Multi-Modal Nano-Probes for Radionuclide and 5-color Near Infrared Optical Lymphatic Imaging

PubMed Central

Kobayashi, Hisataka; Koyama, Yoshinori; Barrett, Tristan; Hama, Yukihiro; Regino, Celeste A. S.; Shin, In Soo; Jang, Beom-Su; Le, Nhat; Paik, Chang H.; Choyke, Peter L.; Urano, Yasuteru

2008-01-01

Current contrast agents generally have one function and can only be imaged in monochrome, therefore, the majority of imaging methods can only impart uniparametric information. A single nano-particle has the potential to be loaded with multiple payloads. Such multi-modality probes have the ability to be imaged by more than one imaging technique, which could compensate for the weakness or even combine the advantages of each individual modality. Furthermore, optical imaging using different optical probes enables us to achieve multi-color in vivo imaging, wherein multiple parameters can be read from a single image. To allow differentiation of multiple optical signals in vivo, each probe should have a close but different near infrared emission. To this end, we synthesized nano-probes with multi-modal and multi-color potential, which employed a polyamidoamine dendrimer platform linked to both radionuclides and optical probes, permitting dual-modality scintigraphic and 5-color near infrared optical lymphatic imaging using a multiple excitation spectrally-resolved fluorescence imaging technique. PMID:19079788

Exogenous Molecular Probes for Targeted Imaging in Cancer: Focus on Multi-modal Imaging

PubMed Central

Joshi, Bishnu P.; Wang, Thomas D.

2010-01-01

Cancer is one of the major causes of mortality and morbidity in our healthcare system. Molecular imaging is an emerging methodology for the early detection of cancer, guidance of therapy, and monitoring of response. The development of new instruments and exogenous molecular probes that can be labeled for multi-modality imaging is critical to this process. Today, molecular imaging is at a crossroad, and new targeted imaging agents are expected to broadly expand our ability to detect and manage cancer. This integrated imaging strategy will permit clinicians to not only localize lesions within the body but also to manage their therapy by visualizing the expression and activity of specific molecules. This information is expected to have a major impact on drug development and understanding of basic cancer biology. At this time, a number of molecular probes have been developed by conjugating various labels to affinity ligands for targeting in different imaging modalities. This review will describe the current status of exogenous molecular probes for optical, scintigraphic, MRI and ultrasound imaging platforms. Furthermore, we will also shed light on how these techniques can be used synergistically in multi-modal platforms and how these techniques are being employed in current research. PMID:22180839

Visual tracking for multi-modality computer-assisted image guidance

NASA Astrophysics Data System (ADS)

Basafa, Ehsan; Foroughi, Pezhman; Hossbach, Martin; Bhanushali, Jasmine; Stolka, Philipp

2017-03-01

With optical cameras, many interventional navigation tasks previously relying on EM, optical, or mechanical guidance can be performed robustly, quickly, and conveniently. We developed a family of novel guidance systems based on wide-spectrum cameras and vision algorithms for real-time tracking of interventional instruments and multi-modality markers. These navigation systems support the localization of anatomical targets, support placement of imaging probe and instruments, and provide fusion imaging. The unique architecture - low-cost, miniature, in-hand stereo vision cameras fitted directly to imaging probes - allows for an intuitive workflow that fits a wide variety of specialties such as anesthesiology, interventional radiology, interventional oncology, emergency medicine, urology, and others, many of which see increasing pressure to utilize medical imaging and especially ultrasound, but have yet to develop the requisite skills for reliable success. We developed a modular system, consisting of hardware (the Optical Head containing the mini cameras) and software (components for visual instrument tracking with or without specialized visual features, fully automated marker segmentation from a variety of 3D imaging modalities, visual observation of meshes of widely separated markers, instant automatic registration, and target tracking and guidance on real-time multi-modality fusion views). From these components, we implemented a family of distinct clinical and pre-clinical systems (for combinations of ultrasound, CT, CBCT, and MRI), most of which have international regulatory clearance for clinical use. We present technical and clinical results on phantoms, ex- and in-vivo animals, and patients.

Cross contrast multi-channel image registration using image synthesis for MR brain images.

PubMed

Chen, Min; Carass, Aaron; Jog, Amod; Lee, Junghoon; Roy, Snehashis; Prince, Jerry L

2017-02-01

Multi-modal deformable registration is important for many medical image analysis tasks such as atlas alignment, image fusion, and distortion correction. Whereas a conventional method would register images with different modalities using modality independent features or information theoretic metrics such as mutual information, this paper presents a new framework that addresses the problem using a two-channel registration algorithm capable of using mono-modal similarity measures such as sum of squared differences or cross-correlation. To make it possible to use these same-modality measures, image synthesis is used to create proxy images for the opposite modality as well as intensity-normalized images from each of the two available images. The new deformable registration framework was evaluated by performing intra-subject deformation recovery, intra-subject boundary alignment, and inter-subject label transfer experiments using multi-contrast magnetic resonance brain imaging data. Three different multi-channel registration algorithms were evaluated, revealing that the framework is robust to the multi-channel deformable registration algorithm that is used. With a single exception, all results demonstrated improvements when compared against single channel registrations using the same algorithm with mutual information. Copyright © 2016 Elsevier B.V. All rights reserved.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

Enhancing image classification models with multi-modal biomarkers

NASA Astrophysics Data System (ADS)

Caban, Jesus J.; Liao, David; Yao, Jianhua; Mollura, Daniel J.; Gochuico, Bernadette; Yoo, Terry

2011-03-01

Currently, most computer-aided diagnosis (CAD) systems rely on image analysis and statistical models to diagnose, quantify, and monitor the progression of a particular disease. In general, CAD systems have proven to be effective at providing quantitative measurements and assisting physicians during the decision-making process. As the need for more flexible and effective CADs continues to grow, questions about how to enhance their accuracy have surged. In this paper, we show how statistical image models can be augmented with multi-modal physiological values to create more robust, stable, and accurate CAD systems. In particular, this paper demonstrates how highly correlated blood and EKG features can be treated as biomarkers and used to enhance image classification models designed to automatically score subjects with pulmonary fibrosis. In our results, a 3-5% improvement was observed when comparing the accuracy of CADs that use multi-modal biomarkers with those that only used image features. Our results show that lab values such as Erythrocyte Sedimentation Rate and Fibrinogen, as well as EKG measurements such as QRS and I:40, are statistically significant and can provide valuable insights about the severity of the pulmonary fibrosis disease.

Multimodal Imaging of Human Brain Activity: Rational, Biophysical Aspects and Modes of Integration

PubMed Central

Blinowska, Katarzyna; Müller-Putz, Gernot; Kaiser, Vera; Astolfi, Laura; Vanderperren, Katrien; Van Huffel, Sabine; Lemieux, Louis

2009-01-01

Until relatively recently the vast majority of imaging and electrophysiological studies of human brain activity have relied on single-modality measurements usually correlated with readily observable or experimentally modified behavioural or brain state patterns. Multi-modal imaging is the concept of bringing together observations or measurements from different instruments. We discuss the aims of multi-modal imaging and the ways in which it can be accomplished using representative applications. Given the importance of haemodynamic and electrophysiological signals in current multi-modal imaging applications, we also review some of the basic physiology relevant to understanding their relationship. PMID:19547657

XML-based scripting of multimodality image presentations in multidisciplinary clinical conferences

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Allada, Vivekanand; Dahlbom, Magdalena; Marcus, Phillip; Fine, Ian; Lapstra, Lorelle

2002-05-01

We developed a multi-modality image presentation software for display and analysis of images and related data from different imaging modalities. The software is part of a cardiac image review and presentation platform that supports integration of digital images and data from digital and analog media such as videotapes, analog x-ray films and 35 mm cine films. The software supports standard DICOM image files as well as AVI and PDF data formats. The system is integrated in a digital conferencing room that includes projections of digital and analog sources, remote videoconferencing capabilities, and an electronic whiteboard. The goal of this pilot project is to: 1) develop a new paradigm for image and data management for presentation in a clinically meaningful sequence adapted to case-specific scenarios, 2) design and implement a multi-modality review and conferencing workstation using component technology and customizable 'plug-in' architecture to support complex review and diagnostic tasks applicable to all cardiac imaging modalities and 3) develop an XML-based scripting model of image and data presentation for clinical review and decision making during routine clinical tasks and multidisciplinary clinical conferences.

Hybrid-modality high-resolution imaging: for diagnostic biomedical imaging and sensing for disease diagnosis

NASA Astrophysics Data System (ADS)

Murukeshan, Vadakke M.; Hoong Ta, Lim

2014-11-01

Medical diagnostics in the recent past has seen the challenging trend to come up with dual and multi-modality imaging for implementing better diagnostic procedures. The changes in tissues in the early disease stages are often subtle and can occur beneath the tissue surface. In most of these cases, conventional types of medical imaging using optics may not be able to detect these changes easily due to its penetration depth of the orders of 1 mm. Each imaging modality has its own advantages and limitations, and the use of a single modality is not suitable for every diagnostic applications. Therefore the need for multi or hybrid-modality imaging arises. Combining more than one imaging modalities overcomes the limitation of individual imaging method and integrates the respective advantages into a single setting. In this context, this paper will be focusing on the research and development of two multi-modality imaging platforms. The first platform combines ultrasound and photoacoustic imaging for diagnostic applications in the eye. The second platform consists of optical hyperspectral and photoacoustic imaging for diagnostic applications in the colon. Photoacoustic imaging is used as one of the modalities in both platforms as it can offer deeper penetration depth compared to optical imaging. The optical engineering and research challenges in developing the dual/multi-modality platforms will be discussed, followed by initial results validating the proposed scheme. The proposed schemes offer high spatial and spectral resolution imaging and sensing, and is expected to offer potential biomedical imaging solutions in the near future.

WE-H-206-03: Promises and Challenges of Benchtop X-Ray Fluorescence CT (XFCT) for Quantitative in Vivo Imaging

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

Cho, S.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

WE-H-206-01: Photoacoustic Tomography: Multiscale Imaging From Organelles to Patients by Ultrasonically Beating the Optical Diffusion Limit

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

Wang, L.

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

WE-H-206-00: Advances in Preclinical Imaging

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

NONE

Lihong V. Wang: Photoacoustic tomography (PAT), combining non-ionizing optical and ultrasonic waves via the photoacoustic effect, provides in vivo multiscale functional, metabolic, and molecular imaging. Broad applications include imaging of the breast, brain, skin, esophagus, colon, vascular system, and lymphatic system in humans or animals. Light offers rich contrast but does not penetrate biological tissue in straight paths as x-rays do. Consequently, high-resolution pure optical imaging (e.g., confocal microscopy, two-photon microscopy, and optical coherence tomography) is limited to penetration within the optical diffusion limit (∼1 mm in the skin). Ultrasonic imaging, on the contrary, provides fine spatial resolution but suffersmore » from both poor contrast in early-stage tumors and strong speckle artifacts. In PAT, pulsed laser light penetrates tissue and generates a small but rapid temperature rise, which induces emission of ultrasonic waves due to thermoelastic expansion. The ultrasonic waves, orders of magnitude less scattering than optical waves, are then detected to form high-resolution images of optical absorption at depths up to 7 cm, conquering the optical diffusion limit. PAT is the only modality capable of imaging across the length scales of organelles, cells, tissues, and organs (up to whole-body small animals) with consistent contrast. This rapidly growing technology promises to enable multiscale biological research and accelerate translation from microscopic laboratory discoveries to macroscopic clinical practice. PAT may also hold the key to label-free early detection of cancer by in vivo quantification of hypermetabolism, the quintessential hallmark of malignancy. Learning Objectives: To understand the contrast mechanism of PAT To understand the multiscale applications of PAT Benjamin M. W. Tsui: Multi-modality molecular imaging instrumentation and techniques have been major developments in small animal imaging that has contributed significantly to biomedical research during the past decade. The initial development was an extension of clinical PET/CT and SPECT/CT from human to small animals and combine the unique functional information obtained from PET and SPECT with anatomical information provided by the CT in registered multi-modality images. The requirements to image a mouse whose size is an order of magnitude smaller than that of a human have spurred advances in new radiation detector technologies, novel imaging system designs and special image reconstruction and processing techniques. Examples are new detector materials and designs with high intrinsic resolution, multi-pinhole (MPH) collimator design for much improved resolution and detection efficiency compared to the conventional collimator designs in SPECT, 3D high-resolution and artifact-free MPH and sparse-view image reconstruction techniques, and iterative image reconstruction methods with system response modeling for resolution recovery and image noise reduction for much improved image quality. The spatial resolution of PET and SPECT has improved from ∼6–12 mm to ∼1 mm a few years ago to sub-millimeter today. A recent commercial small animal SPECT system has achieved a resolution of ∼0.25 mm which surpasses that of a state-of-art PET system whose resolution is limited by the positron range. More recently, multimodality SA PET/MRI and SPECT/MRI systems have been developed in research laboratories. Also, multi-modality SA imaging systems that include other imaging modalities such as optical and ultrasound are being actively pursued. In this presentation, we will provide a review of the development, recent advances and future outlook of multi-modality molecular imaging of small animals. Learning Objectives: To learn about the two major multi-modality molecular imaging techniques of small animals. To learn about the spatial resolution achievable by the molecular imaging systems for small animal today. To learn about the new multi-modality imaging instrumentation and techniques that are being developed. Sang Hyun Cho; X-ray fluorescence (XRF) imaging, such as x-ray fluorescence computed tomography (XFCT), offers unique capabilities for accurate identification and quantification of metals within the imaging objects. As a result, it has emerged as a promising quantitative imaging modality in recent years, especially in conjunction with metal-based imaging probes. This talk will familiarize the audience with the basic principles of XRF/XFCT imaging. It will also cover the latest development of benchtop XFCT technology. Additionally, the use of metallic nanoparticles such as gold nanoparticles, in conjunction with benchtop XFCT, will be discussed within the context of preclinical multimodal multiplexed molecular imaging. Learning Objectives: To learn the basic principles of XRF/XFCT imaging To learn the latest advances in benchtop XFCT development for preclinical imaging Funding support received from NIH and DOD; Funding support received from GE Healthcare; Funding support received from Siemens AX; Patent royalties received from GE Healthcare; L. Wang, Funding Support: NIH; COI: Microphotoacoustics; S. Cho, Yes: ;NIH/NCI grant R01CA155446 DOD/PCRP grant W81XWH-12-1-0198.« less

Intraoperative imaging-guided cancer surgery: from current fluorescence molecular imaging methods to future multi-modality imaging technology.

PubMed

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery.

Intraoperative Imaging-Guided Cancer Surgery: From Current Fluorescence Molecular Imaging Methods to Future Multi-Modality Imaging Technology

PubMed Central

Chi, Chongwei; Du, Yang; Ye, Jinzuo; Kou, Deqiang; Qiu, Jingdan; Wang, Jiandong; Tian, Jie; Chen, Xiaoyuan

2014-01-01

Cancer is a major threat to human health. Diagnosis and treatment using precision medicine is expected to be an effective method for preventing the initiation and progression of cancer. Although anatomical and functional imaging techniques such as radiography, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) have played an important role for accurate preoperative diagnostics, for the most part these techniques cannot be applied intraoperatively. Optical molecular imaging is a promising technique that provides a high degree of sensitivity and specificity in tumor margin detection. Furthermore, existing clinical applications have proven that optical molecular imaging is a powerful intraoperative tool for guiding surgeons performing precision procedures, thus enabling radical resection and improved survival rates. However, detection depth limitation exists in optical molecular imaging methods and further breakthroughs from optical to multi-modality intraoperative imaging methods are needed to develop more extensive and comprehensive intraoperative applications. Here, we review the current intraoperative optical molecular imaging technologies, focusing on contrast agents and surgical navigation systems, and then discuss the future prospects of multi-modality imaging technology for intraoperative imaging-guided cancer surgery. PMID:25250092

Cross-Modality Image Synthesis via Weakly Coupled and Geometry Co-Regularized Joint Dictionary Learning.

PubMed

Huang, Yawen; Shao, Ling; Frangi, Alejandro F

2018-03-01

Multi-modality medical imaging is increasingly used for comprehensive assessment of complex diseases in either diagnostic examinations or as part of medical research trials. Different imaging modalities provide complementary information about living tissues. However, multi-modal examinations are not always possible due to adversary factors, such as patient discomfort, increased cost, prolonged scanning time, and scanner unavailability. In additionally, in large imaging studies, incomplete records are not uncommon owing to image artifacts, data corruption or data loss, which compromise the potential of multi-modal acquisitions. In this paper, we propose a weakly coupled and geometry co-regularized joint dictionary learning method to address the problem of cross-modality synthesis while considering the fact that collecting the large amounts of training data is often impractical. Our learning stage requires only a few registered multi-modality image pairs as training data. To employ both paired images and a large set of unpaired data, a cross-modality image matching criterion is proposed. Then, we propose a unified model by integrating such a criterion into the joint dictionary learning and the observed common feature space for associating cross-modality data for the purpose of synthesis. Furthermore, two regularization terms are added to construct robust sparse representations. Our experimental results demonstrate superior performance of the proposed model over state-of-the-art methods.

Multi-modal molecular diffuse optical tomography system for small animal imaging

PubMed Central

Guggenheim, James A.; Basevi, Hector R. A.; Frampton, Jon; Styles, Iain B.; Dehghani, Hamid

2013-01-01

A multi-modal optical imaging system for quantitative 3D bioluminescence and functional diffuse imaging is presented, which has no moving parts and uses mirrors to provide multi-view tomographic data for image reconstruction. It is demonstrated that through the use of trans-illuminated spectral near infrared measurements and spectrally constrained tomographic reconstruction, recovered concentrations of absorbing agents can be used as prior knowledge for bioluminescence imaging within the visible spectrum. Additionally, the first use of a recently developed multi-view optical surface capture technique is shown and its application to model-based image reconstruction and free-space light modelling is demonstrated. The benefits of model-based tomographic image recovery as compared to 2D planar imaging are highlighted in a number of scenarios where the internal luminescence source is not visible or is confounding in 2D images. The results presented show that the luminescence tomographic imaging method produces 3D reconstructions of individual light sources within a mouse-sized solid phantom that are accurately localised to within 1.5mm for a range of target locations and depths indicating sensitivity and accurate imaging throughout the phantom volume. Additionally the total reconstructed luminescence source intensity is consistent to within 15% which is a dramatic improvement upon standard bioluminescence imaging. Finally, results from a heterogeneous phantom with an absorbing anomaly are presented demonstrating the use and benefits of a multi-view, spectrally constrained coupled imaging system that provides accurate 3D luminescence images. PMID:24954977

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.

PubMed

Li, Xiaomeng; Dou, Qi; Chen, Hao; Fu, Chi-Wing; Qi, Xiaojuan; Belavý, Daniel L; Armbrecht, Gabriele; Felsenberg, Dieter; Zheng, Guoyan; Heng, Pheng-Ann

2018-04-01

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on extended data collected from two different time points demonstrate the efficacy of our method on tracking the morphological changes in a longitudinal study. Copyright © 2018 Elsevier B.V. All rights reserved.

MINC 2.0: A Flexible Format for Multi-Modal Images.

PubMed

Vincent, Robert D; Neelin, Peter; Khalili-Mahani, Najmeh; Janke, Andrew L; Fonov, Vladimir S; Robbins, Steven M; Baghdadi, Leila; Lerch, Jason; Sled, John G; Adalat, Reza; MacDonald, David; Zijdenbos, Alex P; Collins, D Louis; Evans, Alan C

2016-01-01

It is often useful that an imaging data format can afford rich metadata, be flexible, scale to very large file sizes, support multi-modal data, and have strong inbuilt mechanisms for data provenance. Beginning in 1992, MINC was developed as a system for flexible, self-documenting representation of neuroscientific imaging data with arbitrary orientation and dimensionality. The MINC system incorporates three broad components: a file format specification, a programming library, and a growing set of tools. In the early 2000's the MINC developers created MINC 2.0, which added support for 64-bit file sizes, internal compression, and a number of other modern features. Because of its extensible design, it has been easy to incorporate details of provenance in the header metadata, including an explicit processing history, unique identifiers, and vendor-specific scanner settings. This makes MINC ideal for use in large scale imaging studies and databases. It also makes it easy to adapt to new scanning sequences and modalities.

Results from the commissioning of a multi-modal endoscope for ultrasound and time of flight PET

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

Bugalho, Ricardo

2015-07-01

The EndoTOFPET-US collaboration has developed a multi-modal imaging system combining Ultrasound with Time-of-Flight Positron Emission Tomography into an endoscopic imaging device. The objective of the project is to obtain a coincidence time resolution of about 200 ps FWHM and to achieve about 1 mm spatial resolution of the PET system, while integrating all the components in a very compact detector suitable for endoscopic use. This scanner aims to be exploited for diagnostic and surgical oncology, as well as being instrumental in the clinical test of new biomarkers especially targeted for prostate and pancreatic cancer. (authors)

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

PubMed Central

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

2014-01-01

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

A multi-image approach to CADx of breast cancer with integration into PACS

NASA Astrophysics Data System (ADS)

Elter, Matthias; Wittenberg, Thomas; Schulz-Wendtland, Rüdiger; Deserno, Thomas M.

2009-02-01

While screening mammography is accepted as the most adequate technique for the early detection of breast cancer, its low positive predictive value leads to many breast biopsies performed on benign lesions. Therefore, we have previously developed a knowledge-based system for computer-aided diagnosis (CADx) of mammographic lesions. It supports the radiologist in the discrimination of benign and malignant lesions. So far, our approach operates on the lesion level and employs the paradigm of content-based image retrieval (CBIR). Similar lesions with known diagnosis are retrieved automatically from a library of references. However, radiologists base their diagnostic decisions on additional resources, such as related mammographic projections, other modalities (e.g. ultrasound, MRI), and clinical data. Nonetheless, most CADx systems disregard the relation between the craniocaudal (CC) and mediolateral-oblique (MLO) views of conventional mammography. Therefore, we extend our approach to the full case level: (i) Multi-frame features are developed that jointly describe a lesion in different views of mammography. Taking into account the geometric relation between different images, these features can also be extracted from multi-modal data; (ii) the CADx system architecture is extended appropriately; (iii) the CADx system is integrated into the radiology information system (RIS) and the picture archiving and communication system (PACS). Here, the framework for image retrieval in medical applications (IRMA) is used to support access to the patient's health care record. Of particular interest is the application of the proposed CADx system to digital breast tomosynthesis (DBT), which has the potential to succeed digital mammography as the standard technique for breast cancer screening. The proposed system is a natural extension of CADx approaches that integrate only two modalities. However, we are still collecting a large enough database of breast lesions with images from multiple modalities to evaluate the benefits of the proposed approach on.

A versatile clearing agent for multi-modal brain imaging

PubMed Central

Costantini, Irene; Ghobril, Jean-Pierre; Di Giovanna, Antonino Paolo; Mascaro, Anna Letizia Allegra; Silvestri, Ludovico; Müllenbroich, Marie Caroline; Onofri, Leonardo; Conti, Valerio; Vanzi, Francesco; Sacconi, Leonardo; Guerrini, Renzo; Markram, Henry; Iannello, Giulio; Pavone, Francesco Saverio

2015-01-01

Extensive mapping of neuronal connections in the central nervous system requires high-throughput µm-scale imaging of large volumes. In recent years, different approaches have been developed to overcome the limitations due to tissue light scattering. These methods are generally developed to improve the performance of a specific imaging modality, thus limiting comprehensive neuroanatomical exploration by multi-modal optical techniques. Here, we introduce a versatile brain clearing agent (2,2′-thiodiethanol; TDE) suitable for various applications and imaging techniques. TDE is cost-efficient, water-soluble and low-viscous and, more importantly, it preserves fluorescence, is compatible with immunostaining and does not cause deformations at sub-cellular level. We demonstrate the effectiveness of this method in different applications: in fixed samples by imaging a whole mouse hippocampus with serial two-photon tomography; in combination with CLARITY by reconstructing an entire mouse brain with light sheet microscopy and in translational research by imaging immunostained human dysplastic brain tissue. PMID:25950610

Composite PET and MRI for accurate localization and metabolic modeling: a very useful tool for research and clinic

NASA Astrophysics Data System (ADS)

Bidaut, Luc M.

1991-06-01

In order to help in analyzing PET data and really take advantage of their metabolic content, a system was designed and implemented to align and process data from various medical imaging modalities, particularly (but not only) for brain studies. Although this system is for now mostly used for anatomical localization, multi-modality ROIs and pharmaco-kinetic modeling, more multi-modality protocols will be implemented in the future, not only to help in PET reconstruction data correction and semi-automated ROI definition, but also for helping in improving diagnostic accuracy along with surgery and therapy planning.

The sweet spot: FDG and other 2-carbon glucose analogs for multi-modal metabolic imaging of tumor metabolism

PubMed Central

Cox, Benjamin L; Mackie, Thomas R; Eliceiri, Kevin W

2015-01-01

Multi-modal imaging approaches of tumor metabolism that provide improved specificity, physiological relevance and spatial resolution would improve diagnosing of tumors and evaluation of tumor progression. Currently, the molecular probe FDG, glucose fluorinated with 18F at the 2-carbon, is the primary metabolic approach for clinical diagnostics with PET imaging. However, PET lacks the resolution necessary to yield intratumoral distributions of deoxyglucose, on the cellular level. Multi-modal imaging could elucidate this problem, but requires the development of new glucose analogs that are better suited for other imaging modalities. Several such analogs have been created and are reviewed here. Also reviewed are several multi-modal imaging studies that have been performed that attempt to shed light on the cellular distribution of glucose analogs within tumors. Some of these studies are performed in vitro, while others are performed in vivo, in an animal model. The results from these studies introduce a visualization gap between the in vitro and in vivo studies that, if solved, could enable the early detection of tumors, the high resolution monitoring of tumors during treatment, and the greater accuracy in assessment of different imaging agents. PMID:25625022

Validation of diffuse optical tomography using a bi-functional optical-MRI contrast agent and a hybrid MRI-DOT system

NASA Astrophysics Data System (ADS)

Luk, Alex T.; Lin, Yuting; Grimmond, Brian; Sood, Anup; Uzgiris, Egidijus E.; Nalcioglu, Orhan; Gulsen, Gultekin

2013-03-01

Since diffuse optical tomography (DOT) is a low spatial resolution modality, it is desirable to validate its quantitative accuracy with another well-established imaging modality, such as magnetic resonance imaging (MRI). In this work, we have used a polymer based bi-functional MRI-optical contrast agent (Gd-DTPA-polylysine-IR800) in collaboration with GE Global Research. This multi-modality contrast agent provided not only co-localization but also the same kinetics, to cross-validate two imaging modalities. Bi-functional agents are injected to the rats and pharmacokinetics at the bladder are recovered using both optical and MR imaging. DOT results are validated using MRI results as "gold standard"

Quantitative reconstructions in multi-modal photoacoustic and optical coherence tomography imaging

NASA Astrophysics Data System (ADS)

Elbau, P.; Mindrinos, L.; Scherzer, O.

2018-01-01

In this paper we perform quantitative reconstruction of the electric susceptibility and the Grüneisen parameter of a non-magnetic linear dielectric medium using measurement of a multi-modal photoacoustic and optical coherence tomography system. We consider the mathematical model presented in Elbau et al (2015 Handbook of Mathematical Methods in Imaging ed O Scherzer (New York: Springer) pp 1169-204), where a Fredholm integral equation of the first kind for the Grüneisen parameter was derived. For the numerical solution of the integral equation we consider a Galerkin type method.

Volume curtaining: a focus+context effect for multimodal volume visualization

NASA Astrophysics Data System (ADS)

Fairfield, Adam J.; Plasencia, Jonathan; Jang, Yun; Theodore, Nicholas; Crawford, Neil R.; Frakes, David H.; Maciejewski, Ross

2014-03-01

In surgical preparation, physicians will often utilize multimodal imaging scans to capture complementary information to improve diagnosis and to drive patient-specific treatment. These imaging scans may consist of data from magnetic resonance imaging (MR), computed tomography (CT), or other various sources. The challenge in using these different modalities is that the physician must mentally map the two modalities together during the diagnosis and planning phase. Furthermore, the different imaging modalities will be generated at various resolutions as well as slightly different orientations due to patient placement during scans. In this work, we present an interactive system for multimodal data fusion, analysis and visualization. Developed with partners from neurological clinics, this work discusses initial system requirements and physician feedback at the various stages of component development. Finally, we present a novel focus+context technique for the interactive exploration of coregistered multi-modal data.

Simulation of brain tumors in MR images for evaluation of segmentation efficacy.

PubMed

Prastawa, Marcel; Bullitt, Elizabeth; Gerig, Guido

2009-04-01

Obtaining validation data and comparison metrics for segmentation of magnetic resonance images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even more evident for images presenting pathology, which can both alter tissue appearance through infiltration and cause geometric distortions. Systems for generating synthetic images with user-defined degradation by noise and intensity inhomogeneity offer the possibility for testing and comparison of segmentation methods. Such systems do not yet offer simulation of sufficiently realistic looking pathology. This paper presents a system that combines physical and statistical modeling to generate synthetic multi-modal 3D brain MRI with tumor and edema, along with the underlying anatomical ground truth, Main emphasis is placed on simulation of the major effects known for tumor MRI, such as contrast enhancement, local distortion of healthy tissue, infiltrating edema adjacent to tumors, destruction and deformation of fiber tracts, and multi-modal MRI contrast of healthy tissue and pathology. The new method synthesizes pathology in multi-modal MRI and diffusion tensor imaging (DTI) by simulating mass effect, warping and destruction of white matter fibers, and infiltration of brain tissues by tumor cells. We generate synthetic contrast enhanced MR images by simulating the accumulation of contrast agent within the brain. The appearance of the the brain tissue and tumor in MRI is simulated by synthesizing texture images from real MR images. The proposed method is able to generate synthetic ground truth and synthesized MR images with tumor and edema that exhibit comparable segmentation challenges to real tumor MRI. Such image data sets will find use in segmentation reliability studies, comparison and validation of different segmentation methods, training and teaching, or even in evaluating standards for tumor size like the RECIST criteria (response evaluation criteria in solid tumors).

Wave analysis of a plenoptic system and its applications

NASA Astrophysics Data System (ADS)

Shroff, Sapna A.; Berkner, Kathrin

2013-03-01

Traditional imaging systems directly image a 2D object plane on to the sensor. Plenoptic imaging systems contain a lenslet array at the conventional image plane and a sensor at the back focal plane of the lenslet array. In this configuration the data captured at the sensor is not a direct image of the object. Each lenslet effectively images the aperture of the main imaging lens at the sensor. Therefore the sensor data retains angular light-field information which can be used for a posteriori digital computation of multi-angle images and axially refocused images. If a filter array, containing spectral filters or neutral density or polarization filters, is placed at the pupil aperture of the main imaging lens, then each lenslet images the filters on to the sensor. This enables the digital separation of multiple filter modalities giving single snapshot, multi-modal images. Due to the diversity of potential applications of plenoptic systems, their investigation is increasing. As the application space moves towards microscopes and other complex systems, and as pixel sizes become smaller, the consideration of diffraction effects in these systems becomes increasingly important. We discuss a plenoptic system and its wave propagation analysis for both coherent and incoherent imaging. We simulate a system response using our analysis and discuss various applications of the system response pertaining to plenoptic system design, implementation and calibration.

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2018-01-01

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials. PMID:29401725

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

[Research on non-rigid registration of multi-modal medical image based on Demons algorithm].

PubMed

Hao, Peibo; Chen, Zhen; Jiang, Shaofeng; Wang, Yang

2014-02-01

Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large de formation and multi-modal three-dimensional medical image registration had good effects.

Evaluation of state-of-the-art imaging systems for in vivo monitoring of retinal structure in mice: current capabilities and limitations

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Zam, Azhar; Pugh, Edward N.; Zawadzki, Robert J.

