavelet denoising we determine the best wavelet that shows a segmentation with the largest area in the cell. We study different wavelet families and we conclude that the wavelet db1 is the best and it can serve for posterior works on blood pathologies. The proposed method generates goods results when it is applied on several images. Finally, the proposed algorithm made in MatLab environment is verified for a selected blood cells.

Automation of Hessian-Based Tubularity Measure Response Function in 3D Biomedical Images.

PubMed

Dzyubak, Oleksandr P; Ritman, Erik L

2011-01-01

The blood vessels and nerve trees consist of tubular objects interconnected into a complex tree- or web-like structure that has a range of structural scale 5 μm diameter capillaries to 3 cm aorta. This large-scale range presents two major problems; one is just making the measurements, and the other is the exponential increase of component numbers with decreasing scale. With the remarkable increase in the volume imaged by, and resolution of, modern day 3D imagers, it is almost impossible to make manual tracking of the complex multiscale parameters from those large image data sets. In addition, the manual tracking is quite subjective and unreliable. We propose a solution for automation of an adaptive nonsupervised system for tracking tubular objects based on multiscale framework and use of Hessian-based object shape detector incorporating National Library of Medicine Insight Segmentation and Registration Toolkit (ITK) image processing libraries.

Hyperpolarized Porous Silicon Nanoparticles: Potential Theragnostic Material for ²⁹Si Magnetic Resonance Imaging.

PubMed

Seo, Hyeonglim; Choi, Ikjang; Whiting, Nicholas; Hu, Jingzhe; Luu, Quy Son; Pudakalakatti, Shivanand; McCowan, Caitlin; Kim, Yaewon; Zacharias, Niki; Lee, Seunghyun; Bhattacharya, Pratip; Lee, Youngbok

2018-05-20

Porous silicon nanoparticles have recently garnered attention as potentially-promising biomedical platforms for drug delivery and medical diagnostics. Here, we demonstrate porous silicon nanoparticles as contrast agents for ²⁹Si magnetic resonance imaging. Size-controlled porous silicon nanoparticles were synthesized by magnesiothermic reduction of silica nanoparticles and were surface activated for further functionalization. Particles were hyperpolarized via dynamic nuclear polarization to enhance their ²⁹Si MR signals; the particles demonstrated long ²⁹Si spin-lattice relaxation (T₁) times (~ 25 mins), which suggests potential applicability for medical imaging. Furthermore, ²⁹Si hyperpolarization levels were sufficient to allow ²⁹Si MRI in phantoms. These results underscore the potential of porous silicon nanoparticles that, when combined with hyperpolarized magnetic resonance imaging, can be a powerful theragnostic deep tissue imaging platform to interrogate various biomolecular processes in vivo. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Regional shape-based feature space for segmenting biomedical images using neural networks

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Gopal; Hoford, John D.; Hoffman, Eric A.

1993-07-01

In biomedical images, structure of interest, particularly the soft tissue structures, such as the heart, airways, bronchial and arterial trees often have grey-scale and textural characteristics similar to other structures in the image, making it difficult to segment them using only gray- scale and texture information. However, these objects can be visually recognized by their unique shapes and sizes. In this paper we discuss, what we believe to be, a novel, simple scheme for extracting features based on regional shapes. To test the effectiveness of these features for image segmentation (classification), we use an artificial neural network and a statistical cluster analysis technique. The proposed shape-based feature extraction algorithm computes regional shape vectors (RSVs) for all pixels that meet a certain threshold criteria. The distance from each such pixel to a boundary is computed in 8 directions (or in 26 directions for a 3-D image). Together, these 8 (or 26) values represent the pixel's (or voxel's) RSV. All RSVs from an image are used to train a multi-layered perceptron neural network which uses these features to 'learn' a suitable classification strategy. To clearly distinguish the desired object from other objects within an image, several examples from inside and outside the desired object are used for training. Several examples are presented to illustrate the strengths and weaknesses of our algorithm. Both synthetic and actual biomedical images are considered. Future extensions to this algorithm are also discussed.

In vivo bioluminescence and reflectance imaging of multiple organs in bioluminescence reporter mice by bundled-fiber-coupled microscopy

PubMed Central

Ando, Yoriko; Sakurai, Takashi; Koida, Kowa; Tei, Hajime; Hida, Akiko; Nakao, Kazuki; Natsume, Mistuo; Numano, Rika

2016-01-01

Bioluminescence imaging (BLI) is used in biomedical research to monitor biological processes within living organisms. Recently, fiber bundles with high transmittance and density have been developed to detect low light with high resolution. Therefore, we have developed a bundled-fiber-coupled microscope with a highly sensitive cooled-CCD camera that enables the BLI of organs within the mouse body. This is the first report of in vivo BLI of the brain and multiple organs in luciferase-reporter mice using bundled-fiber optics. With reflectance imaging, the structures of blood vessels and organs can be seen clearly with light illumination, and it allowed identification of the structural details of bioluminescence images. This technique can also be applied to clinical diagnostics in a low invasive manner. PMID:27231601

Deep-tissue focal fluorescence imaging with digitally time-reversed ultrasound-encoded light

PubMed Central

Wang, Ying Min; Judkewitz, Benjamin; DiMarzio, Charles A.; Yang, Changhuei

2012-01-01

Fluorescence imaging is one of the most important research tools in biomedical sciences. However, scattering of light severely impedes imaging of thick biological samples beyond the ballistic regime. Here we directly show focusing and high-resolution fluorescence imaging deep inside biological tissues by digitally time-reversing ultrasound-tagged light with high optical gain (~5×105). We confirm the presence of a time-reversed optical focus along with a diffuse background—a corollary of partial phase conjugation—and develop an approach for dynamic background cancellation. To illustrate the potential of our method, we image complex fluorescent objects and tumour microtissues at an unprecedented depth of 2.5 mm in biological tissues at a lateral resolution of 36 μm×52 μm and an axial resolution of 657 μm. Our results set the stage for a range of deep-tissue imaging applications in biomedical research and medical diagnostics. PMID:22735456

Medical imaging education in biomedical engineering curriculum: courseware development and application through a hybrid teaching model.

PubMed

Zhao, Weizhao; Li, Xiping; Chen, Hairong; Manns, Fabrice

2012-01-01

Medical Imaging is a key training component in Biomedical Engineering programs. Medical imaging education is interdisciplinary training, involving physics, mathematics, chemistry, electrical engineering, computer engineering, and applications in biology and medicine. Seeking an efficient teaching method for instructors and an effective learning environment for students has long been a goal for medical imaging education. By the support of NSF grants, we developed the medical imaging teaching software (MITS) and associated dynamic assessment tracking system (DATS). The MITS/DATS system has been applied to junior and senior medical imaging classes through a hybrid teaching model. The results show that student's learning gain improved, particularly in concept understanding and simulation project completion. The results also indicate disparities in subjective perception between junior and senior classes. Three institutions are collaborating to expand the courseware system and plan to apply it to different class settings.

USNCTAM perspectives on mechanics in medicine

PubMed Central

Bao, Gang; Bazilevs, Yuri; Chung, Jae-Hyun; Decuzzi, Paolo; Espinosa, Horacio D.; Ferrari, Mauro; Gao, Huajian; Hossain, Shaolie S.; Hughes, Thomas J. R.; Kamm, Roger D.; Liu, Wing Kam; Marsden, Alison; Schrefler, Bernhard

2014-01-01

Over decades, the theoretical and applied mechanics community has developed sophisticated approaches for analysing the behaviour of complex engineering systems. Most of these approaches have targeted systems in the transportation, materials, defence and energy industries. Applying and further developing engineering approaches for understanding, predicting and modulating the response of complicated biomedical processes not only holds great promise in meeting societal needs, but also poses serious challenges. This report, prepared for the US National Committee on Theoretical and Applied Mechanics, aims to identify the most pressing challenges in biological sciences and medicine that can be tackled within the broad field of mechanics. This echoes and complements a number of national and international initiatives aiming at fostering interdisciplinary biomedical research. This report also comments on cultural/educational challenges. Specifically, this report focuses on three major thrusts in which we believe mechanics has and will continue to have a substantial impact. (i) Rationally engineering injectable nano/microdevices for imaging and therapy of disease. Within this context, we discuss nanoparticle carrier design, vascular transport and adhesion, endocytosis and tumour growth in response to therapy, as well as uncertainty quantification techniques to better connect models and experiments. (ii) Design of biomedical devices, including point-of-care diagnostic systems, model organ and multi-organ microdevices, and pulsatile ventricular assistant devices. (iii) Mechanics of cellular processes, including mechanosensing and mechanotransduction, improved characterization of cellular constitutive behaviour, and microfluidic systems for single-cell studies. PMID:24872502

CALL FOR PAPERS: Special cluster in Biomedical Optics: honouring Professor Valery Tuchin, Saratov University

NASA Astrophysics Data System (ADS)

Wang, Ruikang K.; Priezzhev, Alexander; Fantini, Sergio

2004-07-01

To honour Professor Valery Tuchin, one of the pioneers in biomedical optics, Journal of Physics D: Applied Physics invites manuscript submissions on topics in biomedical optics, for publication in a Special section in May 2005. Papers may cover a variety of topics related to photon propagation in turbid media, spectroscopy and imaging. This Special cluster will reflect the diversity, breadth and impact of Professor Tuchin's contributions to the field of biomedical optics over the course of his distinguished career. Biomedical optics is a recently emerged discipline providing a broad variety of optical techniques and instruments for diagnostic, therapeutic and basic science applications. Together with contributions from other pioneers in the field, Professor Tuchin's work on fundamental and experimental aspects in tissue optics contributed enormously to the formation of this exciting field. Although general submissions in biomedical optics are invited, the Special cluster Editors especially encourage submissions in areas that are explicitly or implicitly influenced by Professor Tuchin's contributions to the field of biomedical optics. Manuscripts submitted to this Special cluster of Journal of Physics D: Applied Physics will be refereed according to the normal criteria and procedures of the journal, in accordance with the following schedule: Deadline for receipt of contributed papers: 31 November 2004 Deadline for acceptance and completion of refereeing process: 28 February 2005 Publication of special issue: May 2005 Please submit your manuscript electronically to jphysd@iop.org or via the Web site at www.iop.org/Journals. Otherwise, please send a copy of your typescript, a set of original figures and a cover letter to: The Publishing Administrator, Journal of Physics D: Applied Physics, Institute of Physics Publishing, Dirac House, Temple Back, Bristol BS1 6BE, United Kingdom. Further information on how to submit may be obtained upon request by e-mailing the journal at the above address. Alternatively, visit the homepage of the journal on the World Wide Web (http://www.iop.org/journals/jphysd)

Precise diagnosis in different scenarios using photoacoustic and fluorescence imaging with dual-modality nanoparticles

NASA Astrophysics Data System (ADS)

Peng, Dong; Du, Yang; Shi, Yiwen; Mao, Duo; Jia, Xiaohua; Li, Hui; Zhu, Yukun; Wang, Kun; Tian, Jie

2016-07-01

Photoacoustic imaging and fluorescence molecular imaging are emerging as important research tools for biomedical studies. Photoacoustic imaging offers both strong optical absorption contrast and high ultrasonic resolution, and fluorescence molecular imaging provides excellent superficial resolution, high sensitivity, high throughput, and the ability for real-time imaging. Therefore, combining the imaging information of both modalities can provide comprehensive in vivo physiological and pathological information. However, currently there are limited probes available that can realize both fluorescence and photoacoustic imaging, and advanced biomedical applications for applying this dual-modality imaging approach remain underexplored. In this study, we developed a dual-modality photoacoustic-fluorescence imaging nanoprobe, ICG-loaded Au@SiO2, which was uniquely designed, consisting of gold nanorod cores and indocyanine green with silica shell spacer layers to overcome fluorophore quenching. This nanoprobe was examined by both PAI and FMI for in vivo imaging on tumor and ischemia mouse models. Our results demonstrated that the nanoparticles can specifically accumulate at the tumor and ischemic areas and be detected by both imaging modalities. Moreover, this dual-modality imaging strategy exhibited superior advantages for a precise diagnosis in different scenarios. The new nanoprobe with the dual-modality imaging approach holds great potential for diagnosis and stage classification of tumor and ischemia related diseases.Photoacoustic imaging and fluorescence molecular imaging are emerging as important research tools for biomedical studies. Photoacoustic imaging offers both strong optical absorption contrast and high ultrasonic resolution, and fluorescence molecular imaging provides excellent superficial resolution, high sensitivity, high throughput, and the ability for real-time imaging. Therefore, combining the imaging information of both modalities can provide comprehensive in vivo physiological and pathological information. However, currently there are limited probes available that can realize both fluorescence and photoacoustic imaging, and advanced biomedical applications for applying this dual-modality imaging approach remain underexplored. In this study, we developed a dual-modality photoacoustic-fluorescence imaging nanoprobe, ICG-loaded Au@SiO2, which was uniquely designed, consisting of gold nanorod cores and indocyanine green with silica shell spacer layers to overcome fluorophore quenching. This nanoprobe was examined by both PAI and FMI for in vivo imaging on tumor and ischemia mouse models. Our results demonstrated that the nanoparticles can specifically accumulate at the tumor and ischemic areas and be detected by both imaging modalities. Moreover, this dual-modality imaging strategy exhibited superior advantages for a precise diagnosis in different scenarios. The new nanoprobe with the dual-modality imaging approach holds great potential for diagnosis and stage classification of tumor and ischemia related diseases. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr03809c

Anatomy for Biomedical Engineers

ERIC Educational Resources Information Center

Carmichael, Stephen W.; Robb, Richard A.

2008-01-01

There is a perceived need for anatomy instruction for graduate students enrolled in a biomedical engineering program. This appeared especially important for students interested in and using medical images. These students typically did not have a strong background in biology. The authors arranged for students to dissect regions of the body that…

Bond-selective photoacoustic imaging by converting molecular vibration into acoustic waves

PubMed Central

Hui, Jie; Li, Rui; Phillips, Evan H.; Goergen, Craig J.; Sturek, Michael; Cheng, Ji-Xin

2016-01-01

The quantized vibration of chemical bonds provides a way of detecting specific molecules in a complex tissue environment. Unlike pure optical methods, for which imaging depth is limited to a few hundred micrometers by significant optical scattering, photoacoustic detection of vibrational absorption breaks through the optical diffusion limit by taking advantage of diffused photons and weak acoustic scattering. Key features of this method include both high scalability of imaging depth from a few millimeters to a few centimeters and chemical bond selectivity as a novel contrast mechanism for photoacoustic imaging. Its biomedical applications spans detection of white matter loss and regeneration, assessment of breast tumor margins, and diagnosis of vulnerable atherosclerotic plaques. This review provides an overview of the recent advances made in vibration-based photoacoustic imaging and various biomedical applications enabled by this new technology. PMID:27069873

Gram-Schmidt orthonormalization for retrieval of amplitude images under sinusoidal patterns of illumination

USDA-ARS?s Scientific Manuscript database

Structured illumination using sinusoidal patterns has been utilized for optical imaging of biological tissues in biomedical research and, of horticultural products. Implementation of structured-illumination imaging relies on retrieval of amplitude images, which is conventionally achieved by a phase-...

K-edge subtraction synchrotron X-ray imaging in bio-medical research.

PubMed

Thomlinson, W; Elleaume, H; Porra, L; Suortti, P

2018-05-01

High contrast in X-ray medical imaging, while maintaining acceptable radiation dose levels to the patient, has long been a goal. One of the most promising methods is that of K-edge subtraction imaging. This technique, first advanced as long ago as 1953 by B. Jacobson, uses the large difference in the absorption coefficient of elements at energies above and below the K-edge. Two images, one taken above the edge and one below the edge, are subtracted leaving, ideally, only the image of the distribution of the target element. This paper reviews the development of the KES techniques and technology as applied to bio-medical imaging from the early low-power tube sources of X-rays to the latest high-power synchrotron sources. Applications to coronary angiography, functional lung imaging and bone growth are highlighted. A vision of possible imaging with new compact sources is presented. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Are we studying what matters? Health priorities and NIH-funded biomedical engineering research.

PubMed

Rubin, Jessica B; Paltiel, A David; Saltzman, W Mark

2010-07-01

With the founding of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) in 1999, the National Institutes of Health (NIH) made explicit its dedication to expanding research in biomedical engineering. Ten years later, we sought to examine how closely federal funding for biomedical engineering aligns with U.S. health priorities. Using a publicly accessible database of research projects funded by the NIH in 2008, we identified 641 grants focused on biomedical engineering, 48% of which targeted specific diseases. Overall, we found that these disease-specific NIH-funded biomedical engineering research projects align with national health priorities, as quantified by three commonly utilized measures of disease burden: cause of death, disability-adjusted survival losses, and expenditures. However, we also found some illnesses (e.g., cancer and heart disease) for which the number of research projects funded deviated from our expectations, given their disease burden. Our findings suggest several possibilities for future studies that would serve to further inform the allocation of limited research dollars within the field of biomedical engineering.

Perspective on nanoparticle technology for biomedical use

PubMed Central

Raliya, Ramesh; Chadha, Tandeep Singh; Hadad, Kelsey; Biswas, Pratim

2016-01-01

This review gives a short overview on the widespread use of nanostructured and nanocomposite materials for disease diagnostics, drug delivery, imaging and biomedical sensing applications. Nanoparticle interaction with a biological matrix/entity is greatly influenced by its morphology, crystal phase, surface chemistry, functionalization, physicochemical and electronic properties of the particle. Various nanoparticle synthesis routes, characteristization, and functionalization methodologies to be used for biomedical applications ranging from drug delivery to molecular probing of underlying mechanisms and concepts are described with several examples (150 references). PMID:26951098

Exploitation of realistic computational anthropomorphic phantoms for the optimization of nuclear imaging acquisition and processing protocols.

PubMed

Loudos, George K; Papadimitroulas, Panagiotis G; Kagadis, George C

2014-01-01

Monte Carlo (MC) simulations play a crucial role in nuclear medical imaging since they can provide the ground truth for clinical acquisitions, by integrating and quantifing all physical parameters that affect image quality. The last decade a number of realistic computational anthropomorphic models have been developed to serve imaging, as well as other biomedical engineering applications. The combination of MC techniques with realistic computational phantoms can provide a powerful tool for pre and post processing in imaging, data analysis and dosimetry. This work aims to create a global database for simulated Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) exams and the methodology, as well as the first elements are presented. Simulations are performed using the well validated GATE opensource toolkit, standard anthropomorphic phantoms and activity distribution of various radiopharmaceuticals, derived from literature. The resulting images, projections and sinograms of each study are provided in the database and can be further exploited to evaluate processing and reconstruction algorithms. Patient studies using different characteristics are included in the database and different computational phantoms were tested for the same acquisitions. These include the XCAT, Zubal and the Virtual Family, which some of which are used for the first time in nuclear imaging. The created database will be freely available and our current work is towards its extension by simulating additional clinical pathologies.

Histology image analysis for carcinoma detection and grading

PubMed Central

He, Lei; Long, L. Rodney; Antani, Sameer; Thoma, George R.

2012-01-01

This paper presents an overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification. As in other biomedical imaging areas such as radiology, many computer assisted diagnosis (CAD) systems have been implemented to aid histopathologists and clinicians in cancer diagnosis and research, which have been attempted to significantly reduce the labor and subjectivity of traditional manual intervention with histology images. The task of automated histology image analysis is usually not simple due to the unique characteristics of histology imaging, including the variability in image preparation techniques, clinical interpretation protocols, and the complex structures and very large size of the images themselves. In this paper we discuss those characteristics, provide relevant background information about slide preparation and interpretation, and review the application of digital image processing techniques to the field of histology image analysis. In particular, emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification. Four major carcinomas of cervix, prostate, breast, and lung are selected to illustrate the functions and capabilities of existing CAD systems. PMID:22436890

In vitro and ex vivo evaluation of silica-coated super paramagnetic iron oxide nanoparticles (SPION) as biomedical photoacoustic contrast agent

NASA Astrophysics Data System (ADS)

Alwi, Rudolf; Telenkov, Sergey A.; Mandelis, Andreas; Leshuk, Timothy; Gu, Frank; Oladepo, Sulayman; Michaelian, Kirk; Dickie, Kristopher

2013-03-01

The employment of contrast agents in photoacoustic imaging has gained significant attention within the past few years for their biomedical applications. In this study, the use of silica-coated superparamagnetic iron oxide (Fe3O4) nanoparticles (SPION) was investigated as a contrast agent in biomedical photoacoustic imaging. SPIONs have been widely used as Food-and-Drug-Administration (FDA)-approved contrast agents for magnetic resonance imaging (MRI) and are known to have an excellent safety profile. Using our frequency-domain photoacoustic correlation technique ("the photoacoustic radar") with modulated laser excitation, we examined the effects of nanoparticle size, concentration and biological medium (e.g. serum, sheep blood) on its photoacoustic response in turbid media (intralipid solution). Maximum detection depth and minimum measurable SPION concentration were determined experimentally. The detection was performed using a single element transducer. The nanoparticle-induced optical contrast ex vivo in dense muscular tissues (avian pectus) was evaluated using a phased array photoacoustic probe and the strong potential of silicacoated SPION as a possible photoacoustic contrast agent was demonstrated. This study opens the way for future clinical applications of nanoparticle-enhanced photoacoustic imaging in cancer therapy.

National Institute of Biomedical Imaging and Bioengineering Point-of-Care Technology Research Network: Advancing Precision Medicine

PubMed Central

Ford Carleton, Penny; Parrish, John A.; Collins, John M.; Crocker, J. Benjamin; Dixon, Ronald F.; Edgman-Levitan, Susan; Lewandrowski, Kent B.; Stahl, James E.; Klapperich, Catherine; Cabodi, Mario; Gaydos, Charlotte A.; Rompalo, Anne M.; Manabe, Yukari; Wang, Tza-Huei; Rothman, Richard; Geddes, Chris D.; Widdice, Lea; Jackman, Joany; Mathura, Rishi A.; Lash, Tiffani Bailey

2016-01-01

To advance the development of point-of-care technology (POCT), the National Institute of Biomedical Imaging and Bioengineering established the POCT Research Network (POCTRN), comprised of Centers that emphasize multidisciplinary partnerships and close facilitation to move technologies from an early stage of development into clinical testing and patient use. This paper describes the POCTRN and the three currently funded Centers as examples of academic-based organizations that support collaborations across disciplines, institutions, and geographic regions to successfully drive innovative solutions from concept to patient care. PMID:27730014

Web tools for large-scale 3D biological images and atlases

PubMed Central

2012-01-01

Background Large-scale volumetric biomedical image data of three or more dimensions are a significant challenge for distributed browsing and visualisation. Many images now exceed 10GB which for most users is too large to handle in terms of computer RAM and network bandwidth. This is aggravated when users need to access tens or hundreds of such images from an archive. Here we solve the problem for 2D section views through archive data delivering compressed tiled images enabling users to browse through very-large volume data in the context of a standard web-browser. The system provides an interactive visualisation for grey-level and colour 3D images including multiple image layers and spatial-data overlay. Results The standard Internet Imaging Protocol (IIP) has been extended to enable arbitrary 2D sectioning of 3D data as well a multi-layered images and indexed overlays. The extended protocol is termed IIP3D and we have implemented a matching server to deliver the protocol and a series of Ajax/Javascript client codes that will run in an Internet browser. We have tested the server software on a low-cost linux-based server for image volumes up to 135GB and 64 simultaneous users. The section views are delivered with response times independent of scale and orientation. The exemplar client provided multi-layer image views with user-controlled colour-filtering and overlays. Conclusions Interactive browsing of arbitrary sections through large biomedical-image volumes is made possible by use of an extended internet protocol and efficient server-based image tiling. The tools open the possibility of enabling fast access to large image archives without the requirement of whole image download and client computers with very large memory configurations. The system was demonstrated using a range of medical and biomedical image data extending up to 135GB for a single image volume. PMID:22676296

Biomedical image segmentation using geometric deformable models and metaheuristics.

PubMed

Mesejo, Pablo; Valsecchi, Andrea; Marrakchi-Kacem, Linda; Cagnoni, Stefano; Damas, Sergio

2015-07-01

This paper describes a hybrid level set approach for medical image segmentation. This new geometric deformable model combines region- and edge-based information with the prior shape knowledge introduced using deformable registration. Our proposal consists of two phases: training and test. The former implies the learning of the level set parameters by means of a Genetic Algorithm, while the latter is the proper segmentation, where another metaheuristic, in this case Scatter Search, derives the shape prior. In an experimental comparison, this approach has shown a better performance than a number of state-of-the-art methods when segmenting anatomical structures from different biomedical image modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multifunctional fluorescent and magnetic nanoparticles for biomedical applications

NASA Astrophysics Data System (ADS)

Selvan, Subramanian T.

2012-03-01

Hybrid multifunctional nanoparticles (NPs) are emerging as useful probes for magnetic based targeting, delivery, cell separation, magnetic resonance imaging (MRI), and fluorescence-based bio-labeling applications. Assessing from the literature, the development of multifunctional NPs for multimodality imaging is still in its infancy state. This report focuses on our recent work on quantum dots (QDs), magnetic NPs (MNPs) and bi-functional NPs (composed of either QDs or rare-earth NPs, and magnetic NPs - iron oxide or gadolinium oxide) for multimodality imaging based biomedical applications. The combination of MRI and fluorescence would ally each other in improving the sensitivity and resolution, resulting in improved and early diagnosis of the disease. The challenges in this area are discussed.