2014-02-01

Animal models of human diseases play an important role in studying and advancing our understanding of these conditions, allowing molecular level studies of pathogenesis as well as testing of new therapies. Recently several non-invasive imaging modalities including Fundus Camera, Scanning Laser Ophthalmoscopy (SLO) and Optical Coherence Tomography (OCT) have been successfully applied to monitor changes in the retinas of the living animals in experiments in which a single animal is followed over a portion of its lifespan. Here we evaluate the capabilities and limitations of these three imaging modalities for visualization of specific structures in the mouse eye. Example images acquired from different types of mice are presented. Future directions of development for these instruments and potential advantages of multi-modal imaging systems are discussed as well.

IMAGES: A digital computer program for interactive modal analysis and gain estimation for eigensystem synthesis

NASA Technical Reports Server (NTRS)

Jones, R. L.

1984-01-01

An interactive digital computer program for modal analysis and gain estimation for eigensystem synthesis was written. Both mathematical and operation considerations are described; however, the mathematical presentation is limited to those concepts essential to the operational capability of the program. The program is capable of both modal and spectral synthesis of multi-input control systems. It is user friendly, has scratchpad capability and dynamic memory, and can be used to design either state or output feedback systems.

MIND: modality independent neighbourhood descriptor for multi-modal deformable registration.

PubMed

Heinrich, Mattias P; Jenkinson, Mark; Bhushan, Manav; Matin, Tahreema; Gleeson, Fergus V; Brady, Sir Michael; Schnabel, Julia A

2012-10-01

Deformable registration of images obtained from different modalities remains a challenging task in medical image analysis. This paper addresses this important problem and proposes a modality independent neighbourhood descriptor (MIND) for both linear and deformable multi-modal registration. Based on the similarity of small image patches within one image, it aims to extract the distinctive structure in a local neighbourhood, which is preserved across modalities. The descriptor is based on the concept of image self-similarity, which has been introduced for non-local means filtering for image denoising. It is able to distinguish between different types of features such as corners, edges and homogeneously textured regions. MIND is robust to the most considerable differences between modalities: non-functional intensity relations, image noise and non-uniform bias fields. The multi-dimensional descriptor can be efficiently computed in a dense fashion across the whole image and provides point-wise local similarity across modalities based on the absolute or squared difference between descriptors, making it applicable for a wide range of transformation models and optimisation algorithms. We use the sum of squared differences of the MIND representations of the images as a similarity metric within a symmetric non-parametric Gauss-Newton registration framework. In principle, MIND would be applicable to the registration of arbitrary modalities. In this work, we apply and validate it for the registration of clinical 3D thoracic CT scans between inhale and exhale as well as the alignment of 3D CT and MRI scans. Experimental results show the advantages of MIND over state-of-the-art techniques such as conditional mutual information and entropy images, with respect to clinically annotated landmark locations. Copyright © 2012 Elsevier B.V. All rights reserved.

Simultaneous acquisition of magnetic resonance spectroscopy (MRS) data and positron emission tomography (PET) images with a prototype MR-compatible, small animal PET imager

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Velan, S. Sendhil; Lemieux, Susan; Kross, Brian; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.

2007-06-01

Multi-modality imaging (such as PET-CT) is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET, fused with anatomical images created by MRI, allow the correlation of form with function. Perhaps more exciting than the combination of anatomical MRI with PET, is the melding of PET with MR spectroscopy (MRS). Thus, two aspects of physiology could be combined in novel ways to produce new insights into the physiology of normal and pathological processes. Our team is developing a system to acquire MRI images and MRS spectra, and PET images contemporaneously. The prototype MR-compatible PET system consists of two opposed detector heads (appropriate in size for small animal imaging), operating in coincidence mode with an active field-of-view of ˜14 cm in diameter. Each detector consists of an array of LSO detector elements coupled through a 2-m long fiber optic light guide to a single position-sensitive photomultiplier tube. The use of light guides allows these magnetic field-sensitive elements of the PET imager to be positioned outside the strong magnetic field of our 3T MRI scanner. The PET scanner imager was integrated with a 12-cm diameter, 12-leg custom, birdcage coil. Simultaneous MRS spectra and PET images were successfully acquired from a multi-modality phantom consisting of a sphere filled with 17 brain relevant substances and a positron-emitting radionuclide. There were no significant changes in MRI or PET scanner performance when both were present in the MRI magnet bore. This successful initial test demonstrates the potential for using such a multi-modality to obtain complementary MRS and PET data.

Drug-related webpages classification based on multi-modal local decision fusion

NASA Astrophysics Data System (ADS)

Hu, Ruiguang; Su, Xiaojing; Liu, Yanxin

2018-03-01

In this paper, multi-modal local decision fusion is used for drug-related webpages classification. First, meaningful text are extracted through HTML parsing, and effective images are chosen by the FOCARSS algorithm. Second, six SVM classifiers are trained for six kinds of drug-taking instruments, which are represented by PHOG. One SVM classifier is trained for the cannabis, which is represented by the mid-feature of BOW model. For each instance in a webpage, seven SVMs give seven labels for its image, and other seven labels are given by searching the names of drug-taking instruments and cannabis in its related text. Concatenating seven labels of image and seven labels of text, the representation of those instances in webpages are generated. Last, Multi-Instance Learning is used to classify those drugrelated webpages. Experimental results demonstrate that the classification accuracy of multi-instance learning with multi-modal local decision fusion is much higher than those of single-modal classification.

The evolution of gadolinium based contrast agents: from single-modality to multi-modality

NASA Astrophysics Data System (ADS)

Zhang, Li; Liu, Ruiqing; Peng, Hui; Li, Penghui; Xu, Zushun; Whittaker, Andrew K.

2016-05-01

Gadolinium-based contrast agents are extensively used as magnetic resonance imaging (MRI) contrast agents due to their outstanding signal enhancement and ease of chemical modification. However, it is increasingly recognized that information obtained from single modal molecular imaging cannot satisfy the higher requirements on the efficiency and accuracy for clinical diagnosis and medical research, due to its limitation and default rooted in single molecular imaging technique itself. To compensate for the deficiencies of single function magnetic resonance imaging contrast agents, the combination of multi-modality imaging has turned to be the research hotpot in recent years. This review presents an overview on the recent developments of the functionalization of gadolinium-based contrast agents, and their application in biomedicine applications.

Multi-Modal Curriculum Learning for Semi-Supervised Image Classification.

PubMed

Gong, Chen; Tao, Dacheng; Maybank, Stephen J; Liu, Wei; Kang, Guoliang; Yang, Jie

2016-07-01

Semi-supervised image classification aims to classify a large quantity of unlabeled images by typically harnessing scarce labeled images. Existing semi-supervised methods often suffer from inadequate classification accuracy when encountering difficult yet critical images, such as outliers, because they treat all unlabeled images equally and conduct classifications in an imperfectly ordered sequence. In this paper, we employ the curriculum learning methodology by investigating the difficulty of classifying every unlabeled image. The reliability and the discriminability of these unlabeled images are particularly investigated for evaluating their difficulty. As a result, an optimized image sequence is generated during the iterative propagations, and the unlabeled images are logically classified from simple to difficult. Furthermore, since images are usually characterized by multiple visual feature descriptors, we associate each kind of features with a teacher, and design a multi-modal curriculum learning (MMCL) strategy to integrate the information from different feature modalities. In each propagation, each teacher analyzes the difficulties of the currently unlabeled images from its own modality viewpoint. A consensus is subsequently reached among all the teachers, determining the currently simplest images (i.e., a curriculum), which are to be reliably classified by the multi-modal learner. This well-organized propagation process leveraging multiple teachers and one learner enables our MMCL to outperform five state-of-the-art methods on eight popular image data sets.

Image-guided thoracic surgery in the hybrid operation room.

PubMed

Ujiie, Hideki; Effat, Andrew; Yasufuku, Kazuhiro

2017-01-01

There has been an increase in the use of image-guided technology to facilitate minimally invasive therapy. The next generation of minimally invasive therapy is focused on advancement and translation of novel image-guided technologies in therapeutic interventions, including surgery, interventional pulmonology, radiation therapy, and interventional laser therapy. To establish the efficacy of different minimally invasive therapies, we have developed a hybrid operating room, known as the guided therapeutics operating room (GTx OR) at the Toronto General Hospital. The GTx OR is equipped with multi-modality image-guidance systems, which features a dual source-dual energy computed tomography (CT) scanner, a robotic cone-beam CT (CBCT)/fluoroscopy, high-performance endobronchial ultrasound system, endoscopic surgery system, near-infrared (NIR) fluorescence imaging system, and navigation tracking systems. The novel multimodality image-guidance systems allow physicians to quickly, and accurately image patients while they are on the operating table. This yield improved outcomes since physicians are able to use image guidance during their procedures, and carry out innovative multi-modality therapeutics. Multiple preclinical translational studies pertaining to innovative minimally invasive technology is being developed in our guided therapeutics laboratory (GTx Lab). The GTx Lab is equipped with similar technology, and multimodality image-guidance systems as the GTx OR, and acts as an appropriate platform for translation of research into human clinical trials. Through the GTx Lab, we are able to perform basic research, such as the development of image-guided technologies, preclinical model testing, as well as preclinical imaging, and then translate that research into the GTx OR. This OR allows for the utilization of new technologies in cancer therapy, including molecular imaging, and other innovative imaging modalities, and therefore enables a better quality of life for patients, both during and after the procedure. In this article, we describe capabilities of the GTx systems, and discuss the first-in-human technologies used, and evaluated in GTx OR.

Project MICAS: a multivendor open-system incremental approach to implementing an integrated enterprise-wide PACS: works in progress

NASA Astrophysics Data System (ADS)

Smith, Edward M.; Wright, Jeffrey; Fontaine, Marc T.; Robinson, Arvin E.

1998-07-01

The Medical Information, Communication and Archive System (MICAS) is a multi-vendor incremental approach to PACS. MICAS is a multi-modality integrated image management system that incorporates the radiology information system (RIS) and radiology image database (RID) with future 'hooks' to other hospital databases. Even though this approach to PACS is more risky than a single-vendor turn-key approach, it offers significant advantages. The vendors involved in the initial phase of MICAS are IDX Corp., ImageLabs, Inc. and Digital Equipment Corp (DEC). The network architecture operates at 100 MBits per sec except between the modalities and the stackable intelligent switch which is used to segment MICAS by modality. Each modality segment contains the acquisition engine for the modality, a temporary archive and one or more diagnostic workstations. All archived studies are available at all workstations, but there is no permanent archive at this time. At present, the RIS vendor is responsible for study acquisition and workflow as well as maintenance of the temporary archive. Management of study acquisition, workflow and the permanent archive will become the responsibility of the archive vendor when the archive is installed in the second quarter of 1998. The modalities currently interfaced to MICAS are MRI, CT and a Howtek film digitizer with Nuclear Medicine and computed radiography (CR) to be added when the permanent archive is installed. There are six dual-monitor diagnostic workstations which use ImageLabs Shared Vision viewer software located in MRI, CT, Nuclear Medicine, musculoskeletal reading areas and two in Radiology's main reading area. One of the major lessons learned to date is that the permanent archive should have been part of the initial MICAS installation and the archive vendor should have been responsible for image acquisition rather than the RIS vendor. Currently an archive vendor is being selected who will be responsible for the management of the archive plus the HIS/RIS interface, image acquisition, modality work list manager and interfacing to the current DICOM viewer software. The next phase of MICAS will include interfacing ultrasound, locating servers outside of the Radiology LAN to support the distribution of images and reports to the clinical floors and physician offices both within and outside of the University of Rochester Medical Center (URMC) campus and the teaching archive.

Integration of Multi-Modal Biomedical Data to Predict Cancer Grade and Patient Survival.

PubMed

Phan, John H; Hoffman, Ryan; Kothari, Sonal; Wu, Po-Yen; Wang, May D

2016-02-01

The Big Data era in Biomedical research has resulted in large-cohort data repositories such as The Cancer Genome Atlas (TCGA). These repositories routinely contain hundreds of matched patient samples for genomic, proteomic, imaging, and clinical data modalities, enabling holistic and multi-modal integrative analysis of human disease. Using TCGA renal and ovarian cancer data, we conducted a novel investigation of multi-modal data integration by combining histopathological image and RNA-seq data. We compared the performances of two integrative prediction methods: majority vote and stacked generalization. Results indicate that integration of multiple data modalities improves prediction of cancer grade and outcome. Specifically, stacked generalization, a method that integrates multiple data modalities to produce a single prediction result, outperforms both single-data-modality prediction and majority vote. Moreover, stacked generalization reveals the contribution of each data modality (and specific features within each data modality) to the final prediction result and may provide biological insights to explain prediction performance.

Magnetic Nanoparticles for Multi-Imaging and Drug Delivery

PubMed Central

Lee, Jae-Hyun; Kim, Ji-wook; Cheon, Jinwoo

2013-01-01

Various bio-medical applications of magnetic nanoparticles have been explored during the past few decades. As tools that hold great potential for advancing biological sciences, magnetic nanoparticles have been used as platform materials for enhanced magnetic resonance imaging (MRI) agents, biological separation and magnetic drug delivery systems, and magnetic hyperthermia treatment. Furthermore, approaches that integrate various imaging and bioactive moieties have been used in the design of multi-modality systems, which possess synergistically enhanced properties such as better imaging resolution and sensitivity, molecular recognition capabilities, stimulus responsive drug delivery with on-demand control, and spatio-temporally controlled cell signal activation. Below, recent studies that focus on the design and synthesis of multi-mode magnetic nanoparticles will be briefly reviewed and their potential applications in the imaging and therapy areas will be also discussed. PMID:23579479

Introduction to clinical and laboratory (small-animal) image registration and fusion.

PubMed

Zanzonico, Pat B; Nehmeh, Sadek A

2006-01-01

Imaging has long been a vital component of clinical medicine and, increasingly, of biomedical research in small-animals. Clinical and laboratory imaging modalities can be divided into two general categories, structural (or anatomical) and functional (or physiological). The latter, in particular, has spawned what has come to be known as "molecular imaging". Image registration and fusion have rapidly emerged as invaluable components of both clinical and small-animal imaging and has lead to the development and marketing of a variety of multi-modality, e.g. PET-CT, devices which provide registered and fused three-dimensional image sets. This paper briefly reviews the basics of image registration and fusion and available clinical and small-animal multi-modality instrumentation.

On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

NASA Astrophysics Data System (ADS)

LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

2017-12-01

The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

DTIC Science & Technology

2015-10-01

eyes and image choroidal vessels/capillaries using CARS intravital microscopy Subtask 3: Measure oxy-hemoglobin levels in PBI test and control eyes...AWARD NUMBER: W81XWH-14-1-0537 TITLE: Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia...4. TITLE AND SUBTITLE Mobile, Multimodal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia 5a. CONTRACT NUMBER W81XWH

Joint MR-PET reconstruction using a multi-channel image regularizer

PubMed Central

Koesters, Thomas; Otazo, Ricardo; Bredies, Kristian; Sodickson, Daniel K

2016-01-01

While current state of the art MR-PET scanners enable simultaneous MR and PET measurements, the acquired data sets are still usually reconstructed separately. We propose a new multi-modality reconstruction framework using second order Total Generalized Variation (TGV) as a dedicated multi-channel regularization functional that jointly reconstructs images from both modalities. In this way, information about the underlying anatomy is shared during the image reconstruction process while unique differences are preserved. Results from numerical simulations and in-vivo experiments using a range of accelerated MR acquisitions and different MR image contrasts demonstrate improved PET image quality, resolution, and quantitative accuracy. PMID:28055827

Direct visualization of gastrointestinal tract with lanthanide-doped BaYbF5 upconversion nanoprobes.

PubMed

Liu, Zhen; Ju, Enguo; Liu, Jianhua; Du, Yingda; Li, Zhengqiang; Yuan, Qinghai; Ren, Jinsong; Qu, Xiaogang

2013-10-01

Nanoparticulate contrast agents have attracted a great deal of attention along with the rapid development of modern medicine. Here, a binary contrast agent based on PAA modified BaYbF5:Tm nanoparticles for direct visualization of gastrointestinal (GI) tract has been designed and developed via a one-pot solvothermal route. By taking advantages of excellent colloidal stability, low cytotoxicity, and neglectable hemolysis of these well-designed nanoparticles, their feasibility as a multi-modal contrast agent for GI tract was intensively investigated. Significant enhancement of contrast efficacy relative to clinical barium meal and iodine-based contrast agent was evaluated via X-ray imaging and CT imaging in vivo. By doping Tm(3+) ions into these nanoprobes, in vivo NIR-NIR imaging was then demonstrated. Unlike some invasive imaging modalities, non-invasive imaging strategy including X-ray imaging, CT imaging, and UCL imaging for GI tract could extremely reduce the painlessness to patients, effectively facilitate imaging procedure, as well as rationality economize diagnostic time. Critical to clinical applications, long-term toxicity of our contrast agent was additionally investigated in detail, indicating their overall safety. Based on our results, PAA-BaYbF5:Tm nanoparticles were the excellent multi-modal contrast agent to integrate X-ray imaging, CT imaging, and UCL imaging for direct visualization of GI tract with low systemic toxicity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiscale and multi-modality visualization of angiogenesis in a human breast cancer model

PubMed Central

Cebulla, Jana; Kim, Eugene; Rhie, Kevin; Zhang, Jiangyang

2017-01-01

Angiogenesis in breast cancer helps fulfill the metabolic demands of the progressing tumor and plays a critical role in tumor metastasis. Therefore, various imaging modalities have been used to characterize tumor angiogenesis. While micro-CT (μCT) is a powerful tool for analyzing the tumor microvascular architecture at micron-scale resolution, magnetic resonance imaging (MRI) with its sub-millimeter resolution is useful for obtaining in vivo vascular data (e.g. tumor blood volume and vessel size index). However, integration of these microscopic and macroscopic angiogenesis data across spatial resolutions remains challenging. Here we demonstrate the feasibility of ‘multiscale’ angiogenesis imaging in a human breast cancer model, wherein we bridge the resolution gap between ex vivo μCT and in vivo MRI using intermediate resolution ex vivo MR microscopy (μMRI). To achieve this integration, we developed suitable vessel segmentation techniques for the ex vivo imaging data and co-registered the vascular data from all three imaging modalities. We showcase two applications of this multiscale, multi-modality imaging approach: (1) creation of co-registered maps of vascular volume from three independent imaging modalities, and (2) visualization of differences in tumor vasculature between viable and necrotic tumor regions by integrating μCT vascular data with tumor cellularity data obtained using diffusion-weighted MRI. Collectively, these results demonstrate the utility of ‘mesoscopic’ resolution μMRI for integrating macroscopic in vivo MRI data and microscopic μCT data. Although focused on the breast tumor xenograft vasculature, our imaging platform could be extended to include additional data types for a detailed characterization of the tumor microenvironment and computational systems biology applications. PMID:24719185

A Review of Intravascular Ultrasound–Based Multimodal Intravascular Imaging: The Synergistic Approach to Characterizing Vulnerable Plaques

PubMed Central

Ma, Teng; Zhou, Bill; Hsiai, Tzung K.; Shung, K. Kirk

2015-01-01

Catheter-based intravascular imaging modalities are being developed to visualize pathologies in coronary arteries, such as high-risk vulnerable atherosclerotic plaques known as thin-cap fibroatheroma, to guide therapeutic strategy at preventing heart attacks. Mounting evidences have shown three distinctive histopathological features—the presence of a thin fibrous cap, a lipid-rich necrotic core, and numerous infiltrating macrophages—are key markers of increased vulnerability in atherosclerotic plaques. To visualize these changes, the majority of catheter-based imaging modalities used intravascular ultrasound (IVUS) as the technical foundation and integrated emerging intravascular imaging techniques to enhance the characterization of vulnerable plaques. However, no current imaging technology is the unequivocal “gold standard” for the diagnosis of vulnerable atherosclerotic plaques. Each intravascular imaging technology possesses its own unique features that yield valuable information although encumbered by inherent limitations not seen in other modalities. In this context, the aim of this review is to discuss current scientific innovations, technical challenges, and prospective strategies in the development of IVUS-based multi-modality intravascular imaging systems aimed at assessing atherosclerotic plaque vulnerability. PMID:26400676

Label-aligned Multi-task Feature Learning for Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zu, Chen; Jie, Biao; Liu, Mingxia; Chen, Songcan

2015-01-01

Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer’s disease (AD), as well as its prodromal stage, i.e., mild cognitive impairment (MCI). However, to the best of our knowledge, most existing methods focus on mining the relationship across multiple modalities of the same subjects, while ignoring the potentially useful relationship across different subjects. Accordingly, in this paper, we propose a novel learning method for multimodal classification of AD/MCI, by fully exploring the relationships across both modalities and subjects. Specifically, our proposed method includes two subsequent components, i.e., label-aligned multi-task feature selection and multimodal classification. In the first step, the feature selection learning from multiple modalities are treated as different learning tasks and a group sparsity regularizer is imposed to jointly select a subset of relevant features. Furthermore, to utilize the discriminative information among labeled subjects, a new label-aligned regularization term is added into the objective function of standard multi-task feature selection, where label-alignment means that all multi-modality subjects with the same class labels should be closer in the new feature-reduced space. In the second step, a multi-kernel support vector machine (SVM) is adopted to fuse the selected features from multi-modality data for final classification. To validate our method, we perform experiments on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database using baseline MRI and FDG-PET imaging data. The experimental results demonstrate that our proposed method achieves better classification performance compared with several state-of-the-art methods for multimodal classification of AD/MCI. PMID:26572145

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.

Integrated photoacoustic microscopy, optical coherence tomography, and fluorescence microscopy for multimodal chorioretinal imaging

NASA Astrophysics Data System (ADS)

Tian, Chao; Zhang, Wei; Nguyen, Van Phuc; Huang, Ziyi; Wang, Xueding; Paulus, Yannis M.

2018-02-01

Current clinical available retinal imaging techniques have limitations, including limited depth of penetration or requirement for the invasive injection of exogenous contrast agents. Here, we developed a novel multimodal imaging system for high-speed, high-resolution retinal imaging of larger animals, such as rabbits. The system integrates three state-of-the-art imaging modalities, including photoacoustic microscopy (PAM), optical coherence tomography (OCT), and fluorescence microscopy (FM). In vivo experimental results of rabbit eyes show that the PAM is able to visualize laser-induced retinal burns and distinguish individual eye blood vessels using a laser exposure dose of 80 nJ, which is well below the American National Standards Institute (ANSI) safety limit 160 nJ. The OCT can discern different retinal layers and visualize laser burns and choroidal detachments. The novel multi-modal imaging platform holds great promise in ophthalmic imaging.

Prussian blue nanocubes: multi-functional nanoparticles for multimodal imaging and image-guided therapy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cook, Jason R.; Dumani, Diego S.; Kubelick, Kelsey P.; Luci, Jeffrey; Emelianov, Stanislav Y.

2017-03-01

Imaging modalities utilize contrast agents to improve morphological visualization and to assess functional and molecular/cellular information. Here we present a new type of nanometer scale multi-functional particle that can be used for multi-modal imaging and therapeutic applications. Specifically, we synthesized monodisperse 20 nm Prussian Blue Nanocubes (PBNCs) with desired optical absorption in the near-infrared region and superparamagnetic properties. PBNCs showed excellent contrast in photoacoustic (700 nm wavelength) and MR (3T) imaging. Furthermore, photostability was assessed by exposing the PBNCs to nearly 1,000 laser pulses (5 ns pulse width) with up to 30 mJ/cm2 laser fluences. The PBNCs exhibited insignificant changes in photoacoustic signal, demonstrating enhanced robustness compared to the commonly used gold nanorods (substantial photodegradation with fluences greater than 5 mJ/cm2). Furthermore, the PBNCs exhibited superparamagnetism with a magnetic saturation of 105 emu/g, a 5x improvement over superparamagnetic iron-oxide (SPIO) nanoparticles. PBNCs exhibited enhanced T2 contrast measured using 3T clinical MRI. Because of the excellent optical absorption and magnetism, PBNCs have potential uses in other imaging modalities including optical tomography, microscopy, magneto-motive OCT/ultrasound, etc. In addition to multi-modal imaging, the PBNCs are multi-functional and, for example, can be used to enhance magnetic delivery and as therapeutic agents. Our initial studies show that stem cells can be labeled with PBNCs to perform image-guided magnetic delivery. Overall, PBNCs can act as imaging/therapeutic agents in diverse applications including cancer, cardiovascular disease, ophthalmology, and tissue engineering. Furthermore, PBNCs are based on FDA approved Prussian Blue thus potentially easing clinical translation of PBNCs.

Scientific and industrial challenges of developing nanoparticle-based theranostics and multiple-modality contrast agents for clinical application

NASA Astrophysics Data System (ADS)

Wáng, Yì Xiáng J.; Idée, Jean-Marc; Corot, Claire

2015-10-01

Designing of theranostics and dual or multi-modality contrast agents are currently two of the hottest topics in biotechnology and biomaterials science. However, for single entity theranostics, a right ratio of their diagnostic component and their therapeutic component may not always be realized in a composite suitable for clinical application. For dual/multiple modality molecular imaging agents, after in vivo administration, there is an optimal time window for imaging, when an agent is imaged by one modality, the pharmacokinetics of this agent may not allow imaging by another modality. Due to reticuloendothelial system clearance, efficient in vivo delivery of nanoparticles to the lesion site is sometimes difficult. The toxicity of these entities also remains poorly understood. While the medical need of theranostics is admitted, the business model remains to be established. There is an urgent need for a global and internationally harmonized re-evaluation of the approval and marketing processes of theranostics. However, a reasonable expectation exists that, in the near future, the current obstacles will be removed, thus allowing the wide use of these very promising agents.

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

PubMed

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

2018-03-23

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

Multi-detector CT imaging in the postoperative orthopedic patient with metal hardware.

PubMed

Vande Berg, Bruno; Malghem, Jacques; Maldague, Baudouin; Lecouvet, Frederic

2006-12-01

Multi-detector CT imaging (MDCT) becomes routine imaging modality in the assessment of the postoperative orthopedic patients with metallic instrumentation that degrades image quality at MR imaging. This article reviews the physical basis and CT appearance of such metal-related artifacts. It also addresses the clinical value of MDCT in postoperative orthopedic patients with emphasis on fracture healing, spinal fusion or arthrodesis, and joint replacement. MDCT imaging shows limitations in the assessment of the bone marrow cavity and of the soft tissues for which MR imaging remains the imaging modality of choice despite metal-related anatomic distortions and signal alteration.

Multi-modality endoscopic imaging for the detection of colorectal cancer

NASA Astrophysics Data System (ADS)

Wall, Richard Andrew

Optical coherence tomography (OCT) is an imaging method that is considered the optical analog to ultrasound, using the technique of optical interferometry to construct two-dimensional depth-resolved images of tissue microstructure. With a resolution on the order of 10 um and a penetration depth of 1-2 mm in highly scattering tissue, fiber optics-coupled OCT is an ideal modality for the inspection of the mouse colon with its miniaturization capabilities. In the present study, the complementary modalities laser-induced fluorescence (LIF), which offers information on the biochemical makeup of the tissue, and surface magnifying chromoendoscopy, which offers high contrast surface visualization, are combined with OCT in endoscopic imaging systems for the greater specificity and sensitivity in the differentiation between normal and neoplastic tissue, and for the visualization of biomarkers which are indicative of early events in colorectal carcinogenesis. Oblique incidence reflectometry (OIR) also offers advantages, allowing the calculation of bulk tissue optical properties for use as a diagnostic tool. The study was broken up into three specific sections. First, a dual-modality OCTLIF imaging system was designed, capable of focusing light over 325-1300 nm using a reflective distal optics design. A dual-modality fluorescence-based SMC-OCT system was then designed and constructed, capable of resolving the stained mucosal crypt structure of the in vivo mouse colon. The SMC-OCT instrument's OIR capabilities were then modeled, as a modified version of the probe was used measure tissue scattering and absorption coefficients.

Whole-body diffusion-weighted MR image stitching and alignment to anatomical MRI

NASA Astrophysics Data System (ADS)

Ceranka, Jakub; Polfliet, Mathias; Lecouvet, Frederic; Michoux, Nicolas; Vandemeulebroucke, Jef

2017-02-01

Whole-body diffusion-weighted (WB-DW) MRI in combination with anatomical MRI has shown a great poten- tial in bone and soft tissue tumour detection, evaluation of lymph nodes and treatment response assessment. Because of the vast body coverage, whole-body MRI is acquired in separate stations, which are subsequently combined into a whole-body image. However, inter-station and inter-modality image misalignments can occur due to image distortions and patient motion during acquisition, which may lead to inaccurate representations of patient anatomy and hinder visual assessment. Automated and accurate whole-body image formation and alignment of the multi-modal MRI images is therefore crucial. We investigated several registration approaches for the formation or stitching of the whole-body image stations, followed by a deformable alignment of the multi- modal whole-body images. We compared a pairwise approach, where diffusion-weighted (DW) image stations were sequentially aligned to a reference station (pelvis), to a groupwise approach, where all stations were simultaneously mapped to a common reference space while minimizing the overall transformation. For each, a choice of input images and corresponding metrics was investigated. Performance was evaluated by assessing the quality of the obtained whole-body images, and by verifying the accuracy of the alignment with whole-body anatomical sequences. The groupwise registration approach provided the best compromise between the formation of WB- DW images and multi-modal alignment. The fully automated method was found to be robust, making its use in the clinic feasible.

Computer-aided, multi-modal, and compression diffuse optical studies of breast tissue

NASA Astrophysics Data System (ADS)

Busch, David Richard, Jr.

Diffuse Optical Tomography and Spectroscopy permit measurement of important physiological parameters non-invasively through ˜10 cm of tissue. I have applied these techniques in measurements of human breast and breast cancer. My thesis integrates three loosely connected themes in this context: multi-modal breast cancer imaging, automated data analysis of breast cancer images, and microvascular hemodynamics of breast under compression. As per the first theme, I describe construction, testing, and the initial clinical usage of two generations of imaging systems for simultaneous diffuse optical and magnetic resonance imaging. The second project develops a statistical analysis of optical breast data from many spatial locations in a population of cancers to derive a novel optical signature of malignancy; I then apply this data-derived signature for localization of cancer in additional subjects. Finally, I construct and deploy diffuse optical instrumentation to measure blood content and blood flow during breast compression; besides optics, this research has implications for any method employing breast compression, e.g., mammography.

Noninvasively measuring oxygen saturation of human finger-joint vessels by multi-transducer functional photoacoustic tomography

NASA Astrophysics Data System (ADS)

Deng, Zijian; Li, Changhui

2016-06-01

Imaging small blood vessels and measuring their functional information in finger joint are still challenges for clinical imaging modalities. In this study, we developed a multi-transducer functional photoacoustic tomography (PAT) system and successfully imaged human finger-joint vessels from ˜1 mm to <0.2 mm in diameter. In addition, the oxygen saturation (SO2) values of these vessels were also measured. Our results demonstrate that PAT can provide both anatomical and functional information of individual finger-joint vessels with different sizes, which might help the study of finger-joint diseases, such as rheumatoid arthritis.