Determining the relative importance of figures in journal articles to find representative images

NASA Astrophysics Data System (ADS)

Müller, Henning; Foncubierta-Rodríguez, Antonio; Lin, Chang; Eggel, Ivan

2013-03-01

When physicians are searching for articles in the medical literature, images of the articles can help determining relevance of the article content for a specific information need. The visual image representation can be an advantage in effectiveness (quality of found articles) and also in efficiency (speed of determining relevance or irrelevance) as many articles can likely be excluded much quicker by looking at a few representative images. In domains such as medical information retrieval, allowing to determine relevance quickly and accurately is an important criterion. This becomes even more important when small interfaces are used as it is frequently the case on mobile phones and tablets to access scientific data whenever information needs arise. In scientific articles many figures are used and particularly in the biomedical literature only a subset may be relevant for determining the relevance of a specific article to an information need. In many cases clinical images can be seen as more important for visual appearance than graphs or histograms that require looking at the context for interpretation. To get a clearer idea of image relevance in articles, a user test with a physician was performed who classified images of biomedical research articles into categories of importance that can subsequently be used to evaluate algorithms that automatically select images as representative examples. The manual sorting of images of 50 journal articles of BioMedCentral with each containing more than 8 figures by importance also allows to derive several rules that determine how to choose images and how to develop algorithms for choosing the most representative images of specific texts. This article describes the user tests and can be a first important step to evaluate automatic tools to select representative images for representing articles and potentially also images in other contexts, for example when representing patient records or other medical concepts when selecting images to represent RadLex terms in tutorials or interactive interfaces for example. This can help to make the image retrieval process more efficient and effective for physicians.

Computational intelligence for target assessment in Parkinson's disease

NASA Astrophysics Data System (ADS)

Micheli-Tzanakou, Evangelia; Hamilton, J. L.; Zheng, J.; Lehman, Richard M.

2001-11-01

Recent advances in image and signal processing have created a new challenging environment for biomedical engineers. Methods that were developed for different fields are now finding a fertile ground in biomedicine, especially in the analysis of bio-signals and in the understanding of images. More and more, these methods are used in the operating room, helping surgeons, and in the physician's office as aids for diagnostic purposes. Neural Network (NN) research on the other hand, has gone a long way in the past decade. NNs now consist of many thousands of highly interconnected processing elements that can encode, store and recall relationships between different patterns by altering the weighting coefficients of inputs in a systematic way. Although they can generate reasonable outputs from unknown input patterns, and can tolerate a great deal of noise, they are very slow when run on a serial machine. We have used advanced signal processing and innovative image processing methods that are used along with computational intelligence for diagnostic purposes and as visualization aids inside and outside the operating room. Applications to be discussed include EEGs and field potentials in Parkinson's disease along with 3D reconstruction of MR or fMR brain images in Parkinson's patients, are currently used in the operating room for Pallidotomies and Deep Brain Stimulation (DBS).

NCI Visuals Online

Cancer.gov

NCI Visuals Online contains images from the collections of the National Cancer Institute's Office of Communications and Public Liaison, including general biomedical and science-related images, cancer-specific scientific and patient care-related images, and portraits of directors and staff of the National Cancer Institute.

Biomedical Applications of Zinc Oxide Nanomaterials

PubMed Central

Zhang, Yin; Nayak, Tapas R.; Hong, Hao; Cai, Weibo

2013-01-01

Nanotechnology has witnessed tremendous advancement over the last several decades. Zinc oxide (ZnO), which can exhibit a wide variety of nanostructures, possesses unique semiconducting, optical, and piezoelectric properties hence has been investigated for a wide variety of applications. One of the most important features of ZnO nanomaterials is low toxicity and biodegradability. Zn2+ is an indispensable trace element for adults (~10 mg of Zn2+ per day is recommended) and it is involved in various aspects of metabolism. Chemically, the surface of ZnO is rich in -OH groups, which can be readily functionalized by various surface decorating molecules. In this review article, we summarized the current status of the use of ZnO nanomaterials for biomedical applications, such as biomedical imaging (which includes fluorescence, magnetic resonance, positron emission tomography, as well as dual-modality imaging), drug delivery, gene delivery, and biosensing of a wide array of molecules of interest. Research in biomedical applications of ZnO nanomaterials will continue to flourish over the next decade, and much research effort will be needed to develop biocompatible/biodegradable ZnO nanoplatforms for potential clinical translation. PMID:24206130

Image Decoding of Photonic Crystal Beads Array in the Microfluidic Chip for Multiplex Assays

PubMed Central

Yuan, Junjie; Zhao, Xiangwei; Wang, Xiaoxia; Gu, Zhongze

2014-01-01

Along with the miniaturization and intellectualization of biomedical instruments, the increasing demand of health monitoring at anywhere and anytime elevates the need for the development of point of care testing (POCT). Photonic crystal beads (PCBs) as one kind of good encoded microcarriers can be integrated with microfluidic chips in order to realize cost-effective and high sensitive multiplex bioassays. However, there are difficulties in analyzing them towards automated analysis due to the characters of the PCBs and the unique detection manner. In this paper, we propose a strategy to take advantage of automated image processing for the color decoding of the PCBs array in the microfluidic chip for multiplex assays. By processing and alignment of two modal images of epi-fluorescence and epi-white light, every intact bead in the image is accurately extracted and decoded by PC colors, which stand for the target species. This method, which shows high robustness and accuracy under various configurations, eliminates the high hardware requirement of spectroscopy analysis and user-interaction software, and provides adequate supports for the general automated analysis of POCT based on PCBs array. PMID:25341876

Cell-phone-based platform for biomedical device development and education applications.

PubMed

Smith, Zachary J; Chu, Kaiqin; Espenson, Alyssa R; Rahimzadeh, Mehdi; Gryshuk, Amy; Molinaro, Marco; Dwyre, Denis M; Lane, Stephen; Matthews, Dennis; Wachsmann-Hogiu, Sebastian

2011-03-02

In this paper we report the development of two attachments to a commercial cell phone that transform the phone's integrated lens and image sensor into a 350x microscope and visible-light spectrometer. The microscope is capable of transmission and polarized microscopy modes and is shown to have 1.5 micron resolution and a usable field-of-view of 150 x 50 with no image processing, and approximately 350 x 350 when post-processing is applied. The spectrometer has a 300 nm bandwidth with a limiting spectral resolution of close to 5 nm. We show applications of the devices to medically relevant problems. In the case of the microscope, we image both stained and unstained blood-smears showing the ability to acquire images of similar quality to commercial microscope platforms, thus allowing diagnosis of clinical pathologies. With the spectrometer we demonstrate acquisition of a white-light transmission spectrum through diffuse tissue as well as the acquisition of a fluorescence spectrum. We also envision the devices to have immediate relevance in the educational field.

Cell-Phone-Based Platform for Biomedical Device Development and Education Applications

PubMed Central

Smith, Zachary J.; Chu, Kaiqin; Espenson, Alyssa R.; Rahimzadeh, Mehdi; Gryshuk, Amy; Molinaro, Marco; Dwyre, Denis M.; Lane, Stephen; Matthews, Dennis; Wachsmann-Hogiu, Sebastian

2011-01-01

In this paper we report the development of two attachments to a commercial cell phone that transform the phone's integrated lens and image sensor into a 350× microscope and visible-light spectrometer. The microscope is capable of transmission and polarized microscopy modes and is shown to have 1.5 micron resolution and a usable field-of-view of 150×150 with no image processing, and approximately 350×350 when post-processing is applied. The spectrometer has a 300 nm bandwidth with a limiting spectral resolution of close to 5 nm. We show applications of the devices to medically relevant problems. In the case of the microscope, we image both stained and unstained blood-smears showing the ability to acquire images of similar quality to commercial microscope platforms, thus allowing diagnosis of clinical pathologies. With the spectrometer we demonstrate acquisition of a white-light transmission spectrum through diffuse tissue as well as the acquisition of a fluorescence spectrum. We also envision the devices to have immediate relevance in the educational field. PMID:21399693

País de gordos/país de muertos: Obesity, death and nation in biomedical and forensic genetics in Mexico

PubMed Central

García-Deister, Vivette; López-Beltrán, Carlos

2015-01-01

This article provides a comparison between genomic medicine and forensic genetics in Mexico, in light of recent depictions of the nation as a ‘país de gordos’ (country of the fat) and a ‘país de muertos’ (country of the dead). We examine the continuities and ruptures in the public image of genetics in these two areas of attention, health and security, focusing especially on how the relevant publics of genetic science are assembled in each case. Publics of biomedical and forensic genetics are assembled through processes of recruitment and interpellation, in ways that modulate current theorizations of co-production. The comparison also provides a vista onto discussions regarding the involvement of genetics in regimes of governance and citizenship and about the relationship between the state and biopower in a context of perceived health crisis and war-like violence. PMID:27479997

País de gordos/país de muertos: Obesity, death and nation in biomedical and forensic genetics in Mexico.

PubMed

García-Deister, Vivette; López-Beltrán, Carlos

2015-12-01

This article provides a comparison between genomic medicine and forensic genetics in Mexico, in light of recent depictions of the nation as a 'país de gordos' (country of the fat) and a 'país de muertos' (country of the dead). We examine the continuities and ruptures in the public image of genetics in these two areas of attention, health and security, focusing especially on how the relevant publics of genetic science are assembled in each case. Publics of biomedical and forensic genetics are assembled through processes of recruitment and interpellation, in ways that modulate current theorizations of co-production. The comparison also provides a vista onto discussions regarding the involvement of genetics in regimes of governance and citizenship and about the relationship between the state and biopower in a context of perceived health crisis and war-like violence.

Figure Text Extraction in Biomedical Literature

PubMed Central

Kim, Daehyun; Yu, Hong

2011-01-01

Background Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org) to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures. Methodology We first evaluated an off-the-shelf Optical Character Recognition (OCR) tool on its ability to extract text from figures appearing in biomedical full-text articles. We then developed a Figure Text Extraction Tool (FigTExT) to improve the performance of the OCR tool for figure text extraction through the use of three innovative components: image preprocessing, character recognition, and text correction. We first developed image preprocessing to enhance image quality and to improve text localization. Then we adapted the off-the-shelf OCR tool on the improved text localization for character recognition. Finally, we developed and evaluated a novel text correction framework by taking advantage of figure-specific lexicons. Results/Conclusions The evaluation on 382 figures (9,643 figure texts in total) randomly selected from PubMed Central full-text articles shows that FigTExT performed with 84% precision, 98% recall, and 90% F1-score for text localization and with 62.5% precision, 51.0% recall and 56.2% F1-score for figure text extraction. When limiting figure texts to those judged by domain experts to be important content, FigTExT performed with 87.3% precision, 68.8% recall, and 77% F1-score. FigTExT significantly improved the performance of the off-the-shelf OCR tool we used, which on its own performed with 36.6% precision, 19.3% recall, and 25.3% F1-score for text extraction. In addition, our results show that FigTExT can extract texts that do not appear in figure captions or other associated text, further suggesting the potential utility of FigTExT for improving figure search. PMID:21249186

Figure text extraction in biomedical literature.

PubMed

Kim, Daehyun; Yu, Hong

2011-01-13

Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures. Therefore, we are developing the Biomedical Figure Search engine (http://figuresearch.askHERMES.org) to allow bioscientists to access figures efficiently. Since text frequently appears in figures, automatically extracting such text may assist the task of mining information from figures. Little research, however, has been conducted exploring text extraction from biomedical figures. We first evaluated an off-the-shelf Optical Character Recognition (OCR) tool on its ability to extract text from figures appearing in biomedical full-text articles. We then developed a Figure Text Extraction Tool (FigTExT) to improve the performance of the OCR tool for figure text extraction through the use of three innovative components: image preprocessing, character recognition, and text correction. We first developed image preprocessing to enhance image quality and to improve text localization. Then we adapted the off-the-shelf OCR tool on the improved text localization for character recognition. Finally, we developed and evaluated a novel text correction framework by taking advantage of figure-specific lexicons. The evaluation on 382 figures (9,643 figure texts in total) randomly selected from PubMed Central full-text articles shows that FigTExT performed with 84% precision, 98% recall, and 90% F1-score for text localization and with 62.5% precision, 51.0% recall and 56.2% F1-score for figure text extraction. When limiting figure texts to those judged by domain experts to be important content, FigTExT performed with 87.3% precision, 68.8% recall, and 77% F1-score. FigTExT significantly improved the performance of the off-the-shelf OCR tool we used, which on its own performed with 36.6% precision, 19.3% recall, and 25.3% F1-score for text extraction. In addition, our results show that FigTExT can extract texts that do not appear in figure captions or other associated text, further suggesting the potential utility of FigTExT for improving figure search.

Welcome to health information science and systems.

PubMed

Zhang, Yanchun

2013-01-01

Health Information Science and Systems is an exciting, new, multidisciplinary journal that aims to use technologies in computer science to assist in disease diagnoses, treatment, prediction and monitoring through the modeling, design, development, visualization, integration and management of health related information. These computer-science technologies include such as information systems, web technologies, data mining, image processing, user interaction and interface, sensors and wireless networking and are applicable to a wide range of health related information including medical data, biomedical data, bioinformatics data, public health data.

Applied Nonlinear Dynamics and Stochastic Systems Near The Millenium. Proceedings

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

Kadtke, J.B.; Bulsara, A.

These proceedings represent papers presented at the Applied Nonlinear Dynamics and Stochastic Systems conference held in San Diego, California in July 1997. The conference emphasized the applications of nonlinear dynamical systems theory in fields as diverse as neuroscience and biomedical engineering, fluid dynamics, chaos control, nonlinear signal/image processing, stochastic resonance, devices and nonlinear dynamics in socio{minus}economic systems. There were 56 papers presented at the conference and 5 have been abstracted for the Energy Science and Technology database.(AIP)

MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU.

PubMed

Katsigiannis, Stamos; Zacharia, Eleni; Maroulis, Dimitris

2017-05-01

Complementary DNA (cDNA) microarray is a powerful tool for simultaneously studying the expression level of thousands of genes. Nevertheless, the analysis of microarray images remains an arduous and challenging task due to the poor quality of the images that often suffer from noise, artifacts, and uneven background. In this study, the MIGS-GPU [Microarray Image Gridding and Segmentation on Graphics Processing Unit (GPU)] software for gridding and segmenting microarray images is presented. MIGS-GPU's computations are performed on the GPU by means of the compute unified device architecture (CUDA) in order to achieve fast performance and increase the utilization of available system resources. Evaluation on both real and synthetic cDNA microarray images showed that MIGS-GPU provides better performance than state-of-the-art alternatives, while the proposed GPU implementation achieves significantly lower computational times compared to the respective CPU approaches. Consequently, MIGS-GPU can be an advantageous and useful tool for biomedical laboratories, offering a user-friendly interface that requires minimum input in order to run.

High power THz sources for nonlinear imaging

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

Tekavec, Patrick F.; Kozlov, Vladimir G.

2014-02-18

Many biological and chemical compounds have unique absorption features in the THz (0.1 - 10 THz) region, making the use of THz waves attractive for imaging in defense, security, biomedical imaging, and monitoring of industrial processes. Unlike optical radiation, THz frequencies can pass through many substances such as paper, clothing, ceramic, etc. with little attenuation. The use of currently available THz systems is limited by lack of highpower, sources as well as sensitive detectors and detector arrays operating at room temperature. Here we present a novel, high power THz source based on intracavity downconverison of optical pulses. The source deliversmore » 6 ps pulses at 1.5 THz, with an average power of >300 μW and peak powers >450 mW. We propose an imaging method based on frequency upconverison that is ideally suited to use the narrow bandwidth and high peak powers produced by the source. By upconverting the THz image to the infrared, commercially available detectors can be used for real time imaging.« less

High power THz sources for nonlinear imaging

NASA Astrophysics Data System (ADS)

Tekavec, Patrick F.; Kozlov, Vladimir G.

2014-02-01

Many biological and chemical compounds have unique absorption features in the THz (0.1 - 10 THz) region, making the use of THz waves attractive for imaging in defense, security, biomedical imaging, and monitoring of industrial processes. Unlike optical radiation, THz frequencies can pass through many substances such as paper, clothing, ceramic, etc. with little attenuation. The use of currently available THz systems is limited by lack of highpower, sources as well as sensitive detectors and detector arrays operating at room temperature. Here we present a novel, high power THz source based on intracavity downconverison of optical pulses. The source delivers 6 ps pulses at 1.5 THz, with an average power of >300 μW and peak powers >450 mW. We propose an imaging method based on frequency upconverison that is ideally suited to use the narrow bandwidth and high peak powers produced by the source. By upconverting the THz image to the infrared, commercially available detectors can be used for real time imaging.

Hot topics in biomedical ultrasound: ultrasound therapy and its integration with ultrasonic imaging

NASA Astrophysics Data System (ADS)

Everbach, E. Carr

2005-09-01

Since the development of biomedical ultrasound imaging from sonar after WWII, there has been a clear divide between ultrasonic imaging and ultrasound therapy. While imaging techniques are designed to cause as little change as possible in the tissues through which ultrasound propagates, ultrasound therapy typically relies upon heating or acoustic cavitation to produce a desirable therapeutic effect. Concerns over the increasingly high acoustic outputs of diagnostic ultrasound scanners prompted the adoption of the Mechanical Index (MI) and Thermal Index (TI) in the early 1990s. Therapeutic applications of ultrasound, meanwhile, have evolved from deep tissue heating in sports medicine to include targeted drug delivery, tumor and plaque ablation, cauterization via high intensity focused ultrasound (HIFU), and accelerated dissolution of blood clots. The integration of ultrasonic imaging and therapy in one device is just beginning, but the promise of improved patient outcomes is balanced by regulatory and practical impediments.

Polysaccharide-Coated Magnetic Nanoparticles for Imaging and Gene Therapy

PubMed Central

Uthaman, Saji; Cherukula, Kondareddy; Cho, Chong-Su; Park, In-Kyu

2015-01-01

Today, nanotechnology plays a vital role in biomedical applications, especially for the diagnosis and treatment of various diseases. Among the many different types of fabricated nanoparticles, magnetic metal oxide nanoparticles stand out as unique and useful tools for biomedical applications, because of their imaging characteristics and therapeutic properties such as drug and gene carriers. Polymer-coated magnetic particles are currently of particular interest to investigators in the fields of nanobiomedicine and fundamental biomaterials. Theranostic magnetic nanoparticles that are encapsulated or coated with polymers not only exhibit imaging properties in response to stimuli, but also can efficiently deliver various drugs and therapeutic genes. Even though a large number of polymer-coated magnetic nanoparticles have been fabricated over the last decade, most of these have only been used for imaging purposes. The focus of this review is on polysaccharide-coated magnetic nanoparticles used for imaging and gene delivery. PMID:26078971

Biologically Relevant Heterogeneity: Metrics and Practical Insights.

PubMed

Gough, Albert; Stern, Andrew M; Maier, John; Lezon, Timothy; Shun, Tong-Ying; Chennubhotla, Chakra; Schurdak, Mark E; Haney, Steven A; Taylor, D Lansing

2017-03-01

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

Rendering an archive in three dimensions

NASA Astrophysics Data System (ADS)

Leiman, David A.; Twose, Claire; Lee, Teresa Y. H.; Fletcher, Alex; Yoo, Terry S.

2003-05-01

We examine the requirements for a publicly accessible, online collection of three-dimensional biomedical image data, including those yielded by radiological processes such as MRI, ultrasound and others. Intended as a repository and distribution mechanism for such medical data, we created the National Online Volumetric Archive (NOVA) as a case study aimed at identifying the multiple issues involved in realizing a large-scale digital archive. In the paper we discuss such factors as the current legal and health information privacy policy affecting the collection of human medical images, retrieval and management of information and technical implementation. This project culminated in the launching of a website that includes downloadable datasets and a prototype data submission system.

Synthesis of Water-Dispersible Mn2+ Functionalized Silicon Nanoparticles under Room Temperature and Atmospheric Pressure for Fluorescence and Magnetic Resonance Dual-Modality Imaging.

PubMed

Dou, Ya-Kun; Chen, Yang; He, Xi-Wen; Li, Wen-You; Li, Yu-Hao; Zhang, Yu-Kui

2017-11-07

Silicon nanoparticles (Si NPs) have been widely used in fluorescence imaging. However, rigorous synthesis conditions and the single modality imaging limit the further development of Si NPs in the field of biomedical imaging. Here, we reported a method for synthesizing water-dispersible Mn 2+ functionalized Si NPs (Mn-Si NPs) under mild experimental conditions for fluorescence and magnetic resonance dual-modality imaging. The whole synthesis process was completed under room temperature and atmospheric pressure, and no special and expensive equipment was required. The synthetic nanoparticles, with favorable pH stability, NaCl stability, photostability, and low toxicity, emitted green fluorescence (512 nm). At the same time, the nanoparticles also demonstrated excellent magnetic resonance imaging ability. In vitro, their T 1 -weighted magnetic resonance imaging effect was obvious, and the value of longitudinal relaxation degree r 1 reached 4.25 mM -1 s -1 . On the basis of their good biocompatibility, Mn-Si NPs were successfully used for the fluorescence imaging as well as magnetic resonance imaging in vivo.

IJ-OpenCV: Combining ImageJ and OpenCV for processing images in biomedicine.

PubMed

Domínguez, César; Heras, Jónathan; Pascual, Vico

2017-05-01

The effective processing of biomedical images usually requires the interoperability of diverse software tools that have different aims but are complementary. The goal of this work is to develop a bridge to connect two of those tools: ImageJ, a program for image analysis in life sciences, and OpenCV, a computer vision and machine learning library. Based on a thorough analysis of ImageJ and OpenCV, we detected the features of these systems that could be enhanced, and developed a library to combine both tools, taking advantage of the strengths of each system. The library was implemented on top of the SciJava converter framework. We also provide a methodology to use this library. We have developed the publicly available library IJ-OpenCV that can be employed to create applications combining features from both ImageJ and OpenCV. From the perspective of ImageJ developers, they can use IJ-OpenCV to easily create plugins that use any functionality provided by the OpenCV library and explore different alternatives. From the perspective of OpenCV developers, this library provides a link to the ImageJ graphical user interface and all its features to handle regions of interest. The IJ-OpenCV library bridges the gap between ImageJ and OpenCV, allowing the connection and the cooperation of these two systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

PubMed

Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

Computer systems for annotation of single molecule fragments

DOEpatents

Schwartz, David Charles; Severin, Jessica

2016-07-19

There are provided computer systems for visualizing and annotating single molecule images. Annotation systems in accordance with this disclosure allow a user to mark and annotate single molecules of interest and their restriction enzyme cut sites thereby determining the restriction fragments of single nucleic acid molecules. The markings and annotations may be automatically generated by the system in certain embodiments and they may be overlaid translucently onto the single molecule images. An image caching system may be implemented in the computer annotation systems to reduce image processing time. The annotation systems include one or more connectors connecting to one or more databases capable of storing single molecule data as well as other biomedical data. Such diverse array of data can be retrieved and used to validate the markings and annotations. The annotation systems may be implemented and deployed over a computer network. They may be ergonomically optimized to facilitate user interactions.

Real-time and quantitative isotropic spatial resolution susceptibility imaging for magnetic nanoparticles

NASA Astrophysics Data System (ADS)

Pi, Shiqiang; Liu, Wenzhong; Jiang, Tao

2018-03-01

The magnetic transparency of biological tissue allows the magnetic nanoparticle (MNP) to be a promising functional sensor and contrast agent. The complex susceptibility of MNPs, strongly influenced by particle concentration, excitation magnetic field and their surrounding microenvironment, provides significant implications for biomedical applications. Therefore, magnetic susceptibility imaging of high spatial resolution will give more detailed information during the process of MNP-aided diagnosis and therapy. In this study, we present a novel spatial magnetic susceptibility extraction method for MNPs under a gradient magnetic field, a low-frequency drive magnetic field, and a weak strength high-frequency magnetic field. Based on this novel method, a magnetic particle susceptibility imaging (MPSI) of millimeter-level spatial resolution (<3 mm) was achieved using our homemade imaging system. Corroborated by the experimental results, the MPSI shows real-time (1 s per frame acquisition) and quantitative abilities, and isotropic high resolution.

Orthogonal Luciferase-Luciferin Pairs for Bioluminescence Imaging.

PubMed

Jones, Krysten A; Porterfield, William B; Rathbun, Colin M; McCutcheon, David C; Paley, Miranda A; Prescher, Jennifer A

2017-02-15

Bioluminescence imaging with luciferase-luciferin pairs is widely used in biomedical research. Several luciferases have been identified in nature, and many have been adapted for tracking cells in whole animals. Unfortunately, the optimal luciferases for imaging in vivo utilize the same substrate and therefore cannot easily differentiate multiple cell types in a single subject. To develop a broader set of distinguishable probes, we crafted custom luciferins that can be selectively processed by engineered luciferases. Libraries of mutant enzymes were iteratively screened with sterically modified luciferins, and orthogonal enzyme-substrate "hits" were identified. These tools produced light when complementary enzyme-substrate partners interacted both in vitro and in cultured cell models. Based on their selectivity, these designer pairs will bolster multicomponent imaging and enable the direct interrogation of cell networks not currently possible with existing tools. Our screening platform is also general and will expedite the identification of more unique luciferases and luciferins, further expanding the bioluminescence toolkit.

Leveraging Engineering of Indocyanine Green-Encapsulated Polymeric Nanocomposites for Biomedical Applications.