A Multi-Modal Face Recognition Method Using Complete Local Derivative Patterns and Depth Maps

PubMed Central

Yin, Shouyi; Dai, Xu; Ouyang, Peng; Liu, Leibo; Wei, Shaojun

2014-01-01

In this paper, we propose a multi-modal 2D + 3D face recognition method for a smart city application based on a Wireless Sensor Network (WSN) and various kinds of sensors. Depth maps are exploited for the 3D face representation. As for feature extraction, we propose a new feature called Complete Local Derivative Pattern (CLDP). It adopts the idea of layering and has four layers. In the whole system, we apply CLDP separately on Gabor features extracted from a 2D image and depth map. Then, we obtain two features: CLDP-Gabor and CLDP-Depth. The two features weighted by the corresponding coefficients are combined together in the decision level to compute the total classification distance. At last, the probe face is assigned the identity with the smallest classification distance. Extensive experiments are conducted on three different databases. The results demonstrate the robustness and superiority of the new approach. The experimental results also prove that the proposed multi-modal 2D + 3D method is superior to other multi-modal ones and CLDP performs better than other Local Binary Pattern (LBP) based features. PMID:25333290

A Multi-Modality CMOS Sensor Array for Cell-Based Assay and Drug Screening.

PubMed

Chi, Taiyun; Park, Jong Seok; Butts, Jessica C; Hookway, Tracy A; Su, Amy; Zhu, Chengjie; Styczynski, Mark P; McDevitt, Todd C; Wang, Hua

2015-12-01

In this paper, we present a fully integrated multi-modality CMOS cellular sensor array with four sensing modalities to characterize different cell physiological responses, including extracellular voltage recording, cellular impedance mapping, optical detection with shadow imaging and bioluminescence sensing, and thermal monitoring. The sensor array consists of nine parallel pixel groups and nine corresponding signal conditioning blocks. Each pixel group comprises one temperature sensor and 16 tri-modality sensor pixels, while each tri-modality sensor pixel can be independently configured for extracellular voltage recording, cellular impedance measurement (voltage excitation/current sensing), and optical detection. This sensor array supports multi-modality cellular sensing at the pixel level, which enables holistic cell characterization and joint-modality physiological monitoring on the same cellular sample with a pixel resolution of 80 μm × 100 μm. Comprehensive biological experiments with different living cell samples demonstrate the functionality and benefit of the proposed multi-modality sensing in cell-based assay and drug screening.

Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy

NASA Astrophysics Data System (ADS)

McReynolds, Naomi; Cooke, Fiona G. M.; Chen, Mingzhou; Powis, Simon J.; Dholakia, Kishan

2017-03-01

The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a means for validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.

Endoscopic tri-modal imaging for detection of early neoplasia in Barrett's oesophagus: a multi-centre feasibility study using high-resolution endoscopy, autofluorescence imaging and narrow band imaging incorporated in one endoscopy system.

PubMed

Curvers, W L; Singh, R; Song, L-M Wong-Kee; Wolfsen, H C; Ragunath, K; Wang, K; Wallace, M B; Fockens, P; Bergman, J J G H M

2008-02-01

To investigate the diagnostic potential of endoscopic tri-modal imaging and the relative contribution of each imaging modality (i.e. high-resolution endoscopy (HRE), autofluorescence imaging (AFI) and narrow-band imaging (NBI)) for the detection of early neoplasia in Barrett's oesophagus. Prospective multi-centre study. Tertiary referral centres. 84 Patients with Barrett's oesophagus. The Barrett's oesophagus was inspected with HRE followed by AFI. All lesions detected with HRE and/or AFI were subsequently inspected in detail by NBI for the presence of abnormal mucosal and/or microvascular patterns. Biopsies were obtained from all suspicious lesions for blinded histopathological assessment followed by random biopsies. (1) Number of patients with early neoplasia diagnosed by HRE and AFI; (2) number of lesions with early neoplasia detected with HRE and AFI; and (3) reduction of false positive AFI findings after NBI. Per patient analysis: AFI identified all 16 patients with early neoplasia identified with HRE and detected an additional 11 patients with early neoplasia that were not identified with HRE. In three patients no abnormalities were seen but random biopsies revealed HGIN. After HRE inspection, AFI detected an additional 102 lesions; 19 contained HGIN/EC (false positive rate of AFI after HRE: 81%). Detailed inspection with NBI reduced this false positive rate to 26%. In this international multi-centre study, the addition of AFI to HRE increased the detection of both the number of patients and the number of lesions with early neoplasia in patients with Barrett's oesophagus. The false positive rate of AFI was reduced after detailed inspection with NBI.

A DICOM-based 2nd generation Molecular Imaging Data Grid implementing the IHE XDS-i integration profile.

PubMed

Lee, Jasper; Zhang, Jianguo; Park, Ryan; Dagliyan, Grant; Liu, Brent; Huang, H K

2012-07-01

A Molecular Imaging Data Grid (MIDG) was developed to address current informatics challenges in archival, sharing, search, and distribution of preclinical imaging studies between animal imaging facilities and investigator sites. This manuscript presents a 2nd generation MIDG replacing the Globus Toolkit with a new system architecture that implements the IHE XDS-i integration profile. Implementation and evaluation were conducted using a 3-site interdisciplinary test-bed at the University of Southern California. The 2nd generation MIDG design architecture replaces the initial design's Globus Toolkit with dedicated web services and XML-based messaging for dedicated management and delivery of multi-modality DICOM imaging datasets. The Cross-enterprise Document Sharing for Imaging (XDS-i) integration profile from the field of enterprise radiology informatics was adopted into the MIDG design because streamlined image registration, management, and distribution dataflow are likewise needed in preclinical imaging informatics systems as in enterprise PACS application. Implementation of the MIDG is demonstrated at the University of Southern California Molecular Imaging Center (MIC) and two other sites with specified hardware, software, and network bandwidth. Evaluation of the MIDG involves data upload, download, and fault-tolerance testing scenarios using multi-modality animal imaging datasets collected at the USC Molecular Imaging Center. The upload, download, and fault-tolerance tests of the MIDG were performed multiple times using 12 collected animal study datasets. Upload and download times demonstrated reproducibility and improved real-world performance. Fault-tolerance tests showed that automated failover between Grid Node Servers has minimal impact on normal download times. Building upon the 1st generation concepts and experiences, the 2nd generation MIDG system improves accessibility of disparate animal-model molecular imaging datasets to users outside a molecular imaging facility's LAN using a new architecture, dataflow, and dedicated DICOM-based management web services. Productivity and efficiency of preclinical research for translational sciences investigators has been further streamlined for multi-center study data registration, management, and distribution.

Robust multi-site MR data processing: iterative optimization of bias correction, tissue classification, and registration.

PubMed

Young Kim, Eun; Johnson, Hans J

2013-01-01

A robust multi-modal tool, for automated registration, bias correction, and tissue classification, has been implemented for large-scale heterogeneous multi-site longitudinal MR data analysis. This work focused on improving the an iterative optimization framework between bias-correction, registration, and tissue classification inspired from previous work. The primary contributions are robustness improvements from incorporation of following four elements: (1) utilize multi-modal and repeated scans, (2) incorporate high-deformable registration, (3) use extended set of tissue definitions, and (4) use of multi-modal aware intensity-context priors. The benefits of these enhancements were investigated by a series of experiments with both simulated brain data set (BrainWeb) and by applying to highly-heterogeneous data from a 32 site imaging study with quality assessments through the expert visual inspection. The implementation of this tool is tailored for, but not limited to, large-scale data processing with great data variation with a flexible interface. In this paper, we describe enhancements to a joint registration, bias correction, and the tissue classification, that improve the generalizability and robustness for processing multi-modal longitudinal MR scans collected at multi-sites. The tool was evaluated by using both simulated and simulated and human subject MRI images. With these enhancements, the results showed improved robustness for large-scale heterogeneous MRI processing.

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

PubMed

Patel, Meenal J; Andreescu, Carmen; Price, Julie C; Edelman, Kathryn L; Reynolds, Charles F; Aizenstein, Howard J

2015-10-01

Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of evaluating associated underlying brain characteristics. Unlike past studies, we attempted to estimate accurate prediction models for late-life depression diagnosis and treatment response using multiple machine learning methods with inputs of multi-modal imaging and non-imaging whole brain and network-based features. Late-life depression patients (medicated post-recruitment) (n = 33) and older non-depressed individuals (n = 35) were recruited. Their demographics and cognitive ability scores were recorded, and brain characteristics were acquired using multi-modal magnetic resonance imaging pretreatment. Linear and nonlinear learning methods were tested for estimating accurate prediction models. A learning method called alternating decision trees estimated the most accurate prediction models for late-life depression diagnosis (87.27% accuracy) and treatment response (89.47% accuracy). The diagnosis model included measures of age, Mini-mental state examination score, and structural imaging (e.g. whole brain atrophy and global white mater hyperintensity burden). The treatment response model included measures of structural and functional connectivity. Combinations of multi-modal imaging and/or non-imaging measures may help better predict late-life depression diagnosis and treatment response. As a preliminary observation, we speculate that the results may also suggest that different underlying brain characteristics defined by multi-modal imaging measures-rather than region-based differences-are associated with depression versus depression recovery because to our knowledge this is the first depression study to accurately predict both using the same approach. These findings may help better understand late-life depression and identify preliminary steps toward personalized late-life depression treatment. Copyright © 2015 John Wiley & Sons, Ltd.

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.

Depth-resolved imaging of colon tumor using optical coherence tomography and fluorescence laminar optical tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Tang, Qinggong; Frank, Aaron; Wang, Jianting; Chen, Chao-wei; Jin, Lily; Lin, Jon; Chan, Joanne M.; Chen, Yu

2016-03-01

Early detection of neoplastic changes remains a critical challenge in clinical cancer diagnosis and treatment. Many cancers arise from epithelial layers such as those of the gastrointestinal (GI) tract. Current standard endoscopic technology is unable to detect those subsurface lesions. Since cancer development is associated with both morphological and molecular alterations, imaging technologies that can quantitative image tissue's morphological and molecular biomarkers and assess the depth extent of a lesion in real time, without the need for tissue excision, would be a major advance in GI cancer diagnostics and therapy. In this research, we investigated the feasibility of multi-modal optical imaging including high-resolution optical coherence tomography (OCT) and depth-resolved high-sensitivity fluorescence laminar optical tomography (FLOT) for structural and molecular imaging. APC (adenomatous polyposis coli) mice model were imaged using OCT and FLOT and the correlated histopathological diagnosis was obtained. Quantitative structural (the scattering coefficient) and molecular imaging parameters (fluorescence intensity) from OCT and FLOT images were developed for multi-parametric analysis. This multi-modal imaging method has demonstrated the feasibility for more accurate diagnosis with 87.4% (87.3%) for sensitivity (specificity) which gives the most optimal diagnosis (the largest area under receiver operating characteristic (ROC) curve). This project results in a new non-invasive multi-modal imaging platform for improved GI cancer detection, which is expected to have a major impact on detection, diagnosis, and characterization of GI cancers, as well as a wide range of epithelial cancers.

Performance evaluation of a compact PET/SPECT/CT tri-modality system for small animal imaging applications

NASA Astrophysics Data System (ADS)

Wei, Qingyang; Wang, Shi; Ma, Tianyu; Wu, Jing; Liu, Hui; Xu, Tianpeng; Xia, Yan; Fan, Peng; Lyu, Zhenlei; Liu, Yaqiang

2015-06-01

PET, SPECT and CT imaging techniques are widely used in preclinical small animal imaging applications. In this paper, we present a compact small animal PET/SPECT/CT tri-modality system. A dual-functional, shared detector design is implemented which enables PET and SPECT imaging with a same LYSO ring detector. A multi-pinhole collimator is mounted on the system and inserted into the detector ring in SPECT imaging mode. A cone-beam CT consisting of a micro focus X-ray tube and a CMOS detector is implemented. The detailed design and the performance evaluations are reported in this paper. In PET imaging mode, the measured NEMA based spatial resolution is 2.12 mm (FWHM), and the sensitivity at the central field of view (CFOV) is 3.2%. The FOV size is 50 mm (∅)×100 mm (L). The SPECT has a spatial resolution of 1.32 mm (FWHM) and an average sensitivity of 0.031% at the center axial, and a 30 mm (∅)×90 mm (L) FOV. The CT spatial resolution is 8.32 lp/mm @10%MTF, and the contrast discrimination function value is 2.06% with 1.5 mm size cubic box object. In conclusion, a compact, tri-modality PET/SPECT/CT system was successfully built with low cost and high performance.

Content-independent embedding scheme for multi-modal medical image watermarking.

PubMed

Nyeem, Hussain; Boles, Wageeh; Boyd, Colin

2015-02-04

As the increasing adoption of information technology continues to offer better distant medical services, the distribution of, and remote access to digital medical images over public networks continues to grow significantly. Such use of medical images raises serious concerns for their continuous security protection, which digital watermarking has shown great potential to address. We present a content-independent embedding scheme for medical image watermarking. We observe that the perceptual content of medical images varies widely with their modalities. Recent medical image watermarking schemes are image-content dependent and thus they may suffer from inconsistent embedding capacity and visual artefacts. To attain the image content-independent embedding property, we generalise RONI (region of non-interest, to the medical professionals) selection process and use it for embedding by utilising RONI's least significant bit-planes. The proposed scheme thus avoids the need for RONI segmentation that incurs capacity and computational overheads. Our experimental results demonstrate that the proposed embedding scheme performs consistently over a dataset of 370 medical images including their 7 different modalities. Experimental results also verify how the state-of-the-art reversible schemes can have an inconsistent performance for different modalities of medical images. Our scheme has MSSIM (Mean Structural SIMilarity) larger than 0.999 with a deterministically adaptable embedding capacity. Our proposed image-content independent embedding scheme is modality-wise consistent, and maintains a good image quality of RONI while keeping all other pixels in the image untouched. Thus, with an appropriate watermarking framework (i.e., with the considerations of watermark generation, embedding and detection functions), our proposed scheme can be viable for the multi-modality medical image applications and distant medical services such as teleradiology and eHealth.

A graph-based approach for the retrieval of multi-modality medical images.

PubMed

Kumar, Ashnil; Kim, Jinman; Wen, Lingfeng; Fulham, Michael; Feng, Dagan

2014-02-01

In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging. The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours and organs. These attributes and relationships, which are used for tumour staging and classification, can be formulated as a graph. It has been demonstrated that graph-based methods have high accuracy for retrieval by spatial similarity. However, naïvely representing all relationships on a complete graph obscures the structure of the tumour-anatomy relationships. We propose a new graph structure derived from complete graphs that structurally constrains the edges connected to tumour vertices based upon the spatial proximity of tumours and organs. This enables retrieval on the basis of tumour localisation. We also present a similarity matching algorithm that accounts for different feature sets for graph elements from different imaging modalities. Our method emphasises the relationships between a tumour and related organs, while still modelling patient-specific anatomical variations. Constraining tumours to related anatomical structures improves the discrimination potential of graphs, making it easier to retrieve similar images based on tumour location. We evaluated our retrieval methodology on a dataset of clinical PET-CT volumes. Our results showed that our method enabled the retrieval of multi-modality images using spatial features. Our graph-based retrieval algorithm achieved a higher precision than several other retrieval techniques: gray-level histograms as well as state-of-the-art methods such as visual words using the scale- invariant feature transform (SIFT) and relational matrices representing the spatial arrangements of objects. Copyright © 2013 Elsevier B.V. All rights reserved.

Current status of the joint Mayo Clinic-IBM PACS project

NASA Astrophysics Data System (ADS)

Hangiandreou, Nicholas J.; Williamson, Byrn, Jr.; Gehring, Dale G.; Persons, Kenneth R.; Reardon, Frank J.; Salutz, James R.; Felmlee, Joel P.; Loewen, M. D.; Forbes, Glenn S.

1994-05-01

A multi-phase collaboration between Mayo Clinic and IBM-Rochester was undertaken, with the goal of developing a picture archiving and communication system for routine clinical use in the Radiology Department. The initial phase of this project (phase 0) was started in 1988. The current system has been fully integrated into the clinical practice and, to date, over 6.5 million images from 16 imaging modalities have been archived. Phase 3 of this project has recently concluded.

The new frontiers of multimodality and multi-isotope imaging

NASA Astrophysics Data System (ADS)

Behnam Azad, Babak; Nimmagadda, Sridhar

2014-06-01

Technological advances in imaging systems and the development of target specific imaging tracers has been rapidly growing over the past two decades. Recent progress in "all-in-one" imaging systems that allow for automated image coregistration has significantly added to the growth of this field. These developments include ultra high resolution PET and SPECT scanners that can be integrated with CT or MR resulting in PET/CT, SPECT/CT, SPECT/PET and PET/MRI scanners for simultaneous high resolution high sensitivity anatomical and functional imaging. These technological developments have also resulted in drastic enhancements in image quality and acquisition time while eliminating cross compatibility issues between modalities. Furthermore, the most cutting edge technology, though mostly preclinical, also allows for simultaneous multimodality multi-isotope image acquisition and image reconstruction based on radioisotope decay characteristics. These scientific advances, in conjunction with the explosion in the development of highly specific multimodality molecular imaging agents, may aid in realizing simultaneous imaging of multiple biological processes and pave the way towards more efficient diagnosis and improved patient care.

Multi-modality molecular imaging: pre-clinical laboratory configuration

NASA Astrophysics Data System (ADS)

Wu, Yanjun; Wellen, Jeremy W.; Sarkar, Susanta K.

2006-02-01

In recent years, the prevalence of in vivo molecular imaging applications has rapidly increased. Here we report on the construction of a multi-modality imaging facility in a pharmaceutical setting that is expected to further advance existing capabilities for in vivo imaging of drug distribution and the interaction with their target. The imaging instrumentation in our facility includes a microPET scanner, a four wavelength time-domain optical imaging scanner, a 9.4T/30cm MRI scanner and a SPECT/X-ray CT scanner. An electronics shop and a computer room dedicated to image analysis are additional features of the facility. The layout of the facility was designed with a central animal preparation room surrounded by separate laboratory rooms for each of the major imaging modalities to accommodate the work-flow of simultaneous in vivo imaging experiments. This report will focus on the design of and anticipated applications for our microPET and optical imaging laboratory spaces. Additionally, we will discuss efforts to maximize the daily throughput of animal scans through development of efficient experimental work-flows and the use of multiple animals in a single scanning session.

DataViewer3D: An Open-Source, Cross-Platform Multi-Modal Neuroimaging Data Visualization Tool

PubMed Central

Gouws, André; Woods, Will; Millman, Rebecca; Morland, Antony; Green, Gary

2008-01-01

Integration and display of results from multiple neuroimaging modalities [e.g. magnetic resonance imaging (MRI), magnetoencephalography, EEG] relies on display of a diverse range of data within a common, defined coordinate frame. DataViewer3D (DV3D) is a multi-modal imaging data visualization tool offering a cross-platform, open-source solution to simultaneous data overlay visualization requirements of imaging studies. While DV3D is primarily a visualization tool, the package allows an analysis approach where results from one imaging modality can guide comparative analysis of another modality in a single coordinate space. DV3D is built on Python, a dynamic object-oriented programming language with support for integration of modular toolkits, and development of cross-platform software for neuroimaging. DV3D harnesses the power of the Visualization Toolkit (VTK) for two-dimensional (2D) and 3D rendering, calling VTK's low level C++ functions from Python. Users interact with data via an intuitive interface that uses Python to bind wxWidgets, which in turn calls the user's operating system dialogs and graphical user interface tools. DV3D currently supports NIfTI-1, ANALYZE™ and DICOM formats for MRI data display (including statistical data overlay). Formats for other data types are supported. The modularity of DV3D and ease of use of Python allows rapid integration of additional format support and user development. DV3D has been tested on Mac OSX, RedHat Linux and Microsoft Windows XP. DV3D is offered for free download with an extensive set of tutorial resources and example data. PMID:19352444

Multi-modal Registration for Correlative Microscopy using Image Analogies

PubMed Central

Cao, Tian; Zach, Christopher; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

2014-01-01

Correlative microscopy is a methodology combining the functionality of light microscopy with the high resolution of electron microscopy and other microscopy technologies for the same biological specimen. In this paper, we propose an image registration method for correlative microscopy, which is challenging due to the distinct appearance of biological structures when imaged with different modalities. Our method is based on image analogies and allows to transform images of a given modality into the appearance-space of another modality. Hence, the registration between two different types of microscopy images can be transformed to a mono-modality image registration. We use a sparse representation model to obtain image analogies. The method makes use of corresponding image training patches of two different imaging modalities to learn a dictionary capturing appearance relations. We test our approach on backscattered electron (BSE) scanning electron microscopy (SEM)/confocal and transmission electron microscopy (TEM)/confocal images. We perform rigid, affine, and deformable registration via B-splines and show improvements over direct registration using both mutual information and sum of squared differences similarity measures to account for differences in image appearance. PMID:24387943

Integrated photoacoustic, ultrasound and fluorescence platform for diagnostic medical imaging-proof of concept study with a tissue mimicking phantom.

PubMed

James, Joseph; Murukeshan, Vadakke Matham; Woh, Lye Sun

2014-07-01

The structural and molecular heterogeneities of biological tissues demand the interrogation of the samples with multiple energy sources and provide visualization capabilities at varying spatial resolution and depth scales for obtaining complementary diagnostic information. A novel multi-modal imaging approach that uses optical and acoustic energies to perform photoacoustic, ultrasound and fluorescence imaging at multiple resolution scales from the tissue surface and depth is proposed in this paper. The system comprises of two distinct forms of hardware level integration so as to have an integrated imaging system under a single instrumentation set-up. The experimental studies show that the system is capable of mapping high resolution fluorescence signatures from the surface, optical absorption and acoustic heterogeneities along the depth (>2cm) of the tissue at multi-scale resolution (<1µm to <0.5mm).

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

Multi-modal imaging, model-based tracking, and mixed reality visualisation for orthopaedic surgery

PubMed Central

Fuerst, Bernhard; Tateno, Keisuke; Johnson, Alex; Fotouhi, Javad; Osgood, Greg; Tombari, Federico; Navab, Nassir

2017-01-01

Orthopaedic surgeons are still following the decades old workflow of using dozens of two-dimensional fluoroscopic images to drill through complex 3D structures, e.g. pelvis. This Letter presents a mixed reality support system, which incorporates multi-modal data fusion and model-based surgical tool tracking for creating a mixed reality environment supporting screw placement in orthopaedic surgery. A red–green–blue–depth camera is rigidly attached to a mobile C-arm and is calibrated to the cone-beam computed tomography (CBCT) imaging space via iterative closest point algorithm. This allows real-time automatic fusion of reconstructed surface and/or 3D point clouds and synthetic fluoroscopic images obtained through CBCT imaging. An adapted 3D model-based tracking algorithm with automatic tool segmentation allows for tracking of the surgical tools occluded by hand. This proposed interactive 3D mixed reality environment provides an intuitive understanding of the surgical site and supports surgeons in quickly localising the entry point and orienting the surgical tool during screw placement. The authors validate the augmentation by measuring target registration error and also evaluate the tracking accuracy in the presence of partial occlusion. PMID:29184659

Three-dimensional multi bioluminescent sources reconstruction based on adaptive finite element method

NASA Astrophysics Data System (ADS)

Ma, Xibo; Tian, Jie; Zhang, Bo; Zhang, Xing; Xue, Zhenwen; Dong, Di; Han, Dong

2011-03-01

Among many optical molecular imaging modalities, bioluminescence imaging (BLI) has more and more wide application in tumor detection and evaluation of pharmacodynamics, toxicity, pharmacokinetics because of its noninvasive molecular and cellular level detection ability, high sensitivity and low cost in comparison with other imaging technologies. However, BLI can not present the accurate location and intensity of the inner bioluminescence sources such as in the bone, liver or lung etc. Bioluminescent tomography (BLT) shows its advantage in determining the bioluminescence source distribution inside a small animal or phantom. Considering the deficiency of two-dimensional imaging modality, we developed three-dimensional tomography to reconstruct the information of the bioluminescence source distribution in transgenic mOC-Luc mice bone with the boundary measured data. In this paper, to study the osteocalcin (OC) accumulation in transgenic mOC-Luc mice bone, a BLT reconstruction method based on multilevel adaptive finite element (FEM) algorithm was used for localizing and quantifying multi bioluminescence sources. Optical and anatomical information of the tissues are incorporated as a priori knowledge in this method, which can reduce the ill-posedness of BLT. The data was acquired by the dual modality BLT and Micro CT prototype system that was developed by us. Through temperature control and absolute intensity calibration, a relative accurate intensity can be calculated. The location of the OC accumulation was reconstructed, which was coherent with the principle of bone differentiation. This result also was testified by ex vivo experiment in the black 96-plate well using the BLI system and the chemiluminescence apparatus.

CISUS: an integrated 3D ultrasound system for IGT using a modular tracking API

NASA Astrophysics Data System (ADS)

Boctor, Emad M.; Viswanathan, Anand; Pieper, Steve; Choti, Michael A.; Taylor, Russell H.; Kikinis, Ron; Fichtinger, Gabor

2004-05-01

Ultrasound has become popular in clinical/surgical applications, both as the primary image guidance modality and also in conjunction with other modalities like CT or MRI. Three dimensional ultrasound (3DUS) systems have also demonstrated usefulness in image-guided therapy (IGT). At the same time, however, current lack of open-source and open-architecture multi-modal medical visualization systems prevents 3DUS from fulfilling its potential. Several stand-alone 3DUS systems, like Stradx or In-Vivo exist today. Although these systems have been found to be useful in real clinical setting, it is difficult to augment their functionality and integrate them in versatile IGT systems. To address these limitations, a robotic/freehand 3DUS open environment (CISUS) is being integrated into the 3D Slicer, an open-source research tool developed for medical image analysis and surgical planning. In addition, the system capitalizes on generic application programming interfaces (APIs) for tracking devices and robotic control. The resulting platform-independent open-source system may serve as a valuable tool to the image guided surgery community. Other researchers could straightforwardly integrate the generic CISUS system along with other functionalities (i.e. dual view visualization, registration, real-time tracking, segmentation, etc) to rapidly create their medical/surgical applications. Our current driving clinical application is robotically assisted and freehand 3DUS-guided liver ablation, which is fully being integrated under the CISUS-3D Slicer. Initial functionality and pre-clinical feasibility are demonstrated on phantom and ex-vivo animal models.

The year 2012 in the European Heart Journal-Cardiovascular Imaging: Part I.

PubMed

Edvardsen, Thor; Plein, Sven; Saraste, Antti; Knuuti, Juhani; Maurer, Gerald; Lancellotti, Patrizio

2013-06-01

The new multi-modality cardiovascular imaging journal, European Heart Journal - Cardiovascular Imaging, was started in 2012. During its first year, the new Journal has published an impressive collection of cardiovascular studies utilizing all cardiovascular imaging modalities. We will summarize the most important studies from its first year in two articles. The present 'Part I' of the review will focus on studies in myocardial function, myocardial ischaemia, and emerging techniques in cardiovascular imaging.

A digital 3D atlas of the marmoset brain based on multi-modal MRI.

PubMed

Liu, Cirong; Ye, Frank Q; Yen, Cecil Chern-Chyi; Newman, John D; Glen, Daniel; Leopold, David A; Silva, Afonso C

2018-04-01

The common marmoset (Callithrix jacchus) is a New-World monkey of growing interest in neuroscience. Magnetic resonance imaging (MRI) is an essential tool to unveil the anatomical and functional organization of the marmoset brain. To facilitate identification of regions of interest, it is desirable to register MR images to an atlas of the brain. However, currently available atlases of the marmoset brain are mainly based on 2D histological data, which are difficult to apply to 3D imaging techniques. Here, we constructed a 3D digital atlas based on high-resolution ex-vivo MRI images, including magnetization transfer ratio (a T1-like contrast), T2w images, and multi-shell diffusion MRI. Based on the multi-modal MRI images, we manually delineated 54 cortical areas and 16 subcortical regions on one hemisphere of the brain (the core version). The 54 cortical areas were merged into 13 larger cortical regions according to their locations to yield a coarse version of the atlas, and also parcellated into 106 sub-regions using a connectivity-based parcellation method to produce a refined atlas. Finally, we compared the new atlas set with existing histology atlases and demonstrated its applications in connectome studies, and in resting state and stimulus-based fMRI. The atlas set has been integrated into the widely-distributed neuroimaging data analysis software AFNI and SUMA, providing a readily usable multi-modal template space with multi-level anatomical labels (including labels from the Paxinos atlas) that can facilitate various neuroimaging studies of marmosets. Published by Elsevier Inc.

Multi-modality imaging: Bird's-eye view from the 2014 American Heart Association Scientific Sessions.

PubMed

AlJaroudi, Wael A; Einstein, Andrew J; Chaudhry, Farooq A; Lloyd, Steven G; Hage, Fadi G

2015-04-01

A large number of studies were presented at the 2014 American Heart Association Scientific Sessions. In this review, we will summarize key studies in nuclear cardiology, computed tomography, echocardiography, and cardiac magnetic resonance imaging. This brief review will be helpful for readers of the Journal who are interested in being updated on the latest research covering these imaging modalities.

Rational chemical design of the next generation of molecular imaging probes based on physics and biology: mixing modalities, colors and signals

PubMed Central

Longmire, Michelle R.; Ogawa, Mikako; Choyke, Peter L.

2012-01-01

In recent years, numerous in vivo molecular imaging probes have been developed. As a consequence, much has been published on the design and synthesis of molecular imaging probes focusing on each modality, each type of material, or each target disease. More recently, second generation molecular imaging probes with unique, multi-functional, or multiplexed characteristics have been designed. This critical review focuses on (i) molecular imaging using combinations of modalities and signals that employ the full range of the electromagnetic spectra, (ii) optimized chemical design of molecular imaging probes for in vivo kinetics based on biology and physiology across a range of physical sizes, (iii) practical examples of second generation molecular imaging probes designed to extract complementary data from targets using multiple modalities, color, and comprehensive signals (277 references). PMID:21607237

Quantitative Imaging Biomarkers of NAFLD

PubMed Central

Kinner, Sonja; Reeder, Scott B.

2016-01-01

Conventional imaging modalities, including ultrasonography (US), computed tomography (CT), and magnetic resonance (MR), play an important role in the diagnosis and management of patients with nonalcoholic fatty liver disease (NAFLD) by allowing noninvasive diagnosis of hepatic steatosis. However, conventional imaging modalities are limited as biomarkers of NAFLD for various reasons. Multi-parametric quantitative MRI techniques overcome many of the shortcomings of conventional imaging and allow comprehensive and objective evaluation of NAFLD. MRI can provide unconfounded biomarkers of hepatic fat, iron, and fibrosis in a single examination—a virtual biopsy has become a clinical reality. In this article, we will review the utility and limitation of conventional US, CT, and MR imaging for the diagnosis NAFLD. Recent advances in imaging biomarkers of NAFLD are also discussed with an emphasis in multi-parametric quantitative MRI. PMID:26848588

SU-E-J-110: A Novel Level Set Active Contour Algorithm for Multimodality Joint Segmentation/Registration Using the Jensen-Rényi Divergence.

PubMed

Markel, D; Naqa, I El; Freeman, C; Vallières, M

2012-06-01

To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. It was found that JR divergence when used for segmentation has an improved robustness to noise compared to using mutual information, or other entropy-based metrics. The MI metric failed at around 2/3 the noise power than the JR divergence. The JR divergence metric is useful for the task of joint segmentation/registration of multimodality images and shows improved results compared entropy based metric. The algorithm can be easily modified to incorporate non-intensity based images, which would allow applications into multi-modality and texture analysis. © 2012 American Association of Physicists in Medicine.

A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models.

PubMed

Lu, Pei; Xia, Jun; Li, Zhicheng; Xiong, Jing; Yang, Jian; Zhou, Shoujun; Wang, Lei; Chen, Mingyang; Wang, Cheng

2016-11-08

Accurate segmentation of blood vessels plays an important role in the computer-aided diagnosis and interventional treatment of vascular diseases. The statistical method is an important component of effective vessel segmentation; however, several limitations discourage the segmentation effect, i.e., dependence of the image modality, uneven contrast media, bias field, and overlapping intensity distribution of the object and background. In addition, the mixture models of the statistical methods are constructed relaying on the characteristics of the image histograms. Thus, it is a challenging issue for the traditional methods to be available in vessel segmentation from multi-modality angiographic images. To overcome these limitations, a flexible segmentation method with a fixed mixture model has been proposed for various angiography modalities. Our method mainly consists of three parts. Firstly, multi-scale filtering algorithm was used on the original images to enhance vessels and suppress noises. As a result, the filtered data achieved a new statistical characteristic. Secondly, a mixture model formed by three probabilistic distributions (two Exponential distributions and one Gaussian distribution) was built to fit the histogram curve of the filtered data, where the expectation maximization (EM) algorithm was used for parameters estimation. Finally, three-dimensional (3D) Markov random field (MRF) were employed to improve the accuracy of pixel-wise classification and posterior probability estimation. To quantitatively evaluate the performance of the proposed method, two phantoms simulating blood vessels with different tubular structures and noises have been devised. Meanwhile, four clinical angiographic data sets from different human organs have been used to qualitatively validate the method. To further test the performance, comparison tests between the proposed method and the traditional ones have been conducted on two different brain magnetic resonance angiography (MRA) data sets. The results of the phantoms were satisfying, e.g., the noise was greatly suppressed, the percentages of the misclassified voxels, i.e., the segmentation error ratios, were no more than 0.3%, and the Dice similarity coefficients (DSCs) were above 94%. According to the opinions of clinical vascular specialists, the vessels in various data sets were extracted with high accuracy since complete vessel trees were extracted while lesser non-vessels and background were falsely classified as vessel. In the comparison experiments, the proposed method showed its superiority in accuracy and robustness for extracting vascular structures from multi-modality angiographic images with complicated background noises. The experimental results demonstrated that our proposed method was available for various angiographic data. The main reason was that the constructed mixture probability model could unitarily classify vessel object from the multi-scale filtered data of various angiography images. The advantages of the proposed method lie in the following aspects: firstly, it can extract the vessels with poor angiography quality, since the multi-scale filtering algorithm can improve the vessel intensity in the circumstance such as uneven contrast media and bias field; secondly, it performed well for extracting the vessels in multi-modality angiographic images despite various signal-noises; and thirdly, it was implemented with better accuracy, and robustness than the traditional methods. Generally, these traits declare that the proposed method would have significant clinical application.

TU-CD-207-12: Impact of Anatomical Noise On Detection Performance of Microcalcifications in Multi-Contrast Breast Imaging

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

Garrett, J; Ge, Y; Li, K

2015-06-15

Purpose: The anatomical noise power spectra (NPS) for differential phase contrast (DPC) and dark field (DF) imaging have recently been characterized using a power-law model with two parameters, alpha and beta, an innovative extension to the methodology used in x-ray attenuation based breast imaging such as mammography, DBT, or cone-beam CT. Beta values of 3.6, 2.6, and 1.3 have been measured for absorption, DPC, and DF respectively for cadaver breasts imaged in the coronal plane; these dramatic differences should be reflected in their detection performance. The purpose of this study was to determine the impact of anatomical noise on breastmore » calcification detection and compare the detection performance of the three contrast mechanisms of a multi-contrast x-ray imaging system. Methods: In our studies, a calcification image object was segmented out of the multi-contrast images of a cadaver breast specimen. 50 measured total NPS were measured from breast cadavers directly. The ideal model observer detectability was calculated for a range of doses (5–100%) and a range of calcification sizes (diameter = 0.25–2.5 mm). Results: Overall we found the highest average detectability corresponded to DPC imaging (7.4 for 1 mm calc.), with DF the next highest (3.8 for 1 mm calc.), and absorption the lowest (3.2 for 1 mm calc.). However, absorption imaging also showed the slowest dependence on dose of the three modalities due to the significant anatomical noise. DPC showed a peak detectability for calcifications ∼1.25 mm in diameter, DF showed a peak for calcifications around 0.75 mm in diameter, and absorption imaging had no such peak in the range explored. Conclusion: Understanding imaging performance for DPC and DF is critical to transition these modalities to the clinic. The results presented here offer new insight into how these modalities complement absorption imaging to maximize the likelihood of detecting early breast cancers. J. Garrett, Y. Ge, K. Li: Nothing to disclose. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.« less

MRI-guided fiber-based fluorescence molecular tomography for preclinical atherosclerosis imaging

NASA Astrophysics Data System (ADS)

Li, Baoqiang; Pouliot, Philippe; Lesage, Frederic

2014-09-01

Multi-modal imaging combining fluorescent molecular tomography (FMT) with MRI could provide information in these two modalities as well as optimize the recovery of functional information with MR-guidance. Here, we present a MRI-guided FMT system. An optical probe was designed consisting of a fiber plate on the top and bottom sides of the animal bed, respectively. In experiment, animal was installed between the two plates. Mounting fibers on each plate, transmission measuring could be conducted from both sides of the animal. Moreover, an accurate fluorescence reconstruction was achieved with MRI-derived anatomical guidance. The sensitivity of the FMT system was evaluated with a phantom showing that with long fibers, it was sufficient to detect 10nM Cy5.5 solution with ~28.5 dB in the phantom. The system was eventually used to image MMP activity involved in atherosclerosis with two ATX mice and two control mice. The reconstruction results were in agreement with ex vivo measurement.

Multi-Modal Traveler Information System - Gateway Functional Requirements

DOT National Transportation Integrated Search

1997-11-17

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

Multi-Modal Traveler Information System - Gateway Interface Control Requirements

DOT National Transportation Integrated Search

1997-10-30

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

Multi-modality image fusion based on enhanced fuzzy radial basis function neural networks.

PubMed

Chao, Zhen; Kim, Dohyeon; Kim, Hee-Joung

2018-04-01

In clinical applications, single modality images do not provide sufficient diagnostic information. Therefore, it is necessary to combine the advantages or complementarities of different modalities of images. Recently, neural network technique was applied to medical image fusion by many researchers, but there are still many deficiencies. In this study, we propose a novel fusion method to combine multi-modality medical images based on the enhanced fuzzy radial basis function neural network (Fuzzy-RBFNN), which includes five layers: input, fuzzy partition, front combination, inference, and output. Moreover, we propose a hybrid of the gravitational search algorithm (GSA) and error back propagation algorithm (EBPA) to train the network to update the parameters of the network. Two different patterns of images are used as inputs of the neural network, and the output is the fused image. A comparison with the conventional fusion methods and another neural network method through subjective observation and objective evaluation indexes reveals that the proposed method effectively synthesized the information of input images and achieved better results. Meanwhile, we also trained the network by using the EBPA and GSA, individually. The results reveal that the EBPGSA not only outperformed both EBPA and GSA, but also trained the neural network more accurately by analyzing the same evaluation indexes. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Integration of Sparse Multi-modality Representation and Anatomical Constraint for Isointense Infant Brain MR Image Segmentation

PubMed Central

Wang, Li; Shi, Feng; Gao, Yaozong; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to poor spatial resolution, severe partial volume effect, and the ongoing maturation and myelination process. During the first year of life, the brain image contrast between white and gray matters undergoes dramatic changes. In particular, the image contrast inverses around 6–8 months of age, where the white and gray matter tissues are isointense in T1 and T2 weighted images and hence exhibit the extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a general framework that adopts sparse representation to fuse the multi-modality image information and further incorporate the anatomical constraints for brain tissue segmentation. Specifically, we first derive an initial segmentation from a library of aligned images with ground-truth segmentations by using sparse representation in a patch-based fashion for the multi-modality T1, T2 and FA images. The segmentation result is further iteratively refined by integration of the anatomical constraint. The proposed method was evaluated on 22 infant brain MR images acquired at around 6 months of age by using a leave-one-out cross-validation, as well as other 10 unseen testing subjects. Our method achieved a high accuracy for the Dice ratios that measure the volume overlap between automated and manual segmentations, i.e., 0.889±0.008 for white matter and 0.870±0.006 for gray matter. PMID:24291615

Multi-Modal Traveler Information System - Alternative GCM Corridor Technologies and Strategies

DOT National Transportation Integrated Search

1997-10-24

The purpose of this working paper is to summarize current and evolving Intelligent Transportation System (ITS) technologies and strategies related to the design, development, and deployment of regional multi-modal traveler information systems. This r...

Multi-Modal Traveler Information System - GCM Corridor Architecture Interface Control Requirements

DOT National Transportation Integrated Search

1997-10-31

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

Multi-Modal Traveler Information System - GCM Corridor Architecture Functional Requirements

DOT National Transportation Integrated Search

1997-11-17

The Multi-Modal Traveler Information System (MMTIS) project involves a large number of Intelligent Transportation System (ITS) related tasks. It involves research of all ITS initiatives in the Gary-Chicago-Milwaukee (GCM) Corridor which are currently...

An image database management system for conducting CAD research

NASA Astrophysics Data System (ADS)

Gruszauskas, Nicholas; Drukker, Karen; Giger, Maryellen L.

2007-03-01

The development of image databases for CAD research is not a trivial task. The collection and management of images and their related metadata from multiple sources is a time-consuming but necessary process. By standardizing and centralizing the methods in which these data are maintained, one can generate subsets of a larger database that match the specific criteria needed for a particular research project in a quick and efficient manner. A research-oriented management system of this type is highly desirable in a multi-modality CAD research environment. An online, webbased database system for the storage and management of research-specific medical image metadata was designed for use with four modalities of breast imaging: screen-film mammography, full-field digital mammography, breast ultrasound and breast MRI. The system was designed to consolidate data from multiple clinical sources and provide the user with the ability to anonymize the data. Input concerning the type of data to be stored as well as desired searchable parameters was solicited from researchers in each modality. The backbone of the database was created using MySQL. A robust and easy-to-use interface for entering, removing, modifying and searching information in the database was created using HTML and PHP. This standardized system can be accessed using any modern web-browsing software and is fundamental for our various research projects on computer-aided detection, diagnosis, cancer risk assessment, multimodality lesion assessment, and prognosis. Our CAD database system stores large amounts of research-related metadata and successfully generates subsets of cases that match the user's desired search criteria.

Reconciliation of diverse telepathology system designs. Historic issues and implications for emerging markets and new applications.

PubMed

Weinstein, Ronald S; Graham, Anna R; Lian, Fangru; Braunhut, Beth L; Barker, Gail R; Krupinski, Elizabeth A; Bhattacharyya, Achyut K

2012-04-01

Telepathology, the distant service component of digital pathology, is a growth industry. The word "telepathology" was introduced into the English Language in 1986. Initially, two different, competing imaging modalities were used for telepathology. These were dynamic (real time) robotic telepathology and static image (store-and-forward) telepathology. In 1989, a hybrid dynamic robotic/static image telepathology system was developed in Norway. This hybrid imaging system bundled these two primary pathology imaging modalities into a single multi-modality pathology imaging system. Similar hybrid systems were subsequently developed and marketed in other countries as well. It is noteworthy that hybrid dynamic robotic/static image telepathology systems provided the infrastructure for the first truly sustainable telepathology services. Since then, impressive progress has been made in developing another telepathology technology, so-called "virtual microscopy" telepathology (also called "whole slide image" telepathology or "WSI" telepathology). Over the past decade, WSI has appeared to be emerging as the preferred digital telepathology digital imaging modality. However, recently, there has been a re-emergence of interest in dynamic-robotic telepathology driven, in part, by concerns over the lack of a means for up-and-down focusing (i.e., Z-axis focusing) using early WSI processors. In 2010, the initial two U.S. patents for robotic telepathology (issued in 1993 and 1994) expired enabling many digital pathology equipment companies to incorporate dynamic-robotic telepathology modules into their WSI products for the first time. The dynamic-robotic telepathology module provided a solution to the up-and-down focusing issue. WSI and dynamic robotic telepathology are now, rapidly, being bundled into a new class of telepathology/digital pathology imaging system, the "WSI-enhanced dynamic robotic telepathology system". To date, six major WSI processor equipment companies have embraced the approach and developed WSI-enhanced dynamic-robotic digital telepathology systems, marketed under a variety of labels. Successful commercialization of such systems could help overcome the current resistance of some pathologists to incorporate digital pathology, and telepathology, into their routine and esoteric laboratory services. Also, WSI-enhanced dynamic robotic telepathology could be useful for providing general pathology and subspecialty pathology services to many of the world's underserved populations in the decades ahead. This could become an important enabler for the delivery of patient-centered healthcare in the future. © 2012 The Authors APMIS © 2012 APMIS.

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

PubMed

Yang, C; Paulson, E; Li, X

2012-06-01

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

LINKS: learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images.

PubMed

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H; Lin, Weili; Shen, Dinggang

2015-03-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.

LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images

PubMed Central

Wang, Li; Gao, Yaozong; Shi, Feng; Li, Gang; Gilmore, John H.; Lin, Weili; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination processes. In the first year of life, the image contrast between white and gray matters of the infant brain undergoes dramatic changes. In particular, the image contrast is inverted around 6-8 months of age, and the white and gray matter tissues are isointense in both T1- and T2-weighted MR images and thus exhibit the extremely low tissue contrast, which poses significant challenges for automated segmentation. Most previous studies used multi-atlas label fusion strategy, which has the limitation of equally treating the different available image modalities and is often computationally expensive. To cope with these limitations, in this paper, we propose a novel learning-based multi-source integration framework for segmentation of infant brain images. Specifically, we employ the random forest technique to effectively integrate features from multi-source images together for tissue segmentation. Here, the multi-source images include initially only the multi-modality (T1, T2 and FA) images and later also the iteratively estimated and refined tissue probability maps of gray matter, white matter, and cerebrospinal fluid. Experimental results on 119 infants show that the proposed method achieves better performance than other state-of-the-art automated segmentation methods. Further validation was performed on the MICCAI grand challenge and the proposed method was ranked top among all competing methods. Moreover, to alleviate the possible anatomical errors, our method can also be combined with an anatomically-constrained multi-atlas labeling approach for further improving the segmentation accuracy. PMID:25541188

Methods to mitigate data truncation artifacts in multi-contrast tomosynthesis image reconstructions

NASA Astrophysics Data System (ADS)

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

2015-03-01

Differential phase contrast imaging is a promising new image modality that utilizes the refraction rather than the absorption of x-rays to image an object. A Talbot-Lau interferometer may be used to permit differential phase contrast imaging with a conventional medical x-ray source and detector. However, the current size of the gratings fabricated for these interferometers are often relatively small. As a result, data truncation image artifacts are often observed in a tomographic acquisition and reconstruction. When data are truncated in x-ray absorption imaging, the methods have been introduced to mitigate the truncation artifacts. However, the same strategy to mitigate absorption truncation artifacts may not be appropriate for differential phase contrast or dark field tomographic imaging. In this work, several new methods to mitigate data truncation artifacts in a multi-contrast imaging system have been proposed and evaluated for tomosynthesis data acquisitions. The proposed methods were validated using experimental data acquired for a bovine udder as well as several cadaver breast specimens using a benchtop system at our facility.

Using IHE and HL7 conformance to specify consistent PACS interoperability for a large multi-center enterprise.

PubMed

Henderson, Michael L; Dayhoff, Ruth E; Titton, Csaba P; Casertano, Andrew

2006-01-01

As part of its patient care mission, the U.S. Veterans Health Administration performs diagnostic imaging procedures at 141 medical centers and 850 outpatient clinics. VHA's VistA Imaging Package provides a full archival, display, and communications infrastructure and interfaces to radiology and other HIS modules as well as modalities and a worklist provider In addition, various medical center entities within VHA have elected to install commercial picture archiving and communications systems to enable image organization and interpretation. To evaluate interfaces between commercial PACS, the VistA hospital information system, and imaging modalities, VHA has built a fully constrained specification that is based on the Radiology Technical Framework (Rad-TF) Integrating the Healthcare Enterprise. The Health Level Seven normative conformance mechanism was applied to the IHE Rad-TF and agency requirements to arrive at a baseline set of message specifications. VHA provides a thorough implementation and testing process to promote the adoption of standards-based interoperability by all PACS vendors that want to interface with VistA Imaging.

Multi-modal trip planning system : Northeastern Illinois Regional Transportation Authority.

DOT National Transportation Integrated Search

2013-01-01

This report evaluates the Multi-Modal Trip Planner System (MMTPS) implemented by the Northeastern Illinois Regional Transportation Authority (RTA) against the specific functional objectives enumerated by the Federal Transit Administration (FTA) in it...

A fuzzy feature fusion method for auto-segmentation of gliomas with multi-modality diffusion and perfusion magnetic resonance images in radiotherapy.

PubMed

Guo, Lu; Wang, Ping; Sun, Ranran; Yang, Chengwen; Zhang, Ning; Guo, Yu; Feng, Yuanming

2018-02-19

The diffusion and perfusion magnetic resonance (MR) images can provide functional information about tumour and enable more sensitive detection of the tumour extent. We aimed to develop a fuzzy feature fusion method for auto-segmentation of gliomas in radiotherapy planning using multi-parametric functional MR images including apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV). For each functional modality, one histogram-based fuzzy model was created to transform image volume into a fuzzy feature space. Based on the fuzzy fusion result of the three fuzzy feature spaces, regions with high possibility belonging to tumour were generated automatically. The auto-segmentations of tumour in structural MR images were added in final auto-segmented gross tumour volume (GTV). For evaluation, one radiation oncologist delineated GTVs for nine patients with all modalities. Comparisons between manually delineated and auto-segmented GTVs showed that, the mean volume difference was 8.69% (±5.62%); the mean Dice's similarity coefficient (DSC) was 0.88 (±0.02); the mean sensitivity and specificity of auto-segmentation was 0.87 (±0.04) and 0.98 (±0.01) respectively. High accuracy and efficiency can be achieved with the new method, which shows potential of utilizing functional multi-parametric MR images for target definition in precision radiation treatment planning for patients with gliomas.

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

The following reports are presented on this project:A first year progress report on: Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; A second year progress report on: Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation; An Extensible, Interchangeable and Sharable Database Model for Improving Multidisciplinary Aircraft Design; Interactive, Secure Web-enabled Aircraft Engine Simulation Using XML Databinding Integration; and Improving the Aircraft Design Process Using Web-based Modeling and Simulation.

A new approach of building 3D visualization framework for multimodal medical images display and computed assisted diagnosis

NASA Astrophysics Data System (ADS)

Li, Zhenwei; Sun, Jianyong; Zhang, Jianguo

2012-02-01

As more and more CT/MR studies are scanning with larger volume of data sets, more and more radiologists and clinician would like using PACS WS to display and manipulate these larger data sets of images with 3D rendering features. In this paper, we proposed a design method and implantation strategy to develop 3D image display component not only with normal 3D display functions but also with multi-modal medical image fusion as well as compute-assisted diagnosis of coronary heart diseases. The 3D component has been integrated into the PACS display workstation of Shanghai Huadong Hospital, and the clinical practice showed that it is easy for radiologists and physicians to use these 3D functions such as multi-modalities' (e.g. CT, MRI, PET, SPECT) visualization, registration and fusion, and the lesion quantitative measurements. The users were satisfying with the rendering speeds and quality of 3D reconstruction. The advantages of the component include low requirements for computer hardware, easy integration, reliable performance and comfortable application experience. With this system, the radiologists and the clinicians can manipulate with 3D images easily, and use the advanced visualization tools to facilitate their work with a PACS display workstation at any time.

A portable microscopy system for fluorescence, polarized, and brightfield imaging

NASA Astrophysics Data System (ADS)

Gordon, Paul; Wattinger, Rolla; Lewis, Cody; Venancio, Vinicius Paula; Mertens-Talcott, Susanne U.; Coté, Gerard

2018-02-01

The use of mobile phones to conduct diagnostic microscopy at the point-of-care presents intriguing possibilities for the advancement of high-quality medical care in remote settings. However, it is challenging to create a single device that can adapt to the ever-varying camera technologies in phones or that can image with the customization that multiple modalities require for applications such as malaria diagnosis. A portable multi-modal microscope system is presented that utilizes a Raspberry Pi to collect and transmit data wirelessly to a myriad of electronic devices for image analysis. The microscopy system is capable of providing to the user correlated brightfield, polarized, and fluorescent images of samples fixed on traditional microscopy slides. The multimodal diagnostic capabilities of the microscope were assessed by measuring parasitemia of Plasmodium falciparum-infected thin blood smears. The device is capable of detecting fluorescently-labeled DNA using FITC excitation (490 nm) and emission (525 nm), the birefringent P. falciparum byproduct hemozoin, and detecting brightfield absorption with a resolution of 0.78 micrometers (element 9-3 of a 1951 Air Force Target). This microscopy system is a novel portable imaging tool that may be a viable candidate for field implementation if challenges of system durability, cost considerations, and full automation can be overcome.

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

PubMed Central

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Fall Risk Assessment and Early-Warning for Toddler Behaviors at Home

PubMed Central

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-01-01

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second. PMID:24335727

Fall risk assessment and early-warning for toddler behaviors at home.

PubMed

Yang, Mau-Tsuen; Chuang, Min-Wen

2013-12-10

Accidental falls are the major cause of serious injuries in toddlers, with most of these falls happening at home. Instead of providing immediate fall detection based on short-term observations, this paper proposes an early-warning childcare system to monitor fall-prone behaviors of toddlers at home. Using 3D human skeleton tracking and floor plane detection based on depth images captured by a Kinect system, eight fall-prone behavioral modules of toddlers are developed and organized according to four essential criteria: posture, motion, balance, and altitude. The final fall risk assessment is generated by a multi-modal fusion using either a weighted mean thresholding or a support vector machine (SVM) classification. Optimizations are performed to determine local parameter in each module and global parameters of the multi-modal fusion. Experimental results show that the proposed system can assess fall risks and trigger alarms with an accuracy rate of 92% at a speed of 20 frames per second.

Cloud-based processing of multi-spectral imaging data

NASA Astrophysics Data System (ADS)

Bernat, Amir S.; Bolton, Frank J.; Weiser, Reuven; Levitz, David

2017-03-01

Multispectral imaging holds great promise as a non-contact tool for the assessment of tissue composition. Performing multi - spectral imaging on a hand held mobile device would allow to bring this technology and with it knowledge to low resource settings to provide a state of the art classification of tissue health. This modality however produces considerably larger data sets than white light imaging and requires preliminary image analysis for it to be used. The data then needs to be analyzed and logged, while not requiring too much of the system resource or a long computation time and battery use by the end point device. Cloud environments were designed to allow offloading of those problems by allowing end point devices (smartphones) to offload computationally hard tasks. For this end we present a method where the a hand held device based around a smartphone captures a multi - spectral dataset in a movie file format (mp4) and compare it to other image format in size, noise and correctness. We present the cloud configuration used for segmenting images to frames where they can later be used for further analysis.

A small field of view camera for hybrid gamma and optical imaging

NASA Astrophysics Data System (ADS)

Lees, J. E.; Bugby, S. L.; Bhatia, B. S.; Jambi, L. K.; Alqahtani, M. S.; McKnight, W. R.; Ng, A. H.; Perkins, A. C.

2014-12-01

The development of compact low profile gamma-ray detectors has allowed the production of small field of view, hand held imaging devices for use at the patient bedside and in operating theatres. The combination of an optical and a gamma camera, in a co-aligned configuration, offers high spatial resolution multi-modal imaging giving a superimposed scintigraphic and optical image. This innovative introduction of hybrid imaging offers new possibilities for assisting surgeons in localising the site of uptake in procedures such as sentinel node detection. Recent improvements to the camera system along with results of phantom and clinical imaging are reported.

Comparison of the application of B-mode and strain elastography ultrasound in the estimation of lymph node metastasis of papillary thyroid carcinoma based on a radiomics approach.

PubMed

Liu, Tongtong; Ge, Xifeng; Yu, Jinhua; Guo, Yi; Wang, Yuanyuan; Wang, Wenping; Cui, Ligang

2018-06-21

B-mode ultrasound (B-US) and strain elastography ultrasound (SE-US) images have a potential to distinguish thyroid tumor with different lymph node (LN) status. The purpose of our study is to investigate whether the application of multi-modality images including B-US and SE-US can improve the discriminability of thyroid tumor with LN metastasis based on a radiomics approach. Ultrasound (US) images including B-US and SE-US images of 75 papillary thyroid carcinoma (PTC) cases were retrospectively collected. A radiomics approach was developed in this study to estimate LNs status of PTC patients. The approach included image segmentation, quantitative feature extraction, feature selection and classification. Three feature sets were extracted from B-US, SE-US, and multi-modality containing B-US and SE-US. They were used to evaluate the contribution of different modalities. A total of 684 radiomics features have been extracted in our study. We used sparse representation coefficient-based feature selection method with 10-bootstrap to reduce the dimension of feature sets. Support vector machine with leave-one-out cross-validation was used to build the model for estimating LN status. Using features extracted from both B-US and SE-US, the radiomics-based model produced an area under the receiver operating characteristic curve (AUC) [Formula: see text] 0.90, accuracy (ACC) [Formula: see text] 0.85, sensitivity (SENS) [Formula: see text] 0.77 and specificity (SPEC) [Formula: see text] 0.88, which was better than using features extracted from B-US or SE-US separately. Multi-modality images provided more information in radiomics study. Combining use of B-US and SE-US could improve the LN metastasis estimation accuracy for PTC patients.

Multi-modal anatomical optical coherence tomography and CT for in vivo dynamic upper airway imaging

NASA Astrophysics Data System (ADS)

Balakrishnan, Santosh; Bu, Ruofei; Price, Hillel; Zdanski, Carlton; Oldenburg, Amy L.

2017-02-01

We describe a novel, multi-modal imaging protocol for validating quantitative dynamic airway imaging performed using anatomical Optical Coherence Tomography (aOCT). The aOCT system consists of a catheter-based aOCT probe that is deployed via a bronchoscope, while a programmable ventilator is used to control airway pressure. This setup is employed on the bed of a Siemens Biograph CT system capable of performing respiratory-gated acquisitions. In this arrangement the position of the aOCT catheter may be visualized with CT to aid in co-registration. Utilizing this setup we investigate multiple respiratory pressure parameters with aOCT, and respiratory-gated CT, on both ex vivo porcine trachea and live, anesthetized pigs. This acquisition protocol has enabled real-time measurement of airway deformation with simultaneous measurement of pressure under physiologically relevant static and dynamic conditions- inspiratory peak or peak positive airway pressures of 10-40 cm H2O, and 20-30 breaths per minute for dynamic studies. We subsequently compare the airway cross sectional areas (CSA) obtained from aOCT and CT, including the change in CSA at different stages of the breathing cycle for dynamic studies, and the CSA at different peak positive airway pressures for static studies. This approach has allowed us to improve our acquisition methodology and to validate aOCT measurements of the dynamic airway for the first time. We believe that this protocol will prove invaluable for aOCT system development and greatly facilitate translation of OCT systems for airway imaging into the clinical setting.

Multi-Modal Intelligent Traffic Signal Systems (MMITSS) impacts assessment.

DOT National Transportation Integrated Search

2015-08-01

The study evaluates the potential network-wide impacts of the Multi-Modal Intelligent Transportation Signal System (MMITSS) based on a field data analysis utilizing data collected from a MMITSS prototype and a simulation analysis. The Intelligent Tra...

Diagnostic role of (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging for early and atypical bone metastases.

PubMed

Chen, Xiao-Liang; Li, Qian; Cao, Lin; Jiang, Shi-Xi

2014-01-01

The bone metastasis appeared early before the bone imaging for most of the above patients. (99)Tc(m)-MDP ((99)Tc(m) marked methylene diphosphonate) bone imaging could diagnosis the bone metastasis with highly sensitivity, but with lower specificity. The aim of this study is to explore the diagnostic value of (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging for the early period atypical bone metastases. 15 to 30 mCi (99)Tc(m)-MDP was intravenously injected to the 34 malignant patients diagnosed as doubtful early bone metastases. SPECT, CT and SPECT/CT images were captured and analyzed consequently. For the patients diagnosed as early period atypical bone metastases by SPECT/CT, combining the SPECT/CT and MRI together as the SPECT/MRI integrated image. The obtained SPECT/MRI image was analyzed and compared with the pathogenic results of patients. The results indicated that 34 early period doubtful metastatic focus, including 34 SPECT positive focus, 17 focus without special changes by using CT method, 11 bone metastases focus by using SPECT/CT method, 23 doubtful bone metastases focus, 8 doubtful bone metastases focus, 14 doubtful bone metastases focus and 2 focus without clear image. Totally, SPECT/CT combined with SPECT/MRI method diagnosed 30 bone metastatic focus and 4 doubtfully metastatic focus. In conclusion, (99)Tc(m)-MDP SPECT/CT combined SPECT/MRI Multi modality imaging shows a higher diagnostic value for the early period bone metastases, which also enhances the diagnostic accuracy rate.

Big data sharing and analysis to advance research in post-traumatic epilepsy.

PubMed

Duncan, Dominique; Vespa, Paul; Pitkanen, Asla; Braimah, Adebayo; Lapinlampi, Nina; Toga, Arthur W

2018-06-01

We describe the infrastructure and functionality for a centralized preclinical and clinical data repository and analytic platform to support importing heterogeneous multi-modal data, automatically and manually linking data across modalities and sites, and searching content. We have developed and applied innovative image and electrophysiology processing methods to identify candidate biomarkers from MRI, EEG, and multi-modal data. Based on heterogeneous biomarkers, we present novel analytic tools designed to study epileptogenesis in animal model and human with the goal of tracking the probability of developing epilepsy over time. Copyright © 2017. Published by Elsevier Inc.

A combined positron emission tomography (PET)-electron paramagnetic resonance imaging (EPRI) system: initial evaluation of a prototype scanner

NASA Astrophysics Data System (ADS)

Tseytlin, Mark; Stolin, Alexander V.; Guggilapu, Priyaankadevi; Bobko, Andrey A.; Khramtsov, Valery V.; Tseytlin, Oxana; Raylman, Raymond R.

2018-05-01

The advent of hybrid scanners, combining complementary modalities, has revolutionized the application of advanced imaging technology to clinical practice and biomedical research. In this project, we investigated the melding of two complementary, functional imaging methods: positron emission tomography (PET) and electron paramagnetic resonance imaging (EPRI). PET radiotracers can provide important information about cellular parameters, such as glucose metabolism. While EPR probes can provide assessment of tissue microenvironment, measuring oxygenation and pH, for example. Therefore, a combined PET/EPRI scanner promises to provide new insights not attainable with current imagers by simultaneous acquisition of multiple components of tissue microenvironments. To explore the simultaneous acquisition of PET and EPR images, a prototype system was created by combining two existing scanners. Specifically, a silicon photomultiplier (SiPM)-based PET scanner ring designed as a portable scanner was combined with an EPRI scanner designed for the imaging of small animals. The ability of the system to obtain simultaneous images was assessed with a small phantom consisting of four cylinders containing both a PET tracer and EPR spin probe. The resulting images demonstrated the ability to obtain contemporaneous PET and EPR images without cross-modality interference. Given the promising results from this initial investigation, the next step in this project is the construction of the next generation pre-clinical PET/EPRI scanner for multi-parametric assessment of physiologically-important parameters of tissue microenvironments.

Endoscopic optical coherence tomography: technologies and clinical applications [Invited

PubMed Central

Gora, Michalina J.; Suter, Melissa J.; Tearney, Guillermo J.; Li, Xingde

2017-01-01

In this paper, we review the current state of technology development and clinical applications of endoscopic optical coherence tomography (OCT). Key design and engineering considerations are discussed for most OCT endoscopes, including side-viewing and forward-viewing probes, along with different scanning mechanisms (proximal-scanning versus distal-scanning). Multi-modal endoscopes that integrate OCT with other imaging modalities are also discussed. The review of clinical applications of endoscopic OCT focuses heavily on diagnosis of diseases and guidance of interventions. Representative applications in several organ systems are presented, such as in the cardiovascular, digestive, respiratory, and reproductive systems. A brief outlook of the field of endoscopic OCT is also discussed. PMID:28663882

Differences in Multi-Modal Ultrasound Imaging between Triple Negative and Non-Triple Negative Breast Cancer.