PubMed

Han, Ya-Hui; Kankala, Ranjith Kumar; Wang, Shi-Bin; Chen, Ai-Zheng

2018-05-24

In recent times, photo-induced therapeutics have attracted enormous interest from researchers due to such attractive properties as preferential localization, excellent tissue penetration, high therapeutic efficacy, and minimal invasiveness, among others. Numerous photosensitizers have been considered in combination with light to realize significant progress in therapeutics. Along this line, indocyanine green (ICG), a Food and Drug Administration (FDA)-approved near-infrared (NIR, >750 nm) fluorescent dye, has been utilized in various biomedical applications such as drug delivery, imaging, and diagnosis, due to its attractive physicochemical properties, high sensitivity, and better imaging view field. However, ICG still suffers from certain limitations for its utilization as a molecular imaging probe in vivo, such as concentration-dependent aggregation, poor in vitro aqueous stability and photodegradation due to various physicochemical attributes. To overcome these limitations, much research has been dedicated to engineering numerous multifunctional polymeric composites for potential biomedical applications. In this review, we aim to discuss ICG-encapsulated polymeric nanoconstructs, which are of particular interest in various biomedical applications. First, we emphasize some attractive properties of ICG (including physicochemical characteristics, optical properties, metabolic features, and other aspects) and some of its current limitations. Next, we aim to provide a comprehensive overview highlighting recent reports on various polymeric nanoparticles that carry ICG for light-induced therapeutics with a set of examples. Finally, we summarize with perspectives highlighting the significant outcome, and current challenges of these nanocomposites.

Nanoparticles for cancer imaging: The good, the bad, and the promise

PubMed Central

Chapman, Sandra; Dobrovolskaia, Marina; Farahani, Keyvan; Goodwin, Andrew; Joshi, Amit; Lee, Hakho; Meade, Thomas; Pomper, Martin; Ptak, Krzysztof; Rao, Jianghong; Singh, Ravi; Sridhar, Srinivas; Stern, Stephan; Wang, Andrew; Weaver, John B.; Woloschak, Gayle; Yang, Lily

2014-01-01

Summary Recent advances in molecular imaging and nanotechnology are providing new opportunities for biomedical imaging with great promise for the development of novel imaging agents. The unique optical, magnetic, and chemical properties of materials at the scale of nanometers allow the creation of imaging probes with better contrast enhancement, increased sensitivity, controlled biodistribution, better spatial and temporal information, multi-functionality and multi-modal imaging across MRI, PET, SPECT, and ultrasound. These features could ultimately translate to clinical advantages such as earlier detection, real time assessment of disease progression and personalized medicine. However, several years of investigation into the application of these materials to cancer research has revealed challenges that have delayed the successful application of these agents to the field of biomedical imaging. Understanding these challenges is critical to take full advantage of the benefits offered by nano-sized imaging agents. Therefore, this article presents the lessons learned and challenges encountered by a group of leading researchers in this field, and suggests ways forward to develop nanoparticle probes for cancer imaging. Published by Elsevier Ltd. PMID:25419228

IMAGEP - A FORTRAN ALGORITHM FOR DIGITAL IMAGE PROCESSING

NASA Technical Reports Server (NTRS)

Roth, D. J.

1994-01-01

IMAGEP is a FORTRAN computer algorithm containing various image processing, analysis, and enhancement functions. It is a keyboard-driven program organized into nine subroutines. Within the subroutines are other routines, also, selected via keyboard. Some of the functions performed by IMAGEP include digitization, storage and retrieval of images; image enhancement by contrast expansion, addition and subtraction, magnification, inversion, and bit shifting; display and movement of cursor; display of grey level histogram of image; and display of the variation of grey level intensity as a function of image position. This algorithm has possible scientific, industrial, and biomedical applications in material flaw studies, steel and ore analysis, and pathology, respectively. IMAGEP is written in VAX FORTRAN for DEC VAX series computers running VMS. The program requires the use of a Grinnell 274 image processor which can be obtained from Mark McCloud Associates, Campbell, CA. An object library of the required GMR series software is included on the distribution media. IMAGEP requires 1Mb of RAM for execution. The standard distribution medium for this program is a 1600 BPI 9track magnetic tape in VAX FILES-11 format. It is also available on a TK50 tape cartridge in VAX FILES-11 format. This program was developed in 1991. DEC, VAX, VMS, and TK50 are trademarks of Digital Equipment Corporation.

Demons registration for in vivo and deformable laser scanning confocal endomicroscopy.

PubMed

Chiew, Wei-Ming; Lin, Feng; Seah, Hock Soon

2017-09-01

A critical effect found in noninvasive in vivo endomicroscopic imaging modalities is image distortions due to sporadic movement exhibited by living organisms. In three-dimensional confocal imaging, this effect results in a dataset that is tilted across deeper slices. Apart from that, the sequential flow of the imaging-processing pipeline restricts real-time adjustments due to the unavailability of information obtainable only from subsequent stages. To solve these problems, we propose an approach to render Demons-registered datasets as they are being captured, focusing on the coupling between registration and visualization. To improve the acquisition process, we also propose a real-time visual analytics tool, which complements the imaging pipeline and the Demons registration pipeline with useful visual indicators to provide real-time feedback for immediate adjustments. We highlight the problem of deformation within the visualization pipeline for object-ordered and image-ordered rendering. Visualizations of critical information including registration forces and partial renderings of the captured data are also presented in the analytics system. We demonstrate the advantages of the algorithmic design through experimental results with both synthetically deformed datasets and actual in vivo, time-lapse tissue datasets expressing natural deformations. Remarkably, this algorithm design is for embedded implementation in intelligent biomedical imaging instrumentation with customizable circuitry. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Demons registration for in vivo and deformable laser scanning confocal endomicroscopy

NASA Astrophysics Data System (ADS)

Chiew, Wei Ming; Lin, Feng; Seah, Hock Soon

2017-09-01

A critical effect found in noninvasive in vivo endomicroscopic imaging modalities is image distortions due to sporadic movement exhibited by living organisms. In three-dimensional confocal imaging, this effect results in a dataset that is tilted across deeper slices. Apart from that, the sequential flow of the imaging-processing pipeline restricts real-time adjustments due to the unavailability of information obtainable only from subsequent stages. To solve these problems, we propose an approach to render Demons-registered datasets as they are being captured, focusing on the coupling between registration and visualization. To improve the acquisition process, we also propose a real-time visual analytics tool, which complements the imaging pipeline and the Demons registration pipeline with useful visual indicators to provide real-time feedback for immediate adjustments. We highlight the problem of deformation within the visualization pipeline for object-ordered and image-ordered rendering. Visualizations of critical information including registration forces and partial renderings of the captured data are also presented in the analytics system. We demonstrate the advantages of the algorithmic design through experimental results with both synthetically deformed datasets and actual in vivo, time-lapse tissue datasets expressing natural deformations. Remarkably, this algorithm design is for embedded implementation in intelligent biomedical imaging instrumentation with customizable circuitry.

Nanoparticles for Biomedical Imaging: Fundamentals of Clinical Translation

PubMed Central

Choi, Hak Soo; Frangioni, John V.

2010-01-01

Because of their large size compared to small molecules, and their multi-functionality, nanoparticles (NPs) hold promise as biomedical imaging, diagnostic, and theragnostic agents. However, the key to their success hinges on a detailed understanding of their behavior after administration into the body. NP biodistribution, target binding, and clearance are a complex function of their physicochemical properties in serum, which include hydrodynamic diameter, solubility, stability, shape and flexibility, surface charge, composition, and formulation. Moreover, many materials used to construct NPs have real or potential toxicity, or may interfere with other medical tests. In this review, we discuss the design considerations that mediate NP behavior in the body and the fundamental principles that govern clinical translation. By analyzing those nanomaterials that have already received regulatory approval, most of which are actually therapeutic agents, we attempt to predict which types of NPs hold potential as diagnostic agents for biomedical imaging. Finally, using quantum dots as an example, we provide a framework for deciding whether an NP-based agent is the best choice for a particular clinical application. PMID:21084027

An intelligent monitoring and management system for cross-enterprise biomedical data sharing platform

NASA Astrophysics Data System (ADS)

Wang, Tusheng; Yang, Yuanyuan; Zhang, Jianguo

2013-03-01

In order to enable multiple disciplines of medical researchers, clinical physicians and biomedical engineers working together in a secured, efficient, and transparent cooperative environment, we had designed an e-Science platform for biomedical imaging research and application cross multiple academic institutions and hospitals in Shanghai by using grid-based or cloud-based distributed architecture and presented this work in SPIE Medical Imaging conference held in San Diego in 2012. However, when the platform integrates more and more nodes over different networks, the first challenge is that how to monitor and maintain all the hosts and services operating cross multiple academic institutions and hospitals in the e-Science platform, such as DICOM and Web based image communication services, messaging services and XDS ITI transaction services. In this presentation, we presented a system design and implementation of intelligent monitoring and management which can collect system resource status of every node in real time, alert when node or service failure occurs, and can finally improve the robustness, reliability and service continuity of this e-Science platform.

RysannMD: A biomedical semantic annotator balancing speed and accuracy.

PubMed

Cuzzola, John; Jovanović, Jelena; Bagheri, Ebrahim

2017-07-01

Recently, both researchers and practitioners have explored the possibility of semantically annotating large and continuously evolving collections of biomedical texts such as research papers, medical reports, and physician notes in order to enable their efficient and effective management and use in clinical practice or research laboratories. Such annotations can be automatically generated by biomedical semantic annotators - tools that are specifically designed for detecting and disambiguating biomedical concepts mentioned in text. The biomedical community has already presented several solid automated semantic annotators. However, the existing tools are either strong in their disambiguation capacity, i.e., the ability to identify the correct biomedical concept for a given piece of text among several candidate concepts, or they excel in their processing time, i.e., work very efficiently, but none of the semantic annotation tools reported in the literature has both of these qualities. In this paper, we present RysannMD (Ryerson Semantic Annotator for Medical Domain), a biomedical semantic annotation tool that strikes a balance between processing time and performance while disambiguating biomedical terms. In other words, RysannMD provides reasonable disambiguation performance when choosing the right sense for a biomedical term in a given context, and does that in a reasonable time. To examine how RysannMD stands with respect to the state of the art biomedical semantic annotators, we have conducted a series of experiments using standard benchmarking corpora, including both gold and silver standards, and four modern biomedical semantic annotators, namely cTAKES, MetaMap, NOBLE Coder, and Neji. The annotators were compared with respect to the quality of the produced annotations measured against gold and silver standards using precision, recall, and F 1 measure and speed, i.e., processing time. In the experiments, RysannMD achieved the best median F 1 measure across the benchmarking corpora, independent of the standard used (silver/gold), biomedical subdomain, and document size. In terms of the annotation speed, RysannMD scored the second best median processing time across all the experiments. The obtained results indicate that RysannMD offers the best performance among the examined semantic annotators when both quality of annotation and speed are considered simultaneously. Copyright © 2017 Elsevier Inc. All rights reserved.

Deterministic compressive sampling for high-quality image reconstruction of ultrasound tomography.

PubMed

Huy, Tran Quang; Tue, Huynh Huu; Long, Ton That; Duc-Tan, Tran

2017-05-25

A well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation, compared to the current gold-standard X-ray mammography. Based on inverse scattering technique, ultrasound tomography uses some material properties such as sound contrast or attenuation to detect small targets. The Distorted Born Iterative Method (DBIM) based on first-order Born approximation is an efficient diffraction tomography approach. One of the challenges for a high quality reconstruction is to obtain many measurements from the number of transmitters and receivers. Given the fact that biomedical images are often sparse, the compressed sensing (CS) technique could be therefore effectively applied to ultrasound tomography by reducing the number of transmitters and receivers, while maintaining a high quality of image reconstruction. There are currently several work on CS that dispose randomly distributed locations for the measurement system. However, this random configuration is relatively difficult to implement in practice. Instead of it, we should adopt a methodology that helps determine the locations of measurement devices in a deterministic way. For this, we develop the novel DCS-DBIM algorithm that is highly applicable in practice. Inspired of the exploitation of the deterministic compressed sensing technique (DCS) introduced by the authors few years ago with the image reconstruction process implemented using l 1 regularization. Simulation results of the proposed approach have demonstrated its high performance, with the normalized error approximately 90% reduced, compared to the conventional approach, this new approach can save half of number of measurements and only uses two iterations. Universal image quality index is also evaluated in order to prove the efficiency of the proposed approach. Numerical simulation results indicate that CS and DCS techniques offer equivalent image reconstruction quality with simpler practical implementation. It would be a very promising approach in practical applications of modern biomedical imaging technology.

Effective biomedical document classification for identifying publications relevant to the mouse Gene Expression Database (GXD).

PubMed

Jiang, Xiangying; Ringwald, Martin; Blake, Judith; Shatkay, Hagit

2017-01-01

The Gene Expression Database (GXD) is a comprehensive online database within the Mouse Genome Informatics resource, aiming to provide available information about endogenous gene expression during mouse development. The information stems primarily from many thousands of biomedical publications that database curators must go through and read. Given the very large number of biomedical papers published each year, automatic document classification plays an important role in biomedical research. Specifically, an effective and efficient document classifier is needed for supporting the GXD annotation workflow. We present here an effective yet relatively simple classification scheme, which uses readily available tools while employing feature selection, aiming to assist curators in identifying publications relevant to GXD. We examine the performance of our method over a large manually curated dataset, consisting of more than 25 000 PubMed abstracts, of which about half are curated as relevant to GXD while the other half as irrelevant to GXD. In addition to text from title-and-abstract, we also consider image captions, an important information source that we integrate into our method. We apply a captions-based classifier to a subset of about 3300 documents, for which the full text of the curated articles is available. The results demonstrate that our proposed approach is robust and effectively addresses the GXD document classification. Moreover, using information obtained from image captions clearly improves performance, compared to title and abstract alone, affirming the utility of image captions as a substantial evidence source for automatically determining the relevance of biomedical publications to a specific subject area. www.informatics.jax.org. © The Author(s) 2017. Published by Oxford University Press.

Advances in Biomedical Imaging, Bioengineering, and Related Technologies for the Development of Biomarkers of Pancreatic Disease: Summary of a National Institute of Diabetes and Digestive and Kidney Diseases and National Institute of Biomedical Imaging and Bioengineering Workshop

PubMed Central

Kelly, Kimberly A.; Hollingsworth, Michael A.; Brand, Randall E.; Liu, Christina H.; Singh, Vikesh K.; Srivastava, Sudhir; Wasan, Ajay D.; Yadav, Dhiraj; Andersen, Dana K.

2015-01-01

A workshop sponsored by the National Institute of Diabetes and Digestive and Kidney Diseases and the National Institute of Biomedical Imaging and Bioengineering focused on research gaps and opportunities in the development of new biomarkers of pancreatic disease. The session was held on July 22, 2015, and structured into six sessions: 1) introduction and overview, 2) keynote address, 3) new approaches to the diagnosis of chronic pancreatitis, 4) biomarkers of pain and inflammation, 5) new approaches to the detection of pancreatic cancer, and 6) shed exosomes, shed cells, and shed proteins. Recent advances in the fields of pancreatic imaging, functional markers of pancreatic disease, proteomics, molecular and cellular imaging, and detection of circulating cancer cells and exosomes were reviewed. Knowledge gaps and research needs were highlighted. The development of new methods for the non-invasive determination of pancreatic pathology, the use of cellular markers of pancreatic function, inflammation, pain, and malignancy, and the refinement of methods to identify cells and cellular constituents of pancreatic cancer were discussed. The further refinement of sophisticated technical methods, and the need for clinical studies to validate these new approaches in large-scale studies of patients at risk for the development of pancreatic disease was repeatedly emphasized. PMID:26465948

An Innovative Method for Obtaining Consistent Images and Quantification of Histochemically Stained Specimens

PubMed Central

Sedgewick, Gerald J.; Ericson, Marna

2015-01-01

Obtaining digital images of color brightfield microscopy is an important aspect of biomedical research and the clinical practice of diagnostic pathology. Although the field of digital pathology has had tremendous advances in whole-slide imaging systems, little effort has been directed toward standardizing color brightfield digital imaging to maintain image-to-image consistency and tonal linearity. Using a single camera and microscope to obtain digital images of three stains, we show that microscope and camera systems inherently produce image-to-image variation. Moreover, we demonstrate that post-processing with a widely used raster graphics editor software program does not completely correct for session-to-session inconsistency. We introduce a reliable method for creating consistent images with a hardware/software solution (ChromaCal™; Datacolor Inc., NJ) along with its features for creating color standardization, preserving linear tonal levels, providing automated white balancing and setting automated brightness to consistent levels. The resulting image consistency using this method will also streamline mean density and morphometry measurements, as images are easily segmented and single thresholds can be used. We suggest that this is a superior method for color brightfield imaging, which can be used for quantification and can be readily incorporated into workflows. PMID:25575568

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

PubMed

Kimori, Yoshitaka; Baba, Norio; Morone, Nobuhiro

2010-07-08

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

A contour-based shape descriptor for biomedical image classification and retrieval

NASA Astrophysics Data System (ADS)

You, Daekeun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-12-01

Contours, object blobs, and specific feature points are utilized to represent object shapes and extract shape descriptors that can then be used for object detection or image classification. In this research we develop a shape descriptor for biomedical image type (or, modality) classification. We adapt a feature extraction method used in optical character recognition (OCR) for character shape representation, and apply various image preprocessing methods to successfully adapt the method to our application. The proposed shape descriptor is applied to radiology images (e.g., MRI, CT, ultrasound, X-ray, etc.) to assess its usefulness for modality classification. In our experiment we compare our method with other visual descriptors such as CEDD, CLD, Tamura, and PHOG that extract color, texture, or shape information from images. The proposed method achieved the highest classification accuracy of 74.1% among all other individual descriptors in the test, and when combined with CSD (color structure descriptor) showed better performance (78.9%) than using the shape descriptor alone.

Biomedical imaging ontologies: A survey and proposal for future work

PubMed Central

Smith, Barry; Arabandi, Sivaram; Brochhausen, Mathias; Calhoun, Michael; Ciccarese, Paolo; Doyle, Scott; Gibaud, Bernard; Goldberg, Ilya; Kahn, Charles E.; Overton, James; Tomaszewski, John; Gurcan, Metin

2015-01-01

Background: Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as “cell” or “image” or “tissue” or “microscope”) that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical definitions thereby also supporting reasoning over the tagged data. Aim: This paper provides a survey of the biomedical imaging ontologies that have been developed thus far. It outlines the challenges, particularly faced by ontologies in the fields of histopathological imaging and image analysis, and suggests a strategy for addressing these challenges in the example domain of quantitative histopathology imaging. Results and Conclusions: The ultimate goal is to support the multiscale understanding of disease that comes from using interoperable ontologies to integrate imaging data with clinical and genomics data. PMID:26167381

A color-corrected strategy for information multiplexed Fourier ptychographic imaging

NASA Astrophysics Data System (ADS)

Wang, Mingqun; Zhang, Yuzhen; Chen, Qian; Sun, Jiasong; Fan, Yao; Zuo, Chao

2017-12-01

Fourier ptychography (FP) is a novel computational imaging technique that provides both wide field of view (FoV) and high-resolution (HR) imaging capacity for biomedical imaging. Combined with information multiplexing technology, wavelength multiplexed (or color multiplexed) FP imaging can be implemented by lighting up R/G/B LED units simultaneously. Furthermore, a HR image can be recovered at each wavelength from the multiplexed dataset. This enhances the efficiency of data acquisition. However, since the same dataset of intensity measurement is used to recover the HR image at each wavelength, the mean value in each channel would converge to the same value. In this paper, a color correction strategy embedded in the multiplexing FP scheme is demonstrated, which is termed as color corrected wavelength multiplexed Fourier ptychography (CWMFP). Three images captured by turning on a LED array in R/G/B are required as priori knowledge to improve the accuracy of reconstruction in the recovery process. Using the reported technique, the redundancy requirement of information multiplexed FP is reduced. Moreover, the accuracy of reconstruction at each channel is improved with correct color reproduction of the specimen.

Use of multidimensional, multimodal imaging and PACS to support neurological diagnoses

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

Wong, S.T.C.; Knowlton, R.; Hoo, K.S.

1995-12-31

Technological advances in brain imaging have revolutionized diagnosis in neurology and neurological surgery. Major imaging techniques include magnetic resonance imaging (MRI) to visualize structural anatomy, positron emission tomography (PET) to image metabolic function and cerebral blood flow, magnetoencephalography (MEG) to visualize the location of physiologic current sources, and magnetic resonance spectroscopy (MRS) to measure specific biochemicals. Each of these techniques studies different biomedical aspects of the grain, but there lacks an effective means to quantify and correlate the disparate imaging datasets in order to improve clinical decision making processes. This paper describes several techniques developed in a UNIX-based neurodiagnostic workstationmore » to aid the non-invasive presurgical evaluation of epilepsy patients. These techniques include on-line access to the picture archiving and communication systems (PACS) multimedia archive, coregistration of multimodality image datasets, and correlation and quantitative of structural and functional information contained in the registered images. For illustration, the authors describe the use of these techniques in a patient case of non-lesional neocortical epilepsy. They also present the future work based on preliminary studies.« less

Measurement Marker Recognition In A Time Sequence Of Infrared Images For Biomedical Applications

NASA Astrophysics Data System (ADS)

Fiorini, A. R.; Fumero, R.; Marchesi, R.

1986-03-01

In thermographic measurements, quantitative surface temperature evaluation is often uncertain. The main reason is in the lack of available reference points in transient conditions. Reflective markers were used for automatic marker recognition and pixel coordinate computations. An algorithm selects marker icons to match marker references where particular luminance conditions are satisfied. Automatic marker recognition allows luminance compensation and temperature calibration of recorded infrared images. A biomedical application is presented: the dynamic behaviour of the surface temperature distributions is investigated in order to study the performance of two different pumping systems for extracorporeal circulation. Sequences of images are compared and results are discussed. Finally, the algorithm allows to monitor the experimental environment and to alert for the presence of unusual experimental conditions.

Instrumentation of Molecular Imaging on Site-Specific Targeting Fluorescent Peptide for Early Detection of Breast Cancer

NASA Astrophysics Data System (ADS)

Yu, Ping; Ma, Lixin

2012-02-01

In this work we developed two biomedical imaging techniques for early detection of breast cancer. Both image modalities provide molecular imaging capability to probe site-specific targeting dyes. The first technique, heterodyne CCD fluorescence mediated tomography, is a non-invasive biomedical imaging that uses fluorescent photons from the targeted dye on the tumor cells inside human breast tissue. The technique detects a large volume of tissue (20 cm) with a moderate resolution (1 mm) and provides the high sensitivity. The second technique, dual-band spectral-domain optical coherence tomography, is a high-resolution tissue imaging modality. It uses a low coherence interferometer to detect coherent photons hidden in the incoherent background. Due to the coherence detection, a high resolution (20 microns) is possible. We have finished prototype imaging systems for the development of both image modalities and performed imaging experiments on tumor tissues. The spectroscopic/tomographic images show contrasts of dense tumor tissues and tumor necrotic regions. In order to correlate the findings from our results, a diffusion-weighted magnetic resonance imaging (MRI) of the tumors was performed using a small animal 7-Telsa MRI and demonstrated excellent agreement.

A philosophy for CNS radiotracer design.

PubMed

Van de Bittner, Genevieve C; Ricq, Emily L; Hooker, Jacob M

2014-10-21

Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfalls of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test-retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood-brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Finally, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible.

USNCTAM perspectives on mechanics in medicine.

PubMed

Bao, Gang; Bazilevs, Yuri; Chung, Jae-Hyun; Decuzzi, Paolo; Espinosa, Horacio D; Ferrari, Mauro; Gao, Huajian; Hossain, Shaolie S; Hughes, Thomas J R; Kamm, Roger D; Liu, Wing Kam; Marsden, Alison; Schrefler, Bernhard

2014-08-06

Over decades, the theoretical and applied mechanics community has developed sophisticated approaches for analysing the behaviour of complex engineering systems. Most of these approaches have targeted systems in the transportation, materials, defence and energy industries. Applying and further developing engineering approaches for understanding, predicting and modulating the response of complicated biomedical processes not only holds great promise in meeting societal needs, but also poses serious challenges. This report, prepared for the US National Committee on Theoretical and Applied Mechanics, aims to identify the most pressing challenges in biological sciences and medicine that can be tackled within the broad field of mechanics. This echoes and complements a number of national and international initiatives aiming at fostering interdisciplinary biomedical research. This report also comments on cultural/educational challenges. Specifically, this report focuses on three major thrusts in which we believe mechanics has and will continue to have a substantial impact. (i) Rationally engineering injectable nano/microdevices for imaging and therapy of disease. Within this context, we discuss nanoparticle carrier design, vascular transport and adhesion, endocytosis and tumour growth in response to therapy, as well as uncertainty quantification techniques to better connect models and experiments. (ii) Design of biomedical devices, including point-of-care diagnostic systems, model organ and multi-organ microdevices, and pulsatile ventricular assistant devices. (iii) Mechanics of cellular processes, including mechanosensing and mechanotransduction, improved characterization of cellular constitutive behaviour, and microfluidic systems for single-cell studies. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Multimodal quantitative phase and fluorescence imaging of cell apoptosis

NASA Astrophysics Data System (ADS)

Fu, Xinye; Zuo, Chao; Yan, Hao

2017-06-01

Fluorescence microscopy, utilizing fluorescence labeling, has the capability to observe intercellular changes which transmitted and reflected light microscopy techniques cannot resolve. However, the parts without fluorescence labeling are not imaged. Hence, the processes simultaneously happen in these parts cannot be revealed. Meanwhile, fluorescence imaging is 2D imaging where information in the depth is missing. Therefore the information in labeling parts is also not complete. On the other hand, quantitative phase imaging is capable to image cells in 3D in real time through phase calculation. However, its resolution is limited by the optical diffraction and cannot observe intercellular changes below 200 nanometers. In this work, fluorescence imaging and quantitative phase imaging are combined to build a multimodal imaging system. Such system has the capability to simultaneously observe the detailed intercellular phenomenon and 3D cell morphology. In this study the proposed multimodal imaging system is used to observe the cell behavior in the cell apoptosis. The aim is to highlight the limitations of fluorescence microscopy and to point out the advantages of multimodal quantitative phase and fluorescence imaging. The proposed multimodal quantitative phase imaging could be further applied in cell related biomedical research, such as tumor.