PubMed

Li, Ziyao; Tian, Jiawei; Wang, Xiaowei; Wang, Ying; Wang, Zhenzhen; Zhang, Lei; Jing, Hui; Wu, Tong

2016-04-01

The objective of this study was to identify multi-modal ultrasound imaging parameters that could potentially help to differentiate between triple negative breast cancer (TNBC) and non-TNBC. Conventional ultrasonography, ultrasound strain elastography and 3-D ultrasound (3-D-US) findings from 50 TNBC and 179 non-TNBC patients were retrospectively reviewed. Immunohistochemical examination was used as the reference gold standard for cancer subtyping. Different ultrasound modalities were initially analyzed to define TNBC-related features. Subsequently, logistic regression analysis was applied to TNBC-related features to establish models for predicting TNBC. TNBCs often presented as micro-lobulated, markedly hypo-echoic masses with an abrupt interface (p = 0.015, 0.0015 and 0.004, compared with non-TNBCs, respectively) on conventional ultrasound, and showed a diminished retraction pattern phenomenon in the coronal plane (p = 0.035) on 3-D-US. Our findings suggest that B-mode ultrasound and 3-D-US in multi-modality ultrasonography could be a useful non-invasive technique for differentiating TNBCs from non-TNBCs. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Multi-modal spectroscopic imaging with synchrotron light to study mechanisms of brain disease

NASA Astrophysics Data System (ADS)

Summers, Kelly L.; Fimognari, Nicholas; Hollings, Ashley; Kiernan, Mitchell; Lam, Virginie; Tidy, Rebecca J.; Takechi, Ryu; George, Graham N.; Pickering, Ingrid J.; Mamo, John C.; Harris, Hugh H.; Hackett, Mark J.

2017-04-01

The international health care costs associated with Alzheimer's disease (AD) and dementia have been predicted to reach $2 trillion USD by 2030. As such, there is urgent need to develop new treatments and diagnostic methods to stem an international health crisis. A major limitation to therapy and diagnostic development is the lack of complete understanding about the disease mechanisms. Spectroscopic methods at synchrotron light sources, such as FTIR, XRF, and XAS, offer a "multi-modal imaging platform" to reveal a wealth of important biochemical information in situ within ex vivo tissue sections, to increase our understanding of disease mechanisms.

2D-3D registration using gradient-based MI for image guided surgery systems

NASA Astrophysics Data System (ADS)

Yim, Yeny; Chen, Xuanyi; Wakid, Mike; Bielamowicz, Steve; Hahn, James

2011-03-01

Registration of preoperative CT data to intra-operative video images is necessary not only to compare the outcome of the vocal fold after surgery with the preplanned shape but also to provide the image guidance for fusion of all imaging modalities. We propose a 2D-3D registration method using gradient-based mutual information. The 3D CT scan is aligned to 2D endoscopic images by finding the corresponding viewpoint between the real camera for endoscopic images and the virtual camera for CT scans. Even though mutual information has been successfully used to register different imaging modalities, it is difficult to robustly register the CT rendered image to the endoscopic image due to varying light patterns and shape of the vocal fold. The proposed method calculates the mutual information in the gradient images as well as original images, assigning more weight to the high gradient regions. The proposed method can emphasize the effect of vocal fold and allow a robust matching regardless of the surface illumination. To find the viewpoint with maximum mutual information, a downhill simplex method is applied in a conditional multi-resolution scheme which leads to a less-sensitive result to local maxima. To validate the registration accuracy, we evaluated the sensitivity to initial viewpoint of preoperative CT. Experimental results showed that gradient-based mutual information provided robust matching not only for two identical images with different viewpoints but also for different images acquired before and after surgery. The results also showed that conditional multi-resolution scheme led to a more accurate registration than single-resolution.

Multispectral scanning laser ophthalmoscopy combined with optical coherence tomography for simultaneous in vivo mouse retinal imaging

NASA Astrophysics Data System (ADS)

Zhang, Pengfei; Zam, Azhar; Jian, Yifan; Wang, Xinlei; Burns, Marie E.; Sarunic, Marinko V.; Pugh, Edward N.; Zawadzki, Robert J.

2015-03-01

A compact, non-invasive multi-modal system has been developed for in vivo mouse retina imaging. It is configured for simultaneously detecting green and red fluorescent protein signals with scanning laser ophthalmoscopy (SLO) back-scattered light from the SLO illumination beam, and depth information about different retinal layers by means of Optical Coherence Tomography (OCT). Simultaneous assessment of retinal characteristics with different modalities can provide a wealth of information about the structural and functional changes in the retinal neural tissue and chorio-retinal vasculature in vivo. Additionally, simultaneous acquisition of multiple channels facilitates analysis of the data of different modalities by automatic temporal and structural co-registration. As an example of the instrument's performance we imaged the retina of a mouse with constitutive expression of GFP in microglia cells (Cx3cr1GFP/+), and which also expressed the red fluorescent protein mCherry in Müller glial cells by means of adeno-associated virus delivery (AAV2) of an mCherry cDNA driven by the GFAP (glial fibrillary acid protein) promoter.

Extending Whole Slide Imaging: Color Darkfield Internal Reflection Illumination (DIRI) for Biological Applications

PubMed Central

Namiki, Kana; Miyawaki, Atsushi; Ishikawa, Takuji

2017-01-01

Whole slide imaging (WSI) is a useful tool for multi-modal imaging, and in our work, we have often combined WSI with darkfield microscopy. However, traditional darkfield microscopy cannot use a single condenser to support high- and low-numerical-aperture objectives, which limits the modality of WSI. To overcome this limitation, we previously developed a darkfield internal reflection illumination (DIRI) microscope using white light-emitting diodes (LEDs). Although the developed DIRI is useful for biological applications, substantial problems remain to be resolved. In this study, we propose a novel illumination technique called color DIRI. The use of three-color LEDs dramatically improves the capability of the system, such that color DIRI (1) enables optimization of the illumination color; (2) can be combined with an oil objective lens; (3) can produce fluorescence excitation illumination; (4) can adjust the wavelength of light to avoid cell damage or reactions; and (5) can be used as a photostimulator. These results clearly illustrate that the proposed color DIRI can significantly extend WSI modalities for biological applications. PMID:28085892

Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

NASA Astrophysics Data System (ADS)

Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

2015-03-01

Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings

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

Bouchard, Kristofer E.; Conant, David F.; Anumanchipalli, Gopala K.

A complete neurobiological understanding of speech motor control requires determination of the relationship between simultaneously recorded neural activity and the kinematics of the lips, jaw, tongue, and larynx. Many speech articulators are internal to the vocal tract, and therefore simultaneously tracking the kinematics of all articulators is nontrivial-especially in the context of human electrophysiology recordings. Here, we describe a noninvasive, multi-modal imaging system to monitor vocal tract kinematics, demonstrate this system in six speakers during production of nine American English vowels, and provide new analysis of such data. Classification and regression analysis revealed considerable variability in the articulator-to-acoustic relationship acrossmore » speakers. Non-negative matrix factorization extracted basis sets capturing vocal tract shapes allowing for higher vowel classification accuracy than traditional methods. Statistical speech synthesis generated speech from vocal tract measurements, and we demonstrate perceptual identification. We demonstrate the capacity to predict lip kinematics from ventral sensorimotor cortical activity. These results demonstrate a multi-modal system to non-invasively monitor articulator kinematics during speech production, describe novel analytic methods for relating kinematic data to speech acoustics, and provide the first decoding of speech kinematics from electrocorticography. These advances will be critical for understanding the cortical basis of speech production and the creation of vocal prosthetics.« less

High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings

PubMed Central

Anumanchipalli, Gopala K.; Dichter, Benjamin; Chaisanguanthum, Kris S.; Johnson, Keith; Chang, Edward F.

2016-01-01

A complete neurobiological understanding of speech motor control requires determination of the relationship between simultaneously recorded neural activity and the kinematics of the lips, jaw, tongue, and larynx. Many speech articulators are internal to the vocal tract, and therefore simultaneously tracking the kinematics of all articulators is nontrivial—especially in the context of human electrophysiology recordings. Here, we describe a noninvasive, multi-modal imaging system to monitor vocal tract kinematics, demonstrate this system in six speakers during production of nine American English vowels, and provide new analysis of such data. Classification and regression analysis revealed considerable variability in the articulator-to-acoustic relationship across speakers. Non-negative matrix factorization extracted basis sets capturing vocal tract shapes allowing for higher vowel classification accuracy than traditional methods. Statistical speech synthesis generated speech from vocal tract measurements, and we demonstrate perceptual identification. We demonstrate the capacity to predict lip kinematics from ventral sensorimotor cortical activity. These results demonstrate a multi-modal system to non-invasively monitor articulator kinematics during speech production, describe novel analytic methods for relating kinematic data to speech acoustics, and provide the first decoding of speech kinematics from electrocorticography. These advances will be critical for understanding the cortical basis of speech production and the creation of vocal prosthetics. PMID:27019106

High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings

DOE PAGES

Bouchard, Kristofer E.; Conant, David F.; Anumanchipalli, Gopala K.; ...

2016-03-28

A complete neurobiological understanding of speech motor control requires determination of the relationship between simultaneously recorded neural activity and the kinematics of the lips, jaw, tongue, and larynx. Many speech articulators are internal to the vocal tract, and therefore simultaneously tracking the kinematics of all articulators is nontrivial-especially in the context of human electrophysiology recordings. Here, we describe a noninvasive, multi-modal imaging system to monitor vocal tract kinematics, demonstrate this system in six speakers during production of nine American English vowels, and provide new analysis of such data. Classification and regression analysis revealed considerable variability in the articulator-to-acoustic relationship acrossmore » speakers. Non-negative matrix factorization extracted basis sets capturing vocal tract shapes allowing for higher vowel classification accuracy than traditional methods. Statistical speech synthesis generated speech from vocal tract measurements, and we demonstrate perceptual identification. We demonstrate the capacity to predict lip kinematics from ventral sensorimotor cortical activity. These results demonstrate a multi-modal system to non-invasively monitor articulator kinematics during speech production, describe novel analytic methods for relating kinematic data to speech acoustics, and provide the first decoding of speech kinematics from electrocorticography. These advances will be critical for understanding the cortical basis of speech production and the creation of vocal prosthetics.« less

Multi-Modal Traveler Information System - Performance Criteria for Evaluating GCM Corridor Strategies & Technologies

DOT National Transportation Integrated Search

1997-07-16

The Gary-Chicago-Milwaukee (GCM) Multi-Modal Traveler Information System (MMTIS) is a complex project involving a wide spectrum of participants. In order to facilitate its implementation it is important to understand the direction of the MMTIS. This ...

Dynamic mobility applications policy analysis : policy and institutional issues for multi-modal intelligent traffic signal system (MMITSS).

DOT National Transportation Integrated Search

2015-03-01

The Connected Vehicle Mobility Policy team (herein, policy team) developed this report to document policy considerations for the Multi-Modal Intelligent Traffic Signal System, or MMITSS. MMITSS comprises a bundle of dynamic mobility application...

Biological fiducial point based registration for multiple brain tissues reconstructed from different imaging modalities

NASA Astrophysics Data System (ADS)

Wu, Huiqun; Zhou, Gangping; Geng, Xingyun; Zhang, Xiaofeng; Jiang, Kui; Tang, Lemin; Zhou, Guomin; Dong, Jiancheng

2013-10-01

With the development of computer aided navigation system, more and more tissues shall be reconstructed to provide more useful information for surgical pathway planning. In this study, we aimed to propose a registration framework for different reconstructed tissues from multi-modalities based on some fiducial points on lateral ventricles. A male patient with brain lesion was admitted and his brain scans were performed by different modalities. Then, the different brain tissues were segmented in different modality with relevant suitable algorithms. Marching cubes were calculated for three dimensional reconstructions, and then the rendered tissues were imported to a common coordinate system for registration. Four pairs of fiducial markers were selected to calculate the rotation and translation matrix using least-square measure method. The registration results were satisfied in a glioblastoma surgery planning as it provides the spatial relationship between tumors and surrounding fibers as well as vessels. Hence, our framework is of potential value for clinicians to plan surgery.

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2010-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...research, we designed a pilot study utilizing large scale parallel Grid computing harnessing nationwide infrastructure for medical image analysis . Also

Fimag: the United Kingdom disaster victim/forensic identification imaging system.

PubMed

Rutty, Guy N; Robinson, Claire; Morgan, Bruno; Black, Sue; Adams, Catherine; Webster, Philip

2009-11-01

Imaging is an integral diagnostic tool in mass fatality investigations undertaken traditionally by plain X-rays, fluoroscopy, and dental radiography. However, little attention has been given to appropriate image reporting, secure data transfer and storage particularly in relation to the need to meet stringent judicial requirements. Notwithstanding these limitations, it is the risk associated with the safe handling and investigation of contaminated fatalities which is providing new challenges for mass fatality radiological imaging. Mobile multi-slice computed tomography is an alternative to these traditional modalities as it provides a greater diagnostic yield and an opportunity to address the requirements of the criminal justice system. We present a new national disaster victim/forensic identification imaging system--Fimag--which is applicable for both contaminated and non-contaminated mass fatality imaging and addresses the issues of judicial reporting. We suggest this system opens a new era in radiological diagnostics for mass fatalities.

Evaluating laser-driven Bremsstrahlung radiation sources for imaging and analysis of nuclear waste packages.

PubMed

Jones, Christopher P; Brenner, Ceri M; Stitt, Camilla A; Armstrong, Chris; Rusby, Dean R; Mirfayzi, Seyed R; Wilson, Lucy A; Alejo, Aarón; Ahmed, Hamad; Allott, Ric; Butler, Nicholas M H; Clarke, Robert J; Haddock, David; Hernandez-Gomez, Cristina; Higginson, Adam; Murphy, Christopher; Notley, Margaret; Paraskevoulakos, Charilaos; Jowsey, John; McKenna, Paul; Neely, David; Kar, Satya; Scott, Thomas B

2016-11-15

A small scale sample nuclear waste package, consisting of a 28mm diameter uranium penny encased in grout, was imaged by absorption contrast radiography using a single pulse exposure from an X-ray source driven by a high-power laser. The Vulcan laser was used to deliver a focused pulse of photons to a tantalum foil, in order to generate a bright burst of highly penetrating X-rays (with energy >500keV), with a source size of <0.5mm. BAS-TR and BAS-SR image plates were used for image capture, alongside a newly developed Thalium doped Caesium Iodide scintillator-based detector coupled to CCD chips. The uranium penny was clearly resolved to sub-mm accuracy over a 30cm(2) scan area from a single shot acquisition. In addition, neutron generation was demonstrated in situ with the X-ray beam, with a single shot, thus demonstrating the potential for multi-modal criticality testing of waste materials. This feasibility study successfully demonstrated non-destructive radiography of encapsulated, high density, nuclear material. With recent developments of high-power laser systems, to 10Hz operation, a laser-driven multi-modal beamline for waste monitoring applications is envisioned. Copyright © 2016. Published by Elsevier B.V.

Patients at Risk for Peritoneal Surface Malignancy of Colorectal Cancer Origin: The Role of Second Look Laparotomy

PubMed Central

Brücher, Björn LDM; Stojadinovic, Alexander; Bilchik, Anton J.; Protic, Mladjan; Daumer, Martin; Nissan, Aviram; Avital, Itzhak

2013-01-01

Peritoneal surface malignancy (PSM) is a frequent occurrence in the natural history of colorectal cancer (CRC). Although significant advances have been made in screening of CRC, similar progress has yet to be made in the early detection of PSM of colorectal cancer origin. The fact that advanced CRC can be confined to the peritoneal surface without distant dissemination forms the basis for aggressive multi-modality therapy consisting of cytoreductive surgery (CRS) plus hyperthermic intra-peritoneal chemotherapy (HIPEC), and neoadjuvant and/or adjuvant systemic therapy. Reported overall survival with complete CRS+HIPEC exceeds that of systemic therapy alone for the treatment of PSM from CRC, underscoring the advantage of this multi-modality therapeutic approach. Patients with limited peritoneal disease from CRC can undergo complete cytoreduction, which is associated with the best reported outcomes. As early or limited peritoneal carcinomatosis is undetectable by conventional imaging modalities, second look laparotomy is an important means to identify disease in high-risk patients at a stage most amenable to complete cytoreduction. This review focuses on the identification of patients at risk for PSM from CRC and discusses the role of second look laparotomy. PMID:23459716

A feasibility study of evaluating transportation security systems and associated multi-modal efficiency impacts

DOT National Transportation Integrated Search

2006-08-01

The overall purpose of this research project is to conduct a feasibility study and development of a general methodology to determine the impacts on multi-modal and system efficiency of alternative freight security measures. The methodology to be exam...

Multi-modality PET-CT imaging of breast cancer in an animal model using nanoparticle x-ray contrast agent and 18F-FDG

NASA Astrophysics Data System (ADS)

Badea, C. T.; Ghaghada, K.; Espinosa, G.; Strong, L.; Annapragada, A.

2011-03-01

Multi-modality PET-CT imaging is playing an important role in the field of oncology. While PET imaging facilitates functional interrogation of tumor status, the use of CT imaging is primarily limited to anatomical reference. In an attempt to extract comprehensive information about tumor cells and its microenvironment, we used a nanoparticle xray contrast agent to image tumor vasculature and vessel 'leakiness' and 18F-FDG to investigate the metabolic status of tumor cells. In vivo PET/CT studies were performed in mice implanted with 4T1 mammary breast cancer cells.Early-phase micro-CT imaging enabled visualization 3D vascular architecture of the tumors whereas delayedphase micro-CT demonstrated highly permeable vessels as evident by nanoparticle accumulation within the tumor. Both imaging modalities demonstrated the presence of a necrotic core as indicated by a hypo-enhanced region in the center of the tumor. At early time-points, the CT-derived fractional blood volume did not correlate with 18F-FDG uptake. At delayed time-points, the tumor enhancement in 18F-FDG micro-PET images correlated with the delayed signal enhanced due to nanoparticle extravasation seen in CT images. The proposed hybrid imaging approach could be used to better understand tumor angiogenesis and to be the basis for monitoring and evaluating anti-angiogenic and nano-chemotherapies.

Role of HIS/RIS DICOM interfaces in the integration of imaging into the Department of Veterans Affairs healthcare enterprise

NASA Astrophysics Data System (ADS)

Kuzmak, Peter M.; Dayhoff, Ruth E.

1998-07-01

The U.S. Department of Veterans Affairs is integrating imaging into the healthcare enterprise using the Digital Imaging and Communication in Medicine (DICOM) standard protocols. Image management is directly integrated into the VistA Hospital Information System (HIS) software and clinical database. Radiology images are acquired via DICOM, and are stored directly in the HIS database. Images can be displayed on low- cost clinician's workstations throughout the medical center. High-resolution diagnostic quality multi-monitor VistA workstations with specialized viewing software can be used for reading radiology images. DICOM has played critical roles in the ability to integrate imaging functionality into the Healthcare Enterprise. Because of its openness, it allows the integration of system components from commercial and non- commercial sources to work together to provide functional cost-effective solutions (see Figure 1). Two approaches are used to acquire and handle images within the radiology department. At some VA Medical Centers, DICOM is used to interface a commercial Picture Archiving and Communications System (PACS) to the VistA HIS. At other medical centers, DICOM is used to interface the image producing modalities directly to the image acquisition and display capabilities of VistA itself. Both of these approaches use a small set of DICOM services that has been implemented by VistA to allow patient and study text data to be transmitted to image producing modalities and the commercial PACS, and to enable images and study data to be transferred back.

Accurate Learning with Few Atlases (ALFA): an algorithm for MRI neonatal brain extraction and comparison with 11 publicly available methods.

PubMed

Serag, Ahmed; Blesa, Manuel; Moore, Emma J; Pataky, Rozalia; Sparrow, Sarah A; Wilkinson, A G; Macnaught, Gillian; Semple, Scott I; Boardman, James P

2016-03-24

Accurate whole-brain segmentation, or brain extraction, of magnetic resonance imaging (MRI) is a critical first step in most neuroimage analysis pipelines. The majority of brain extraction algorithms have been developed and evaluated for adult data and their validity for neonatal brain extraction, which presents age-specific challenges for this task, has not been established. We developed a novel method for brain extraction of multi-modal neonatal brain MR images, named ALFA (Accurate Learning with Few Atlases). The method uses a new sparsity-based atlas selection strategy that requires a very limited number of atlases 'uniformly' distributed in the low-dimensional data space, combined with a machine learning based label fusion technique. The performance of the method for brain extraction from multi-modal data of 50 newborns is evaluated and compared with results obtained using eleven publicly available brain extraction methods. ALFA outperformed the eleven compared methods providing robust and accurate brain extraction results across different modalities. As ALFA can learn from partially labelled datasets, it can be used to segment large-scale datasets efficiently. ALFA could also be applied to other imaging modalities and other stages across the life course.

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness

PubMed Central

Calhoun, Vince D; Sui, Jing

2016-01-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness. PMID:27347565

Multimodal fusion of brain imaging data: A key to finding the missing link(s) in complex mental illness.

PubMed

Calhoun, Vince D; Sui, Jing

2016-05-01

It is becoming increasingly clear that combining multi-modal brain imaging data is able to provide more information for individual subjects by exploiting the rich multimodal information that exists. However, the number of studies that do true multimodal fusion (i.e. capitalizing on joint information among modalities) is still remarkably small given the known benefits. In part, this is because multi-modal studies require broader expertise in collecting, analyzing, and interpreting the results than do unimodal studies. In this paper, we start by introducing the basic reasons why multimodal data fusion is important and what it can do, and importantly how it can help us avoid wrong conclusions and help compensate for imperfect brain imaging studies. We also discuss the challenges that need to be confronted for such approaches to be more widely applied by the community. We then provide a review of the diverse studies that have used multimodal data fusion (primarily focused on psychosis) as well as provide an introduction to some of the existing analytic approaches. Finally, we discuss some up-and-coming approaches to multi-modal fusion including deep learning and multimodal classification which show considerable promise. Our conclusion is that multimodal data fusion is rapidly growing, but it is still underutilized. The complexity of the human brain coupled with the incomplete measurement provided by existing imaging technology makes multimodal fusion essential in order to mitigate against misdirection and hopefully provide a key to finding the missing link(s) in complex mental illness.

Integration of Fiber-Optic Sensor Arrays into a Multi-Modal Tactile Sensor Processing System for Robotic End-Effectors

PubMed Central

Kampmann, Peter; Kirchner, Frank

2014-01-01

With the increasing complexity of robotic missions and the development towards long-term autonomous systems, the need for multi-modal sensing of the environment increases. Until now, the use of tactile sensor systems has been mostly based on sensing one modality of forces in the robotic end-effector. The use of a multi-modal tactile sensory system is motivated, which combines static and dynamic force sensor arrays together with an absolute force measurement system. This publication is focused on the development of a compact sensor interface for a fiber-optic sensor array, as optic measurement principles tend to have a bulky interface. Mechanical, electrical and software approaches are combined to realize an integrated structure that provides decentralized data pre-processing of the tactile measurements. Local behaviors are implemented using this setup to show the effectiveness of this approach. PMID:24743158

Detection of relationships among multi-modal brain imaging meta-features via information flow.

PubMed

Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

2018-01-15

Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is powerful, intuitive and very efficiently provides a high-level overview of a massive data space. In our application it exposes both expected relationships and relationships very rarely considered worth investigating by clinical researchers. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-Modal Ultra-Widefield Imaging Features in Waardenburg Syndrome

PubMed Central

Choudhry, Netan; Rao, Rajesh C.

2015-01-01

Background Waardenburg syndrome is characterized by a group of features including; telecanthus, a broad nasal root, synophrys of the eyebrows, piedbaldism, heterochromia irides, and deaf-mutism. Hypopigmentation of the choroid is a unique feature of this condition examined with multi-modal Ultra-Widefield Imaging in this report. Material/Methods Report of a single case. Results Bilateral symmetric choroidal hypopigmentation was observed with hypoautofluorescence in the region of hypopigmentation. Fluorescein angiography revealed a normal vasculature, however a thickened choroid was seen on Enhanced-Depth Imaging Spectral-Domain OCT (EDI SD-OCT). Conclusion(s) Choroidal hypopigmentation is a unique feature of Waardenburg syndrome, which can be visualized with ultra-widefield fundus autofluorescence. The choroid may also be thickened in this condition and its thickness measured with EDI SD-OCT. PMID:26114849

Key informant interviews test plan : model deployment of a regional, multi-modal 511 traveler information system

DOT National Transportation Integrated Search

2004-01-28

This document presents the detailed plan to conduct the Key Informants Interviews Test, one of several test activities to be conducted as part of the national evaluation of the regional, multi-modal 511 Traveler Information System Model Deployment. T...

Identifying Multimodal Intermediate Phenotypes between Genetic Risk Factors and Disease Status in Alzheimer’s Disease

PubMed Central

Hao, Xiaoke; Yao, Xiaohui; Yan, Jingwen; Risacher, Shannon L.; Saykin, Andrew J.; Zhang, Daoqiang; Shen, Li

2016-01-01

Neuroimaging genetics has attracted growing attention and interest, which is thought to be a powerful strategy to examine the influence of genetic variants (i.e., single nucleotide polymorphisms (SNPs)) on structures or functions of human brain. In recent studies, univariate or multivariate regression analysis methods are typically used to capture the effective associations between genetic variants and quantitative traits (QTs) such as brain imaging phenotypes. The identified imaging QTs, although associated with certain genetic markers, may not be all disease specific. A useful, but underexplored, scenario could be to discover only those QTs associated with both genetic markers and disease status for revealing the chain from genotype to phenotype to symptom. In addition, multimodal brain imaging phenotypes are extracted from different perspectives and imaging markers consistently showing up in multimodalities may provide more insights for mechanistic understanding of diseases (i.e., Alzheimer’s disease (AD)). In this work, we propose a general framework to exploit multi-modal brain imaging phenotypes as intermediate traits that bridge genetic risk factors and multi-class disease status. We applied our proposed method to explore the relation between the well-known AD risk SNP APOE rs429358 and three baseline brain imaging modalities (i.e., structural magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and F-18 florbetapir PET scans amyloid imaging (AV45)) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The empirical results demonstrate that our proposed method not only helps improve the performances of imaging genetic associations, but also discovers robust and consistent regions of interests (ROIs) across multi-modalities to guide the disease-induced interpretation. PMID:27277494

Multi-modal measurement of the myelin-to-axon diameter g-ratio in preterm-born neonates and adult controls.

PubMed

Melbourne, Andrew; Eaton-Rosen, Zach; De Vita, Enrico; Bainbridge, Alan; Cardoso, Manuel Jorge; Price, David; Cady, Ernest; Kendall, Giles S; Robertson, Nicola J; Marlow, Neil; Ourselin, Sébastien

2014-01-01

Infants born prematurely are at increased risk of adverse functional outcome. The measurement of white matter tissue composition and structure can help predict functional performance and this motivates the search for new multi-modal imaging biomarkers. In this work we develop a novel combined biomarker from diffusion MRI and multi-component T2 relaxation measurements in a group of infants born very preterm and scanned between 30 and 40 weeks equivalent gestational age. We also investigate this biomarker on a group of seven adult controls, using a multi-modal joint model-fitting strategy. The proposed emergent biomarker is tentatively related to axonal energetic efficiency (in terms of axonal membrane charge storage) and conduction velocity and is thus linked to the tissue electrical properties, giving it a good theoretical justification as a predictive measurement of functional outcome.

MMX-I: data-processing software for multimodal X-ray imaging and tomography.

PubMed

Bergamaschi, Antoine; Medjoubi, Kadda; Messaoudi, Cédric; Marco, Sergio; Somogyi, Andrea

2016-05-01

A new multi-platform freeware has been developed for the processing and reconstruction of scanning multi-technique X-ray imaging and tomography datasets. The software platform aims to treat different scanning imaging techniques: X-ray fluorescence, phase, absorption and dark field and any of their combinations, thus providing an easy-to-use data processing tool for the X-ray imaging user community. A dedicated data input stream copes with the input and management of large datasets (several hundred GB) collected during a typical multi-technique fast scan at the Nanoscopium beamline and even on a standard PC. To the authors' knowledge, this is the first software tool that aims at treating all of the modalities of scanning multi-technique imaging and tomography experiments.

Hybrid imaging: Instrumentation and Data Processing

NASA Astrophysics Data System (ADS)

Cal-Gonzalez, Jacobo; Rausch, Ivo; Shiyam Sundar, Lalith K.; Lassen, Martin L.; Muzik, Otto; Moser, Ewald; Papp, Laszlo; Beyer, Thomas

2018-05-01

State-of-the-art patient management frequently requires the use of non-invasive imaging methods to assess the anatomy, function or molecular-biological conditions of patients or study subjects. Such imaging methods can be singular, providing either anatomical or molecular information, or they can be combined, thus, providing "anato-metabolic" information. Hybrid imaging denotes image acquisitions on systems that physically combine complementary imaging modalities for an improved diagnostic accuracy and confidence as well as for increased patient comfort. The physical combination of formerly independent imaging modalities was driven by leading innovators in the field of clinical research and benefited from technological advances that permitted the operation of PET and MR in close physical proximity, for example. This review covers milestones of the development of various hybrid imaging systems for use in clinical practice and small-animal research. Special attention is given to technological advances that helped the adoption of hybrid imaging, as well as to introducing methodological concepts that benefit from the availability of complementary anatomical and biological information, such as new types of image reconstruction and data correction schemes. The ultimate goal of hybrid imaging is to provide useful, complementary and quantitative information during patient work-up. Hybrid imaging also opens the door to multi-parametric assessment of diseases, which will help us better understand the causes of various diseases that currently contribute to a large fraction of healthcare costs.

Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.

PubMed

Yang, Xin; Liu, Chaoyue; Wang, Zhiwei; Yang, Jun; Min, Hung Le; Wang, Liang; Cheng, Kwang-Ting Tim

2017-12-01

Multi-parameter magnetic resonance imaging (mp-MRI) is increasingly popular for prostate cancer (PCa) detection and diagnosis. However, interpreting mp-MRI data which typically contains multiple unregistered 3D sequences, e.g. apparent diffusion coefficient (ADC) and T2-weighted (T2w) images, is time-consuming and demands special expertise, limiting its usage for large-scale PCa screening. Therefore, solutions to computer-aided detection of PCa in mp-MRI images are highly desirable. Most recent advances in automated methods for PCa detection employ a handcrafted feature based two-stage classification flow, i.e. voxel-level classification followed by a region-level classification. This work presents an automated PCa detection system which can concurrently identify the presence of PCa in an image and localize lesions based on deep convolutional neural network (CNN) features and a single-stage SVM classifier. Specifically, the developed co-trained CNNs consist of two parallel convolutional networks for ADC and T2w images respectively. Each network is trained using images of a single modality in a weakly-supervised manner by providing a set of prostate images with image-level labels indicating only the presence of PCa without priors of lesions' locations. Discriminative visual patterns of lesions can be learned effectively from clutters of prostate and surrounding tissues. A cancer response map with each pixel indicating the likelihood to be cancerous is explicitly generated at the last convolutional layer of the network for each modality. A new back-propagated error E is defined to enforce both optimized classification results and consistent cancer response maps for different modalities, which help capture highly representative PCa-relevant features during the CNN feature learning process. The CNN features of each modality are concatenated and fed into a SVM classifier. For images which are classified to contain cancers, non-maximum suppression and adaptive thresholding are applied to the corresponding cancer response maps for PCa foci localization. Evaluation based on 160 patient data with 12-core systematic TRUS-guided prostate biopsy as the reference standard demonstrates that our system achieves a sensitivity of 0.46, 0.92 and 0.97 at 0.1, 1 and 10 false positives per normal/benign patient which is significantly superior to two state-of-the-art CNN-based methods (Oquab et al., 2015; Zhou et al., 2015) and 6-core systematic prostate biopsies. Copyright © 2017 Elsevier B.V. All rights reserved.

Development and reliability of a multi-modality scoring system for evaluation of disease progression in pre-clinical models of osteoarthritis: celecoxib may possess disease-modifying properties.

PubMed

Panahifar, A; Jaremko, J L; Tessier, A G; Lambert, R G; Maksymowych, W P; Fallone, B G; Doschak, M R

2014-10-01

We sought to develop a comprehensive scoring system for evaluation of pre-clinical models of osteoarthritis (OA) progression, and use this to evaluate two different classes of drugs for management of OA. Post-traumatic OA (PTOA) was surgically induced in skeletally mature rats. Rats were randomly divided in three groups receiving either glucosamine (high dose of 192 mg/kg) or celecoxib (clinical dose) or no treatment. Disease progression was monitored utilizing micro-magnetic resonance imaging (MRI), micro-computed tomography (CT) and histology. Pertinent features such as osteophytes, subchondral sclerosis, joint effusion, bone marrow lesion (BML), cysts, loose bodies and cartilage abnormalities were included in designing a sensitive multi-modality based scoring system, termed the rat arthritis knee scoring system (RAKSS). Overall, an inter-observer correlation coefficient (ICC) of greater than 0.750 was achieved for each scored feature. None of the treatments prevented cartilage loss, synovitis, joint effusion, or sclerosis. However, celecoxib significantly reduced osteophyte development compared to placebo. Although signs of inflammation such as synovitis and joint effusion were readily identified at 4 weeks post-operation, we did not detect any BML. We report the development of a sensitive and reliable multi-modality scoring system, the RAKSS, for evaluation of OA severity in pre-clinical animal models. Using this scoring system, we found that celecoxib prevented enlargement of osteophytes in this animal model of PTOA, and thus it may be useful in preventing OA progression. However, it did not show any chondroprotective effect using the recommended dose. In contrast, high dose glucosamine had no measurable effects. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

New bone post-processing tools in forensic imaging: a multi-reader feasibility study to evaluate detection time and diagnostic accuracy in rib fracture assessment.

PubMed

Glemser, Philip A; Pfleiderer, Michael; Heger, Anna; Tremper, Jan; Krauskopf, Astrid; Schlemmer, Heinz-Peter; Yen, Kathrin; Simons, David

2017-03-01

The aim of this multi-reader feasibility study was to evaluate new post-processing CT imaging tools in rib fracture assessment of forensic cases by analyzing detection time and diagnostic accuracy. Thirty autopsy cases (20 with and 10 without rib fractures in autopsy) were randomly selected and included in this study. All cases received a native whole body CT scan prior to the autopsy procedure, which included dissection and careful evaluation of each rib. In addition to standard transverse sections (modality A), CT images were subjected to a reconstruction algorithm to compute axial labelling of the ribs (modality B) as well as "unfolding" visualizations of the rib cage (modality C, "eagle tool"). Three radiologists with different clinical and forensic experience who were blinded to autopsy results evaluated all cases in a random manner of modality and case. Rib fracture assessment of each reader was evaluated compared to autopsy and a CT consensus read as radiologic reference. A detailed evaluation of relevant test parameters revealed a better accordance to the CT consensus read as to the autopsy. Modality C was the significantly quickest rib fracture detection modality despite slightly reduced statistic test parameters compared to modalities A and B. Modern CT post-processing software is able to shorten reading time and to increase sensitivity and specificity compared to standard autopsy alone. The eagle tool as an easy to use tool is suited for an initial rib fracture screening prior to autopsy and can therefore be beneficial for forensic pathologists.

A practical salient region feature based 3D multi-modality registration method for medical images

NASA Astrophysics Data System (ADS)

Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

2006-03-01

We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Development of a platform for co-registered ultrasound and MR contrast imaging in vivo

NASA Astrophysics Data System (ADS)

Chandrana, Chaitanya; Bevan, Peter; Hudson, John; Pang, Ian; Burns, Peter; Plewes, Donald; Chopra, Rajiv

2011-02-01

Imaging of the microvasculature is often performed using contrast agents in combination with either ultrasound (US) or magnetic resonance (MR) imaging. Contrast agents are used to enhance medical imaging by highlighting microvascular properties and function. Dynamic signal changes arising from the passage of contrast agents through the microvasculature can be used to characterize different pathologies; however, comparisons across modalities are difficult due to differences in the interactions of contrast agents with the microvasculature. Better knowledge of the relationship of contrast enhancement patterns with both modalities could enable better characterization of tissue microvasculature. We developed a co-registration platform for multi-modal US and MR imaging using clinical imaging systems in order to study the relationship between US and MR contrast enhancement. A preliminary validation study was performed in phantoms to determine the registration accuracy of the platform. In phantoms, the in-plane registration accuracy was measured to be 0.2 ± 0.2 and 0.3 ± 0.2 mm, in the lateral and axial directions, respectively. The out-of-plane registration accuracy was estimated to be 0.5 mm ±0.1. Co-registered US and MR imaging was performed in a rabbit model to evaluate contrast kinetics in different tissue types after bolus injections of US and MR contrast agents. The arrival time of the contrast agent in the plane of imaging was relatively similar for both modalities. We studied three different tissue types: muscle, large vessels and fat. In US, the temporal kinetics of signal enhancement were not strongly dependent on tissue type. In MR, however, due to the different amounts of agent extravasation in each tissue type, tissue-specific contrast kinetics were observed. This study demonstrates the feasibility of performing in vivo co-registered contrast US and MR imaging to study the relationships of the enhancement patterns with each modality.

High frame-rate MR-guided near-infrared tomography system to monitor breast hemodynamics

NASA Astrophysics Data System (ADS)

Li, Zhiqiu; Jiang, Shudong; Krishnaswamy, Venkataramanan; Davis, Scott C.; Srinivasan, Subhadra; Paulsen, Keith D.; Pogue, Brian W.

2011-02-01

A near-infrared (NIR) tomography system with spectral-encoded sources at two wavelength bands was built to quantify the temporal contrast at 20 Hz bandwidth, while imaging breast tissue. The NIR system was integrated with a magnetic resonance (MR) machine through a custom breast coil interface, and both NIR data and MR images were acquired simultaneously. MR images provided breast tissue structural information for NIR reconstruction. Acquisition of finger pulse oximeter (PO) plethysmogram was synchronized with the NIR system in the experiment to offer a frequency-locked reference. The recovered absorption coefficients of the breast at two wavelengths showed identical temporal frequency as the PO output, proving this multi-modality design can recover the small pulsatile variation of absorption property in breast tissue related to the heartbeat. And it also showed the system's ability on novel contrast imaging of fast flow signals in deep tissue.

Bedside functional brain imaging in critically-ill children using high-density EEG source modeling and multi-modal sensory stimulation.

PubMed

Eytan, Danny; Pang, Elizabeth W; Doesburg, Sam M; Nenadovic, Vera; Gavrilovic, Bojan; Laussen, Peter; Guerguerian, Anne-Marie

2016-01-01

Acute brain injury is a common cause of death and critical illness in children and young adults. Fundamental management focuses on early characterization of the extent of injury and optimizing recovery by preventing secondary damage during the days following the primary injury. Currently, bedside technology for measuring neurological function is mainly limited to using electroencephalography (EEG) for detection of seizures and encephalopathic features, and evoked potentials. We present a proof of concept study in patients with acute brain injury in the intensive care setting, featuring a bedside functional imaging set-up designed to map cortical brain activation patterns by combining high density EEG recordings, multi-modal sensory stimulation (auditory, visual, and somatosensory), and EEG source modeling. Use of source-modeling allows for examination of spatiotemporal activation patterns at the cortical region level as opposed to the traditional scalp potential maps. The application of this system in both healthy and brain-injured participants is demonstrated with modality-specific source-reconstructed cortical activation patterns. By combining stimulation obtained with different modalities, most of the cortical surface can be monitored for changes in functional activation without having to physically transport the subject to an imaging suite. The results in patients in an intensive care setting with anatomically well-defined brain lesions suggest a topographic association between their injuries and activation patterns. Moreover, we report the reproducible application of a protocol examining a higher-level cortical processing with an auditory oddball paradigm involving presentation of the patient's own name. This study reports the first successful application of a bedside functional brain mapping tool in the intensive care setting. This application has the potential to provide clinicians with an additional dimension of information to manage critically-ill children and adults, and potentially patients not suited for magnetic resonance imaging technologies.

Multi-Modality Imaging in the Evaluation and Treatment of Mitral Regurgitation.

PubMed

Bouchard, Marc-André; Côté-Laroche, Claudia; Beaudoin, Jonathan

2017-10-13

Mitral regurgitation (MR) is frequent and associated with increased mortality and morbidity when severe. It may be caused by intrinsic valvular disease (primary MR) or ventricular deformation (secondary MR). Imaging has a critical role to document the severity, mechanism, and impact of MR on heart function as selected patients with MR may benefit from surgery whereas other will not. In patients planned for a surgical intervention, imaging is also important to select candidates for mitral valve (MV) repair over replacement and to predict surgical success. Although standard transthoracic echocardiography is the first-line modality to evaluate MR, newer imaging modalities like three-dimensional (3D) transesophageal echocardiography, stress echocardiography, cardiac magnetic resonance (CMR), and computed tomography (CT) are emerging and complementary tools for MR assessment. While some of these modalities can provide insight into MR severity, others will help to determine its mechanism. Understanding the advantages and limitations of each imaging modality is important to appreciate their respective role for MR assessment and help to resolve eventual discrepancies between different diagnostic methods. With the increasing use of transcatheter mitral procedures (repair or replacement) for high-surgical-risk patients, multimodality imaging has now become even more important to determine eligibility, preinterventional planning, and periprocedural guidance.

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

MO-DE-202-00: Image-Guided Interventions: Advances in Intraoperative Imaging, Guidance, and An Emerging Role for Medical Physics in Surgery

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

NONE

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-03: Image-Guided Surgery and Interventions in the Advanced Multimodality Image-Guided Operating (AMIGO) Suite

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

Kapur, T.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-02: Advances in Image Registration and Reconstruction for Image-Guided Neurosurgery

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

Siewerdsen, J.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

Image acquisition unit for the Mayo/IBM PACS project

NASA Astrophysics Data System (ADS)

Reardon, Frank J.; Salutz, James R.

1991-07-01

The Mayo Clinic and IBM Rochester, Minnesota, have jointly developed a picture archiving, distribution and viewing system for use with Mayo's CT and MRI imaging modalities. Images are retrieved from the modalities and sent over the Mayo city-wide token ring network to optical storage subsystems for archiving, and to server subsystems for viewing on image review stations. Images may also be retrieved from archive and transmitted back to the modalities. The subsystems that interface to the modalities and communicate to the other components of the system are termed Image Acquisition Units (LAUs). The IAUs are IBM Personal System/2 (PS/2) computers with specially developed software. They operate independently in a network of cooperative subsystems and communicate with the modalities, archive subsystems, image review server subsystems, and a central subsystem that maintains information about the content and location of images. This paper provides a detailed description of the function and design of the Image Acquisition Units.

MO-DE-202-01: Image-Guided Focused Ultrasound Surgery and Therapy

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

Farahani, K.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

MO-DE-202-04: Multimodality Image-Guided Surgery and Intervention: For the Rest of Us

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

Shekhar, R.

At least three major trends in surgical intervention have emerged over the last decade: a move toward more minimally invasive (or non-invasive) approach to the surgical target; the development of high-precision treatment delivery techniques; and the increasing role of multi-modality intraoperative imaging in support of such procedures. This symposium includes invited presentations on recent advances in each of these areas and the emerging role for medical physics research in the development and translation of high-precision interventional techniques. The four speakers are: Keyvan Farahani, “Image-guided focused ultrasound surgery and therapy” Jeffrey H. Siewerdsen, “Advances in image registration and reconstruction for image-guidedmore » neurosurgery” Tina Kapur, “Image-guided surgery and interventions in the advanced multimodality image-guided operating (AMIGO) suite” Raj Shekhar, “Multimodality image-guided interventions: Multimodality for the rest of us” Learning Objectives: Understand the principles and applications of HIFU in surgical ablation. Learn about recent advances in 3D–2D and 3D deformable image registration in support of surgical safety and precision. Learn about recent advances in model-based 3D image reconstruction in application to intraoperative 3D imaging. Understand the multi-modality imaging technologies and clinical applications investigated in the AMIGO suite. Understand the emerging need and techniques to implement multi-modality image guidance in surgical applications such as neurosurgery, orthopaedic surgery, vascular surgery, and interventional radiology. Research supported by the NIH and Siemens Healthcare.; J. Siewerdsen; Grant Support - National Institutes of Health; Grant Support - Siemens Healthcare; Grant Support - Carestream Health; Advisory Board - Carestream Health; Licensing Agreement - Carestream Health; Licensing Agreement - Elekta Oncology.; T. Kapur, P41EB015898; R. Shekhar, Funding: R42CA137886 and R41CA192504 Disclosure and CoI: IGI Technologies, small-business partner on the grants.« less

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI.

PubMed

Sauwen, N; Acou, M; Van Cauter, S; Sima, D M; Veraart, J; Maes, F; Himmelreich, U; Achten, E; Van Huffel, S

2016-01-01

Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

A Dual Modality System for Simultaneous Fluorescence and Positron Emission Tomography Imaging of Small Animals

NASA Astrophysics Data System (ADS)

Liu, Shuangquan; Zhang, Bin; Wang, Xin; Li, Lin; Chen, Yan; Liu, Xin; Liu, Fei; Shan, Baoci; Bai, Jing

2011-02-01

A dual-modality imaging system for simultaneous fluorescence molecular tomography (FMT) and positron emission tomography (PET) of small animals has been developed. The system consists of a noncontact 360°-projection FMT module and a flat panel detector pair based PET module, which are mounted orthogonally for the sake of eliminating cross interference. The FMT images and PET data are simultaneously acquired by employing dynamic sampling mode. Phantom experiments, in which the localization and range of radioactive and fluorescence probes are exactly indicated, have been carried out to verify the feasibility of the system. An experimental tumor-bearing mouse is also scanned using the dual-modality simultaneous imaging system, the preliminary fluorescence tomographic images and PET images demonstrate the in vivo performance of the presented dual-modality system.

Multiset singular value decomposition for joint analysis of multi-modal data: application to fingerprint analysis

NASA Astrophysics Data System (ADS)

Emge, Darren K.; Adalı, Tülay

2014-06-01

As the availability and use of imaging methodologies continues to increase, there is a fundamental need to jointly analyze data that is collected from multiple modalities. This analysis is further complicated when, the size or resolution of the images differ, implying that the observation lengths of each of modality can be highly varying. To address this expanding landscape, we introduce the multiset singular value decomposition (MSVD), which can perform a joint analysis on any number of modalities regardless of their individual observation lengths. Through simulations, the inter modal relationships across the different modalities which are revealed by the MSVD are shown. We apply the MSVD to forensic fingerprint analysis, showing that MSVD joint analysis successfully identifies relevant similarities for further analysis, significantly reducing the processing time required. This reduction, takes this technique from a laboratory method to a useful forensic tool with applications across the law enforcement and security regimes.

MMX-I: data-processing software for multimodal X-ray imaging and tomography

PubMed Central

Bergamaschi, Antoine; Medjoubi, Kadda; Messaoudi, Cédric; Marco, Sergio; Somogyi, Andrea

2016-01-01

A new multi-platform freeware has been developed for the processing and reconstruction of scanning multi-technique X-ray imaging and tomography datasets. The software platform aims to treat different scanning imaging techniques: X-ray fluorescence, phase, absorption and dark field and any of their combinations, thus providing an easy-to-use data processing tool for the X-ray imaging user community. A dedicated data input stream copes with the input and management of large datasets (several hundred GB) collected during a typical multi-technique fast scan at the Nanoscopium beamline and even on a standard PC. To the authors’ knowledge, this is the first software tool that aims at treating all of the modalities of scanning multi-technique imaging and tomography experiments. PMID:27140159

Multimodal microscopy and the stepwise multi-photon activation fluorescence of melanin

NASA Astrophysics Data System (ADS)

Lai, Zhenhua

The author's work is divided into three aspects: multimodal microscopy, stepwise multi-photon activation fluorescence (SMPAF) of melanin, and customized-profile lenses (CPL) for on-axis laser scanners, which will be introduced respectively. A multimodal microscope provides the ability to image samples with multiple modalities on the same stage, which incorporates the benefits of all modalities. The multimodal microscopes developed in this dissertation are the Keck 3D fusion multimodal microscope 2.0 (3DFM 2.0), upgraded from the old 3DFM with improved performance and flexibility, and the multimodal microscope for targeting small particles (the "Target" system). The control systems developed for both microscopes are low-cost and easy-to-build, with all components off-the-shelf. The control system have not only significantly decreased the complexity and size of the microscope, but also increased the pixel resolution and flexibility. The SMPAF of melanin, activated by a continuous-wave (CW) mode near-infrared (NIR) laser, has potential applications for a low-cost and reliable method of detecting melanin. The photophysics of melanin SMPAF has been studied by theoretical analysis of the excitation process and investigation of the spectra, activation threshold, and photon number absorption of melanin SMPAF. SMPAF images of melanin in mouse hair and skin, mouse melanoma, and human black and white hairs are compared with images taken by conventional multi-photon fluorescence microscopy (MPFM) and confocal reflectance microscopy (CRM). SMPAF images significantly increase specificity and demonstrate the potential to increase sensitivity for melanin detection compared to MPFM images and CRM images. Employing melanin SMPAF imaging to detect melanin inside human skin in vivo has been demonstrated, which proves the effectiveness of melanin detection using SMPAF for medical purposes. Selective melanin ablation with micrometer resolution has been presented using the Target system. Compared to the traditional selective photothermolysis, this method demonstrates higher precision, higher specificity and deeper penetration. Therefore, the SMPAF guided selective ablation of melanin is a promising tool of removing melanin for both medical and cosmetic purposes. Three CPLs have been designed for low-cost linear-motion scanners, low-cost fast spinning scanners and high-precision fast spinning scanners. Each design has been tailored to the industrial manufacturing ability and market demands.

Left ventricular mass and hypertrophy by echocardiography and cardiac magnetic resonance: the multi-ethnic study of atherosclerosis.

PubMed

Armstrong, Anderson C; Gjesdal, Ola; Almeida, André; Nacif, Marcelo; Wu, Colin; Bluemke, David A; Brumback, Lyndia; Lima, João A C

2014-01-01

Left ventricular mass (LVM) and hypertrophy (LVH) are important parameters, but their use is surrounded by controversies. We compare LVM by echocardiography and cardiac magnetic resonance (CMR), investigating reproducibility aspects and the effect of echocardiography image quality. We also compare indexing methods within and between imaging modalities for classification of LVH and cardiovascular risk. Multi-Ethnic Study of Atherosclerosis enrolled 880 participants in Baltimore city, 146 had echocardiograms and CMR on the same day. LVM was then assessed using standard techniques. Echocardiography image quality was rated (good/limited) according to the parasternal view. LVH was defined after indexing LVM to body surface area, height(1.7) , height(2.7) , or by the predicted LVM from a reference group. Participants were classified for cardiovascular risk according to Framingham score. Pearson's correlation, Bland-Altman plots, percent agreement, and kappa coefficient assessed agreement within and between modalities. Left ventricular mass by echocardiography (140 ± 40 g) and by CMR were correlated (r = 0.8, P < 0.001) regardless of the echocardiography image quality. The reproducibility profile had strong correlations and agreement for both modalities. Image quality groups had similar characteristics; those with good images compared to CMR slightly superiorly. The prevalence of LVH tended to be higher with higher cardiovascular risk. The agreement for LVH between imaging modalities ranged from 77% to 98% and the kappa coefficient from 0.10 to 0.76. Echocardiography has a reliable performance for LVM assessment and classification of LVH, with limited influence of image quality. Echocardiography and CMR differ in the assessment of LVH, and additional differences rise from the indexing methods. © 2013. This article is a U.S. Government work and is in the public domain in the USA.

Advances in combined endoscopic fluorescence confocal microscopy and optical coherence tomography

NASA Astrophysics Data System (ADS)

Risi, Matthew D.

Confocal microendoscopy provides real-time high resolution cellular level images via a minimally invasive procedure. Results from an ongoing clinical study to detect ovarian cancer with a novel confocal fluorescent microendoscope are presented. As an imaging modality, confocal fluorescence microendoscopy typically requires exogenous fluorophores, has a relatively limited penetration depth (100 μm), and often employs specialized aperture configurations to achieve real-time imaging in vivo. Two primary research directions designed to overcome these limitations and improve diagnostic capability are presented. Ideal confocal imaging performance is obtained with a scanning point illumination and confocal aperture, but this approach is often unsuitable for real-time, in vivo biomedical imaging. By scanning a slit aperture in one direction, image acquisition speeds are greatly increased, but at the cost of a reduction in image quality. The design, implementation, and experimental verification of a custom multi-point-scanning modification to a slit-scanning multi-spectral confocal microendoscope is presented. This new design improves the axial resolution while maintaining real-time imaging rates. In addition, the multi-point aperture geometry greatly reduces the effects of tissue scatter on imaging performance. Optical coherence tomography (OCT) has seen wide acceptance and FDA approval as a technique for ophthalmic retinal imaging, and has been adapted for endoscopic use. As a minimally invasive imaging technique, it provides morphological characteristics of tissues at a cellular level without requiring the use of exogenous fluorophores. OCT is capable of imaging deeper into biological tissue (˜1-2 mm) than confocal fluorescence microscopy. A theoretical analysis of the use of a fiber-bundle in spectral-domain OCT systems is presented. The fiber-bundle enables a flexible endoscopic design and provides fast, parallelized acquisition of the optical coherence tomography data. However, the multi-mode characteristic of the fibers in the fiber-bundle affects the depth sensitivity of the imaging system. A description of light interference in a multi-mode fiber is presented along with numerical simulations and experimental studies to illustrate the theoretical analysis.

Ultrahigh-speed X-ray imaging of hypervelocity projectiles

NASA Astrophysics Data System (ADS)

Miller, Stuart; Singh, Bipin; Cool, Steven; Entine, Gerald; Campbell, Larry; Bishel, Ron; Rushing, Rick; Nagarkar, Vivek V.

2011-08-01

High-speed X-ray imaging is an extremely important modality for healthcare, industrial, military and research applications such as medical computed tomography, non-destructive testing, imaging in-flight projectiles, characterizing exploding ordnance, and analyzing ballistic impacts. We report on the development of a modular, ultrahigh-speed, high-resolution digital X-ray imaging system with large active imaging area and microsecond time resolution, capable of acquiring at a rate of up to 150,000 frames per second. The system is based on a high-resolution, high-efficiency, and fast-decay scintillator screen optically coupled to an ultra-fast image-intensified CCD camera designed for ballistic impact studies and hypervelocity projectile imaging. A specially designed multi-anode, high-fluence X-ray source with 50 ns pulse duration provides a sequence of blur-free images of hypervelocity projectiles traveling at speeds exceeding 8 km/s (18,000 miles/h). This paper will discuss the design, performance, and high frame rate imaging capability of the system.

Cardiac Sarcoidosis: Clinical Manifestations, Imaging Characteristics, and Therapeutic Approach

PubMed Central

Houston, Brian A; Mukherjee, Monica

2014-01-01

Sarcoidosis is a multi-system disease pathologically characterized by the accumulation of T-lymphocytes and mononuclear phagocytes into the sine qua non pathologic structure of the noncaseating granuloma. Cardiac involvement remains a key source of morbidity and mortality in sarcoidosis. Definitive diagnosis of cardiac sarcoidosis, particularly early enough in the disease course to provide maximal therapeutic impact, has proven a particularly difficult challenge. However, major advancements in imaging techniques have been made in the last decade. Advancements in imaging modalities including echocardiography, nuclear spectroscopy, positron emission tomography, and magnetic resonance imaging all have improved our ability to diagnose cardiac sarcoidosis, and in many cases to provide a more accurate prognosis and thus targeted therapy. Likewise, therapy for cardiac sarcoidosis is beginning to advance past a “steroids-only” approach, as novel immunosuppressant agents provide effective steroid-sparing options. The following focused review will provide a brief discussion of the epidemiology and clinical presentation of cardiac sarcoidosis followed by a discussion of up-to-date imaging modalities employed in its assessment and therapeutic approaches. PMID:25452702

In vivo multi-modality photoacoustic and pulse echo tracking of prostate tumor growth using a window chamber

NASA Astrophysics Data System (ADS)

Bauer, Daniel R.; Olafsson, Ragnar; Montilla, Leonardo G.; Witte, Russell S.

2010-02-01

Understanding the tumor microenvironment is critical to characterizing how cancers operate and predicting how they will eventually respond to treatment. The mouse window chamber model is an excellent tool for cancer research, because it enables high resolution tumor imaging and cross-validation using multiple modalities. We describe a novel multimodality imaging system that incorporates three dimensional (3D) photoacoustics with pulse echo ultrasound for imaging the tumor microenvironment and tracking tissue growth in mice. Three mice were implanted with a dorsal skin flap window chamber. PC-3 prostate tumor cells, expressing green fluorescent protein (GFP), were injected into the skin. The ensuing tumor invasion was mapped using photoacoustic and pulse echo imaging, as well as optical and fluorescent imaging for comparison and cross validation. The photoacoustic imaging and spectroscopy system, consisting of a tunable (680-1000nm) pulsed laser and 25 MHz ultrasound transducer, revealed near infrared absorbing regions, primarily blood vessels. Pulse echo images, obtained simultaneously, provided details of the tumor microstructure and growth with 100-μm3 resolution. The tumor size in all three mice increased between three and five fold during 3+ weeks of imaging. Results were consistent with the optical and fluorescent images. Photoacoustic imaging revealed detailed maps of the tumor vasculature, whereas photoacoustic spectroscopy identified regions of oxygenated and deoxygenated blood vessels. The 3D photoacoustic and pulse echo imaging system provided complementary information to track the tumor microenvironment, evaluate new cancer therapies, and develop molecular imaging agents in vivo. Finally, these safe and noninvasive techniques are potentially applicable for human cancer imaging.

Frequency bandwidth extension by use of multiple Zeeman field offsets for electron spin-echo EPR oxygen imaging of large objects

PubMed Central

Seifi, Payam; Epel, Boris; Sundramoorthy, Subramanian V.; Mailer, Colin; Halpern, Howard J.

2011-01-01

Purpose: Electron spin-echo (ESE) oxygen imaging is a new and evolving electron paramagnetic resonance (EPR) imaging (EPRI) modality that is useful for physiological in vivo applications, such as EPR oxygen imaging (EPROI), with potential application to imaging of multicentimeter objects as large as human tumors. A present limitation on the size of the object to be imaged at a given resolution is the frequency bandwidth of the system, since the location is encoded as a frequency offset in ESE imaging. The authors’ aim in this study was to demonstrate the object size advantage of the multioffset bandwidth extension technique.Methods: The multiple-stepped Zeeman field offset (or simply multi-B) technique was used for imaging of an 8.5-cm-long phantom containing a narrow single line triaryl methyl compound (trityl) solution at the 250 MHz imaging frequency. The image is compared to a standard single-field ESE image of the same phantom.Results: For the phantom used in this study, transverse relaxation (T2e) electron spin-echo (ESE) images from multi-B acquisition are more uniform, contain less prominent artifacts, and have a better signal to noise ratio (SNR) compared to single-field T2e images.Conclusions: The multi-B method is suitable for imaging of samples whose physical size restricts the applicability of the conventional single-field ESE imaging technique. PMID:21815379

SU-E-J-97: Evaluation of Multi-Modality (CT/MR/PET) Image Registration Accuracy in Radiotherapy Planning.

PubMed

Sethi, A; Rusu, I; Surucu, M; Halama, J

2012-06-01

Evaluate accuracy of multi-modality image registration in radiotherapy planning process. A water-filled anthropomorphic head phantom containing eight 'donut-shaped' fiducial markers (3 internal + 5 external) was selected for this study. Seven image sets (3CTs, 3MRs and PET) of phantom were acquired and fused in a commercial treatment planning system. First, a narrow slice (0.75mm) baseline CT scan was acquired (CT1). Subsequently, the phantom was re-scanned with a coarse slice width = 1.5mm (CT2) and after subjecting phantom to rotation/displacement (CT3). Next, the phantom was scanned in a 1.5 Tesla MR scanner and three MR image sets (axial T1, axial T2, coronal T1) were acquired at 2mm slice width. Finally, the phantom and center of fiducials were doped with 18F and a PET scan was performed with 2mm cubic voxels. All image scans (CT/MR/PET) were fused to the baseline (CT1) data using automated mutual-information based fusion algorithm. Difference between centroids of fiducial markers in various image modalities was used to assess image registration accuracy. CT/CT image registration was superior to CT/MR and CT/PET: average CT/CT fusion error was found to be 0.64 ± 0.14 mm. Corresponding values for CT/MR and CT/PET fusion were 1.33 ± 0.71mm and 1.11 ± 0.37mm. Internal markers near the center of phantom fused better than external markers placed on the phantom surface. This was particularly true for the CT/MR and CT/PET. The inferior quality of external marker fusion indicates possible distortion effects toward the edges of MR image. Peripheral targets in the PET scan may be subject to parallax error caused by depth of interaction of photons in detectors. Current widespread use of multimodality imaging in radiotherapy planning calls for periodic quality assurance of image registration process. Such studies may help improve safety and accuracy in treatment planning. © 2012 American Association of Physicists in Medicine.

Multi Modality Brain Mapping System (MBMS) Using Artificial Intelligence and Pattern Recognition

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Kateb, Babak (Inventor)

2017-01-01

A Multimodality Brain Mapping System (MBMS), comprising one or more scopes (e.g., microscopes or endoscopes) coupled to one or more processors, wherein the one or more processors obtain training data from one or more first images and/or first data, wherein one or more abnormal regions and one or more normal regions are identified; receive a second image captured by one or more of the scopes at a later time than the one or more first images and/or first data and/or captured using a different imaging technique; and generate, using machine learning trained using the training data, one or more viewable indicators identifying one or abnormalities in the second image, wherein the one or more viewable indicators are generated in real time as the second image is formed. One or more of the scopes display the one or more viewable indicators on the second image.

Advanced magnetic resonance imaging in glioblastoma: a review.

PubMed

Shukla, Gaurav; Alexander, Gregory S; Bakas, Spyridon; Nikam, Rahul; Talekar, Kiran; Palmer, Joshua D; Shi, Wenyin

2017-08-01

Glioblastoma, the most common and most rapidly progressing primary malignant tumor of the central nervous system, continues to portend a dismal prognosis, despite improvements in diagnostic and therapeutic strategies over the last 20 years. The standard of care radiographic characterization of glioblastoma is magnetic resonance imaging (MRI), which is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma. Basic MRI modalities available from any clinical scanner, including native T1-weighted (T1w) and contrast-enhanced (T1CE), T2-weighted (T2w), and T2-fluid-attenuated inversion recovery (T2-FLAIR) sequences, provide critical clinical information about various processes in the tumor environment. In the last decade, advanced MRI modalities are increasingly utilized to further characterize glioblastomas more comprehensively. These include multi-parametric MRI sequences, such as dynamic susceptibility contrast (DSC), dynamic contrast enhancement (DCE), higher order diffusion techniques such as diffusion tensor imaging (DTI), and MR spectroscopy (MRS). Significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. Functional MRI (fMRI) and tractography are increasingly being used to identify eloquent cortices and important tracts to minimize postsurgical neuro-deficits. A contemporary review of the application of standard and advanced MRI in clinical neuro-oncologic practice is presented here.