77 FR 37684 - National Institute of Biomedical Imaging and Bioengineering; Notice of Closed Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-22

... Imaging and Bioengineering Special Emphasis Panel; Center for Multiscale Simulations in the Human....D., Scientific Review Officer, 6707 Democracy Boulevard, Room 959, Bethesda, MD 20892, 301-451- 3398...

Photoacoustic tomography based on the Green's function retrieval with ultrasound interferometry for sample partially behind an acoustically scattering layer

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

Yin, Jie; Department of Automation, Nanjing Polytechnic Institute, 210048 Nanjing; Tao, Chao, E-mail: taochao@nju.edu.cn

2015-06-08

Acoustically inhomogeneous mediums with multiple scattering are often the nightmare of photoacoustic tomography. In order to break this limitation, a photoacoustic tomography scheme combining ultrasound interferometry and time reversal is proposed to achieve images in acoustically scattering medium. An ultrasound interferometry is developed to determine the unknown Green's function of strong scattering tissue. Using the determined Greens' function, a time-reversal process is carried out to restore images behind an acoustically inhomogeneous layer from the scattering photoacoustic signals. This method effectively decreases the false contrast, noise, and position deviation of images induced by the multiple scattering. Phantom experiment is carried outmore » to validate the method. Therefore, the proposed method could have potential value in extending the biomedical applications of photoacoustic tomography in acoustically inhomogeneous tissue.« less

Introducing anisotropic Minkowski functionals and quantitative anisotropy measures for local structure analysis in biomedical imaging

NASA Astrophysics Data System (ADS)

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2013-03-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.

Introducing Anisotropic Minkowski Functionals and Quantitative Anisotropy Measures for Local Structure Analysis in Biomedical Imaging

PubMed Central

Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

2017-01-01

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10−4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications. PMID:29170580

Fast noninvasive eye-tracking and eye-gaze determination for biomedical and remote monitoring applications

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Morookian, John M.; Monacos, Steve P.; Lam, Raymond K.; Lebaw, C.; Bond, A.

2004-04-01

Eyetracking is one of the latest technologies that has shown potential in several areas including human-computer interaction for people with and without disabilities, and for noninvasive monitoring, detection, and even diagnosis of physiological and neurological problems in individuals. Current non-invasive eyetracking methods achieve a 30 Hz rate with possibly low accuracy in gaze estimation, that is insufficient for many applications. We propose a new non-invasive visual eyetracking system that is capable of operating at speeds as high as 6-12 KHz. A new CCD video camera and hardware architecture is used, and a novel fast image processing algorithm leverages specific features of the input CCD camera to yield a real-time eyetracking system. A field programmable gate array (FPGA) is used to control the CCD camera and execute the image processing operations. Initial results show the excellent performance of our system under severe head motion and low contrast conditions.

Wavelet transform: fundamentals, applications, and implementation using acousto-optic correlators

NASA Astrophysics Data System (ADS)

DeCusatis, Casimer M.; Koay, J.; Litynski, Daniel M.; Das, Pankaj K.

1995-10-01

In recent years there has been a great deal of interest in the use of wavelets to supplement or replace conventional Fourier transform signal processing. This paper provides a review of wavelet transforms for signal processing applications, and discusses several emerging applications which benefit from the advantages of wavelets. The wavelet transform can be implemented as an acousto-optic correlator; perfect reconstruction of digital signals may also be achieved using acousto-optic finite impulse response filter banks. Acousto-optic image correlators are discussed as a potential implementation of the wavelet transform, since a 1D wavelet filter bank may be encoded as a 2D image. We discuss applications of the wavelet transform including nondestructive testing of materials, biomedical applications in the analysis of EEG signals, and interference excision in spread spectrum communication systems. Computer simulations and experimental results for these applications are also provided.

Development of a Germanium Small-Animal SPECT System

NASA Astrophysics Data System (ADS)

Johnson, Lindsay C.; Ovchinnikov, Oleg; Shokouhi, Sepideh; Peterson, Todd E.

2015-10-01

Advances in fabrication techniques, electronics, and mechanical cooling systems have given rise to germanium detectors suitable for biomedical imaging. We are developing a small-animal SPECT system that uses a double-sided Ge strip detector. The detector's excellent energy resolution may help to reduce scatter and simplify processing of multi-isotope imaging, while its ability to measure depth of interaction has the potential to mitigate parallax error in pinhole imaging. The detector's energy resolution is <; 1% FWHM at 140 keV and its spatial resolution is approximately 1.5 mm FWHM. The prototype system described has a single-pinhole collimator with a 1-mm diameter and a 70-degree opening angle with a focal length variable between 4.5 and 9 cm. Phantom images from the gantry-mounted system are presented, including the NEMA NU-2008 phantom and a hot-rod phantom. Additionally, the benefit of energy resolution is demonstrated by imaging a dual-isotope phantom with 99mTc and 123I without cross-talk correction.

Subcellular object quantification with Squassh3C and SquasshAnalyst.

PubMed

Rizk, Aurélien; Mansouri, Maysam; Ballmer-Hofer, Kurt; Berger, Philipp

2015-11-01

Quantitative image analysis plays an important role in contemporary biomedical research. Squassh is a method for automatic detection, segmentation, and quantification of subcellular structures and analysis of their colocalization. Here we present the applications Squassh3C and SquasshAnalyst. Squassh3C extends the functionality of Squassh to three fluorescence channels and live-cell movie analysis. SquasshAnalyst is an interactive web interface for the analysis of Squassh3C object data. It provides segmentation image overview and data exploration, figure generation, object and image filtering, and a statistical significance test in an easy-to-use interface. The overall procedure combines the Squassh3C plug-in for the free biological image processing program ImageJ and a web application working in conjunction with the free statistical environment R, and it is compatible with Linux, MacOS X, or Microsoft Windows. Squassh3C and SquasshAnalyst are available for download at www.psi.ch/lbr/SquasshAnalystEN/SquasshAnalyst.zip.

Rapid development of medical imaging tools with open-source libraries.

PubMed

Caban, Jesus J; Joshi, Alark; Nagy, Paul

2007-11-01

Rapid prototyping is an important element in researching new imaging analysis techniques and developing custom medical applications. In the last ten years, the open source community and the number of open source libraries and freely available frameworks for biomedical research have grown significantly. What they offer are now considered standards in medical image analysis, computer-aided diagnosis, and medical visualization. A cursory review of the peer-reviewed literature in imaging informatics (indeed, in almost any information technology-dependent scientific discipline) indicates the current reliance on open source libraries to accelerate development and validation of processes and techniques. In this survey paper, we review and compare a few of the most successful open source libraries and frameworks for medical application development. Our dual intentions are to provide evidence that these approaches already constitute a vital and essential part of medical image analysis, diagnosis, and visualization and to motivate the reader to use open source libraries and software for rapid prototyping of medical applications and tools.

Bioapplications of graphene constructed functional nanomaterials.

PubMed

Gulzar, Arif; Yang, Piaoping; He, Fei; Xu, Jiating; Yang, Dan; Xu, Liangge; Jan, Mohammad Omar

2017-01-25

Graphene has distinctive mechanical, electronic, and optical properties, which researchers have applied to develop innovative electronic materials including transparent conductors and ultrafast transistors. Lately, the understanding of various chemical properties of graphene has expedited its application in high-performance devices that generate and store energy. Graphene is now increasing its terrain outside electronic and chemical applications toward biomedical areas such as precise bio sensing through graphene-quenched fluorescence, graphene-enhanced cell differentiation and growth, and graphene-assisted laser desorption/ionization for mass spectrometry. In this Account, we evaluate recent efforts to apply graphene and graphene oxides (GO) to biomedical research and a few different approaches to prepare graphene materials designed for biomedical applications and a brief perspective on their future applications. Because of its outstanding aqueous processability, amphiphilicity, surface functionalizability, surface enhanced Raman scattering (SERS), and fluorescence quenching ability, GO chemically exfoliated from oxidized graphite is considered a promising material for biological applications. In addition, the hydrophobicity and flexibility of large-area graphene synthesized by chemical vapor deposition (CVD) allow this material to play an important role in cell growth and differentiation. Graphene is considered to be an encouraging and smart candidate for numerous biomedical applications such as NIR-responsive cancer therapy and fluorescence bio-imaging and drug delivery. To that end, suitable preparation and unique approaches to utilize graphene-based materials such as graphene oxides (GOs), reduced graphene oxides (rGOs), and graphene quantum dots (GQDs) in biology and medical science are gaining growing interest. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Analysis of thirteen predatory publishers: a trap for eager-to-publish researchers.

PubMed

Bolshete, Pravin

2018-01-01

To demonstrate a strategy employed by predatory publishers to trap eager-to-publish authors or researchers into submitting their work. This was a case study of 13 potential, possible, or probable predatory scholarly open-access publishers with similar characteristics. Eleven publishers were included from Beall's list and two additional publishers were identified from a Google web search. Each publisher's site was visited and its content analyzed. Publishers publishing biomedical journals were further explored and additional data was collected regarding their volumes, details of publications and editorial-board members. Overall, the look and feel of all 13 publishers was similar including names of publishers, website addresses, homepage content, homepage images, list of journals and subject areas, as if they were copied and pasted. There were discrepancies in article-processing charges within the publishers. None of the publishers identified names in their contact details and primarily included only email addresses. Author instructions were similar across all 13 publishers. Most publishers listed journals of varied subject areas including biomedical journals (12 publishers) covering different geographic locations. Most biomedical journals published none or very few articles. The highest number of articles published by any single biomedical journal was 28. Several editorial-board members were listed across more than one journals, with one member listed 81 times in different 69 journals (i.e. twice in 12 journals). There was a strong reason to believe that predatory publishers may have several publication houses with different names under a single roof to trap authors from different geographic locations.

Innovations in Nuclear Imaging Instrumentation: Cerenkov Imaging.

PubMed

Tamura, Ryo; Pratt, Edwin C; Grimm, Jan

2018-07-01

Cerenkov luminescence (CL) is blue glow light produced by charged subatomic particles travelling faster than the phase velocity of light in a dielectric medium such as water or tissue. CL was first discovered in 1934, but for biomedical research it was recognized only in 2009 after advances in optical camera sensors brought the required high sensitivity. Recently, applications of CL from clinical radionuclides have been rapidly expanding to include not only preclinical and clinical biomedical imaging but also an approach to therapy. Cerenkov Luminescence Imaging (CLI) utilizes CL generated from clinically relevant radionuclides alongside optical imaging instrumentation. CLI is advantageous over traditional nuclear imaging methods in terms of infrastructure cost, resolution, and imaging time. Furthermore, CLI is a truly multimodal imaging method where the same agent can be detected by two independent modalities, with optical (CL) imaging and with positron emission tomography (PET) imaging. CL has been combined with small molecules, biomolecules and nanoparticles to improve diagnosis and therapy in cancer research. Here, we cover the fundamental breakthroughs and recent advances in reagents and instrumentation methods for CLI as well as therapeutic application of CL. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed

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

2010-05-21

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

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

PubMed

Renganathan, Vinaitheerthan

2017-07-01

With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.

BioSig: The Free and Open Source Software Library for Biomedical Signal Processing

PubMed Central

Vidaurre, Carmen; Sander, Tilmann H.; Schlögl, Alois

2011-01-01

BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems, and sleep research. Moreover, the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), or respiration signals is a very relevant element of the BioSig project. Specifically, BioSig provides solutions for data acquisition, artifact processing, quality control, feature extraction, classification, modeling, and data visualization, to name a few. In this paper, we highlight several methods to help students and researchers to work more efficiently with biomedical signals. PMID:21437227

BioSig: the free and open source software library for biomedical signal processing.

PubMed

Vidaurre, Carmen; Sander, Tilmann H; Schlögl, Alois

2011-01-01

BioSig is an open source software library for biomedical signal processing. The aim of the BioSig project is to foster research in biomedical signal processing by providing free and open source software tools for many different application areas. Some of the areas where BioSig can be employed are neuroinformatics, brain-computer interfaces, neurophysiology, psychology, cardiovascular systems, and sleep research. Moreover, the analysis of biosignals such as the electroencephalogram (EEG), electrocorticogram (ECoG), electrocardiogram (ECG), electrooculogram (EOG), electromyogram (EMG), or respiration signals is a very relevant element of the BioSig project. Specifically, BioSig provides solutions for data acquisition, artifact processing, quality control, feature extraction, classification, modeling, and data visualization, to name a few. In this paper, we highlight several methods to help students and researchers to work more efficiently with biomedical signals.

Blind source separation of ex-vivo aorta tissue multispectral images

PubMed Central

Galeano, July; Perez, Sandra; Montoya, Yonatan; Botina, Deivid; Garzón, Johnson

2015-01-01

Blind Source Separation methods (BSS) aim for the decomposition of a given signal in its main components or source signals. Those techniques have been widely used in the literature for the analysis of biomedical images, in order to extract the main components of an organ or tissue under study. The analysis of skin images for the extraction of melanin and hemoglobin is an example of the use of BSS. This paper presents a proof of concept of the use of source separation of ex-vivo aorta tissue multispectral Images. The images are acquired with an interference filter-based imaging system. The images are processed by means of two algorithms: Independent Components analysis and Non-negative Matrix Factorization. In both cases, it is possible to obtain maps that quantify the concentration of the main chromophores present in aortic tissue. Also, the algorithms allow for spectral absorbance of the main tissue components. Those spectral signatures were compared against the theoretical ones by using correlation coefficients. Those coefficients report values close to 0.9, which is a good estimator of the method’s performance. Also, correlation coefficients lead to the identification of the concentration maps according to the evaluated chromophore. The results suggest that Multi/hyper-spectral systems together with image processing techniques is a potential tool for the analysis of cardiovascular tissue. PMID:26137366

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma.

PubMed

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-07-21

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene's expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment.

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma

PubMed Central

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-01-01

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene’s expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment. PMID:27468205

Metrological reliability of optical coherence tomography in biomedical applications

NASA Astrophysics Data System (ADS)

Goloni, C. M.; Temporão, G. P.; Monteiro, E. C.

2013-09-01

Optical coherence tomography (OCT) has been proving to be an efficient diagnostics technique for imaging in vivo tissues, an optical biopsy with important perspectives as a diagnostic tool for quantitative characterization of tissue structures. Despite its established clinical use, there is no international standard to address the specific requirements for basic safety and essential performance of OCT devices for biomedical imaging. The present work studies the parameters necessary for conformity assessment of optoelectronics equipment used in biomedical applications like Laser, Intense Pulsed Light (IPL), and OCT, targeting to identify the potential requirements to be considered in the case of a future development of a particular standard for OCT equipment. In addition to some of the particular requirements standards for laser and IPL, also applicable for metrological reliability analysis of OCT equipment, specific parameters for OCT's evaluation have been identified, considering its biomedical application. For each parameter identified, its information on the accompanying documents and/or its measurement has been recommended. Among the parameters for which the measurement requirement was recommended, including the uncertainty evaluation, the following are highlighted: optical radiation output, axial and transverse resolution, pulse duration and interval, and beam divergence.

Listening to light scattering in turbid media: quantitative optical scattering imaging using photoacoustic measurements with one-wavelength illumination

NASA Astrophysics Data System (ADS)

Yuan, Zhen; Li, Xiaoqi; Xi, Lei

2014-06-01

Biomedical photoacoustic tomography (PAT), as a potential imaging modality, can visualize tissue structure and function with high spatial resolution and excellent optical contrast. It is widely recognized that the ability of quantitatively imaging optical absorption and scattering coefficients from photoacoustic measurements is essential before PAT can become a powerful imaging modality. Existing quantitative PAT (qPAT), while successful, has been focused on recovering absorption coefficient only by assuming scattering coefficient a constant. An effective method for photoacoustically recovering optical scattering coefficient is presently not available. Here we propose and experimentally validate such a method for quantitative scattering coefficient imaging using photoacoustic data from one-wavelength illumination. The reconstruction method developed combines conventional PAT with the photon diffusion equation in a novel way to realize the recovery of scattering coefficient. We demonstrate the method using various objects having scattering contrast only or both absorption and scattering contrasts embedded in turbid media. The listening-to-light-scattering method described will be able to provide high resolution scattering imaging for various biomedical applications ranging from breast to brain imaging.

A high performance biometric signal and image processing method to reveal blood perfusion towards 3D oxygen saturation mapping

NASA Astrophysics Data System (ADS)

Imms, Ryan; Hu, Sijung; Azorin-Peris, Vicente; Trico, Michaël.; Summers, Ron

2014-03-01

Non-contact imaging photoplethysmography (PPG) is a recent development in the field of physiological data acquisition, currently undergoing a large amount of research to characterize and define the range of its capabilities. Contact-based PPG techniques have been broadly used in clinical scenarios for a number of years to obtain direct information about the degree of oxygen saturation for patients. With the advent of imaging techniques, there is strong potential to enable access to additional information such as multi-dimensional blood perfusion and saturation mapping. The further development of effective opto-physiological monitoring techniques is dependent upon novel modelling techniques coupled with improved sensor design and effective signal processing methodologies. The biometric signal and imaging processing platform (bSIPP) provides a comprehensive set of features for extraction and analysis of recorded iPPG data, enabling direct comparison with other biomedical diagnostic tools such as ECG and EEG. Additionally, utilizing information about the nature of tissue structure has enabled the generation of an engineering model describing the behaviour of light during its travel through the biological tissue. This enables the estimation of the relative oxygen saturation and blood perfusion in different layers of the tissue to be calculated, which has the potential to be a useful diagnostic tool.

Web-based document image processing

NASA Astrophysics Data System (ADS)

Walker, Frank L.; Thoma, George R.

1999-12-01

Increasing numbers of research libraries are turning to the Internet for electron interlibrary loan and for document delivery to patrons. This has been made possible through the widespread adoption of software such as Ariel and DocView. Ariel, a product of the Research Libraries Group, converts paper-based documents to monochrome bitmapped images, and delivers them over the Internet. The National Library of Medicine's DocView is primarily designed for library patrons are beginning to reap the benefits of this new technology, barriers exist, e.g., differences in image file format, that lead to difficulties in the use of library document information. To research how to overcome such barriers, the Communications Engineering Branch of the Lister Hill National Center for Biomedical Communications, an R and D division of NLM, has developed a web site called the DocMorph Server. This is part of an ongoing intramural R and D program in document imaging that has spanned many aspects of electronic document conversion and preservation, Internet document transmission and document usage. The DocMorph Server Web site is designed to fill two roles. First, in a role that will benefit both libraries and their patrons, it allows Internet users to upload scanned image files for conversion to alternative formats, thereby enabling wider delivery and easier usage of library document information. Second, the DocMorph Server provides the design team an active test bed for evaluating the effectiveness and utility of new document image processing algorithms and functions, so that they may be evaluated for possible inclusion in other image processing software products being developed at NLM or elsewhere. This paper describes the design of the prototype DocMorph Server and the image processing functions being implemented on it.

Eventogram: A Visual Representation of Main Events in Biomedical Signals.

PubMed

Elgendi, Mohamed

2016-09-22

Biomedical signals carry valuable physiological information and many researchers have difficulty interpreting and analyzing long-term, one-dimensional, quasi-periodic biomedical signals. Traditionally, biomedical signals are analyzed and visualized using periodogram, spectrogram, and wavelet methods. However, these methods do not offer an informative visualization of main events within the processed signal. This paper attempts to provide an event-related framework to overcome the drawbacks of the traditional visualization methods and describe the main events within the biomedical signal in terms of duration and morphology. Electrocardiogram and photoplethysmogram signals are used in the analysis to demonstrate the differences between the traditional visualization methods, and their performance is compared against the proposed method, referred to as the " eventogram " in this paper. The proposed method is based on two event-related moving averages that visualizes the main time-domain events in the processed biomedical signals. The traditional visualization methods were unable to find dominant events in processed signals while the eventogram was able to visualize dominant events in signals in terms of duration and morphology. Moreover, eventogram -based detection algorithms succeeded with detecting main events in different biomedical signals with a sensitivity and positive predictivity >95%. The output of the eventogram captured unique patterns and signatures of physiological events, which could be used to visualize and identify abnormal waveforms in any quasi-periodic signal.

Imaging Strategies for Tissue Engineering Applications

PubMed Central

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

2015-01-01

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

Nanoparticle-facilitated functional and molecular imaging for the early detection of cancer

PubMed Central

Sivasubramanian, Maharajan; Hsia, Yu; Lo, Leu-Wei

2014-01-01

Cancer detection in its early stages is imperative for effective cancer treatment and patient survival. In recent years, biomedical imaging techniques, such as magnetic resonance imaging, computed tomography and ultrasound have been greatly developed and have served pivotal roles in clinical cancer management. Molecular imaging (MI) is a non-invasive imaging technique that monitors biological processes at the cellular and sub-cellular levels. To achieve these goals, MI uses targeted imaging agents that can bind targets of interest with high specificity and report on associated abnormalities, a task that cannot be performed by conventional imaging techniques. In this respect, MI holds great promise as a potential therapeutic tool for the early diagnosis of cancer. Nevertheless, the clinical applications of targeted imaging agents are limited due to their inability to overcome biological barriers inside the body. The use of nanoparticles has made it possible to overcome these limitations. Hence, nanoparticles have been the subject of a great deal of recent studies. Therefore, developing nanoparticle-based imaging agents that can target tumors via active or passive targeting mechanisms is desirable. This review focuses on the applications of various functionalized nanoparticle-based imaging agents used in MI for the early detection of cancer. PMID:25988156

CW laser use in biomedical research and practice

NASA Astrophysics Data System (ADS)

Matthopoulos, D. P.

2003-04-01

The communication of humans with their surrouding is achieved through their senses and the related organs. Visual communication using the eyes is made possible because the various sources of light, natural i.e. the sun or the lightning, or artificial such as Lasers, emit electromagnetic radiation which is either reflected or scattered by surfaces. This radiation received by eyes is processed in the brain where the images of the environment are developed. The luminous processing can be either macro- or microscopic. The macroscopic processing is the result of light coming from the sun or from wide range lamps, while the microscopic results from light coming from wide range lamps, mercury lamps, lasers or electron beam. The microscopic processing is the subject we are dealing with in this presentation.

Polysaccharide Nanosystems for Future Progress in Cardiovascular Pathologies

PubMed Central

Silva, Amanda Karine Andriola; Letourneur, Didier; Chauvierre, Cédric

2014-01-01

Natural polysaccharides have received a lot of attention in the biomedical field. Indeed, sources of polysaccharides, extracted or produced from plants, bacteria, fungi or algae, are diverse and renewable. Moreover, recent progresses in polysaccharide chemistry and nanotechnologies allow elaborating new dedicated nanosystems. Polysaccharide-based nanosystems may be designed for interacting in several biological processes. In particular, the atherothrombotic pathology is highly concerned by polysaccharide-mediated recognition. Atherothrombotic diseases, regardless of the anatomical localization, remain the main causes of morbidity and mortality in the industrialized world. This review intends to provide an overview on polysaccharide-based nanosystems as drug delivery systems and targeted contrast agents for molecular imaging with an emphasis on the treatment and imaging of cardiovascular pathologies. PMID:24723980

Compact Microscope Imaging System With Intelligent Controls Improved

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

The Compact Microscope Imaging System (CMIS) with intelligent controls is a diagnostic microscope analysis tool with intelligent controls for use in space, industrial, medical, and security applications. This compact miniature microscope, which can perform tasks usually reserved for conventional microscopes, has unique advantages in the fields of microscopy, biomedical research, inline process inspection, and space science. Its unique approach integrates a machine vision technique with an instrumentation and control technique that provides intelligence via the use of adaptive neural networks. The CMIS system was developed at the NASA Glenn Research Center specifically for interface detection used for colloid hard spheres experiments; biological cell detection for patch clamping, cell movement, and tracking; and detection of anode and cathode defects for laboratory samples using microscope technology.

Biostatistical analysis of quantitative immunofluorescence microscopy images.

PubMed

Giles, C; Albrecht, M A; Lam, V; Takechi, R; Mamo, J C

2016-12-01

Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Imaging Mass Spectrometry in Neuroscience

PubMed Central

2013-01-01

Imaging mass spectrometry is an emerging technique of great potential for investigating the chemical architecture in biological matrices. Although the potential for studying neurobiological systems is evident, the relevance of the technique for application in neuroscience is still in its infancy. In the present Review, a principal overview of the different approaches, including matrix assisted laser desorption ionization and secondary ion mass spectrometry, is provided with particular focus on their strengths and limitations for studying different neurochemical species in situ and in vitro. The potential of the various approaches is discussed based on both fundamental and biomedical neuroscience research. This Review aims to serve as a general guide to familiarize the neuroscience community and other biomedical researchers with the technique, highlighting its great potential and suitability for comprehensive and specific chemical imaging. PMID:23530951

Piezoelectric single crystals for ultrasonic transducers in biomedical applications

PubMed Central

Zhou, Qifa; Lam, Kwok Ho; Zheng, Hairong; Qiu, Weibao; Shung, K. Kirk

2014-01-01

Piezoelectric single crystals, which have excellent piezoelectric properties, have extensively been employed for various sensors and actuators applications. In this paper, the state–of–art in piezoelectric single crystals for ultrasonic transducer applications is reviewed. Firstly, the basic principles and design considerations of piezoelectric ultrasonic transducers will be addressed. Then, the popular piezoelectric single crystals used for ultrasonic transducer applications, including LiNbO3 (LN), PMN–PT and PIN–PMN–PT, will be introduced. After describing the preparation and performance of the single crystals, the recent development of both the single–element and array transducers fabricated using the single crystals will be presented. Finally, various biomedical applications including eye imaging, intravascular imaging, blood flow measurement, photoacoustic imaging, and microbeam applications of the single crystal transducers will be discussed. PMID:25386032

Elemental and isotopic imaging of biological samples using NanoSIMS.

PubMed

Kilburn, Matt R; Clode, Peta L

2014-01-01

With its low detection limits and the ability to analyze most of the elements in the periodic table, secondary ion mass spectrometry (SIMS) represents one of the most versatile in situ analytical techniques available, and recent developments have resulted in significant advantages for the use of imaging mass spectrometry in biological and biomedical research. Increases in spatial resolution and sensitivity allow detailed interrogation of samples at relevant scales and chemical concentrations. Advances in dynamic SIMS, specifically with the advent of NanoSIMS, now allow the tracking of stable isotopes within biological systems at subcellular length scales, while static SIMS combines subcellular imaging with molecular identification. In this chapter, we present an introduction to the SIMS technique, with particular reference to NanoSIMS, and discuss its application in biological and biomedical research.

Nanoparticles speckled by ready-to-conjugate lanthanide complexes for multimodal imaging

NASA Astrophysics Data System (ADS)

Biju, Vasudevanpillai; Hamada, Morihiko; Ono, Kenji; Sugino, Sakiko; Ohnishi, Takashi; Shibu, Edakkattuparambil Sidharth; Yamamura, Shohei; Sawada, Makoto; Nakanishi, Shunsuke; Shigeri, Yasushi; Wakida, Shin-Ichi

2015-09-01

Multimodal and multifunctional contrast agents receive enormous attention in the biomedical imaging field. Such contrast agents are routinely prepared by the incorporation of organic molecules and inorganic nanoparticles (NPs) into host materials such as gold NPs, silica NPs, polymer NPs, and liposomes. Despite their non-cytotoxic nature, the large size of these NPs limits the in vivo distribution and clearance and inflames complex pharmacokinetics, which hinder the regulatory approval for clinical applications. Herein, we report a unique method that combines magnetic resonance imaging (MRI) and fluorescence imaging modalities together in nanoscale entities by the simple, direct and stable conjugation of novel biotinylated coordination complexes of gadolinium(iii) to CdSe/ZnS quantum dots (QD) and terbium(iii) to super paramagnetic iron oxide NPs (SPION) but without any host material. Subsequently, we evaluate the potentials of such lanthanide-speckled fluorescent-magnetic NPs for bioimaging at single-molecule, cell and in vivo levels. The simple preparation and small size make such fluorescent-magnetic NPs promising contrast agents for biomedical imaging.

Informatics in radiology: An open-source and open-access cancer biomedical informatics grid annotation and image markup template builder.

PubMed

Mongkolwat, Pattanasak; Channin, David S; Kleper, Vladimir; Rubin, Daniel L

2012-01-01

In a routine clinical environment or clinical trial, a case report form or structured reporting template can be used to quickly generate uniform and consistent reports. Annotation and image markup (AIM), a project supported by the National Cancer Institute's cancer biomedical informatics grid, can be used to collect information for a case report form or structured reporting template. AIM is designed to store, in a single information source, (a) the description of pixel data with use of markups or graphical drawings placed on the image, (b) calculation results (which may or may not be directly related to the markups), and (c) supplemental information. To facilitate the creation of AIM annotations with data entry templates, an AIM template schema and an open-source template creation application were developed to assist clinicians, image researchers, and designers of clinical trials to quickly create a set of data collection items, thereby ultimately making image information more readily accessible.

Informatics in Radiology: An Open-Source and Open-Access Cancer Biomedical Informatics Grid Annotation and Image Markup Template Builder

PubMed Central

Channin, David S.; Rubin, Vladimir Kleper Daniel L.

2012-01-01

In a routine clinical environment or clinical trial, a case report form or structured reporting template can be used to quickly generate uniform and consistent reports. Annotation and Image Markup (AIM), a project supported by the National Cancer Institute’s cancer Biomedical Informatics Grid, can be used to collect information for a case report form or structured reporting template. AIM is designed to store, in a single information source, (a) the description of pixel data with use of markups or graphical drawings placed on the image, (b) calculation results (which may or may not be directly related to the markups), and (c) supplemental information. To facilitate the creation of AIM annotations with data entry templates, an AIM template schema and an open-source template creation application were developed to assist clinicians, image researchers, and designers of clinical trials to quickly create a set of data collection items, thereby ultimately making image information more readily accessible. © RSNA, 2012 PMID:22556315

Design and development of a simple UV fluorescence multi-spectral imaging system

NASA Astrophysics Data System (ADS)

Tovar, Carlos; Coker, Zachary; Yakovlev, Vladislav V.

2018-02-01

Healthcare access in low-resource settings is compromised by the availability of affordable and accurate diagnostic equipment. The four primary poverty-related diseases - AIDS, pneumonia, malaria, and tuberculosis - account for approximately 400 million annual deaths worldwide as of 2016 estimates. Current diagnostic procedures for these diseases are prolonged and can become unreliable under various conditions. We present the development of a simple low-cost UV fluorescence multi-spectral imaging system geared towards low resource settings for a variety of biological and in-vitro applications. Fluorescence microscopy serves as a useful diagnostic indicator and imaging tool. The addition of a multi-spectral imaging modality allows for the detection of fluorophores within specific wavelength bands, as well as the distinction between fluorophores possessing overlapping spectra. The developed instrument has the potential for a very diverse range of diagnostic applications in basic biomedical science and biomedical diagnostics and imaging. Performance assessment of the microscope will be validated with a variety of samples ranging from organic compounds to biological samples.

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Biomimetic synthesis of highly biocompatible gold nanoparticles with amino acid-dithiocarbamate as a precursor for SERS imaging

NASA Astrophysics Data System (ADS)

Li, Li; Liu, Jianbo; Yang, Xiaohai; Huang, Jin; He, Dinggeng; Guo, Xi; Wan, Lan; He, Xiaoxiao; Wang, Kemin

2016-03-01

Amino acid-dithiocarbamate (amino acid-DTC) was developed as both the reductant and ligand stabilizer for biomimetic synthesis of gold nanoparticles (AuNPs), which served as an excellent surface-enhanced Raman scattering (SERS) contrast nanoprobe for cell imaging. Glycine (Gly), glutamic acid (Glu), and histidine (His) with different isoelectric points were chosen as representative amino acid candidates to synthesize corresponding amino acid-DTC compounds through mixing with carbon disulfide (CS2), respectively. The pyrogenic decomposition of amino acid-DTC initiated the reduction synthesis of AuNPs, and the strong coordinating dithiocarbamate group of amino acid-DTC served as a stabilizer that grafted onto the surface of the AuNPs, which rendered the as-prepared nanoparticles a negative surface charge and high colloidal stability. MTT cell viability assay demonstrated that the biomimetic AuNPs possessed neglectful toxicity to the human hepatoma cell, which guaranteed them good biocompatibility for biomedical application. Meanwhile, the biomimetic AuNPs showed a strong SERS effect with an enhancement factor of 9.8 × 105 for the sensing of Rhodamine 6G, and two distinct Raman peaks located at 1363 and 1509 cm-1 could be clearly observed in the cell-imaging experiments. Therefore, biomimetic AuNPs can be explored as an excellent SERS contrast nanoprobe for biomedical imaging, and the amino acid-DTC mediated synthesis of the AuNPs has a great potential in bio-engineering and biomedical imaging applications.

Conformal image-guided microbeam radiation therapy at the ESRF biomedical beamline ID17

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

Donzelli, Mattia, E-mail: donzelli@esrf.fr; Bräuer-Krisch, Elke; Nemoz, Christian

Purpose: Upcoming veterinary trials in microbeam radiation therapy (MRT) demand for more advanced irradiation techniques than in preclinical research with small animals. The treatment of deep-seated tumors in cats and dogs with MRT requires sophisticated irradiation geometries from multiple ports, which impose further efforts to spare the normal tissue surrounding the target. Methods: This work presents the development and benchmarking of a precise patient alignment protocol for MRT at the biomedical beamline ID17 of the European Synchrotron Radiation Facility (ESRF). The positioning of the patient prior to irradiation is verified by taking x-ray projection images from different angles. Results: Usingmore » four external fiducial markers of 1.7  mm diameter and computed tomography-based treatment planning, a target alignment error of less than 2  mm can be achieved with an angular deviation of less than 2{sup ∘}. Minor improvements on the protocol and the use of smaller markers indicate that even a precision better than 1  mm is technically feasible. Detailed investigations concerning the imaging dose lead to the conclusion that doses for skull radiographs lie in the same range as dose reference levels for human head radiographs. A currently used online dose monitor for MRT has been proven to give reliable results for the imaging beam. Conclusions: The ESRF biomedical beamline ID17 is technically ready to apply conformal image-guided MRT from multiple ports to large animals during future veterinary trials.« less

Rising Expectations: Access to Biomedical Information

PubMed Central

Lindberg, D. A. B.; Humphreys, B. L.

2008-01-01

Summary Objective To provide an overview of the expansion in public access to electronic biomedical information over the past two decades, with an emphasis on developments to which the U.S. National Library of Medicine contributed. Methods Review of the increasingly broad spectrum of web-accessible genomic data, biomedical literature, consumer health information, clinical trials data, and images. Results The amount of publicly available electronic biomedical information has increased dramatically over the past twenty years. Rising expectations regarding access to biomedical information were stimulated by the spread of the Internet, the World Wide Web, advanced searching and linking techniques. These informatics advances simplified and improved access to electronic information and reduced costs, which enabled inter-organizational collaborations to build and maintain large international information resources and also aided outreach and education efforts The demonstrated benefits of free access to electronic biomedical information encouraged the development of public policies that further increase the amount of information available. Conclusions Continuing rapid growth of publicly accessible electronic biomedical information presents tremendous opportunities and challenges, including the need to ensure uninterrupted access during disasters or emergencies and to manage digital resources so they remain available for future generations. PMID:18587496

Elucidation of the mechanisms of optical clearing in collagen tissue with multiphoton imaging

NASA Astrophysics Data System (ADS)

Hovhannisyan, Vladimir; Hu, Po-Sheng; Chen, Shean-Jen; Kim, Chang-Seok; Dong, Chen-Yuan

2013-04-01

Optical clearing (OC) is a promising method to overcome limitations in biomedical depth-resolved optical studies. Mechanisms of OC in purified bovine Achilles tendon, chicken skin, and chicken tendon were studied using time-lapsed, three-dimensional second harmonic generation (SHG) and two-photon fluorescence microscopic imaging. Quantified nonlinear optical measurements allowed temporal separation of two processes in collagen OC with glycerol. The first one is a fast process of tissue dehydration accompanied with collagen shrinkage and the second relatively slow process is glycerol penetration into the interfibrillar space of collagen alongside with CF swelling. The use of 50% glycerol induced less-expressed OC via partial substitution of water molecules with glycerol molecules. We also found that phosphate-buffered saline- and glycerol-treatments were reversible, and fiber morphology and SHG signal intensity were recovered after the removal of immersion agents. It was shown that tissue OC was a dynamic process and elucidation of its physical mechanisms may help choose optimal diagnostic, treatment, and modification regimes for collagen-based as well as other types of biomaterials.

Performance and scalability of Fourier domain optical coherence tomography acceleration using graphics processing units.

PubMed

Li, Jian; Bloch, Pavel; Xu, Jing; Sarunic, Marinko V; Shannon, Lesley

2011-05-01

Fourier domain optical coherence tomography (FD-OCT) provides faster line rates, better resolution, and higher sensitivity for noninvasive, in vivo biomedical imaging compared to traditional time domain OCT (TD-OCT). However, because the signal processing for FD-OCT is computationally intensive, real-time FD-OCT applications demand powerful computing platforms to deliver acceptable performance. Graphics processing units (GPUs) have been used as coprocessors to accelerate FD-OCT by leveraging their relatively simple programming model to exploit thread-level parallelism. Unfortunately, GPUs do not "share" memory with their host processors, requiring additional data transfers between the GPU and CPU. In this paper, we implement a complete FD-OCT accelerator on a consumer grade GPU/CPU platform. Our data acquisition system uses spectrometer-based detection and a dual-arm interferometer topology with numerical dispersion compensation for retinal imaging. We demonstrate that the maximum line rate is dictated by the memory transfer time and not the processing time due to the GPU platform's memory model. Finally, we discuss how the performance trends of GPU-based accelerators compare to the expected future requirements of FD-OCT data rates.

Biomedical Nanomagnetics: A Spin Through Possibilities in Imaging, Diagnostics, and Therapy

PubMed Central

Krishnan, Kannan M.

2010-01-01

Biomedical nanomagnetics is a multidisciplinary area of research in science, engineering and medicine with broad applications in imaging, diagnostics and therapy. Recent developments offer exciting possibilities in personalized medicine provided a truly integrated approach, combining chemistry, materials science, physics, engineering, biology and medicine, is implemented. Emphasizing this perspective, here we address important issues for the rapid development of the field, i.e., magnetic behavior at the nanoscale with emphasis on the relaxation dynamics, synthesis and surface functionalization of nanoparticles and core-shell structures, biocompatibility and toxicity studies, biological constraints and opportunities, and in vivo and in vitro applications. Specifically, we discuss targeted drug delivery and triggered release, novel contrast agents for magnetic resonance imaging, cancer therapy using magnetic fluid hyperthermia, in vitro diagnostics and the emerging magnetic particle imaging technique, that is quantitative and sensitive enough to compete with established imaging methods. In addition, the physics of self-assembly, which is fundamental to both biology and the future development of nanoscience, is illustrated with magnetic nanoparticles. It is shown that various competing energies associated with self-assembly converge on the nanometer length scale and different assemblies can be tailored by varying particle size and size distribution. Throughout this paper, while we discuss our recent research in the broad context of the multidisciplinary literature, we hope to bridge the gap between related work in physics/chemistry/engineering and biology/medicine and, at the same time, present the essential concepts in the individual disciplines. This approach is essential as biomedical nanomagnetics moves into the next phase of innovative translational research with emphasis on development of quantitative in vivo imaging, targeted and triggered drug release, and image guided therapy including validation of delivery and therapy response. PMID:20930943

Text Mining in Biomedical Domain with Emphasis on Document Clustering

PubMed Central

2017-01-01

Objectives With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. Methods This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Results Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Conclusions Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise. PMID:28875048

Development of a combined microSPECT/CT system for small animal imaging

NASA Astrophysics Data System (ADS)

Sun, Mingshan

Modern advances in the biomedical sciences have placed increased attention on small animals such as mice and rats as models of human biology and disease in biological research and pharmaceutical development. Their small size and fast breeding rate, their physiologic similarity to human, and, more importantly, the availability of sophisticated genetic manipulations, all have made mice and rats the laboratory mammals of choice in these experimental studies. However, the increased use of small animals in biomedical research also calls for new instruments that can measure the anatomic and metabolic information noninvasively with adequate spatial resolution and measurement sensitivity to facilitate these studies. This dissertation describes the engineering development of a combined single photon emission computed tomography (SPECT) and X-ray computed tomography (CT) system dedicated for small animals imaging. The system aims to obtain both the anatomic and metabolic images with submillimeter spatial resolution in a way that the data can be correlated to provide improved image quality and to offer more complete biological evaluation for biomedical studies involving small animals. The project requires development of complete microSPECT and microCT subsystems. Both subsystems are configured with a shared gantry and animal bed with integrated instrumentation for data acquisition and system control. The microCT employs a microfocus X-ray tube and a CCD-based detector for low noise, high resolution imaging. The microSPECT utilizes three semiconductor detectors coupled with pinhole collimators. A significant contribution of this dissertation project is the development of iterative algorithms with geometrical compensation that allows radionuclide images to be reconstructed at submillimeter spatial resolution, but with significantly higher detection efficiency than conventional methods. Both subsystems are capable of helical scans, offering lengthened field of view and improved axial resolution. System performance of both modalities is characterized with phantoms and animals. The microSPECT shows 0.6 mm resolution and 60 cps/MBq detection efficiency for imaging mice with 0.5 mm pinholes. The microCT achieves 120 mum spatial resolution on detector but with a relatively low detective quantum efficiency of 0.2 at the zero frequency. The combined system demonstrates a flexible platform for instrumentation development and a valuable tool for biomedical research. In summary, this dissertation describes the development of a combined SPECT/CT system for imaging the physiological function and anatomical structure in small animals.

Near-infrared fluorescence imaging with a mobile phone (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ghassemi, Pejhman; Wang, Bohan; Wang, Jianting; Wang, Quanzeng; Chen, Yu; Pfefer, T. Joshua

2017-03-01

Mobile phone cameras employ sensors with near-infrared (NIR) sensitivity, yet this capability has not been exploited for biomedical purposes. Removing the IR-blocking filter from a phone-based camera opens the door to a wide range of techniques and applications for inexpensive, point-of-care biophotonic imaging and sensing. This study provides proof of principle for one of these modalities - phone-based NIR fluorescence imaging. An imaging system was assembled using a 780 nm light source along with excitation and emission filters with 800 nm and 825 nm cut-off wavelengths, respectively. Indocyanine green (ICG) was used as an NIR fluorescence contrast agent in an ex vivo rodent model, a resolution test target and a 3D-printed, tissue-simulating vascular phantom. Raw and processed images for red, green and blue pixel channels were analyzed for quantitative evaluation of fundamental performance characteristics including spectral sensitivity, detection linearity and spatial resolution. Mobile phone results were compared with a scientific CCD. The spatial resolution of CCD system was consistently superior to the phone, and green phone camera pixels showed better resolution than blue or green channels. The CCD exhibited similar sensitivity as processed red and blue pixels channels, yet a greater degree of detection linearity. Raw phone pixel data showed lower sensitivity but greater linearity than processed data. Overall, both qualitative and quantitative results provided strong evidence of the potential of phone-based NIR imaging, which may lead to a wide range of applications from cancer detection to glucose sensing.

The Value of Clinical Needs Assessments for Point-of-Care Diagnostics

PubMed Central

Weigl, Bernhard H.; Gaydos, Charlotte A.; Kost, Gerald; Beyette, Fred R.; Sabourin, Stephanie; Rompalo, Anne; de los Santos, Tala; McMullan, Jason T.; Haller, John

2013-01-01

Most entrepreneurial ventures fail long before the core technology can be brought to the marketplace because of disconnects in performance and usability measures such as accuracy, cost, complexity, assay stability, and time requirements between technology developers’ specifications and needs of the end-users. By going through a clinical needs assessment (CNA) process, developers will gain vital information and a clear focus that will help minimize the risks associated with the development of new technologies available for use within the health care system. This article summarizes best practices of the principal investigators of the National Institute of Biomedical Imaging and Bioengineering point-of-care (POC) centers within the National Institute of Biomedical Imaging and Bioengineering POC Technologies Research Network. Clinical needs assessments are particularly important for product development areas that do not sufficiently benefit from traditional market research, such as grant-funded research and development, new product lines using cutting-edge technologies developed in start-up companies, and products developed through product development partnerships for low-resource settings. The objectives of this article were to (1) highlight the importance of CNAs for development of POC devices, (2) discuss methods applied by POC Technologies Research Network for assessing clinical needs, and (3) provide a road map for future CNAs. PMID:23935405

Case-based statistical learning applied to SPECT image classification

NASA Astrophysics Data System (ADS)

Górriz, Juan M.; Ramírez, Javier; Illán, I. A.; Martínez-Murcia, Francisco J.; Segovia, Fermín.; Salas-Gonzalez, Diego; Ortiz, A.

2017-03-01

Statistical learning and decision theory play a key role in many areas of science and engineering. Some examples include time series regression and prediction, optical character recognition, signal detection in communications or biomedical applications for diagnosis and prognosis. This paper deals with the topic of learning from biomedical image data in the classification problem. In a typical scenario we have a training set that is employed to fit a prediction model or learner and a testing set on which the learner is applied to in order to predict the outcome for new unseen patterns. Both processes are usually completely separated to avoid over-fitting and due to the fact that, in practice, the unseen new objects (testing set) have unknown outcomes. However, the outcome yields one of a discrete set of values, i.e. the binary diagnosis problem. Thus, assumptions on these outcome values could be established to obtain the most likely prediction model at the training stage, that could improve the overall classification accuracy on the testing set, or keep its performance at least at the level of the selected statistical classifier. In this sense, a novel case-based learning (c-learning) procedure is proposed which combines hypothesis testing from a discrete set of expected outcomes and a cross-validated classification stage.

Structural and Functional Biomedical Imaging Using Polarization-Based Optical Coherence Tomography

NASA Astrophysics Data System (ADS)

Black, Adam J.

Biomedical imaging has had an enormous impact in medicine and research. There are numerous imaging modalities covering a large range of spatial and temporal scales, penetration depths, along with indicators for function and disease. As these imaging technologies mature, the quality of the images they produce increases to resolve finer details with greater contrast at higher speeds which aids in a faster, more accurate diagnosis in the clinic. In this dissertation, polarization-based optical coherence tomography (OCT) systems are used and developed to image biological structure and function with greater speeds, signal-to-noise (SNR) and stability. OCT can image with spatial and temporal resolutions in the micro range. When imaging any sample, feedback is very important to verify the fidelity and desired location on the sample being imaged. To increase frame rates for display as well as data throughput, field-programmable gate arrays (FPGAs) were used with custom algorithms to realize real-time display and streaming output for continuous acquisition of large datasets of swept-source OCT systems. For spectral domain (SD) OCT systems, significant increases in signal-to-noise ratios were achieved from a custom balanced detection (BD) OCT system. The BD system doubled measured signals while reducing common term. For functional imaging, a real-time directed scanner was introduced to visualize the 3D image of a sample to identify regions of interest prior to recording. Elucidating the characteristics of functional OCT signals with the aid of simulations, novel processing methods were also developed to stabilize samples being imaged and identify possible origins of functional signals being measured. Polarization-sensitive OCT was used to image cardiac tissue before and after clearing to identify the regions of vascular perfusion from a coronary artery. The resulting 3D image provides a visualization of the perfusion boundaries for the tissue that would be damaged from a myocardial infarction to possibly identity features that lead to fatal cardiac arrhythmias. 3D functional imaging was used to measure functional retinal activity from a light stimulus. In some cases, single trial responses were possible; measured at the outer segment of the photoreceptor layer. The morphology and time-course of these signals are similar to the intrinsic optical signals reported from phototransduction. Assessing function in the retina could aid in early detection of degenerative diseases of the retina, such as glaucoma and macular degeneration.

Low Cost, High-Throughput 3D Pulmonary Imager Using Hyperpolarized Contrast Agents and Low Field MRI

DTIC Science & Technology

2016-10-01

HAS THE PROJECT PROVIDED? ..... 7 HOW WERE THE RESULTS DISSEMINATED TO COMMUNITIES OF INTEREST? ................................................. 8...the results disseminated to communities of interest? Nothing to Report 4. IMPACT What was the impact on the development of the principal...the broader biomedical community , expanding the utility of HP methods as a new tool for probing fundamental biomedical questions. Acknowledgments The

Visually representing reality: aesthetics and accessibility aspects

NASA Astrophysics Data System (ADS)

van Nes, Floris L.

2009-02-01

This paper gives an overview of the visual representation of reality with three imaging technologies: painting, photography and electronic imaging. The contribution of the important image aspects, called dimensions hereafter, such as color, fine detail and total image size, to the degree of reality and aesthetic value of the rendered image are described for each of these technologies. Whereas quite a few of these dimensions - or approximations, or even only suggestions thereof - were already present in prehistoric paintings, apparent motion and true stereoscopic vision only recently were added - unfortunately also introducing accessibility and image safety issues. Efforts are made to reduce the incidence of undesirable biomedical effects such as photosensitive seizures (PSS), visually induced motion sickness (VIMS), and visual fatigue from stereoscopic images (VFSI) by international standardization of the image parameters to be avoided by image providers and display manufacturers. The history of this type of standardization, from an International Workshop Agreement to a strategy for accomplishing effective international standardization by ISO, is treated at some length. One of the difficulties to be mastered in this process is the reconciliation of the, sometimes opposing, interests of vulnerable persons, thrill-seeking viewers, creative video designers and the game industry.

Biologically Relevant Heterogeneity: Metrics and Practical Insights

PubMed Central

Gough, A; Stern, AM; Maier, J; Lezon, T; Shun, T-Y; Chennubhotla, C; Schurdak, ME; Haney, SA; Taylor, DL

2017-01-01

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications including basic biomedical research, drug discovery, diagnostics and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell level data, as well as the need for standard metrics of the spatial, temporal and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics and the design of optimal therapeutic strategies for individual patients. PMID:28231035

Aptamers: multifunctional molecules for biomedical research.

PubMed

Banerjee, Jayeeta; Nilsen-Hamilton, Marit

2013-12-01

Aptamers are single-stranded oligonucleotides that fold into well-defined three-dimensional shapes, allowing them to bind their targets with high affinity and specificity. They can be generated through an in vitro process called "Systemic Evolution of Ligands by Exponential Enrichment" and applied for specific detection, inhibition, and characterization of various targets like small organic and inorganic molecules, proteins, and whole cells. Aptamers have also been called chemical antibodies because of their synthetic origin and their similar modes of action to antibodies. They exhibit significant advantages over antibodies in terms of their small size, synthetic accessibility, and ability to be chemically modified and thus endowed with new properties. The first generation of aptamer drug "Macugen" was available for public use within 25 years of the discovery of aptamers. With others in the pipeline for clinical trials, this emerging field of medical biotechnology is raising significant interest. However, aptamers pose different problems for their development than for antibodies that need to be addressed to achieve practical applications. It is likely that current developments in aptamer engineering will be the basis for the evolution of improved future bioanalytical and biomedical applications. The present review discusses the development of aptamers for therapeutics, drug delivery, target validation and imaging, and reviews some of the challenges to fully realizing the promise of aptamers in biomedical applications.

RX for science literacy: The what, where, how, and why of health science research (A teacher`s manual about biomedical research)

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

Hoffman, K.S.