Computer-assisted stereotactic neurological surgery: pre-planning and on-site real-time operating control and simulation system

NASA Astrophysics Data System (ADS)

Zamorano, Lucia J.; Jiang, Charlie Z. W.

1993-09-01

In this decade the concept and development of computer assisted stereotactic neurological surgery has improved dramatically. First, the computer network replaced the tape as the data transportation media. Second, newer systems include multi-modality image correlation and frameless stereotactics as an integral part of their functionality, and offer extensive assistance to the neurosurgeon from the preplanning stages to and throughout the operation itself. These are very important changes, and have spurred the development of many interesting techniques. Successful systems include the ISG and NSPS-3.0.

In vivo bioluminescence tomography based on multi-view projection and 3D surface reconstruction

NASA Astrophysics Data System (ADS)

Zhang, Shuang; Wang, Kun; Leng, Chengcai; Deng, Kexin; Hu, Yifang; Tian, Jie

2015-03-01

Bioluminescence tomography (BLT) is a powerful optical molecular imaging modality, which enables non-invasive realtime in vivo imaging as well as 3D quantitative analysis in preclinical studies. In order to solve the inverse problem and reconstruct inner light sources accurately, the prior structural information is commonly necessary and obtained from computed tomography or magnetic resonance imaging. This strategy requires expensive hybrid imaging system, complicated operation protocol and possible involvement of ionizing radiation. The overall robustness highly depends on the fusion accuracy between the optical and structural information. In this study we present a pure optical bioluminescence tomographic system (POBTS) and a novel BLT method based on multi-view projection acquisition and 3D surface reconstruction. The POBTS acquired a sparse set of white light surface images and bioluminescent images of a mouse. Then the white light images were applied to an approximate surface model to generate a high quality textured 3D surface reconstruction of the mouse. After that we integrated multi-view luminescent images based on the previous reconstruction, and applied an algorithm to calibrate and quantify the surface luminescent flux in 3D.Finally, the internal bioluminescence source reconstruction was achieved with this prior information. A BALB/C mouse with breast tumor of 4T1-fLuc cells mouse model were used to evaluate the performance of the new system and technique. Compared with the conventional hybrid optical-CT approach using the same inverse reconstruction method, the reconstruction accuracy of this technique was improved. The distance error between the actual and reconstructed internal source was decreased by 0.184 mm.

Dual-Modality, Dual-Functional Nanoprobes for Cellular and Molecular Imaging

PubMed Central

Menon, Jyothi U.; Gulaka, Praveen K.; McKay, Madalyn A.; Geethanath, Sairam; Liu, Li; Kodibagkar, Vikram D.

2012-01-01

An emerging need for evaluation of promising cellular therapies is a non-invasive method to image the movement and health of cells following transplantation. However, the use of a single modality to serve this purpose may not be advantageous as it may convey inaccurate or insufficient information. Multi-modal imaging strategies are becoming more popular for in vivo cellular and molecular imaging because of their improved sensitivity, higher resolution and structural/functional visualization. This study aims at formulating Nile Red doped hexamethyldisiloxane (HMDSO) nanoemulsions as dual modality (Magnetic Resonance Imaging/Fluorescence), dual-functional (oximetry/detection) nanoprobes for cellular and molecular imaging. HMDSO nanoprobes were prepared using a HS15-lecithin combination as surfactant and showed an average radius of 71±39 nm by dynamic light scattering and in vitro particle stability in human plasma over 24 hrs. They were found to readily localize in the cytosol of MCF7-GFP cells within 18 minutes of incubation. As proof of principle, these nanoprobes were successfully used for fluorescence imaging and for measuring pO2 changes in cells by magnetic resonance imaging, in vitro, thus showing potential for in vivo applications. PMID:23382776

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

Imaging and machine learning techniques for diagnosis of Alzheimer's disease.

PubMed

Mirzaei, Golrokh; Adeli, Anahita; Adeli, Hojjat

2016-12-01

Alzheimer's disease (AD) is a common health problem in elderly people. There has been considerable research toward the diagnosis and early detection of this disease in the past decade. The sensitivity of biomarkers and the accuracy of the detection techniques have been defined to be the key to an accurate diagnosis. This paper presents a state-of-the-art review of the research performed on the diagnosis of AD based on imaging and machine learning techniques. Different segmentation and machine learning techniques used for the diagnosis of AD are reviewed including thresholding, supervised and unsupervised learning, probabilistic techniques, Atlas-based approaches, and fusion of different image modalities. More recent and powerful classification techniques such as the enhanced probabilistic neural network of Ahmadlou and Adeli should be investigated with the goal of improving the diagnosis accuracy. A combination of different image modalities can help improve the diagnosis accuracy rate. Research is needed on the combination of modalities to discover multi-modal biomarkers.

MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery

PubMed Central

Reaungamornrat, S.; De Silva, T.; Uneri, A.; Wolinsky, J.-P.; Khanna, A. J.; Kleinszig, G.; Vogt, S.; Prince, J. L.; Siewerdsen, J. H.

2016-01-01

Purpose Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration accuracy suitable to application in image-guided spine surgery across a broad range of anatomical sites and modes of deformation. PMID:27330239

MIND Demons for MR-to-CT deformable image registration in image-guided spine surgery

NASA Astrophysics Data System (ADS)

Reaungamornrat, S.; De Silva, T.; Uneri, A.; Wolinsky, J.-P.; Khanna, A. J.; Kleinszig, G.; Vogt, S.; Prince, J. L.; Siewerdsen, J. H.

2016-03-01

Purpose: Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. Method: The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. Result: The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. Conclusions: A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration accuracy suitable to application in image-guided spine surgery across a broad range of anatomical sites and modes of deformation.

MIND Demons for MR-to-CT Deformable Image Registration In Image-Guided Spine Surgery.

PubMed

Reaungamornrat, S; De Silva, T; Uneri, A; Wolinsky, J-P; Khanna, A J; Kleinszig, G; Vogt, S; Prince, J L; Siewerdsen, J H

2016-02-27

Localization of target anatomy and critical structures defined in preoperative MR images can be achieved by means of multi-modality deformable registration to intraoperative CT. We propose a symmetric diffeomorphic deformable registration algorithm incorporating a modality independent neighborhood descriptor (MIND) and a robust Huber metric for MR-to-CT registration. The method, called MIND Demons, solves for the deformation field between two images by optimizing an energy functional that incorporates both the forward and inverse deformations, smoothness on the velocity fields and the diffeomorphisms, a modality-insensitive similarity function suitable to multi-modality images, and constraints on geodesics in Lagrangian coordinates. Direct optimization (without relying on an exponential map of stationary velocity fields used in conventional diffeomorphic Demons) is carried out using a Gauss-Newton method for fast convergence. Registration performance and sensitivity to registration parameters were analyzed in simulation, in phantom experiments, and clinical studies emulating application in image-guided spine surgery, and results were compared to conventional mutual information (MI) free-form deformation (FFD), local MI (LMI) FFD, and normalized MI (NMI) Demons. The method yielded sub-voxel invertibility (0.006 mm) and nonsingular spatial Jacobians with capability to preserve local orientation and topology. It demonstrated improved registration accuracy in comparison to the reference methods, with mean target registration error (TRE) of 1.5 mm compared to 10.9, 2.3, and 4.6 mm for MI FFD, LMI FFD, and NMI Demons methods, respectively. Validation in clinical studies demonstrated realistic deformation with sub-voxel TRE in cases of cervical, thoracic, and lumbar spine. A modality-independent deformable registration method has been developed to estimate a viscoelastic diffeomorphic map between preoperative MR and intraoperative CT. The method yields registration accuracy suitable to application in image-guided spine surgery across a broad range of anatomical sites and modes of deformation.

Multimodality medical image database for temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-05-01

This paper presents the development of a human brain multi-modality database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted and FLAIR MRI and ictal/interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as non-verbal Wechsler memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication matches the neurosurgeons expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Tumor Lysing Genetically Engineered T Cells Loaded with Multi-Modal Imaging Agents

NASA Astrophysics Data System (ADS)

Bhatnagar, Parijat; Alauddin, Mian; Bankson, James A.; Kirui, Dickson; Seifi, Payam; Huls, Helen; Lee, Dean A.; Babakhani, Aydin; Ferrari, Mauro; Li, King C.; Cooper, Laurence J. N.

2014-03-01

Genetically-modified T cells expressing chimeric antigen receptors (CAR) exert anti-tumor effect by identifying tumor-associated antigen (TAA), independent of major histocompatibility complex. For maximal efficacy and safety of adoptively transferred cells, imaging their biodistribution is critical. This will determine if cells home to the tumor and assist in moderating cell dose. Here, T cells are modified to express CAR. An efficient, non-toxic process with potential for cGMP compliance is developed for loading high cell number with multi-modal (PET-MRI) contrast agents (Super Paramagnetic Iron Oxide Nanoparticles - Copper-64; SPION-64Cu). This can now be potentially used for 64Cu-based whole-body PET to detect T cell accumulation region with high-sensitivity, followed by SPION-based MRI of these regions for high-resolution anatomically correlated images of T cells. CD19-specific-CAR+SPIONpos T cells effectively target in vitro CD19+ lymphoma.

Advanced NDE research in electromagnetic, thermal, and coherent optics

NASA Technical Reports Server (NTRS)

Skinner, S. Ballou

1992-01-01

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

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

NASA Technical Reports Server (NTRS)

Hearn, Tristan A.

2015-01-01

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

A new, open-source, multi-modality digital breast phantom

NASA Astrophysics Data System (ADS)

Graff, Christian G.

2016-03-01

An anthropomorphic digital breast phantom has been developed with the goal of generating random voxelized breast models that capture the anatomic variability observed in vivo. This is a new phantom and is not based on existing digital breast phantoms or segmentation of patient images. It has been designed at the outset to be modality agnostic (i.e., suitable for use in modeling x-ray based imaging systems, magnetic resonance imaging, and potentially other imaging systems) and open source so that users may freely modify the phantom to suit a particular study. In this work we describe the modeling techniques that have been developed, the capabilities and novel features of this phantom, and study simulated images produced from it. Starting from a base quadric, a series of deformations are performed to create a breast with a particular volume and shape. Initial glandular compartments are generated using a Voronoi technique and a ductal tree structure with terminal duct lobular units is grown from the nipple into each compartment. An additional step involving the creation of fat and glandular lobules using a Perlin noise function is performed to create more realistic glandular/fat tissue interfaces and generate a Cooper's ligament network. A vascular tree is grown from the chest muscle into the breast tissue. Breast compression is performed using a neo-Hookean elasticity model. We show simulated mammographic and T1-weighted MRI images and study properties of these images.

Upconverting rare-earth nanoparticles with a paramagnetic lanthanide complex shell for upconversion fluorescent and magnetic resonance dual-modality imaging

NASA Astrophysics Data System (ADS)

Wang, Yan; Ji, Lei; Zhang, Bingbo; Yin, Peihao; Qiu, Yanyan; Song, Daqian; Zhou, Juying; Li, Qi

2013-05-01

Multi-modal imaging based on multifunctional nanoparticles is a promising alternative approach to improve the sensitivity of early cancer diagnosis. In this study, highly upconverting fluorescence and strong relaxivity rare-earth nanoparticles coated with paramagnetic lanthanide complex shells and polyethylene glycol (PEGylated UCNPs@DTPA-Gd3+) are synthesized as dual-modality imaging contrast agents (CAs) for upconverting fluorescent and magnetic resonance dual-modality imaging. PEGylated UCNPs@DTPA-Gd3+ with sizes in the range of 32-86 nm are colloidally stable. They exhibit higher longitudinal relaxivity and transverse relaxivity in water (r1 and r2 values are 7.4 and 27.8 s-1 per mM Gd3+, respectively) than does commercial Gd-DTPA (r1 and r2 values of 3.7 and 4.6 s-1 per mM Gd3+, respectively). They are found to be biocompatible. In vitro cancer cell imaging shows good imaging contrast of PEGylated UCNPs@DTPA-Gd3+. In vivo upconversion fluorescent imaging and T1-weighted MRI show excellent enhancement of both fluorescent and MR signals in the livers of mice administered PEGylated UCNPs@DTPA-Gd3+. All the experimental results indicate that the synthesized PEGylated UCNPs@DTPA-Gd3+ present great potential for biomedical upconversion of fluorescent and magnetic resonance dual-modality imaging applications.

A collaborative interaction and visualization multi-modal environment for surgical planning.

PubMed

Foo, Jung Leng; Martinez-Escobar, Marisol; Peloquin, Catherine; Lobe, Thom; Winer, Eliot

2009-01-01

The proliferation of virtual reality visualization and interaction technologies has changed the way medical image data is analyzed and processed. This paper presents a multi-modal environment that combines a virtual reality application with a desktop application for collaborative surgical planning. Both visualization applications can function independently but can also be synced over a network connection for collaborative work. Any changes to either application is immediately synced and updated to the other. This is an efficient collaboration tool that allows multiple teams of doctors with only an internet connection to visualize and interact with the same patient data simultaneously. With this multi-modal environment framework, one team working in the VR environment and another team from a remote location working on a desktop machine can both collaborate in the examination and discussion for procedures such as diagnosis, surgical planning, teaching and tele-mentoring.

Fully Convolutional Neural Networks Improve Abdominal Organ Segmentation.

PubMed

Bobo, Meg F; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G; Hilmes, Melissa A; Landman, Bennett A

2018-03-01

Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities.

Fully convolutional neural networks improve abdominal organ segmentation

NASA Astrophysics Data System (ADS)

Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

2018-03-01

Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

Design of small confocal endo-microscopic probe working under multiwavelength environment

NASA Astrophysics Data System (ADS)

Kim, Young-Duk; Ahn, MyoungKi; Gweon, Dae-Gab

2010-02-01

Recently, optical imaging system is widely used in medical purpose. By using optical imaging system specific diseases can be easily diagnosed at early stage because optical imaging system has high resolution performance and various imaging method. These methods are used to get high resolution image of human body and can be used to verify whether the cell is infected by virus. Confocal microscope is one of the famous imaging systems which is used for in-vivo imaging. Because most of diseases are accompanied with cellular level changes, doctors can diagnosis at early stage by observing the cellular image of human organ. Current research is focused in the development of endo-microscope that has great advantage in accessibility to human body. In this research, I designed small probe that is connected to confocal microscope through optical fiber bundle and work as endo-microscope. And this small probe is mainly designed to correct chromatic aberration to use various laser sources for both fluorescence type and reflection type confocal images. By using two kinds of laser sources at the same time we demonstrated multi-modality confocal endo-microscope.

Quantitative multi-modal NDT data analysis

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

Heideklang, René; Shokouhi, Parisa

2014-02-18

A single NDT technique is often not adequate to provide assessments about the integrity of test objects with the required coverage or accuracy. In such situations, it is often resorted to multi-modal testing, where complementary and overlapping information from different NDT techniques are combined for a more comprehensive evaluation. Multi-modal material and defect characterization is an interesting task which involves several diverse fields of research, including signal and image processing, statistics and data mining. The fusion of different modalities may improve quantitative nondestructive evaluation by effectively exploiting the augmented set of multi-sensor information about the material. It is the redundantmore » information in particular, whose quantification is expected to lead to increased reliability and robustness of the inspection results. There are different systematic approaches to data fusion, each with its specific advantages and drawbacks. In our contribution, these will be discussed in the context of nondestructive materials testing. A practical study adopting a high-level scheme for the fusion of Eddy Current, GMR and Thermography measurements on a reference metallic specimen with built-in grooves will be presented. Results show that fusion is able to outperform the best single sensor regarding detection specificity, while retaining the same level of sensitivity.« less

Phase congruency map driven brain tumour segmentation

NASA Astrophysics Data System (ADS)

Szilágyi, Tünde; Brady, Michael; Berényi, Ervin

2015-03-01

Computer Aided Diagnostic (CAD) systems are already of proven value in healthcare, especially for surgical planning, nevertheless much remains to be done. Gliomas are the most common brain tumours (70%) in adults, with a survival time of just 2-3 months if detected at WHO grades III or higher. Such tumours are extremely variable, necessitating multi-modal Magnetic Resonance Images (MRI). The use of Gadolinium-based contrast agents is only relevant at later stages of the disease where it highlights the enhancing rim of the tumour. Currently, there is no single accepted method that can be used as a reference. There are three main challenges with such images: to decide whether there is tumour present and is so localize it; to construct a mask that separates healthy and diseased tissue; and to differentiate between the tumour core and the surrounding oedema. This paper presents two contributions. First, we develop tumour seed selection based on multiscale multi-modal texture feature vectors. Second, we develop a method based on a local phase congruency based feature map to drive level-set segmentation. The segmentations achieved with our method are more accurate than previously presented methods, particularly for challenging low grade tumours.

Endoscopic Full-Field Swept-Source Optical Coherence Tomography Neuroimaging System

NASA Astrophysics Data System (ADS)

Felts Almog, Ilan

Optical Coherence Tomography (OCT) has the capability to differentiate brain elements with intrinsic contrast and at a resolution an order-of-magnitude higher than other imaging modalities. This thesis investigates the feasibility of OCT for neuroimaging applied to neurosurgical guidance. We present, to our knowledge, the first Full-Field Swept-Source OCT system operating near a wavelength of 1310 nm, achieving a transverse imaging resolution of 6.5 mum, an axial resolution of 14 mum in tissue and a field of view of 270 mum x 180 mum x 400 mum. Imaging experiments were performed on rat brain tissues ex vivo, human cortical tissue ex vivo, and rats in vivo. A multi-level threshold metric applied on the intensity of the images led to a plausible correlation between the observed density and location in the brain. The proof-of-concept OCT system can be improved and miniaturized for clinical use.

Multishaker modal testing

NASA Technical Reports Server (NTRS)

Craig, Roy R., Jr.

1987-01-01

The major accomplishments of this research are: (1) the refinement and documentation of a multi-input, multi-output modal parameter estimation algorithm which is applicable to general linear, time-invariant dynamic systems; (2) the development and testing of an unsymmetric block-Lanzcos algorithm for reduced-order modeling of linear systems with arbitrary damping; and (3) the development of a control-structure-interaction (CSI) test facility.

Drug related webpages classification using images and text information based on multi-kernel learning

NASA Astrophysics Data System (ADS)

Hu, Ruiguang; Xiao, Liping; Zheng, Wenjuan

2015-12-01

In this paper, multi-kernel learning(MKL) is used for drug-related webpages classification. First, body text and image-label text are extracted through HTML parsing, and valid images are chosen by the FOCARSS algorithm. Second, text based BOW model is used to generate text representation, and image-based BOW model is used to generate images representation. Last, text and images representation are fused with a few methods. Experimental results demonstrate that the classification accuracy of MKL is higher than those of all other fusion methods in decision level and feature level, and much higher than the accuracy of single-modal classification.

Architecture for a PACS primary diagnosis workstation

NASA Astrophysics Data System (ADS)

Shastri, Kaushal; Moran, Byron

1990-08-01

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

Development of a multi-scale and multi-modality imaging system to characterize tumours and their microenvironment in vivo

NASA Astrophysics Data System (ADS)

Rouffiac, Valérie; Ser-Leroux, Karine; Dugon, Emilie; Leguerney, Ingrid; Polrot, Mélanie; Robin, Sandra; Salomé-Desnoulez, Sophie; Ginefri, Jean-Christophe; Sebrié, Catherine; Laplace-Builhé, Corinne

2015-03-01

In vivo high-resolution imaging of tumor development is possible through dorsal skinfold chamber implantable on mice model. However, current intravital imaging systems are weakly tolerated along time by mice and do not allow multimodality imaging. Our project aims to develop a new chamber for: 1- long-term micro/macroscopic visualization of tumor (vascular and cellular compartments) and tissue microenvironment; and 2- multimodality imaging (photonic, MRI and sonography). Our new experimental device was patented in March 2014 and was primarily assessed on 75 mouse engrafted with 4T1-Luc tumor cell line, and validated in confocal and multiphoton imaging after staining the mice vasculature using Dextran 155KDa-TRITC or Dextran 2000kDa-FITC. Simultaneously, a universal stage was designed for optimal removal of respiratory and cardiac artifacts during microscopy assays. Experimental results from optical, ultrasound (Bmode and pulse subtraction mode) and MRI imaging (anatomic sequences) showed that our patented design, unlike commercial devices, improves longitudinal monitoring over several weeks (35 days on average against 12 for the commercial chamber) and allows for a better characterization of the early and late tissue alterations due to tumour development. We also demonstrated the compatibility for multimodality imaging and the increase of mice survival was by a factor of 2.9, with our new skinfold chamber. Current developments include: 1- defining new procedures for multi-labelling of cells and tissue (screening of fluorescent molecules and imaging protocols); 2- developing ultrasound and MRI imaging procedures with specific probes; 3- correlating optical/ultrasound/MRI data for a complete mapping of tumour development and microenvironment.

Dual-modality imaging of function and physiology

NASA Astrophysics Data System (ADS)

Hasegawa, Bruce H.; Iwata, Koji; Wong, Kenneth H.; Wu, Max C.; Da Silva, Angela; Tang, Hamilton R.; Barber, William C.; Hwang, Andrew B.; Sakdinawat, Anne E.

2002-04-01

Dual-modality imaging is a technique where computed tomography or magnetic resonance imaging is combined with positron emission tomography or single-photon computed tomography to acquire structural and functional images with an integrated system. The data are acquired during a single procedure with the patient on a table viewed by both detectors to facilitate correlation between the structural and function images. The resulting data can be useful for localization for more specific diagnosis of disease. In addition, the anatomical information can be used to compensate the correlated radionuclide data for physical perturbations such as photon attenuation, scatter radiation, and partial volume errors. Thus, dual-modality imaging provides a priori information that can be used to improve both the visual quality and the quantitative accuracy of the radionuclide images. Dual-modality imaging systems also are being developed for biological research that involves small animals. The small-animal dual-modality systems offer advantages for measurements that currently are performed invasively using autoradiography and tissue sampling. By acquiring the required data noninvasively, dual-modality imaging has the potential to allow serial studies in a single animal, to perform measurements with fewer animals, and to improve the statistical quality of the data.

Windows on the human body--in vivo high-field magnetic resonance research and applications in medicine and psychology.

PubMed

Moser, Ewald; Meyerspeer, Martin; Fischmeister, Florian Ph S; Grabner, Günther; Bauer, Herbert; Trattnig, Siegfried

2010-01-01

Analogous to the evolution of biological sensor-systems, the progress in "medical sensor-systems", i.e., diagnostic procedures, is paradigmatically described. Outstanding highlights of this progress are magnetic resonance imaging (MRI) and spectroscopy (MRS), which enable non-invasive, in vivo acquisition of morphological, functional, and metabolic information from the human body with unsurpassed quality. Recent achievements in high and ultra-high field MR (at 3 and 7 Tesla) are described, and representative research applications in Medicine and Psychology in Austria are discussed. Finally, an overview of current and prospective research in multi-modal imaging, potential clinical applications, as well as current limitations and challenges is given.

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

PubMed

Peissig, Peggy L; Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries.

Multi-Source Learning for Joint Analysis of Incomplete Multi-Modality Neuroimaging Data

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2013-01-01

Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. We address this problem by proposing two novel learning methods where all the samples (with at least one available data source) can be used. In the first method, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. Our second method learns a base classifier for each data source independently, based on which we represent each source using a single column of prediction scores; we then estimate the missing prediction scores, which, combined with the existing prediction scores, are used to build a multi-source fusion model. To illustrate the proposed approaches, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 Normal), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithms. Comprehensive experiments show that our proposed methods yield stable and promising results. PMID:24014189

Anti-Stokes effect CCD camera and SLD based optical coherence tomography for full-field imaging in the 1550nm region

NASA Astrophysics Data System (ADS)

Kredzinski, Lukasz; Connelly, Michael J.

2012-06-01

Full-field Optical coherence tomography is an en-face interferometric imaging technology capable of carrying out high resolution cross-sectional imaging of the internal microstructure of an examined specimen in a non-invasive manner. The presented system is based on competitively priced optical components available at the main optical communications band located in the 1550 nm region. It consists of a superluminescent diode and an anti-stokes imaging device. The single mode fibre coupled SLD was connected to a multi-mode fibre inserted into a mode scrambler to obtain spatially incoherent illumination, suitable for OCT wide-field modality in terms of crosstalk suppression and image enhancement. This relatively inexpensive system with moderate resolution of approximately 24um x 12um (axial x lateral) was constructed to perform a 3D cross sectional imaging of a human tooth. To our knowledge this is the first 1550 nm full-field OCT system reported.

Implementation and applications of dual-modality imaging

NASA Astrophysics Data System (ADS)

Hasegawa, Bruce H.; Barber, William C.; Funk, Tobias; Hwang, Andrew B.; Taylor, Carmen; Sun, Mingshan; Seo, Youngho

2004-06-01

In medical diagnosis, functional or physiological data can be acquired using radionuclide imaging with positron emission tomography or with single-photon emission computed tomography. However, anatomical or structural data can be acquired using X-ray computed tomography. In dual-modality imaging, both radionuclide and X-ray detectors are incorporated in an imaging system to allow both functional and structural data to be acquired in a single procedure without removing the patient from the imaging system. In a clinical setting, dual-modality imaging systems commonly are used to localize radiopharmaceutical uptake with respect to the patient's anatomy. This helps the clinician to differentiate disease from regions of normal radiopharmaceutical accumulation, to improve diagnosis or cancer staging, or to facilitate planning for radiation therapy or surgery. While initial applications of dual-modality imaging were developed for clinical imaging on humans, it now is recognized that these systems have potentially important applications for imaging small animals involved in experimental studies including basic investigations of mammalian biology and development of new pharmaceuticals for diagnosis or treatment of disease.

MULTI-SOURCE FEATURE LEARNING FOR JOINT ANALYSIS OF INCOMPLETE MULTIPLE HETEROGENEOUS NEUROIMAGING DATA

PubMed Central

Yuan, Lei; Wang, Yalin; Thompson, Paul M.; Narayan, Vaibhav A.; Ye, Jieping

2012-01-01

Analysis of incomplete data is a big challenge when integrating large-scale brain imaging datasets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiative (ADNI), for example, over half of the subjects lack cerebrospinal fluid (CSF) measurements; an independent half of the subjects do not have fluorodeoxyglucose positron emission tomography (FDG-PET) scans; many lack proteomics measurements. Traditionally, subjects with missing measures are discarded, resulting in a severe loss of available information. In this paper, we address this problem by proposing an incomplete Multi-Source Feature (iMSF) learning method where all the samples (with at least one available data source) can be used. To illustrate the proposed approach, we classify patients from the ADNI study into groups with Alzheimer’s disease (AD), mild cognitive impairment (MCI) and normal controls, based on the multi-modality data. At baseline, ADNI’s 780 participants (172 AD, 397 MCI, 211 NC), have at least one of four data types: magnetic resonance imaging (MRI), FDG-PET, CSF and proteomics. These data are used to test our algorithm. Depending on the problem being solved, we divide our samples according to the availability of data sources, and we learn shared sets of features with state-of-the-art sparse learning methods. To build a practical and robust system, we construct a classifier ensemble by combining our method with four other methods for missing value estimation. Comprehensive experiments with various parameters show that our proposed iMSF method and the ensemble model yield stable and promising results. PMID:22498655

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

Multi-Modal Performance Measures in Oregon: Developing a Transportation Cost Index Based Upon Multi-Modal Network and Land Use Information

DOT National Transportation Integrated Search

2016-02-01

Transportation Cost Index is a performance measure for transportation and land use systems originally proposed and piloted by Reiff and Gregor (2005). It fills important niches of existing similar measures in term of policy areas covered and type of ...

Label-Free, High Resolution, Multi-Modal Light Microscopy for Discrimination of Live Stem Cell Differentiation Status.

PubMed

Zhang, Jing; Moradi, Emilia; Somekh, Michael G; Mather, Melissa L

2018-01-15

A label-free microscopy method for assessing the differentiation status of stem cells is presented with potential application for characterization of therapeutic stem cell populations. The microscopy system is capable of characterizing live cells based on the use of evanescent wave microscopy and quantitative phase contrast (QPC) microscopy. The capability of the microscopy system is demonstrated by studying the differentiation of live immortalised neonatal mouse neural stem cells over a 15 day time course. Metrics extracted from microscope images are assessed and images compared with results from endpoint immuno-staining studies to illustrate the system's performance. Results demonstrate the potential of the microscopy system as a valuable tool for cell biologists to readily identify the differentiation status of unlabelled live cells.

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.

Computational Assessment of Blood Flow Heterogeneity in Peritoneal Dialysis Patients' Cardiac Ventricles

PubMed Central

Kharche, Sanjay R.; So, Aaron; Salerno, Fabio; Lee, Ting-Yim; Ellis, Chris; Goldman, Daniel; McIntyre, Christopher W.

2018-01-01

Dialysis prolongs life but augments cardiovascular mortality. Imaging data suggests that dialysis increases myocardial blood flow (BF) heterogeneity, but its causes remain poorly understood. A biophysical model of human coronary vasculature was used to explain the imaging observations, and highlight causes of coronary BF heterogeneity. Post-dialysis CT images from patients under control, pharmacological stress (adenosine), therapy (cooled dialysate), and adenosine and cooled dialysate conditions were obtained. The data presented disparate phenotypes. To dissect vascular mechanisms, a 3D human vasculature model based on known experimental coronary morphometry and a space filling algorithm was implemented. Steady state simulations were performed to investigate the effects of altered aortic pressure and blood vessel diameters on myocardial BF heterogeneity. Imaging showed that stress and therapy potentially increased mean and total BF, while reducing heterogeneity. BF histograms of one patient showed multi-modality. Using the model, it was found that total coronary BF increased as coronary perfusion pressure was increased. BF heterogeneity was differentially affected by large or small vessel blocking. BF heterogeneity was found to be inversely related to small blood vessel diameters. Simulation of large artery stenosis indicates that BF became heterogeneous (increase relative dispersion) and gave multi-modal histograms. The total transmural BF as well as transmural BF heterogeneity reduced due to large artery stenosis, generating large patches of very low BF regions downstream. Blocking of arteries at various orders showed that blocking larger arteries results in multi-modal BF histograms and large patches of low BF, whereas smaller artery blocking results in augmented relative dispersion and fractal dimension. Transmural heterogeneity was also affected. Finally, the effects of augmented aortic pressure in the presence of blood vessel blocking shows differential effects on BF heterogeneity as well as transmural BF. Improved aortic blood pressure may improve total BF. Stress and therapy may be effective if they dilate small vessels. A potential cause for the observed complex BF distributions (multi-modal BF histograms) may indicate existing large vessel stenosis. The intuitive BF heterogeneity methods used can be readily used in clinical studies. Further development of the model and methods will permit personalized assessment of patient BF status. PMID:29867555

Tissue-like phantoms

DOEpatents

Frangioni, John V.; De Grand, Alec M.

2007-10-30

The invention is based, in part, on the discovery that by combining certain components one can generate a tissue-like phantom that mimics any desired tissue, is simple and inexpensive to prepare, and is stable over many weeks or months. In addition, new multi-modal imaging objects (e.g., beads) can be inserted into the phantoms to mimic tissue pathologies, such as cancer, or merely to serve as calibration standards. These objects can be imaged using one, two, or more (e.g., four) different imaging modalities (e.g., x-ray computed tomography (CT), positron emission tomography (PET), single photon emission computed tomography (SPECT), and near-infrared (NIR) fluorescence) simultaneously.

Multi-modality imaging: Bird's eye view from the 2016 American Heart Association Scientific Sessions.