1994-12-31

When the North Carolina Association for Biomedical Research (NCABR) surveyed the state`s science teachers in March 1993, 92% of those responding requested information related to biomedical research. Most of the teachers requested lesson plans and activities designed to help them give students an accurate and balanced perspective on research. In response to that need, NCABR has recently completed production of a 300-page teacher`s manual that provides an overview of the biomedical research process and describes the role and care of animals in that process. Rx for Science Literacy incorporates background information, lesson plans, handouts and activities to assist teachers inmore » K-12 classrooms. Developed by a science teacher with assistance from science and education experts, the manual captures the complex biomedical research process in an easy-to-follow, easy-to-use format. In North Carolina, NCABR plans to begin these workshops in fall 1994. The workshops will include a tour of a biomedical research laboratory and on-site presentations by bench scientists. Teacher evaluation of the manual will be structured into the workshop program. The manual is available at cost to all interested individuals and organizations.« less

Biomedical nuclear and X-ray imager using high-energy grazing incidence mirrors

DOEpatents

Ziock, Klaus-Peter; Craig, William W.; Hasegawa, Bruce; Pivovaroff, Michael J.

2005-09-27

Imaging of radiation sources located in a subject is explored for medical applications. The approach involves using grazing-incidence optics to form images of the location of radiopharmaceuticals administered to a subject. The optics are "true focusing" optics, meaning that they project a real and inverted image of the radiation source onto a detector possessing spatial and energy resolution.

Biomedical engineering for health research and development.

PubMed

Zhang, X-Y

2015-01-01

Biomedical engineering is a new area of research in medicine and biology, providing new concepts and designs for the diagnosis, treatment and prevention of various diseases. There are several types of biomedical engineering, such as tissue, genetic, neural and stem cells, as well as chemical and clinical engineering for health care. Many electronic and magnetic methods and equipments are used for the biomedical engineering such as Computed Tomography (CT) scans, Magnetic Resonance Imaging (MRI) scans, Electroencephalography (EEG), Ultrasound and regenerative medicine and stem cell cultures, preparations of artificial cells and organs, such as pancreas, urinary bladders, liver cells, and fibroblasts cells of foreskin and others. The principle of tissue engineering is described with various types of cells used for tissue engineering purposes. The use of several medical devices and bionics are mentioned with scaffold, cells and tissue cultures and various materials are used for biomedical engineering. The use of biomedical engineering methods is very important for the human health, and research and development of diseases. The bioreactors and preparations of artificial cells or tissues and organs are described here.

Multimodal computational microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

Li, Jiaji; Chen, Qian; Sun, Jiasong; Zhang, Jialin; Zuo, Chao

2016-12-01

Transport of intensity equation (TIE) is a powerful tool for phase retrieval and quantitative phase imaging, which requires intensity measurements only at axially closely spaced planes without a separate reference beam. It does not require coherent illumination and works well on conventional bright-field microscopes. The quantitative phase reconstructed by TIE gives valuable information that has been encoded in the complex wave field by passage through a sample of interest. Such information may provide tremendous flexibility to emulate various microscopy modalities computationally without requiring specialized hardware components. We develop a requisite theory to describe such a hybrid computational multimodal imaging system, which yields quantitative phase, Zernike phase contrast, differential interference contrast, and light field moment imaging, simultaneously. It makes the various observations for biomedical samples easy. Then we give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens-based TIE system, combined with the appropriate postprocessing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

Acoustic imaging with time reversal methods: From medicine to NDT

NASA Astrophysics Data System (ADS)

Fink, Mathias

2015-03-01

This talk will present an overview of the research conducted on ultrasonic time-reversal methods applied to biomedical imaging and to non-destructive testing. We will first describe iterative time-reversal techniques that allow both focusing ultrasonic waves on reflectors in tissues (kidney stones, micro-calcifications, contrast agents) or on flaws in solid materials. We will also show that time-reversal focusing does not need the presence of bright reflectors but it can be achieved only from the speckle noise generated by random distributions of non-resolved scatterers. We will describe the applications of this concept to correct distortions and aberrations in ultrasonic imaging and in NDT. In the second part of the talk we will describe the concept of time-reversal processors to get ultrafast ultrasonic images with typical frame rates of order of 10.000 F/s. It is the field of ultrafast ultrasonic imaging that has plenty medical applications and can be of great interest in NDT. We will describe some applications in the biomedical domain: Quantitative Elasticity imaging of tissues by following shear wave propagation to improve cancer detection and Ultrafast Doppler imaging that allows ultrasonic functional imaging.

Use of graph algorithms in the processing and analysis of images with focus on the biomedical data.

PubMed

Zdimalova, M; Roznovjak, R; Weismann, P; El Falougy, H; Kubikova, E

2017-01-01

Image segmentation is a known problem in the field of image processing. A great number of methods based on different approaches to this issue was created. One of these approaches utilizes the findings of the graph theory. Our work focuses on segmentation using shortest paths in a graph. Specifically, we deal with methods of "Intelligent Scissors," which use Dijkstra's algorithm to find the shortest paths. We created a new software in Microsoft Visual Studio 2013 integrated development environment Visual C++ in the language C++/CLI. We created a format application with a graphical users development environment for system Windows, with using the platform .Net (version 4.5). The program was used for handling and processing the original medical data. The major disadvantage of the method of "Intelligent Scissors" is the computational time length of Dijkstra's algorithm. However, after the implementation of a more efficient priority queue, this problem could be alleviated. The main advantage of this method we see in training that enables to adapt to a particular kind of edge, which we need to segment. The user involvement has a significant influence on the process of segmentation, which enormously aids to achieve high-quality results (Fig. 7, Ref. 13).

An FPGA-Based Rapid Wheezing Detection System

PubMed Central

Lin, Bor-Shing; Yen, Tian-Shiue

2014-01-01

Wheezing is often treated as a crucial indicator in the diagnosis of obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to monitor patients over the long-term. In this study, a portable wheezing detection system based on a field-programmable gate array (FPGA) is proposed. This system accelerates wheezing detection, and can be used as either a single-process system, or as an integrated part of another biomedical signal detection system. The system segments sound signals into 2-second units. A short-time Fourier transform was used to determine the relationship between the time and frequency components of wheezing sound data. A spectrogram was processed using 2D bilateral filtering, edge detection, multithreshold image segmentation, morphological image processing, and image labeling, to extract wheezing features according to computerized respiratory sound analysis (CORSA) standards. These features were then used to train the support vector machine (SVM) and build the classification models. The trained model was used to analyze sound data to detect wheezing. The system runs on a Xilinx Virtex-6 FPGA ML605 platform. The experimental results revealed that the system offered excellent wheezing recognition performance (0.912). The detection process can be used with a clock frequency of 51.97 MHz, and is able to perform rapid wheezing classification. PMID:24481034

Synthesis and Characterization of Mg-doped ZnO Nanorods for Biomedical Applications

NASA Astrophysics Data System (ADS)

Gemar, H.; Das, N. C.; Wanekaya, A.; Delong, R.; Ghosh, K.

2013-03-01

Nanomaterials research has become a major attraction in the field of advanced materials research in the area of Physics, Chemistry, and Materials Science. Bio-compatible and chemically stable metal nanoparticles have biomedical applications that includes drug delivery, cell and DNA separation, gene cloning, magnetic resonance imaging (MRI). This research is aimed at the fabrication and characterization of Mg-doped ZnO nanorods. Hydrothermal synthesis of undoped ZnO and Mg-doped ZnO nanorods is carried out using aqueous solutions of Zn(NO3)2 .6H2O, MgSO4, and using NH4OH as hydrolytic catalyst. Nanomaterials of different sizes and shapes were synthesized by varying the process parameters such as molarity (0.15M, 0.3M, 0.5M) and pH (8-11) of the precursors, growth temperature (130°C), and annealing time during the hydrothermal Process. Structural, morphological, and optical properties are studied using various techniques such as XRD, SEM, UV-vis and PL spectroscopy. Detailed structural, and optical properties will be discussed in this presentation. This work is partially supported by National Cancer Institute (1 R15 CA139390-01).

Time-dependent photon migration imaging

NASA Astrophysics Data System (ADS)

Sevick, Eva M.; Wang, NaiGuang; Chance, Britton

1992-02-01

Recently, the application of both time- and frequency-resolved fluorescence techniques for the determination of photon migration characteristics in strongly scattering media has been used to characterize the optical properties in strongly scattering media. Specifically, Chance and coworkers have utilized measurement of photon migration characteristics to determine tissue hemoglobin absorbance and ultimately oxygenation status in homogeneous tissues. In this study, we present simulation results and experimental measurements for both techniques to show the capacity of time-dependent photon migration characteristics to image optically obscure absorbers located in strongly scattering media. The applications of time-dependent photon imaging in the biomedical community include imaging of light absorbing hematomas, tumors, hypoxic tissue volumes, and other tissue abnormalities. Herein, we show that the time-resolved parameter of mean photon path length, , and the frequency- resolved parameter of phase-shift, (theta) , can be used similarly to obtain three dimensional information of absorber position from two-dimensional measurements. Finally, we show that unlike imaging techniques that monitor the intensity of light without regard to the migration characteristics, the resolution of time-dependent photon migration measurements is enhanced by tissue scattering, further potentiating their use for biomedical imaging.

Imaging and the new biology: What's wrong with this picture?

NASA Astrophysics Data System (ADS)

Vannier, Michael W.

2004-05-01

The Human Genome has been defined, giving us one part of the equation that stems from the central dogma of molecular biology. Despite this awesome scientific achievement, the correspondence between genomics and imaging is weak, since we cannot predict an organism's phenotype from even perfect knowledge of its genetic complement. Biological knowledge comes in several forms, and the genome is perhaps the best known and most completely understood type. Imaging creates another form of biological information, providing the ability to study morphology, growth and development, metabolic processes, and diseases in vitro and in vivo at many levels of scale. The principal challenge in biomedical imaging for the future lies in the need to reconcile the data provided by one or multiple modalities with other forms of biological knowledge, most importantly the genome, proteome, physiome, and other "-ome's." To date, the imaging science community has not set a high priority on the unification of their results with genomics, proteomics, and physiological functions in most published work. Images are relatively isolated from other forms of biological data, impairing our ability to conceive and address many fundamental questions in research and clinical practice. This presentation will explain the challenge of biological knowledge integration in basic research and clinical applications from the standpoint of imaging and image processing. The impediments to progress, isolation of the imaging community, and mainstream of new and future biological science will be identified, so the critical and immediate need for change can be highlighted.

Platform for Automated Real-Time High Performance Analytics on Medical Image Data.

PubMed

Allen, William J; Gabr, Refaat E; Tefera, Getaneh B; Pednekar, Amol S; Vaughn, Matthew W; Narayana, Ponnada A

2018-03-01

Biomedical data are quickly growing in volume and in variety, providing clinicians an opportunity for better clinical decision support. Here, we demonstrate a robust platform that uses software automation and high performance computing (HPC) resources to achieve real-time analytics of clinical data, specifically magnetic resonance imaging (MRI) data. We used the Agave application programming interface to facilitate communication, data transfer, and job control between an MRI scanner and an off-site HPC resource. In this use case, Agave executed the graphical pipeline tool GRAphical Pipeline Environment (GRAPE) to perform automated, real-time, quantitative analysis of MRI scans. Same-session image processing will open the door for adaptive scanning and real-time quality control, potentially accelerating the discovery of pathologies and minimizing patient callbacks. We envision this platform can be adapted to other medical instruments, HPC resources, and analytics tools.

Single-shot full resolution region-of-interest (ROI) reconstruction in image plane digital holographic microscopy

NASA Astrophysics Data System (ADS)

Singh, Mandeep; Khare, Kedar

2018-05-01

We describe a numerical processing technique that allows single-shot region-of-interest (ROI) reconstruction in image plane digital holographic microscopy with full pixel resolution. The ROI reconstruction is modelled as an optimization problem where the cost function to be minimized consists of an L2-norm squared data fitting term and a modified Huber penalty term that are minimized alternately in an adaptive fashion. The technique can provide full pixel resolution complex-valued images of the selected ROI which is not possible to achieve with the commonly used Fourier transform method. The technique can facilitate holographic reconstruction of individual cells of interest from a large field-of-view digital holographic microscopy data. The complementary phase information in addition to the usual absorption information already available in the form of bright field microscopy can make the methodology attractive to the biomedical user community.

Portable optical-resolution photoacoustic microscopy for volumetric imaging of multiscale organisms.

PubMed

Jin, Tian; Guo, Heng; Yao, Lei; Xie, Huikai; Jiang, Huabei; Xi, Lei

2018-04-01

Photoacoustic microscopy (PAM) provides a fundamentally new tool for a broad range of studies of biological structures and functions. However, the use of PAM has been largely limited to small vertebrates due to the large size/weight and the inconvenience of the equipment. Here, we describe a portable optical-resolution photoacoustic microscopy (pORPAM) system for 3-dimensional (3D) imaging of small-to-large rodents and humans with a high spatiotemporal resolution and a large field of view. We show extensive applications of pORPAM to multiscale animals including mice and rabbits. In addition, we image the 3D vascular networks of human lips, and demonstrate the feasibility of pORPAM to observe the recovery process of oral ulcer and cancer-associated capillary loops in human oral cavities. This technology is promising for broad biomedical studies from fundamental biology to clinical diseases. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

High-speed video capillaroscopy method for imaging and evaluation of moving red blood cells

NASA Astrophysics Data System (ADS)

Gurov, Igor; Volkov, Mikhail; Margaryants, Nikita; Pimenov, Aleksei; Potemkin, Andrey

2018-05-01

The video capillaroscopy system with high image recording rate to resolve moving red blood cells with velocity up to 5 mm/s into a capillary is considered. Proposed procedures of the recorded video sequence processing allow evaluating spatial capillary area, capillary diameter and central line with high accuracy and reliability independently on properties of individual capillary. Two-dimensional inter frame procedure is applied to find lateral shift of neighbor images in the blood flow area with moving red blood cells and to measure directly the blood flow velocity along a capillary central line. The developed method opens new opportunities for biomedical diagnostics, particularly, due to long-time continuous monitoring of red blood cells velocity into capillary. Spatio-temporal representation of capillary blood flow is considered. Experimental results of direct measurement of blood flow velocity into separate capillary as well as capillary net are presented and discussed.

Quantitative phase microscopy via optimized inversion of the phase optical transfer function.

PubMed

Jenkins, Micah H; Gaylord, Thomas K

2015-10-01

Although the field of quantitative phase imaging (QPI) has wide-ranging biomedical applicability, many QPI methods are not well-suited for such applications due to their reliance on coherent illumination and specialized hardware. By contrast, methods utilizing partially coherent illumination have the potential to promote the widespread adoption of QPI due to their compatibility with microscopy, which is ubiquitous in the biomedical community. Described herein is a new defocus-based reconstruction method that utilizes a small number of efficiently sampled micrographs to optimally invert the partially coherent phase optical transfer function under assumptions of weak absorption and slowly varying phase. Simulation results are provided that compare the performance of this method with similar algorithms and demonstrate compatibility with large phase objects. The accuracy of the method is validated experimentally using a microlens array as a test phase object. Lastly, time-lapse images of live adherent cells are obtained with an off-the-shelf microscope, thus demonstrating the new method's potential for extending QPI capability widely in the biomedical community.

A framework for biomedical figure segmentation towards image-based document retrieval

PubMed Central

2013-01-01

The figures included in many of the biomedical publications play an important role in understanding the biological experiments and facts described within. Recent studies have shown that it is possible to integrate the information that is extracted from figures in classical document classification and retrieval tasks in order to improve their accuracy. One important observation about the figures included in biomedical publications is that they are often composed of multiple subfigures or panels, each describing different methodologies or results. The use of these multimodal figures is a common practice in bioscience, as experimental results are graphically validated via multiple methodologies or procedures. Thus, for a better use of multimodal figures in document classification or retrieval tasks, as well as for providing the evidence source for derived assertions, it is important to automatically segment multimodal figures into subfigures and panels. This is a challenging task, however, as different panels can contain similar objects (i.e., barcharts and linecharts) with multiple layouts. Also, certain types of biomedical figures are text-heavy (e.g., DNA sequences and protein sequences images) and they differ from traditional images. As a result, classical image segmentation techniques based on low-level image features, such as edges or color, are not directly applicable to robustly partition multimodal figures into single modal panels. In this paper, we describe a robust solution for automatically identifying and segmenting unimodal panels from a multimodal figure. Our framework starts by robustly harvesting figure-caption pairs from biomedical articles. We base our approach on the observation that the document layout can be used to identify encoded figures and figure boundaries within PDF files. Taking into consideration the document layout allows us to correctly extract figures from the PDF document and associate their corresponding caption. We combine pixel-level representations of the extracted images with information gathered from their corresponding captions to estimate the number of panels in the figure. Thus, our approach simultaneously identifies the number of panels and the layout of figures. In order to evaluate the approach described here, we applied our system on documents containing protein-protein interactions (PPIs) and compared the results against a gold standard that was annotated by biologists. Experimental results showed that our automatic figure segmentation approach surpasses pure caption-based and image-based approaches, achieving a 96.64% accuracy. To allow for efficient retrieval of information, as well as to provide the basis for integration into document classification and retrieval systems among other, we further developed a web-based interface that lets users easily retrieve panels containing the terms specified in the user queries. PMID:24565394

Water-Soluble Spinel Ferrites by a Modified Polyol Process as Contrast Agents in MRI

NASA Astrophysics Data System (ADS)

Basina, Georgia; Tzitzios, Vasilis; Niarchos, Dimitris; Li, Wanfeng; Khurshid, Hafsa; Mao, Hui; Hadjipanayis, Costas; Hadjipanayis, George

2010-12-01

Magnetic nanoparticles have recently been very attractive for biomedical applications. In this study, we have synthesized ferrite nanoparticles for application as contrast agents in MRI experiments. Fe3O4 and MnFe2O4 spinel ferrites with a mean size of 11-12 nm, were prepared by a modified polyol route in commercially available polyethylene glycol with molecular weight 600 (PEG-600). The reaction takes place in the presence of water soluble and non-toxic tri-block copolymer known as Pluronic® F-127 (PEO100-PPO65-PEO100). The nanoparticles have saturation magnetization values of 52 and 68 emu/g for MnFe2O4 and Fe3O4, respectively. Both the Fe3O4, and MnFe2O4 nanoparticles make stable solutions in water known as ferrofluids. Preliminary data demonstrated the capability of these nanoparticles to induce imaging contrast in T2 weighted MRI experiments, making these materials suitable for biomedical applications such as medical MRI.

Segmentation and classification of brain images using firefly and hybrid kernel-based support vector machine

NASA Astrophysics Data System (ADS)

Selva Bhuvaneswari, K.; Geetha, P.

2017-05-01

Magnetic resonance imaging segmentation refers to a process of assigning labels to set of pixels or multiple regions. It plays a major role in the field of biomedical applications as it is widely used by the radiologists to segment the medical images input into meaningful regions. In recent years, various brain tumour detection techniques are presented in the literature. The entire segmentation process of our proposed work comprises three phases: threshold generation with dynamic modified region growing phase, texture feature generation phase and region merging phase. by dynamically changing two thresholds in the modified region growing approach, the first phase of the given input image can be performed as dynamic modified region growing process, in which the optimisation algorithm, firefly algorithm help to optimise the two thresholds in modified region growing. After obtaining the region growth segmented image using modified region growing, the edges can be detected with edge detection algorithm. In the second phase, the texture feature can be extracted using entropy-based operation from the input image. In region merging phase, the results obtained from the texture feature-generation phase are combined with the results of dynamic modified region growing phase and similar regions are merged using a distance comparison between regions. After identifying the abnormal tissues, the classification can be done by hybrid kernel-based SVM (Support Vector Machine). The performance analysis of the proposed method will be carried by K-cross fold validation method. The proposed method will be implemented in MATLAB with various images.

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

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.

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

PubMed Central

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

2012-01-01

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

A corpus of full-text journal articles is a robust evaluation tool for revealing differences in performance of biomedical natural language processing tools

PubMed Central

2012-01-01

Background We introduce the linguistic annotation of a corpus of 97 full-text biomedical publications, known as the Colorado Richly Annotated Full Text (CRAFT) corpus. We further assess the performance of existing tools for performing sentence splitting, tokenization, syntactic parsing, and named entity recognition on this corpus. Results Many biomedical natural language processing systems demonstrated large differences between their previously published results and their performance on the CRAFT corpus when tested with the publicly available models or rule sets. Trainable systems differed widely with respect to their ability to build high-performing models based on this data. Conclusions The finding that some systems were able to train high-performing models based on this corpus is additional evidence, beyond high inter-annotator agreement, that the quality of the CRAFT corpus is high. The overall poor performance of various systems indicates that considerable work needs to be done to enable natural language processing systems to work well when the input is full-text journal articles. The CRAFT corpus provides a valuable resource to the biomedical natural language processing community for evaluation and training of new models for biomedical full text publications. PMID:22901054

UMLS content views appropriate for NLP processing of the biomedical literature vs. clinical text.

PubMed

Demner-Fushman, Dina; Mork, James G; Shooshan, Sonya E; Aronson, Alan R

2010-08-01

Identification of medical terms in free text is a first step in such Natural Language Processing (NLP) tasks as automatic indexing of biomedical literature and extraction of patients' problem lists from the text of clinical notes. Many tools developed to perform these tasks use biomedical knowledge encoded in the Unified Medical Language System (UMLS) Metathesaurus. We continue our exploration of automatic approaches to creation of subsets (UMLS content views) which can support NLP processing of either the biomedical literature or clinical text. We found that suppression of highly ambiguous terms in the conservative AutoFilter content view can partially replace manual filtering for literature applications, and suppression of two character mappings in the same content view achieves 89.5% precision at 78.6% recall for clinical applications. Published by Elsevier Inc.

Fluorescent nanodiamond and lanthanide labelled in situ hybridization for the identification of RNA transcripts in fixed and CLARITY-cleared central nervous system tissues (Conference Presentation)

NASA Astrophysics Data System (ADS)

Parker, Lindsay M.; Staikopoulos, Vicky; Cordina, Nicole M.; Sayyadi, Nima; Hutchinson, Mark R.; Packer, Nicolle H.

2016-03-01

Despite significant advancement in the methodology used to conjugate, incorporate and visualize fluorescent molecules at the cellular and tissue levels, biomedical imaging predominantly relies on the limitations of established fluorescent molecules such as fluorescein, cyanine and AlexaFluor dyes or genetic incorporation of fluorescent proteins by viral or other means. These fluorescent dyes and conjugates are highly susceptible to photobleaching and compete with cellular autofluorescence, making biomedical imaging unreliable, difficult and time consuming in many cases. In addition, some proteins have low copy numbers and/or poor antibody recognition, further making detection and imaging difficult. We are developing better methods for imaging central nervous system neuroinflammatory markers using targeted mRNA transcripts labelled with fluorescent nanodiamonds or lanthanide chelates. These tags have increased signal and photostability and can also discriminate against tissue/cell autofluorescence. Brains and spinal cords from BALB/c mice with a chronic constriction model of neuropathic pain (neuroinflammation group) or that have undergone sham surgeries (control group) were collected. A subset of brains and spinal cords were perfused and fixed with paraformaldehyde (n=3 sham and n=3 pain groups) prior to sectioning and in situ hybridization using nanodiamond or lanthanide chelate conjugated complementary RNA probes. Another subset of brains and spinal cords from the same cohort of animals were perfused and processed for CLARITY hydrogel based clearing prior to in situ hybridization with the same probes. We will present our findings on the photostability, sensitivity and discrimination from background tissue autofluorescence of our novel RNA probes, compared to traditional fluorophore tags.

Near-infrared (NIR) emitting conjugated polymers for biomedical applications (Presentation Recording)

NASA Astrophysics Data System (ADS)

Repenko, Tatjana; Kuehne, Alexander J. C.

2015-10-01

Fluorescent biomedical markers of today such as dye-infiltrated colloids, microgels and quantum dots suffer from fast bleaching, lack surface functionality (for targets or pharmaceutical agents) and potentially leach heavy metals in case of quantum dots (e.g. Cd). By contrast, conjugated polymer particles are non-cytotoxic, exhibit reduced bleaching, as the entire particle consists of fluorophore, they are hydrophobic and show high quantum yields. Consequently, conjugated polymer particles represent ideal materials for biological applications and imaging. However currently, conjugated polymer particles for biomedical imaging usually lack near-infrared (NIR) emission and are polydisperse. Fluorescent agents with emission in the NIR spectrum are interesting for biomedical applications due to their low photo-damage towards biological species and the ability of NIR radiation to penetrate deep into biological tissue.. I will present the development and synthesis of new conjugated polymers particles with fluorescence in the NIR spectral region for bio-imaging and clinical diagnosis. The particle synthesis proceeds in a one-step Pd or Ni-catalyzed dispersion polymerization of functional NIR emitters. The resulting monodisperse conjugated polymer particles are obtained as a dispersion in a non-hazardous solvent. Different sizes in the sub-micrometer range with a narrow size distribution can be produced. Furthermore biological recognition motifs can be easily attached to the conjugated polymers via thiol-yne click-chemistry providing specific tumor targeting without quenching of the fluorescence. References [1] Kuehne AJC, Gather MC, Sprakel J., Nature Commun. 2012, 3, 1088. [2] Repenko T, Fokong S, De Laporte L, Go D, Kiessling F, Lammers T, Kuehne AJC.,Chem Commun 2015, accepted.

Evaluating the operational risks of biomedical waste using failure mode and effects analysis.

PubMed

Chen, Ying-Chu; Tsai, Pei-Yi

2017-06-01

The potential problems and risks of biomedical waste generation have become increasingly apparent in recent years. This study applied a failure mode and effects analysis to evaluate the operational problems and risks of biomedical waste. The microbiological contamination of biomedical waste seldom receives the attention of researchers. In this study, the biomedical waste lifecycle was divided into seven processes: Production, classification, packaging, sterilisation, weighing, storage, and transportation. Twenty main failure modes were identified in these phases and risks were assessed based on their risk priority numbers. The failure modes in the production phase accounted for the highest proportion of the risk priority number score (27.7%). In the packaging phase, the failure mode 'sharp articles not placed in solid containers' had the highest risk priority number score, mainly owing to its high severity rating. The sterilisation process is the main difference in the treatment of infectious and non-infectious biomedical waste. The failure modes in the sterilisation phase were mainly owing to human factors (mostly related to operators). This study increases the understanding of the potential problems and risks associated with biomedical waste, thereby increasing awareness of how to improve the management of biomedical waste to better protect workers, the public, and the environment.

Black Phosphorus and its Biomedical Applications

PubMed Central

Choi, Jane Ru; Yong, Kar Wey; Choi, Jean Yu; Nilghaz, Azadeh; Lin, Yang; Xu, Jie; Lu, Xiaonan

2018-01-01

Black phosphorus (BP), also known as phosphorene, has attracted recent scientific attention since its first successful exfoliation in 2014 owing to its unique structure and properties. In particular, its exceptional attributes, such as the excellent optical and mechanical properties, electrical conductivity and electron-transfer capacity, contribute to its increasing demand as an alternative to graphene-based materials in biomedical applications. Although the outlook of this material seems promising, its practical applications are still highly challenging. In this review article, we discuss the unique properties of BP, which make it a potential platform for biomedical applications compared to other 2D materials, including graphene, molybdenum disulphide (MoS2), tungsten diselenide (WSe2) and hexagonal boron nitride (h-BN). We then introduce various synthesis methods of BP and review its latest progress in biomedical applications, such as biosensing, drug delivery, photoacoustic imaging and cancer therapies (i.e., photothermal and photodynamic therapies). Lastly, the existing challenges and future perspective of BP in biomedical applications are briefly discussed. PMID:29463996

An overview of biomedical literature search on the World Wide Web in the third millennium.

PubMed

Kumar, Prince; Goel, Roshni; Jain, Chandni; Kumar, Ashish; Parashar, Abhishek; Gond, Ajay Ratan

2012-06-01

Complete access to the existing pool of biomedical literature and the ability to "hit" upon the exact information of the relevant specialty are becoming essential elements of academic and clinical expertise. With the rapid expansion of the literature database, it is almost impossible to keep up to date with every innovation. Using the Internet, however, most people can freely access this literature at any time, from almost anywhere. This paper highlights the use of the Internet in obtaining valuable biomedical research information, which is mostly available from journals, databases, textbooks and e-journals in the form of web pages, text materials, images, and so on. The authors present an overview of web-based resources for biomedical researchers, providing information about Internet search engines (e.g., Google), web-based bibliographic databases (e.g., PubMed, IndMed) and how to use them, and other online biomedical resources that can assist clinicians in reaching well-informed clinical decisions.

Stimuli-responsive magnetic particles for biomedical applications.

PubMed

Medeiros, S F; Santos, A M; Fessi, H; Elaissari, A

2011-01-17

In recent years, magnetic nanoparticles have been studied due to their potential applications as magnetic carriers in biomedical area. These materials have been increasingly exploited as efficient delivery vectors, leading to opportunities of use as magnetic resonance imaging (MRI) agents, mediators of hyperthermia cancer treatment and in targeted therapies. Much attention has been also focused on "smart" polymers, which are able to respond to environmental changes, such as changes in the temperature and pH. In this context, this article reviews the state-of-the art in stimuli-responsive magnetic systems for biomedical applications. The paper describes different types of stimuli-sensitive systems, mainly temperature- and pH sensitive polymers, the combination of this characteristic with magnetic properties and, finally, it gives an account of their preparation methods. The article also discusses the main in vivo biomedical applications of such materials. A survey of the recent literature on various stimuli-responsive magnetic gels in biomedical applications is also included. Copyright © 2010 Elsevier B.V. All rights reserved.

Figure mining for biomedical research.

PubMed

Rodriguez-Esteban, Raul; Iossifov, Ivan

2009-08-15

Figures from biomedical articles contain valuable information difficult to reach without specialized tools. Currently, there is no search engine that can retrieve specific figure types. This study describes a retrieval method that takes advantage of principles in image understanding, text mining and optical character recognition (OCR) to retrieve figure types defined conceptually. A search engine was developed to retrieve tables and figure types to aid computational and experimental research. http://iossifovlab.cshl.edu/figurome/.

Synthesis and optimization of chitosan nanoparticles: Potential applications in nanomedicine and biomedical engineering.

PubMed

Ghadi, Arezou; Mahjoub, Soleiman; Tabandeh, Fatemeh; Talebnia, Farid

2014-01-01

Chitosan nanoparticles have become of great interest for nanomedicine, biomedical engineering and development of new therapeutic drug release systems with improved bioavailability, increased specificity and sensitivity, and reduced pharmacological toxicity. The aim of the present study was to synthesis and optimize of the chitosan nanoparticles for industrial and biomedical applications. Fe3O4 was synthesized and optimized as magnetic core nanoparticles and then chitosan covered this magnetic core. The size and morphology of the nano-magnetic chitosan was analyzed by scanning electron microscope (SEM). Topography and size distribution of the nanoparticles were shown with two-dimensional and three-dimensional images of atomic force microscopy (AFM). The nanoparticles were analyzed using transmission electron microscopy (TEM). The chitosan nanoparticles prepared in the experiment exhibited white powder shape. The SEM micrographs of the nano-magnetic chitosan showed that they were approximately uniform spheres. The unmodified chitosan nanoparticles composed of clusters of nanoparticles with sizes ranging from 10 nm to 80 nm. AFM provides a three-dimensional surface profile. The TEM image showed physical aggregation of the chitosan nanoparticles. The results show that a novel chitosan nanoparticle was successfully synthesized and characterized. It seems that this nanoparticle like the other chitosan nano particles has potential applications for nanomedicine, biomedical engineering, industrial and pharmaceutical fields.

'Add women & stir'--the biomedical approach to cardiac research!

PubMed

O'Donnell, Sharon; Condell, Sarah; Begley, Cecily M

2004-07-01

In conditions shared by women and men, the biomedical model of disease assumes that illness-symptoms and outcomes are biologically and socially 'neutral'. Consequently, up until a decade ago, white middle-aged men were the model subjects in most funded cardiac trials, with the assumption that whatever the findings, the results would also hold true for women. This 'add women and stir' approach has resulted in imbalances in cardiac care and an image of coronary artery disease, which portrays a middle-aged male as its victim. Moreover, cardiac health care has been designed with the male anatomy and male experience of illness in mind, and health promotional measures have been targeted towards men. Women have received these health promotional messages to protect the hearts of men, and have been less likely to modify their own lifestyles in a cardio-protective manner. However, the biological and social differences that exist between women and men, must surely invalidate such biased biomedical assertions, and signify a need to delve beyond the realm of biomedical reductionism for greater insights and understanding. This review examines how scientific reductionism has failed to explore the impact of coronary artery disease on the lives of women and how the gendered image of this disease has privileged the normative frame.

Early Light Imaging for Biomedical Applications

DTIC Science & Technology

2000-07-01

such as prostate cancer, breast cancer, cervical cancer, glaucoma , macular degeneration, macular endema, and atherosclerosis plaques. Understanding of...harmonic- generation cross-correlation time gating", Opt. Lett., 16 1019-1021 (1991) 17. K. Yoo, Z. Zang, S. Ahmed , R. Alfano, "Imaging objects hidden

Closer Look at Cancer Imaging Tools

MedlinePlus

... download on the Apple Store and Google Play. SOURCE: National Institute of Biomedical Imaging and Bioengineering: Medical Scans Spring 2018 Issue: Volume 13 Number 1 Page 11 MedlinePlus Subscribe Magazine Information Contact Us Viewers & Players Friends of the National Library of Medicine (FNLM) top

Microwave Sensors for Breast Cancer Detection

PubMed Central

2018-01-01

Breast cancer is the leading cause of death among females, early diagnostic methods with suitable treatments improve the 5-year survival rates significantly. Microwave breast imaging has been reported as the most potential to become the alternative or additional tool to the current gold standard X-ray mammography for detecting breast cancer. The microwave breast image quality is affected by the microwave sensor, sensor array, the number of sensors in the array and the size of the sensor. In fact, microwave sensor array and sensor play an important role in the microwave breast imaging system. Numerous microwave biosensors have been developed for biomedical applications, with particular focus on breast tumor detection. Compared to the conventional medical imaging and biosensor techniques, these microwave sensors not only enable better cancer detection and improve the image resolution, but also provide attractive features such as label-free detection. This paper aims to provide an overview of recent important achievements in microwave sensors for biomedical imaging applications, with particular focus on breast cancer detection. The electric properties of biological tissues at microwave spectrum, microwave imaging approaches, microwave biosensors, current challenges and future works are also discussed in the manuscript. PMID:29473867

Microwave Sensors for Breast Cancer Detection.

PubMed

Wang, Lulu

2018-02-23

Breast cancer is the leading cause of death among females, early diagnostic methods with suitable treatments improve the 5-year survival rates significantly. Microwave breast imaging has been reported as the most potential to become the alternative or additional tool to the current gold standard X-ray mammography for detecting breast cancer. The microwave breast image quality is affected by the microwave sensor, sensor array, the number of sensors in the array and the size of the sensor. In fact, microwave sensor array and sensor play an important role in the microwave breast imaging system. Numerous microwave biosensors have been developed for biomedical applications, with particular focus on breast tumor detection. Compared to the conventional medical imaging and biosensor techniques, these microwave sensors not only enable better cancer detection and improve the image resolution, but also provide attractive features such as label-free detection. This paper aims to provide an overview of recent important achievements in microwave sensors for biomedical imaging applications, with particular focus on breast cancer detection. The electric properties of biological tissues at microwave spectrum, microwave imaging approaches, microwave biosensors, current challenges and future works are also discussed in the manuscript.

An exploration of the biomedical optics course construction of undergraduate biomedical engineering program in medical colleges

NASA Astrophysics Data System (ADS)

Guo, Shijun; Lyu, Jie; Zhang, Peiming

2017-08-01

In this paper, the teaching goals, teaching contents and teaching methods in biomedical optics course construction are discussed. From the dimension of teaching goals, students should master the principle of optical inspection on the human body, diagnosis and treatment of methodology and instruments, through the study of the theory and practice of this course, and can utilize biomedical optics methods to solve practical problems in the clinical medical engineering practice. From the dimension of teaching contents, based on the characteristics of biomedical engineering in medical colleges, the organic integration of engineering aspects, medical optical instruments, and biomedical aspects dispersed in human anatomy, human physiology, clinical medicine fundamental related to the biomedical optics is build. Noninvasive measurement of the human body composition and noninvasive optical imaging of the human body were taken as actual problems in biomedical optics fields. Typical medical applications such as eye optics and laser medicine were also integrated into the theory and practice teaching. From the dimension of teaching methods, referencing to organ-system based medical teaching mode, optical principle and instrument principle were taught by teachers from school of medical instruments, and the histological characteristics and clinical actual need in areas such as digestive diseases and urinary surgery were taught by teachers from school of basic medicine or clinical medicine of medical colleges. Furthermore, clinical application guidance would be provided by physician and surgeons in hospitals.

PLGA nanoparticles from nano-emulsion templating as imaging agents: Versatile technology to obtain nanoparticles loaded with fluorescent dyes.

PubMed

Fornaguera, C; Feiner-Gracia, N; Calderó, G; García-Celma, M J; Solans, C

2016-11-01

The interest in polymeric nanoparticles as imaging systems for biomedical applications has increased notably in the last decades. In this work, PLGA nanoparticles, prepared from nano-emulsion templating, have been used to prepare novel fluorescent imaging agents. Two model fluorescent dyes were chosen and dissolved in the oil phase of the nano-emulsions together with PLGA. Nano-emulsions were prepared by the phase inversion composition (PIC) low-energy method. Fluorescent dye-loaded nanoparticles were obtained by solvent evaporation of nano-emulsion templates. PLGA nanoparticles loaded with the fluorescent dyes showed hydrodynamic radii lower than 40nm; markedly lower than those reported in previous studies. The small nanoparticle size was attributed to the nano-emulsification strategy used. PLGA nanoparticles showed negative surface charge and enough stability to be used for biomedical imaging purposes. Encapsulation efficiencies were higher than 99%, which was also attributed to the nano-emulsification approach as well as to the low solubility of the dyes in the aqueous component. Release kinetics of both fluorescent dyes from the nanoparticle dispersions was pH-independent and sustained. These results indicate that the dyes could remain encapsulated enough time to reach any organ and that the decrease of the pH produced during cell internalization by the endocytic route would not affect their release. Therefore, it can be assumed that these nanoparticles are appropriate as systemic imaging agents. In addition, in vitro toxicity tests showed that nanoparticles are non-cytotoxic. Consequently, it can be concluded that the preparation of PLGA nanoparticles from nano-emulsion templating represents a very versatile technology that enables obtaining biocompatible, biodegradable and safe imaging agents suitable for biomedical purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Architecture for biomedical multimedia information delivery on the World Wide Web

NASA Astrophysics Data System (ADS)

Long, L. Rodney; Goh, Gin-Hua; Neve, Leif; Thoma, George R.

1997-10-01

Research engineers at the National Library of Medicine are building a prototype system for the delivery of multimedia biomedical information on the World Wide Web. This paper discuses the architecture and design considerations for the system, which will be used initially to make images and text from the third National Health and Nutrition Examination Survey (NHANES) publicly available. We categorized our analysis as follows: (1) fundamental software tools: we analyzed trade-offs among use of conventional HTML/CGI, X Window Broadway, and Java; (2) image delivery: we examined the use of unconventional TCP transmission methods; (3) database manager and database design: we discuss the capabilities and planned use of the Informix object-relational database manager and the planned schema for the HNANES database; (4) storage requirements for our Sun server; (5) user interface considerations; (6) the compatibility of the system with other standard research and analysis tools; (7) image display: we discuss considerations for consistent image display for end users. Finally, we discuss the scalability of the system in terms of incorporating larger or more databases of similar data, and the extendibility of the system for supporting content-based retrieval of biomedical images. The system prototype is called the Web-based Medical Information Retrieval System. An early version was built as a Java applet and tested on Unix, PC, and Macintosh platforms. This prototype used the MiniSQL database manager to do text queries on a small database of records of participants in the second NHANES survey. The full records and associated x-ray images were retrievable and displayable on a standard Web browser. A second version has now been built, also a Java applet, using the MySQL database manager.

New Trends of Emerging Technologies in Digital Pathology.

PubMed

Bueno, Gloria; Fernández-Carrobles, M Milagro; Deniz, Oscar; García-Rojo, Marcial

2016-01-01

The future paradigm of pathology will be digital. Instead of conventional microscopy, a pathologist will perform a diagnosis through interacting with images on computer screens and performing quantitative analysis. The fourth generation of virtual slide telepathology systems, so-called virtual microscopy and whole-slide imaging (WSI), has allowed for the storage and fast dissemination of image data in pathology and other biomedical areas. These novel digital imaging modalities encompass high-resolution scanning of tissue slides and derived technologies, including automatic digitization and computational processing of whole microscopic slides. Moreover, automated image analysis with WSI can extract specific diagnostic features of diseases and quantify individual components of these features to support diagnoses and provide informative clinical measures of disease. Therefore, the challenge is to apply information technology and image analysis methods to exploit the new and emerging digital pathology technologies effectively in order to process and model all the data and information contained in WSI. The final objective is to support the complex workflow from specimen receipt to anatomic pathology report transmission, that is, to improve diagnosis both in terms of pathologists' efficiency and with new information. This article reviews the main concerns about and novel methods of digital pathology discussed at the latest workshop in the field carried out within the European project AIDPATH (Academia and Industry Collaboration for Digital Pathology). © 2016 S. Karger AG, Basel.

Back in Time

NASA Technical Reports Server (NTRS)

1998-01-01

Under a Jet Propulsion Laboratory SBIR (Small Business Innovative Research), Cambridge Research and Instrumentation Inc., developed a new class of filters for the construction of small, low-cost multispectral imagers. The VariSpec liquid crystal enables users to obtain multi-spectral, ultra-high resolution images using a monochrome CCD (charge coupled device) camera. Application areas include biomedical imaging, remote sensing, and machine vision.

Astronaut Kenneth Reightler processes biomedical samples in SPACEHAB

NASA Image and Video Library

1994-02-09

STS060-301-003 (3-11 Feb 1994) --- Astronaut Kenneth S. Reightler, STS-60 pilot, processes biomedical samples in a centrifuge aboard the SPACEHAB module. Reightler joined four other NASA astronauts and a Russian cosmonaut for eight days of research aboard the Space Shuttle Discovery.

Photochemical coatings for the prevention of bacterial colonization.

PubMed

Dunkirk, S G; Gregg, S L; Duran, L W; Monfils, J D; Haapala, J E; Marcy, J A; Clapper, D L; Amos, R A; Guire, P E

1991-10-01

Biomaterials are being used with increasing frequency for tissue substitution. Implantable, prosthetic devices are instrumental in the saving of patients' lives and enhancing the quality of life for many others. However, the greatest barrier to expanding the use of biomedical devices is the high probability of bacterial adherence and proliferation, causing very difficult and often untreatable medical-device centered infections. The difficulty in treating such infections results in great danger to the patient, and usually retrieval of the device with considerable pain and suffering. Clearly, development of processes that make biomedical devices resistant to bacterial adherence and colonization would have widespread application in the field of biomedical technology. A photochemical surface modification process is being investigated as a generic means of applying antimicrobial coatings to biomedical devices. The photochemical process results in covalent immobilization of coatings to all classes of medical device polymers. A discussion of the photochemical surface modification process and preliminary results demonstrating the success of photochemical coatings in formulating microbial-resistant surfaces are presented in this paper.

A philosophy for CNS radiotracer design

DOE PAGES

Van de Bittner, Genevieve C.; Ricq, Emily L.; Hooker, Jacob M.

2014-10-01

Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfallsmore » of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test–retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood–brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Lastly, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible.« less

A Philosophy for CNS Radiotracer Design

PubMed Central

2015-01-01

Conspectus Decades after its discovery, positron emission tomography (PET) remains the premier tool for imaging neurochemistry in living humans. Technological improvements in radiolabeling methods, camera design, and image analysis have kept PET in the forefront. In addition, the use of PET imaging has expanded because researchers have developed new radiotracers that visualize receptors, transporters, enzymes, and other molecular targets within the human brain. However, of the thousands of proteins in the central nervous system (CNS), researchers have successfully imaged fewer than 40 human proteins. To address the critical need for new radiotracers, this Account expounds on the decisions, strategies, and pitfalls of CNS radiotracer development based on our current experience in this area. We discuss the five key components of radiotracer development for human imaging: choosing a biomedical question, selection of a biological target, design of the radiotracer chemical structure, evaluation of candidate radiotracers, and analysis of preclinical imaging. It is particularly important to analyze the market of scientists or companies who might use a new radiotracer and carefully select a relevant biomedical question(s) for that audience. In the selection of a specific biological target, we emphasize how target localization and identity can constrain this process and discuss the optimal target density and affinity ratios needed for binding-based radiotracers. In addition, we discuss various PET test–retest variability requirements for monitoring changes in density, occupancy, or functionality for new radiotracers. In the synthesis of new radiotracer structures, high-throughput, modular syntheses have proved valuable, and these processes provide compounds with sites for late-stage radioisotope installation. As a result, researchers can manage the time constraints associated with the limited half-lives of isotopes. In order to evaluate brain uptake, a number of methods are available to predict bioavailability, blood–brain barrier (BBB) permeability, and the associated issues of nonspecific binding and metabolic stability. To evaluate the synthesized chemical library, researchers need to consider high-throughput affinity assays, the analysis of specific binding, and the importance of fast binding kinetics. Finally, we describe how we initially assess preclinical radiotracer imaging, using brain uptake, specific binding, and preliminary kinetic analysis to identify promising radiotracers that may be useful for human brain imaging. Although we discuss these five design components separately and linearly in this Account, in practice we develop new PET-based radiotracers using these design components nonlinearly and iteratively to develop new compounds in the most efficient way possible. PMID:25272291

Improved opponent color local binary patterns: an effective local image descriptor for color texture classification

NASA Astrophysics Data System (ADS)

Bianconi, Francesco; Bello-Cerezo, Raquel; Napoletano, Paolo

2018-01-01

Texture classification plays a major role in many computer vision applications. Local binary patterns (LBP) encoding schemes have largely been proven to be very effective for this task. Improved LBP (ILBP) are conceptually simple, easy to implement, and highly effective LBP variants based on a point-to-average thresholding scheme instead of a point-to-point one. We propose the use of this encoding scheme for extracting intra- and interchannel features for color texture classification. We experimentally evaluated the resulting improved opponent color LBP alone and in concatenation with the ILBP of the local color contrast map on a set of image classification tasks over 9 datasets of generic color textures and 11 datasets of biomedical textures. The proposed approach outperformed other grayscale and color LBP variants in nearly all the datasets considered and proved competitive even against image features from last generation convolutional neural networks, particularly for the classification of biomedical images.

Molecular imaging probe development: a chemistry perspective

PubMed Central

Nolting, Donald D; Nickels, Michael L; Guo, Ning; Pham, Wellington

2012-01-01

Molecular imaging is an attractive modality that has been widely employed in many aspects of biomedical research; especially those aimed at the early detection of diseases such as cancer, inflammation and neurodegenerative disorders. The field emerged in response to a new research paradigm in healthcare that seeks to integrate detection capabilities for the prediction and prevention of diseases. This approach made a distinct impact in biomedical research as it enabled researchers to leverage the capabilities of molecular imaging probes to visualize a targeted molecular event non-invasively, repeatedly and continuously in a living system. In addition, since such probes are inherently compact, robust, and amenable to high-throughput production, these probes could potentially facilitate screening of preclinical drug discovery, therapeutic assessment and validation of disease biomarkers. They could also be useful in drug discovery and safety evaluations. In this review, major trends in the chemical synthesis and development of positron emission tomography (PET), optical and magnetic resonance imaging (MRI) probes are discussed. PMID:22943038

Modeling the functional repair of nervous tissue in spinal cord injury

NASA Astrophysics Data System (ADS)

Mantila, Sara M.; Camp, Jon J.; Krych, Aaron J.; Robb, Richard A.

2004-05-01

Functional repair of traumatic spinal cord injury (SCI) is one of the most challenging goals in modern medicine. The annual incidence of SCI in the United States is approximately 11,000 new cases. The prevalence of people in the U.S. currently living with SCI is approximately 200,000. Exploring and understanding nerve regeneration in the central nervous system (CNS) is a critical first step in attempting to reverse the devastating consequences of SCI. At Mayo Clinic, a preliminary study of implants in the transected rat spinal cord model demonstrates potential for promoting axon regeneration. In collaborative research between neuroscientists and bioengineers, this procedure holds promise for solving two critical aspects of axon repair-providing a resorbable structural scaffold to direct focused axon repair, and delivery of relevant signaling molecules necessary to facilitate regeneration. In our preliminary study, regeneration in the rat's spinal cord was modeled in three dimensions utilizing an image processing software system developed in the Biomedical Imaging Resource at Mayo Clinic. Advanced methods for image registration, segmentation, and rendering were used. The raw images were collected at three different magnifications. After image processing the individual channels in the scaffold, axon bundles, and macrophages could be identified. Several axon bundles could be visualized and traced through the entire volume, suggesting axonal growth throughout the length of the scaffold. Such information could potentially allow researchers and physicians to better understand and improve the nerve regeneration process for individuals with SCI.

Medical Image Analysis Facility

NASA Technical Reports Server (NTRS)

1978-01-01

To improve the quality of photos sent to Earth by unmanned spacecraft. NASA's Jet Propulsion Laboratory (JPL) developed a computerized image enhancement process that brings out detail not visible in the basic photo. JPL is now applying this technology to biomedical research in its Medical lrnage Analysis Facility, which employs computer enhancement techniques to analyze x-ray films of internal organs, such as the heart and lung. A major objective is study of the effects of I stress on persons with heart disease. In animal tests, computerized image processing is being used to study coronary artery lesions and the degree to which they reduce arterial blood flow when stress is applied. The photos illustrate the enhancement process. The upper picture is an x-ray photo in which the artery (dotted line) is barely discernible; in the post-enhancement photo at right, the whole artery and the lesions along its wall are clearly visible. The Medical lrnage Analysis Facility offers a faster means of studying the effects of complex coronary lesions in humans, and the research now being conducted on animals is expected to have important application to diagnosis and treatment of human coronary disease. Other uses of the facility's image processing capability include analysis of muscle biopsy and pap smear specimens, and study of the microscopic structure of fibroprotein in the human lung. Working with JPL on experiments are NASA's Ames Research Center, the University of Southern California School of Medicine, and Rancho Los Amigos Hospital, Downey, California.

Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

PubMed Central

Wang, Ge; Zhang, Jie; Gao, Hao; Weir, Victor; Yu, Hengyong; Cong, Wenxiang; Xu, Xiaochen; Shen, Haiou; Bennett, James; Furth, Mark; Wang, Yue; Vannier, Michael

2012-01-01

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine. PMID:22768108

A sprayable luminescent pH sensor and its use for wound imaging in vivo.

PubMed

Schreml, Stephan; Meier, Robert J; Weiß, Katharina T; Cattani, Julia; Flittner, Dagmar; Gehmert, Sebastian; Wolfbeis, Otto S; Landthaler, Michael; Babilas, Philipp

2012-12-01

Non-invasive luminescence imaging is of great interest for studying biological parameters in wound healing, tumors and other biomedical fields. Recently, we developed the first method for 2D luminescence imaging of pH in vivo on humans, and a novel method for one-stop-shop visualization of oxygen and pH using the RGB read-out of digital cameras. Both methods make use of semitransparent sensor foils. Here, we describe a sprayable ratiometric luminescent pH sensor, which combines properties of both these methods. Additionally, a major advantage is that the sensor spray is applicable to very uneven tissue surfaces due to its consistency. A digital RGB image of the spray on tissue is taken. The signal of the pH indicator (fluorescein isothiocyanate) is stored in the green channel (G), while that of the reference dye [ruthenium(II)-tris-(4,7-diphenyl-1,10-phenanthroline)] is stored in the red channel (R). Images are processed by rationing luminescence intensities (G/R) to result in pseudocolor pH maps of tissues, e.g. wounds. © 2012 John Wiley & Sons A/S.

Parallel, confocal, and complete spectrum imager for fluorescent detection of high-density microarray

NASA Astrophysics Data System (ADS)

Bogdanov, Valery L.; Boyce-Jacino, Michael

1999-05-01

Confined arrays of biochemical probes deposited on a solid support surface (analytical microarray or 'chip') provide an opportunity to analysis multiple reactions simultaneously. Microarrays are increasingly used in genetics, medicine and environment scanning as research and analytical instruments. A power of microarray technology comes from its parallelism which grows with array miniaturization, minimization of reagent volume per reaction site and reaction multiplexing. An optical detector of microarray signals should combine high sensitivity, spatial and spectral resolution. Additionally, low-cost and a high processing rate are needed to transfer microarray technology into biomedical practice. We designed an imager that provides confocal and complete spectrum detection of entire fluorescently-labeled microarray in parallel. Imager uses microlens array, non-slit spectral decomposer, and high- sensitive detector (cooled CCD). Two imaging channels provide a simultaneous detection of localization, integrated and spectral intensities for each reaction site in microarray. A dimensional matching between microarray and imager's optics eliminates all in moving parts in instrumentation, enabling highly informative, fast and low-cost microarray detection. We report theory of confocal hyperspectral imaging with microlenses array and experimental data for implementation of developed imager to detect fluorescently labeled microarray with a density approximately 103 sites per cm2.

Automated seeding-based nuclei segmentation in nonlinear optical microscopy.

PubMed

Medyukhina, Anna; Meyer, Tobias; Heuke, Sandro; Vogler, Nadine; Dietzek, Benjamin; Popp, Jürgen

2013-10-01

Nonlinear optical (NLO) microscopy based, e.g., on coherent anti-Stokes Raman scattering (CARS) or two-photon-excited fluorescence (TPEF) is a fast label-free imaging technique, with a great potential for biomedical applications. However, NLO microscopy as a diagnostic tool is still in its infancy; there is a lack of robust and durable nuclei segmentation methods capable of accurate image processing in cases of variable image contrast, nuclear density, and type of investigated tissue. Nonetheless, such algorithms specifically adapted to NLO microscopy present one prerequisite for the technology to be routinely used, e.g., in pathology or intraoperatively for surgical guidance. In this paper, we compare the applicability of different seeding and boundary detection methods to NLO microscopic images in order to develop an optimal seeding-based approach capable of accurate segmentation of both TPEF and CARS images. Among different methods, the Laplacian of Gaussian filter showed the best accuracy for the seeding of the image, while a modified seeded watershed segmentation was the most accurate in the task of boundary detection. The resulting combination of these methods followed by the verification of the detected nuclei performs high average sensitivity and specificity when applied to various types of NLO microscopy images.

A modular framework for biomedical concept recognition

PubMed Central

2013-01-01

Background Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools. Results This article presents Neji, an open source framework optimized for biomedical concept recognition built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules for biomedical natural language processing, such as sentence splitting, tokenization, lemmatization, part-of-speech tagging, chunking and dependency parsing. Concept recognition is provided through dictionary matching and machine learning with normalization methods. Neji also integrates an innovative concept tree implementation, supporting overlapped concept names and respective disambiguation techniques. The most popular input and output formats, namely Pubmed XML, IeXML, CoNLL and A1, are also supported. On top of the built-in functionalities, developers and researchers can implement new processing modules or pipelines, or use the provided command-line interface tool to build their own solutions, applying the most appropriate techniques to identify heterogeneous biomedical concepts. Neji was evaluated against three gold standard corpora with heterogeneous biomedical concepts (CRAFT, AnEM and NCBI disease corpus), achieving high performance results on named entity recognition (F1-measure for overlap matching: species 95%, cell 92%, cellular components 83%, gene and proteins 76%, chemicals 65%, biological processes and molecular functions 63%, disorders 85%, and anatomical entities 82%) and on entity normalization (F1-measure for overlap name matching and correct identifier included in the returned list of identifiers: species 88%, cell 71%, cellular components 72%, gene and proteins 64%, chemicals 53%, and biological processes and molecular functions 40%). Neji provides fast and multi-threaded data processing, annotating up to 1200 sentences/second when using dictionary-based concept identification. Conclusions Considering the provided features and underlying characteristics, we believe that Neji is an important contribution to the biomedical community, streamlining the development of complex concept recognition solutions. Neji is freely available at http://bioinformatics.ua.pt/neji. PMID:24063607

Geometry-constraint-scan imaging for in-line phase contrast micro-CT.

PubMed

Fu, Jian; Yu, Guangyuan; Fan, Dekai

2014-01-01

X-ray phase contrast computed tomography (CT) uses the phase shift that x-rays undergo when passing through matter, rather than their attenuation, as the imaging signal and may provide better image quality in soft-tissue and biomedical materials with low atomic number. Here a geometry-constraint-scan imaging technique for in-line phase contrast micro-CT is reported. It consists of two circular-trajectory scans with x-ray detector at different positions, the phase projection extraction method with the Fresnel free-propagation theory and the filter back-projection reconstruction algorithm. This method removes the contact-detector scan and the pure phase object assumption in classical in-line phase contrast Micro-CT. Consequently it relaxes the experimental conditions and improves the image contrast. This work comprises a numerical study of this technique and its experimental verification using a biomedical composite dataset measured at an x-ray tube source Micro-CT setup. The numerical and experimental results demonstrate the validity of the presented method. It will be of interest for a wide range of in-line phase contrast Micro-CT applications in biology and medicine.

Investigation of skin structures based on infrared wave parameter indirect microscopic imaging

NASA Astrophysics Data System (ADS)

Zhao, Jun; Liu, Xuefeng; Xiong, Jichuan; Zhou, Lijuan

2017-02-01

Detailed imaging and analysis of skin structures are becoming increasingly important in modern healthcare and clinic diagnosis. Nanometer resolution imaging techniques such as SEM and AFM can cause harmful damage to the sample and cannot measure the whole skin structure from the very surface through epidermis, dermis to subcutaneous. Conventional optical microscopy has the highest imaging efficiency, flexibility in onsite applications and lowest cost in manufacturing and usage, but its image resolution is too low to be accepted for biomedical analysis. Infrared parameter indirect microscopic imaging (PIMI) uses an infrared laser as the light source due to its high transmission in skins. The polarization of optical wave through the skin sample was modulated while the variation of the optical field was observed at the imaging plane. The intensity variation curve of each pixel was fitted to extract the near field polarization parameters to form indirect images. During the through-skin light modulation and image retrieving process, the curve fitting removes the blurring scattering from neighboring pixels and keeps only the field variations related to local skin structures. By using the infrared PIMI, we can break the diffraction limit, bring the wide field optical image resolution to sub-200nm, in the meantime of taking advantage of high transmission of infrared waves in skin structures.

Immobilization of biomolecules on the surface of inorganic nanoparticles for biomedical applications

PubMed Central

Xing, Zhi-Cai; Chang, Yongmin; Kang, Inn-Kyu

2010-01-01

Various inorganic nanoparticles have been used for drug delivery, magnetic resonance and fluorescence imaging, and cell targeting owing to their unique properties, such as large surface area and efficient contrasting effect. In this review, we focus on the surface functionalization of inorganic nanoparticles via immobilization of biomolecules and the corresponding surface interactions with biocomponents. Applications of surface-modified inorganic nanoparticles in biomedical fields are also outlined. PMID:27877316

Generation of open biomedical datasets through ontology-driven transformation and integration processes.

PubMed

Carmen Legaz-García, María Del; Miñarro-Giménez, José Antonio; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2016-06-03

Biomedical research usually requires combining large volumes of data from multiple heterogeneous sources, which makes difficult the integrated exploitation of such data. The Semantic Web paradigm offers a natural technological space for data integration and exploitation by generating content readable by machines. Linked Open Data is a Semantic Web initiative that promotes the publication and sharing of data in machine readable semantic formats. We present an approach for the transformation and integration of heterogeneous biomedical data with the objective of generating open biomedical datasets in Semantic Web formats. The transformation of the data is based on the mappings between the entities of the data schema and the ontological infrastructure that provides the meaning to the content. Our approach permits different types of mappings and includes the possibility of defining complex transformation patterns. Once the mappings are defined, they can be automatically applied to datasets to generate logically consistent content and the mappings can be reused in further transformation processes. The results of our research are (1) a common transformation and integration process for heterogeneous biomedical data; (2) the application of Linked Open Data principles to generate interoperable, open, biomedical datasets; (3) a software tool, called SWIT, that implements the approach. In this paper we also describe how we have applied SWIT in different biomedical scenarios and some lessons learned. We have presented an approach that is able to generate open biomedical repositories in Semantic Web formats. SWIT is able to apply the Linked Open Data principles in the generation of the datasets, so allowing for linking their content to external repositories and creating linked open datasets. SWIT datasets may contain data from multiple sources and schemas, thus becoming integrated datasets.

The importance of Zebrafish in biomedical research.

PubMed

Tavares, Bárbara; Santos Lopes, Susana

2013-01-01

Zebrafish (Danio rerio) is an ideal model organism for the study of vertebrate development. This is due to the large clutches that each couple produces, with up to 200 embryos every 7 days, and to the fact that the embryos and larvae are small, transparent and undergo rapid external development. Using scientific literature research tools available online and the keywords Zebrafish, biomedical research, human disease, and drug screening, we reviewed original studies and reviews indexed in PubMed. In this review we summarized work conducted with this model for the advancement of our knowledge related to several human diseases. We also focused on the biomedical research being performed in Portugal with the zebrafish model. Powerful live imaging and genetic tools are currently available for zebrafish making it a valuable model in biomedical research. The combination of these properties with the optimization of automated systems for drug screening has transformed the zebrafish into "a top model" in biomedical research, drug discovery and toxicity testing. Furthermore, with the optimization of xenografts technology it will be possible to use zebrafish to aide in the choice of the best therapy for each patient. Zebrafish is an excellent model organism in biomedical research, drug development and in clinical therapy.

Tutorial on photoacoustic tomography

NASA Astrophysics Data System (ADS)

Zhou, Yong; Yao, Junjie; Wang, Lihong V.

2016-06-01

Photoacoustic tomography (PAT) has become one of the fastest growing fields in biomedical optics. Unlike pure optical imaging, such as confocal microscopy and two-photon microscopy, PAT employs acoustic detection to image optical absorption contrast with high-resolution deep into scattering tissue. So far, PAT has been widely used for multiscale anatomical, functional, and molecular imaging of biological tissues. We focus on PAT's basic principles, major implementations, imaging contrasts, and recent applications.

Functional imaging and assessment of the glucose diffusion rate in epithelial tissues in optical coherence tomography

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

Larin, K V; Tuchin, V V

2008-06-30

Functional imaging, monitoring and quantitative description of glucose diffusion in epithelial and underlying stromal tissues in vivo and controlling of the optical properties of tissues are extremely important for many biomedical applications including the development of noninvasive or minimally invasive glucose sensors as well as for therapy and diagnostics of various diseases, such as cancer, diabetic retinopathy, and glaucoma. Recent progress in the development of a noninvasive molecular diffusion biosensor based on optical coherence tomography (OCT) is described. The diffusion of glucose was studied in several epithelial tissues both in vitro and in vivo. Because OCT provides depth-resolved imaging ofmore » tissues with high in-depth resolution, the glucose diffusion is described not only as a function of time but also as a function of depth. (special issue devoted to application of laser technologies in biophotonics and biomedical studies)« less

Application of Laser Plasma Sources of Soft X-rays and Extreme Ultraviolet (EUV) in Imaging, Processing Materials and Photoionization Studies

NASA Astrophysics Data System (ADS)

Fiedorowicz, H.; Bartnik, A.; Wachulak, P. W.; Jarocki, R.; Kostecki, J.; Szczurek, M.; Ahad, I. U.; Fok, T.; Szczurek, A.; Wȩgrzyński, Ł.

In the paper we present new applications of laser plasma sources of soft X-rays and extreme ultraviolet (EUV) in various areas of plasma physics, nanotechnology and biomedical engineering. The sources are based on a gas puff target irradiated with nanosecond laser pulses from commercial Nd: YAG lasers, generating pulses with time duration from 1 to 10 ns and energies from 0.5 to 10 J at a 10 Hz repetition rate. The targets are produced with the use of a double valve system equipped with a special nozzle to form a double-stream gas puff target which allows for high conversion efficiency of laser energy into soft X-rays and EUV without degradation of the nozzle. The sources are equipped with various optical systems to collect soft X-ray and EUV radiation and form the radiation beam. New applications of these sources in imaging, including EUV tomography and soft X-ray microscopy, processing of materials and photoionization studies are presented.

Particle image velocimetry measurements in an anatomical vascular model fabricated using inkjet 3D printing

NASA Astrophysics Data System (ADS)

Aycock, Kenneth I.; Hariharan, Prasanna; Craven, Brent A.

2017-11-01

For decades, the study of biomedical fluid dynamics using optical flow visualization and measurement techniques has been limited by the inability to fabricate transparent physical models that realistically replicate the complex morphology of biological lumens. In this study, we present an approach for producing optically transparent anatomical models that are suitable for particle image velocimetry (PIV) using a common 3D inkjet printing process (PolyJet) and stock resin (VeroClear). By matching the index of refraction of the VeroClear material using a room-temperature mixture of water, sodium iodide, and glycerol, and by printing the part in an orientation such that the flat, optical surfaces are at an approximately 45° angle to the build plane, we overcome the challenges associated with using this 3D printing technique for PIV. Here, we summarize our methodology and demonstrate the process and the resultant PIV measurements of flow in an optically transparent anatomical model of the human inferior vena cava.

Imaging of Rabbit VX-2 Hepatic Cancer by Cold and Thermal Neutron Radiography

NASA Astrophysics Data System (ADS)

Tsuchiya, Yoshinori; Matsubayashi, Masahito; Takeda, Tohoru; Lwin, Thet Thet; Wu, Jin; Yoneyama, Akio; Matsumura, Akira; Hori, Tomiei; Itai, Yuji

2003-11-01

Neutron radiography is based on differences in neutron mass attenuation coefficients among the elements and is a non-destructive imaging method. To investigate biomedical applications of neutron radiography, imaging of rabbit VX-2 liver cancer was performed using thermal and cold neutron radiography with a neutron imaging plate. Hepatic vessels and VX-2 tumor were clearly observed by neutron radiography, especially by cold neutron imaging. The image contrast of this modality was better than that of absorption-contrast X-ray radiography.

Curriculum in biomedical optics and laser-tissue interactions

NASA Astrophysics Data System (ADS)

Jacques, Steven L.

2003-10-01

A graduate student level curriculum has been developed for teaching the basic principles of how lasers and light interact with biological tissues and materials. The field of Photomedicine can be divided into two topic areas: (1) where tissue affects photons, used for diagnostic sensing, imaging, and spectroscopy of tissues and biomaterials, and (2) where photons affect tissue, used for surgical and therapeutic cutting, dissecting, machining, processing, coagulating, welding, and oxidizing tissues and biomaterials. The courses teach basic principles of tissue optical properties and light transport in tissues, and interaction of lasers and conventional light sources with tissues via photochemical, photothermal and photomechanical mechanisms.

Real-Time Optical Detection of Single Nanoparticles and Viruses Using Heterodyne Interferometry

NASA Astrophysics Data System (ADS)

Mitra, Anirban; Novotny, Lukas

Nanoparticles play a significant role in various fields such as biomedical imaging and diagnostics [1-4], process control in semiconductor manufacturing [5], explosives [6], environmental monitoring and climate change [7, 8], and various other fields. Inhalation of ultrafine particulates in air has been shown to have adverse effects, such as inflammation of lungs or pulmonary and cardiovascular diseases [9, 10]. Nano-sized biological agents and pathogens such as viruses are known to be responsible for a wide variety of human diseases such as flu, AIDS and herpes, and have been used as biowarfare agents [11, 12].

Introducing Theranostics Journal - From the Editor-in-Chief

PubMed Central

Chen, Xiaoyuan (Shawn)

2011-01-01

Theranostics is a multidisciplinary journal that publishes innovative and original research papers reflecting the field of molecular imaging, molecular therapeutics, multifunctional nanoparticle platforms, image-guided therapy, and translational nanomedicine. A broad spectrum of biomedical research that can be applied to future theranostic applications is encouraged. PMID:21547150

Consensus embedding: theory, algorithms and application to segmentation and classification of biomedical data

PubMed Central

2012-01-01

Background Dimensionality reduction (DR) enables the construction of a lower dimensional space (embedding) from a higher dimensional feature space while preserving object-class discriminability. However several popular DR approaches suffer from sensitivity to choice of parameters and/or presence of noise in the data. In this paper, we present a novel DR technique known as consensus embedding that aims to overcome these problems by generating and combining multiple low-dimensional embeddings, hence exploiting the variance among them in a manner similar to ensemble classifier schemes such as Bagging. We demonstrate theoretical properties of consensus embedding which show that it will result in a single stable embedding solution that preserves information more accurately as compared to any individual embedding (generated via DR schemes such as Principal Component Analysis, Graph Embedding, or Locally Linear Embedding). Intelligent sub-sampling (via mean-shift) and code parallelization are utilized to provide for an efficient implementation of the scheme. Results Applications of consensus embedding are shown in the context of classification and clustering as applied to: (1) image partitioning of white matter and gray matter on 10 different synthetic brain MRI images corrupted with 18 different combinations of noise and bias field inhomogeneity, (2) classification of 4 high-dimensional gene-expression datasets, (3) cancer detection (at a pixel-level) on 16 image slices obtained from 2 different high-resolution prostate MRI datasets. In over 200 different experiments concerning classification and segmentation of biomedical data, consensus embedding was found to consistently outperform both linear and non-linear DR methods within all applications considered. Conclusions We have presented a novel framework termed consensus embedding which leverages ensemble classification theory within dimensionality reduction, allowing for application to a wide range of high-dimensional biomedical data classification and segmentation problems. Our generalizable framework allows for improved representation and classification in the context of both imaging and non-imaging data. The algorithm offers a promising solution to problems that currently plague DR methods, and may allow for extension to other areas of biomedical data analysis. PMID:22316103

Enhanced Fluorescence Imaging of Live Cells by Effective Cytosolic Delivery of Probes

PubMed Central

Massignani, Marzia; Canton, Irene; Sun, Tao; Hearnden, Vanessa; MacNeil, Sheila; Blanazs, Adam; Armes, Steven P.; Lewis, Andrew; Battaglia, Giuseppe

2010-01-01

Background Microscopic techniques enable real-space imaging of complex biological events and processes. They have become an essential tool to confirm and complement hypotheses made by biomedical scientists and also allow the re-examination of existing models, hence influencing future investigations. Particularly imaging live cells is crucial for an improved understanding of dynamic biological processes, however hitherto live cell imaging has been limited by the necessity to introduce probes within a cell without altering its physiological and structural integrity. We demonstrate herein that this hurdle can be overcome by effective cytosolic delivery. Principal Findings We show the delivery within several types of mammalian cells using nanometre-sized biomimetic polymer vesicles (a.k.a. polymersomes) that offer both highly efficient cellular uptake and endolysomal escape capability without any effect on the cellular metabolic activity. Such biocompatible polymersomes can encapsulate various types of probes including cell membrane probes and nucleic acid probes as well as labelled nucleic acids, antibodies and quantum dots. Significance We show the delivery of sufficient quantities of probes to the cytosol, allowing sustained functional imaging of live cells over time periods of days to weeks. Finally the combination of such effective staining with three-dimensional imaging by confocal laser scanning microscopy allows cell imaging in complex three-dimensional environments under both mono-culture and co-culture conditions. Thus cell migration and proliferation can be studied in models that are much closer to the in vivo situation. PMID:20454666

Carbon dots: emerging theranostic nanoarchitectures.

PubMed

Mishra, Vijay; Patil, Akshay; Thakur, Sourav; Kesharwani, Prashant

2018-06-01

Nanotechnology has gained significant interest from biomedical and analytical researchers in recent years. Carbon dots (C-dots), a new member of the carbon nanomaterial family, are spherical, nontoxic, biocompatible, and discrete particles less than 10nm in diameter. Research interest has focused on C-dots because of their ultra-compact nanosize, favorable biocompatibility, outstanding photoluminescence, superior electron transfer ability, and versatile surface engineering properties. C-dots show significant potential for use in cellular imaging, biosensing, targeted drug delivery, and other biomedical applications. Here we discuss C-dots, in terms of their physicochemical properties, fabrication techniques, toxicity issues, surface engineering and biomedical potential in drug delivery, targeting as well as bioimaging. Copyright © 2018 Elsevier Ltd. All rights reserved.

In-line phase contrast micro-CT reconstruction for biomedical specimens.

PubMed

Fu, Jian; Tan, Renbo

2014-01-01

X-ray phase contrast micro computed tomography (micro-CT) can non-destructively provide the internal structure information of soft tissues and low atomic number materials. It has become an invaluable analysis tool for biomedical specimens. Here an in-line phase contrast micro-CT reconstruction technique is reported, which consists of a projection extraction method and the conventional filter back-projection (FBP) reconstruction algorithm. The projection extraction is implemented by applying the Fourier transform to the forward projections of in-line phase contrast micro-CT. This work comprises a numerical study of the method and its experimental verification using a biomedical specimen dataset measured at an X-ray tube source micro-CT setup. The numerical and experimental results demonstrate that the presented technique can improve the imaging contrast of biomedical specimens. It will be of interest for a wide range of in-line phase contrast micro-CT applications in medicine and biology.

The surface science of nanocrystals

NASA Astrophysics Data System (ADS)

Boles, Michael A.; Ling, Daishun; Hyeon, Taeghwan; Talapin, Dmitri V.

2016-02-01

All nanomaterials share a common feature of large surface-to-volume ratio, making their surfaces the dominant player in many physical and chemical processes. Surface ligands -- molecules that bind to the surface -- are an essential component of nanomaterial synthesis, processing and application. Understanding the structure and properties of nanoscale interfaces requires an intricate mix of concepts and techniques borrowed from surface science and coordination chemistry. Our Review elaborates these connections and discusses the bonding, electronic structure and chemical transformations at nanomaterial surfaces. We specifically focus on the role of surface ligands in tuning and rationally designing properties of functional nanomaterials. Given their importance for biomedical (imaging, diagnostics and therapeutics) and optoelectronic (light-emitting devices, transistors, solar cells) applications, we end with an assessment of application-targeted surface engineering.

From synchrotron radiation to lab source: advanced speckle-based X-ray imaging using abrasive paper

NASA Astrophysics Data System (ADS)

Wang, Hongchang; Kashyap, Yogesh; Sawhney, Kawal

2016-02-01

X-ray phase and dark-field imaging techniques provide complementary and inaccessible information compared to conventional X-ray absorption or visible light imaging. However, such methods typically require sophisticated experimental apparatus or X-ray beams with specific properties. Recently, an X-ray speckle-based technique has shown great potential for X-ray phase and dark-field imaging using a simple experimental arrangement. However, it still suffers from either poor resolution or the time consuming process of collecting a large number of images. To overcome these limitations, in this report we demonstrate that absorption, dark-field, phase contrast, and two orthogonal differential phase contrast images can simultaneously be generated by scanning a piece of abrasive paper in only one direction. We propose a novel theoretical approach to quantitatively extract the above five images by utilising the remarkable properties of speckles. Importantly, the technique has been extended from a synchrotron light source to utilise a lab-based microfocus X-ray source and flat panel detector. Removing the need to raster the optics in two directions significantly reduces the acquisition time and absorbed dose, which can be of vital importance for many biological samples. This new imaging method could potentially provide a breakthrough for numerous practical imaging applications in biomedical research and materials science.

Sparsity-based multi-height phase recovery in holographic microscopy

NASA Astrophysics Data System (ADS)

Rivenson, Yair; Wu, Yichen; Wang, Hongda; Zhang, Yibo; Feizi, Alborz; Ozcan, Aydogan

2016-11-01

High-resolution imaging of densely connected samples such as pathology slides using digital in-line holographic microscopy requires the acquisition of several holograms, e.g., at >6-8 different sample-to-sensor distances, to achieve robust phase recovery and coherent imaging of specimen. Reducing the number of these holographic measurements would normally result in reconstruction artifacts and loss of image quality, which would be detrimental especially for biomedical and diagnostics-related applications. Inspired by the fact that most natural images are sparse in some domain, here we introduce a sparsity-based phase reconstruction technique implemented in wavelet domain to achieve at least 2-fold reduction in the number of holographic measurements for coherent imaging of densely connected samples with minimal impact on the reconstructed image quality, quantified using a structural similarity index. We demonstrated the success of this approach by imaging Papanicolaou smears and breast cancer tissue slides over a large field-of-view of ~20 mm2 using 2 in-line holograms that are acquired at different sample-to-sensor distances and processed using sparsity-based multi-height phase recovery. This new phase recovery approach that makes use of sparsity can also be extended to other coherent imaging schemes, involving e.g., multiple illumination angles or wavelengths to increase the throughput and speed of coherent imaging.