PubMed

AlJaroudi, Wael A; Lloyd, Steven G; Chaudhry, Farooq A; Hage, Fadi G

2017-06-01

This review summarizes key imaging studies that were presented in the American Heart Association Scientific Sessions 2016 related to the fields of nuclear cardiology, cardiac computed tomography, cardiac magnetic resonance, and echocardiography. This bird's eye view will inform readers about multiple studies from these different modalities. We hope that this general overview will be useful for those that did not attend the conference as well as to those that did since it is often difficult to get exposure to many abstracts at large meetings. The review, therefore, aims to help readers stay updated on the newest imaging studies presented at the meeting.

Hybrid label-free multiphoton and optoacoustic microscopy (MPOM)

NASA Astrophysics Data System (ADS)

Soliman, Dominik; Tserevelakis, George J.; Omar, Murad; Ntziachristos, Vasilis

2015-07-01

Many biological applications require a simultaneous observation of different anatomical features. However, unless potentially harmful staining of the specimens is employed, individual microscopy techniques do generally not provide multi-contrast capabilities. We present a hybrid microscope integrating optoacoustic microscopy and multiphoton microscopy, including second-harmonic generation, into a single device. This combined multiphoton and optoacoustic microscope (MPOM) offers visualization of a broad range of structures by employing different contrast mechanisms and at the same time enables pure label-free imaging of biological systems. We investigate the relative performance of the two microscopy modalities and demonstrate their multi-contrast abilities through the label-free imaging of a zebrafish larva ex vivo, simultaneously visualizing muscles and pigments. This hybrid microscopy application bears great potential for developmental biology studies, enabling more comprehensive information to be obtained from biological specimens without the necessity of staining.

Multimodal 3D cancer-mimicking optical phantom

PubMed Central

Smith, Gennifer T.; Lurie, Kristen L.; Zlatev, Dimitar V.; Liao, Joseph C.; Ellerbee Bowden, Audrey K.

2016-01-01

Three-dimensional (3D) organ-mimicking phantoms provide realistic imaging environments for testing various aspects of optical systems, including for evaluating new probe designs, characterizing the diagnostic potential of new technologies, and assessing novel image processing algorithms prior to validation in real tissue. We introduce and characterize the use of a new material, Dragon Skin (Smooth-On Inc.), and fabrication technique, air-brushing, for fabrication of a 3D phantom that mimics the appearance of a real organ under multiple imaging modalities. We demonstrate the utility of the material and technique by fabricating the first 3D, hollow bladder phantom with realistic normal and multi-stage pathology features suitable for endoscopic detection using the gold standard imaging technique, white light cystoscopy (WLC), as well as the complementary imaging modalities of optical coherence tomography and blue light cystoscopy, which are aimed at improving the sensitivity and specificity of WLC to bladder cancer detection. The flexibility of the material and technique used for phantom construction allowed for the representation of a wide range of diseased tissue states, ranging from inflammation (benign) to high-grade cancerous lesions. Such phantoms can serve as important tools for trainee education and evaluation of new endoscopic instrumentation. PMID:26977369

Retrospective Analysis of Communication Events - Understanding the Dynamics of Collaborative Multi-Party Discourse

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

Cowell, Andrew J.; Haack, Jereme N.; McColgin, Dave W.

2006-06-08

This research is aimed at understanding the dynamics of collaborative multi-party discourse across multiple communication modalities. Before we can truly make sig-nificant strides in devising collaborative communication systems, there is a need to understand how typical users utilize com-putationally supported communications mechanisms such as email, instant mes-saging, video conferencing, chat rooms, etc., both singularly and in conjunction with traditional means of communication such as face-to-face meetings, telephone calls and postal mail. Attempting to un-derstand an individual’s communications profile with access to only a single modal-ity is challenging at best and often futile. Here, we discuss the development of RACE –more » Retrospective Analysis of Com-munications Events – a test-bed prototype to investigate issues relating to multi-modal multi-party discourse.« less

Feature and Intensity Based Medical Image Registration Using Particle Swarm Optimization.

PubMed

Abdel-Basset, Mohamed; Fakhry, Ahmed E; El-Henawy, Ibrahim; Qiu, Tie; Sangaiah, Arun Kumar

2017-11-03

Image registration is an important aspect in medical image analysis, and kinds use in a variety of medical applications. Examples include diagnosis, pre/post surgery guidance, comparing/merging/integrating images from multi-modal like Magnetic Resonance Imaging (MRI), and Computed Tomography (CT). Whether registering images across modalities for a single patient or registering across patients for a single modality, registration is an effective way to combine information from different images into a normalized frame for reference. Registered datasets can be used for providing information relating to the structure, function, and pathology of the organ or individual being imaged. In this paper a hybrid approach for medical images registration has been developed. It employs a modified Mutual Information (MI) as a similarity metric and Particle Swarm Optimization (PSO) method. Computation of mutual information is modified using a weighted linear combination of image intensity and image gradient vector flow (GVF) intensity. In this manner, statistical as well as spatial image information is included into the image registration process. Maximization of the modified mutual information is effected using the versatile Particle Swarm Optimization which is developed easily with adjusted less parameter. The developed approach has been tested and verified successfully on a number of medical image data sets that include images with missing parts, noise contamination, and/or of different modalities (CT, MRI). The registration results indicate the proposed model as accurate and effective, and show the posture contribution in inclusion of both statistical and spatial image data to the developed approach.

Diverse Application of Magnetic Resonance Imaging for Mouse Phenotyping

PubMed Central

Wu, Yijen L.; Lo, Cecilia W.

2017-01-01

Small animal models, particularly mouse models, of human diseases are becoming an indispensable tool for biomedical research. Studies in animal models have provided important insights into the etiology of diseases and accelerated the development of therapeutic strategies. Detailed phenotypic characterization is essential, both for the development of such animal models and mechanistic studies into disease pathogenesis and testing the efficacy of experimental therapeutics. Magnetic Resonance Imaging (MRI) is a versatile and non-invasive imaging modality with excellent penetration depth, tissue coverage, and soft tissue contrast. MRI, being a multi-modal imaging modality, together with proven imaging protocols and availability of good contrast agents, is ideally suited for phenotyping mutant mouse models. Here we describe the applications of MRI for phenotyping structural birth defects involving the brain, heart, and kidney in mice. The versatility of MRI and its ease of use are well suited to meet the rapidly increasing demands for mouse phenotyping in the coming age of functional genomics. PMID:28544650

A brain MRI atlas of the common squirrel monkey, Saimiri sciureus

NASA Astrophysics Data System (ADS)

Gao, Yurui; Schilling, Kurt G.; Khare, Shweta P.; Panda, Swetasudha; Choe, Ann S.; Stepniewska, Iwona; Li, Xia; Ding, Zhoahua; Anderson, Adam; Landman, Bennett A.

2014-03-01

The common squirrel monkey, Saimiri sciureus, is a New World monkey with functional and microstructural organization of central nervous system similar to that of humans. It is one of the most commonly used South American primates in biomedical research. Unlike its Old World macaque cousins, no digital atlases have described the organization of the squirrel monkey brain. Here, we present a multi-modal magnetic resonance imaging (MRI) atlas constructed from the brain of an adult female squirrel monkey. In vivo MRI acquisitions include high resolution T2 structural imaging and low resolution diffusion tensor imaging. Ex vivo MRI acquisitions include high resolution T2 structural imaging and high resolution diffusion tensor imaging. Cortical regions were manually annotated on the co-registered volumes based on published histological sections.

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

Lee, Y; Fullerton, G; Goins, B

Purpose: In our previous study a preclinical multi-modality quality assurance (QA) phantom that contains five tumor-simulating test objects with 2, 4, 7, 10 and 14 mm diameters was developed for accurate tumor size measurement by researchers during cancer drug development and testing. This study analyzed the errors during tumor volume measurement from preclinical magnetic resonance (MR), micro-computed tomography (micro- CT) and ultrasound (US) images acquired in a rodent tumor model using the preclinical multi-modality QA phantom. Methods: Using preclinical 7-Tesla MR, US and micro-CT scanners, images were acquired of subcutaneous SCC4 tumor xenografts in nude rats (3–4 rats per group;more » 5 groups) along with the QA phantom using the same imaging protocols. After tumors were excised, in-air micro-CT imaging was performed to determine reference tumor volume. Volumes measured for the rat tumors and phantom test objects were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three imaging modalities. Then linear regression analysis was performed to compare image-based tumor volumes with the reference tumor volume and known test object volume for the rats and the phantom respectively. Results: The slopes of regression lines for in-vivo tumor volumes measured by three imaging modalities were 1.021, 1.101 and 0.862 for MRI, micro-CT and US respectively. For phantom, the slopes were 0.9485, 0.9971 and 0.9734 for MRI, micro-CT and US respectively. Conclusion: For both animal and phantom studies, random and systematic errors were observed. Random errors were observer-dependent and systematic errors were mainly due to selected imaging protocols and/or measurement method. In the animal study, there were additional systematic errors attributed to ellipsoidal assumption for tumor shape. The systematic errors measured using the QA phantom need to be taken into account to reduce measurement errors during the animal study.« less

Contrast-enhanced photoacoustic tomography of human joints

NASA Astrophysics Data System (ADS)

Tian, Chao; Keswani, Rahul K.; Gandikota, Girish; Rosania, Gus R.; Wang, Xueding

2016-03-01

Photoacoustic tomography (PAT) provides a unique tool to diagnose inflammatory arthritis. However, the specificity and sensitivity of PAT based on endogenous contrasts is limited. The development of contrast enhanced PAT imaging modalities in combination with small molecule contrast agents could lead to improvements in diagnosis and treatment of joint disease. Accordingly, we adapted and tested a PAT clinical imaging system for imaging the human joints, in combination with a novel PAT contrast agent derived from an FDA-approved small molecule drug. Imaging results based on a photoacoustic and ultrasound (PA/US) dual-modality system revealed that this contrast-enhanced PAT imaging system may offer additional information beyond single-modality PA or US imaging system, for the imaging, diagnosis and assessment of inflammatory arthritis.

Fiber optic in vivo imaging in the mammalian nervous system

PubMed Central

Mehta, Amit D; Jung, Juergen C; Flusberg, Benjamin A; Schnitzer, Mark J

2010-01-01

The compact size, mechanical flexibility, and growing functionality of optical fiber and fiber optic devices are enabling several new modalities for imaging the mammalian nervous system in vivo. Fluorescence microendoscopy is a minimally invasive fiber modality that provides cellular resolution in deep brain areas. Diffuse optical tomography is a non-invasive modality that uses assemblies of fiber optic emitters and detectors on the cranium for volumetric imaging of brain activation. Optical coherence tomography is a sensitive interferometric imaging technique that can be implemented in a variety of fiber based formats and that might allow intrinsic optical detection of brain activity at a high resolution. Miniaturized fiber optic microscopy permits cellular level imaging in the brains of behaving animals. Together, these modalities will enable new uses of imaging in the intact nervous system for both research and clinical applications. PMID:15464896

MR-based keyhole SPECT for small animal imaging

PubMed Central

Lee, Keum Sil; Roeck, Werner W; Gullberg, Grant T; Nalcioglu, Orhan

2011-01-01

The rationale for multi-modality imaging is to integrate the strengths of different imaging technologies while reducing the shortcomings of an individual modality. The work presented here proposes a limited-field-of-view (LFOV) SPECT reconstruction technique that can be implemented on a multi-modality MR/SPECT system that can be used to obtain simultaneous MRI and SPECT images for small animal imaging. The reason for using a combined MR/SPECT system in this work is to eliminate any possible misregistration between the two sets of images when MR images are used as a priori information for SPECT. In nuclear imaging the target area is usually smaller than the entire object; thus, focusing the detector on the LFOV results in various advantages including the use of a smaller nuclear detector (less cost), smaller reconstruction region (faster reconstruction) and higher spatial resolution when used in conjunction with pinhole collimators with magnification. The MR/SPECT system can be used to choose a region of interest (ROI) for SPECT. A priori information obtained by the full field-of-view (FOV) MRI combined with the preliminary SPECT image can be used to reduce the dimensions of the SPECT reconstruction by limiting the computation to the smaller FOV while reducing artifacts resulting from the truncated data. Since the technique is based on SPECT imaging within the LFOV it will be called the keyhole SPECT (K-SPECT) method. At first MRI images of the entire object using a larger FOV are obtained to determine the location of the ROI covering the target organ. Once the ROI is determined, the animal is moved inside the radiofrequency (rf) coil to bring the target area inside the LFOV and then simultaneous MRI and SPECT are performed. The spatial resolution of the SPECT image is improved by employing a pinhole collimator with magnification >1 by having carefully calculated acceptance angles for each pinhole to avoid multiplexing. In our design all the pinholes are focused to the center of the LFOV. K-SPECT reconstruction is accomplished by generating an adaptive weighting matrix using a priori information obtained by simultaneously acquired MR images and the radioactivity distribution obtained from the ROI region of the SPECT image that is reconstructed without any a priori input. Preliminary results using simulations with numerical phantoms show that the image resolution of the SPECT image within the LFOV is improved while minimizing artifacts arising from parts of the object outside the LFOV due to the chosen magnification and the new reconstruction technique. The root-mean-square-error (RMSE) in the out-of-field artifacts was reduced by 60% for spherical phantoms using the K-SPECT reconstruction technique and by 48.5–52.6% for the heart in the case with the MOBY phantom. The KSPECT reconstruction technique significantly improved the spatial resolution and quantification while reducing artifacts from the contributions outside the LFOV as well as reducing the dimension of the reconstruction matrix. PMID:21220840

Multi-modality 3D breast imaging with X-Ray tomosynthesis and automated ultrasound.

PubMed

Sinha, Sumedha P; Roubidoux, Marilyn A; Helvie, Mark A; Nees, Alexis V; Goodsitt, Mitchell M; LeCarpentier, Gerald L; Fowlkes, J Brian; Chalek, Carl L; Carson, Paul L

2007-01-01

This study evaluated the utility of 3D automated ultrasound in conjunction with 3D digital X-Ray tomosynthesis for breast cancer detection and assessment, to better localize and characterize lesions in the breast. Tomosynthesis image volumes and automated ultrasound image volumes were acquired in the same geometry and in the same view for 27 patients. 3 MQSA certified radiologists independently reviewed the image volumes, visually correlating the images from the two modalities with in-house software. More sophisticated software was used on a smaller set of 10 cases, which enabled the radiologist to draw a 3D box around the suspicious lesion in one image set and isolate an anatomically correlated, similarly boxed region in the other modality image set. In the primary study, correlation was found to be moderately useful to the readers. In the additional study, using improved software, the median usefulness rating increased and confidence in localizing and identifying the suspicious mass increased in more than half the cases. As automated scanning and reading software techniques advance, superior results are expected.

Interventional multispectral photoacoustic imaging with a clinical linear array ultrasound probe for guiding nerve blocks

NASA Astrophysics Data System (ADS)

Xia, Wenfeng; West, Simeon J.; Nikitichev, Daniil I.; Ourselin, Sebastien; Beard, Paul C.; Desjardins, Adrien E.

2016-03-01

Accurate identification of tissue structures such as nerves and blood vessels is critically important for interventional procedures such as nerve blocks. Ultrasound imaging is widely used as a guidance modality to visualize anatomical structures in real-time. However, identification of nerves and small blood vessels can be very challenging, and accidental intra-neural or intra-vascular injections can result in significant complications. Multi-spectral photoacoustic imaging can provide high sensitivity and specificity for discriminating hemoglobin- and lipid-rich tissues. However, conventional surface-illumination-based photoacoustic systems suffer from limited sensitivity at large depths. In this study, for the first time, an interventional multispectral photoacoustic imaging (IMPA) system was used to image nerves in a swine model in vivo. Pulsed excitation light with wavelengths in the ranges of 750 - 900 nm and 1150 - 1300 nm was delivered inside the body through an optical fiber positioned within the cannula of an injection needle. Ultrasound waves were received at the tissue surface using a clinical linear array imaging probe. Co-registered B-mode ultrasound images were acquired using the same imaging probe. Nerve identification was performed using a combination of B-mode ultrasound imaging and electrical stimulation. Using a linear model, spectral-unmixing of the photoacoustic data was performed to provide image contrast for oxygenated and de-oxygenated hemoglobin, water and lipids. Good correspondence between a known nerve location and a lipid-rich region in the photoacoustic images was observed. The results indicate that IMPA is a promising modality for guiding nerve blocks and other interventional procedures. Challenges involved with clinical translation are discussed.

Multi-modality image registration for effective thermographic fever screening

NASA Astrophysics Data System (ADS)

Dwith, C. Y. N.; Ghassemi, Pejhman; Pfefer, Joshua; Casamento, Jon; Wang, Quanzeng

2017-02-01

Fever screening based on infrared thermographs (IRTs) is a viable mass screening approach during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome (SARS), for temperature monitoring in public places like hospitals and airports. IRTs have been found to be powerful, quick and non-invasive methods for detecting elevated temperatures. Moreover, regions medially adjacent to the inner canthi (called the canthi regions in this paper) are preferred sites for fever screening. Accurate localization of the canthi regions can be achieved through multi-modality registration of infrared (IR) and white-light images. Here we propose a registration method through a coarse-fine registration strategy using different registration models based on landmarks and edge detection on eye contours. We have evaluated the registration accuracy to be within +/- 2.7 mm, which enables accurate localization of the canthi regions.

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2009-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...pilot study to utilize large scale parallel Grid computing to harness the nationwide cluster infrastructure for optimization of medical image ... analysis parameters. Additionally, we investigated the use of cutting edge dataanalysis/ mining techniques as applied to Ultrasound, FFDM, and DCE-MRI Breast

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

PubMed Central

Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. Materials and methods We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. Results An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. Conclusion We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries. PMID:22319176

TheHiveDB image data management and analysis framework.

PubMed

Muehlboeck, J-Sebastian; Westman, Eric; Simmons, Andrew

2014-01-06

The hive database system (theHiveDB) is a web-based brain imaging database, collaboration, and activity system which has been designed as an imaging workflow management system capable of handling cross-sectional and longitudinal multi-center studies. It can be used to organize and integrate existing data from heterogeneous projects as well as data from ongoing studies. It has been conceived to guide and assist the researcher throughout the entire research process, integrating all relevant types of data across modalities (e.g., brain imaging, clinical, and genetic data). TheHiveDB is a modern activity and resource management system capable of scheduling image processing on both private compute resources and the cloud. The activity component supports common image archival and management tasks as well as established pipeline processing (e.g., Freesurfer for extraction of scalar measures from magnetic resonance images). Furthermore, via theHiveDB activity system algorithm developers may grant access to virtual machines hosting versioned releases of their tools to collaborators and the imaging community. The application of theHiveDB is illustrated with a brief use case based on organizing, processing, and analyzing data from the publically available Alzheimer Disease Neuroimaging Initiative.

TheHiveDB image data management and analysis framework

PubMed Central

Muehlboeck, J-Sebastian; Westman, Eric; Simmons, Andrew

2014-01-01

The hive database system (theHiveDB) is a web-based brain imaging database, collaboration, and activity system which has been designed as an imaging workflow management system capable of handling cross-sectional and longitudinal multi-center studies. It can be used to organize and integrate existing data from heterogeneous projects as well as data from ongoing studies. It has been conceived to guide and assist the researcher throughout the entire research process, integrating all relevant types of data across modalities (e.g., brain imaging, clinical, and genetic data). TheHiveDB is a modern activity and resource management system capable of scheduling image processing on both private compute resources and the cloud. The activity component supports common image archival and management tasks as well as established pipeline processing (e.g., Freesurfer for extraction of scalar measures from magnetic resonance images). Furthermore, via theHiveDB activity system algorithm developers may grant access to virtual machines hosting versioned releases of their tools to collaborators and the imaging community. The application of theHiveDB is illustrated with a brief use case based on organizing, processing, and analyzing data from the publically available Alzheimer Disease Neuroimaging Initiative. PMID:24432000

Hybrid PET/MR imaging: physics and technical considerations.

PubMed

Shah, Shetal N; Huang, Steve S

2015-08-01

In just over a decade, hybrid imaging with FDG PET/CT has become a standard bearer in the management of cancer patients. An exquisitely sensitive whole-body imaging modality, it combines the ability to detect subtle biologic changes with FDG PET and the anatomic information offered by CT scans. With advances in MR technology and advent of novel targeted PET radiotracers, hybrid PET/MRI is an evolutionary technique that is poised to revolutionize hybrid imaging. It offers unparalleled spatial resolution and functional multi-parametric data combined with biologic information in the non-invasive detection and characterization of diseases, without the deleterious effects of ionizing radiation. This article reviews the basic principles of FDG PET and MR imaging, discusses the salient technical developments of hybrid PET/MR systems, and provides an introduction to FDG PET/MR image acquisition.

X-ray cargo container inspection system with few-view projection imaging

NASA Astrophysics Data System (ADS)

Duan, Xinhui; Cheng, Jianping; Zhang, Li; Xing, Yuxiang; Chen, Zhiqiang; Zhao, Ziran

2009-01-01

An X-ray cargo inspection system with few-view projection imaging is developed for detecting contraband in air containers. This paper describes this developing inspection system, including its configuration and the process of inspection using three imaging modalities: digital radiography (DR), few view imaging and computed tomography (CT). The few-view imaging can provide 3D images with much faster scanning speed than CT and do great help to quickly locate suspicious cargo in a container. An algorithm to reconstruct tomographic images from severely sparse projection data of few-view imaging is discussed. A cooperative work manner of the three modalities is presented to make the inspection more convenient and effective. Numerous experiments of performance tests and modality comparison are performed on our system for inspecting air containers. Results demonstrate the effectiveness of our methods and implementation of few-view imaging in practical inspection systems.

Example based lesion segmentation

NASA Astrophysics Data System (ADS)

Roy, Snehashis; He, Qing; Carass, Aaron; Jog, Amod; Cuzzocreo, Jennifer L.; Reich, Daniel S.; Prince, Jerry; Pham, Dzung

2014-03-01

Automatic and accurate detection of white matter lesions is a significant step toward understanding the progression of many diseases, like Alzheimer's disease or multiple sclerosis. Multi-modal MR images are often used to segment T2 white matter lesions that can represent regions of demyelination or ischemia. Some automated lesion segmentation methods describe the lesion intensities using generative models, and then classify the lesions with some combination of heuristics and cost minimization. In contrast, we propose a patch-based method, in which lesions are found using examples from an atlas containing multi-modal MR images and corresponding manual delineations of lesions. Patches from subject MR images are matched to patches from the atlas and lesion memberships are found based on patch similarity weights. We experiment on 43 subjects with MS, whose scans show various levels of lesion-load. We demonstrate significant improvement in Dice coefficient and total lesion volume compared to a state of the art model-based lesion segmentation method, indicating more accurate delineation of lesions.

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Multi-modality imaging: Bird's eye view from the 2017 American Heart Association Scientific Sessions.

PubMed

AlJaroudi, Wael A; Lloyd, Steven G; Hage, Fadi G

2018-04-01

This review summarizes key imaging studies that were presented in the American Heart Association Scientific Sessions 2017 related to the fields of nuclear cardiology, cardiac computed tomography, cardiac magnetic resonance, and echocardiography. The aim of this bird's eye view is to inform readers about multiple studies reported at the meeting from these different imaging modalities. While such a review is most useful for those that did not attend the conference, we find that a general overview may also be useful to those that did since it is often difficult to get exposure to many abstracts at large meetings. The review, therefore, aims to help readers stay updated on the newest imaging studies presented at the meeting and will hopefully stimulate new ideas for future research in imaging.

Simultaneous functional photoacoustic and ultrasonic endoscopy of internal organs in vivo

PubMed Central

Yang, Joon-Mo; Favazza, Christopher; Chen, Ruimin; Yao, Junjie; Cai, Xin; Maslov, Konstantin; Zhou, Qifa; Shung, K. Kirk; Wang, Lihong V.

2013-01-01

Presently, clinicians routinely apply ultrasound endoscopy in a variety of interventional procedures which provide treatment solutions for diseased organs. Ultrasound endoscopy not only produces high resolution images, it is also safe for clinical use and broadly applicable. However, for soft tissue imaging, its mechanical wave-based image contrast fundamentally limits its ability to provide physiologically-specific functional information. By contrast, photoacoustic endoscopy possesses a unique combination of functional optical contrast and high spatial resolution at clinically-relevant depths, ideal for soft tissue imaging. With these attributes, photoacoustic endoscopy can overcome the current limitations of ultrasound endoscopy. Moreover, the benefits of photoacoustic imaging do not come at the expense of existing ultrasound functions; photoacoustic endoscopy systems are inherently compatible with ultrasound imaging, enabling multi-modality imaging with complementary contrast. Here, we present simultaneous photoacoustic and ultrasonic dual-mode endoscopy and demonstrate its ability to image internal organs in vivo, illustrating its potential clinical application. PMID:22797808

Development of a new multi-modal Monte-Carlo radiotherapy planning system.

PubMed

Kumada, H; Nakamura, T; Komeda, M; Matsumura, A

2009-07-01

A new multi-modal Monte-Carlo radiotherapy planning system (developing code: JCDS-FX) is under development at Japan Atomic Energy Agency. This system builds on fundamental technologies of JCDS applied to actual boron neutron capture therapy (BNCT) trials in JRR-4. One of features of the JCDS-FX is that PHITS has been applied to particle transport calculation. PHITS is a multi-purpose particle Monte-Carlo transport code. Hence application of PHITS enables to evaluate total doses given to a patient by a combined modality therapy. Moreover, JCDS-FX with PHITS can be used for the study of accelerator based BNCT. To verify calculation accuracy of the JCDS-FX, dose evaluations for neutron irradiation of a cylindrical water phantom and for an actual clinical trial were performed, then the results were compared with calculations by JCDS with MCNP. The verification results demonstrated that JCDS-FX is applicable to BNCT treatment planning in practical use.

Success of HIS DICOM interfaces in the integration of the healthcare enterprise at the Department of Veterans Affairs

NASA Astrophysics Data System (ADS)

Kuzmak, Peter M.; Dayhoff, Ruth E.

1999-07-01

The US Department of Veterans Affairs (VA) is integrating imaging into the healthcare enterprise using the Digital Imaging and Communication in Medicine (DICOM) standard protocols. Image management is directly integrated into the VistA Hospital Information System (HIS) software and the clinical database. Radiology images are acquired via DICOM, and are stored directly in the HIS database. Images can be displayed on low-cost clinician's workstations throughout the medical center. High-resolution diagnostic quality multi-monitor VistA workstations with specialized viewing software can be used for reading radiology images. Two approaches are used to acquire and handle imags within the radiology department. Some sties have a commercial Picture Archiving and Communications System (PACS) interfaced to the VistA HIS, while other sites use the direct image acquisition and integrated diagnostic reading capabilities of VistA itself. A small set of DICOM services have been implemented by VistA to allow patient and study text data to be transmitted to image producing modalities and the commercial PACS, and to enable images and study data to be transferred back. The VistA DICOM capabilities are now used to interface seven different commercial PACS products and over twenty different radiology modalities. The communications capabilities of DICOM and the VA wide area network are begin used to support reading of radiology images form remote sites. DICOM has been the cornerstone in the ability to integrate imaging functionality into the Healthcare Enterprise. Because of its openness, it allows the integration of system component from commercial and non- commercial sources to work together to provide functional cost-effective solutions. As DICOM expands to non-radiology devices, integration must occur with the specialty information subsystems that handle orders and reports, their associated DICOM image capture systems, and the computer- based patient record. The mode and concepts of the DICOM standard can be extended to these other areas, but some adjustments may be required.

Human fatigue expression recognition through image-based dynamic multi-information and bimodal deep learning

NASA Astrophysics Data System (ADS)

Zhao, Lei; Wang, Zengcai; Wang, Xiaojin; Qi, Yazhou; Liu, Qing; Zhang, Guoxin

2016-09-01

Human fatigue is an important cause of traffic accidents. To improve the safety of transportation, we propose, in this paper, a framework for fatigue expression recognition using image-based facial dynamic multi-information and a bimodal deep neural network. First, the landmark of face region and the texture of eye region, which complement each other in fatigue expression recognition, are extracted from facial image sequences captured by a single camera. Then, two stacked autoencoder neural networks are trained for landmark and texture, respectively. Finally, the two trained neural networks are combined by learning a joint layer on top of them to construct a bimodal deep neural network. The model can be used to extract a unified representation that fuses landmark and texture modalities together and classify fatigue expressions accurately. The proposed system is tested on a human fatigue dataset obtained from an actual driving environment. The experimental results demonstrate that the proposed method performs stably and robustly, and that the average accuracy achieves 96.2%.

Multi-scale volumetric cell and tissue imaging based on optical projection tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ban, Sungbea; Cho, Nam Hyun; Ryu, Yongjae; Jung, Sunwoo; Vavilin, Andrey; Min, Eunjung; Jung, Woonggyu

2016-04-01

Optical projection tomography is a new optical imaging method for visualizing small biological specimens in three dimension. The most important advantage of OPT is to fill the gap between MRI and confocal microscope for the specimen having the range of 1-10 mm. Thus, it has been mainly used for whole-mount small animals and developmental study since this imaging modality was developed. The ability of OPT delivering anatomical and functional information of relatively large tissue in 3D has made it a promising platform in biomedical research. Recently, the potential of OPT spans its coverage to cellular scale. Even though there are increasing demand to obtain better understanding of cellular dynamics, only few studies to visualize cellular structure, shape, size and functional morphology over tissue has been investigated in existing OPT system due to its limited field of view. In this study, we develop a novel optical imaging system for 3D cellular imaging with OPT integrated with dynamic focusing technique. Our tomographic setup has great potential to be used for identifying cell characteristic in tissue because it can provide selective contrast on dynamic focal plane allowing for fluorescence as well as absorption. While the dominant contrast of optical imaging technique is to use the fluorescence for detecting certain target only, the newly developed OPT system will offer considerable advantages over currently available method when imaging cellar molecular dynamics by permitting contrast variation. By achieving multi-contrast, it is expected for this new imaging system to play an important role in delivering better cytological information to pathologist.

State-of-the-art radiation detectors for medical imaging: Demands and trends

NASA Astrophysics Data System (ADS)

Darambara, Dimitra G.

2006-12-01

Over the last half-century a variety of significant technical advances in several scientific fields has been pointing to an exploding growth in the field of medical imaging leading to a better interpretation of more specific anatomical, biochemical and molecular pathways. In particular, the development of novel imaging detectors and readout electronics has been critical to the advancement of medical imaging allowing the invention of breakthrough platforms for simultaneous acquisition of multi-modality images at molecular level. The present paper presents a review of the challenges, demands and constraints on radiation imaging detectors imposed by the nature of the modality and the physics of the imaging source. This is followed by a concise review and perspective on various types of state-of-the-art detector technologies that have been developed to meet these requirements. Trends, prospects and new concepts for future imaging detectors are also highlighted.

Fused oblique incidence reflectometry and confocal fluorescence microscopy

NASA Astrophysics Data System (ADS)

Risi, Matthew D.; Rouse, Andrew R.; Gmitro, Arthur F.

2011-03-01

Confocal microendoscopy provides real-time high resolution cellular level images via a minimally invasive procedure, but relies on exogenous fluorophores, has a relatively limited penetration depth (100 μm) and field of view (700 μm), and produces a high rate of detailed information to the user. A new catheter based multi-modal system has been designed that combines confocal imaging and oblique incidence reflectometry (OIR), which is a non-invasive method capable of rapidly extracting tissue absorption, μa, and reduced scattering, μ's, spectra from tissue. The system builds on previous developments of a custom slit-scan multi-spectral confocal microendoscope and is designed to rapidly switch between diffuse spectroscopy and confocal fluorescence imaging modes of operation. An experimental proof-of-principle catheter has been developed that consists of a fiber bundle for traditional confocal fluorescence imaging and a single OIR source fiber which is manually redirected at +/- 26 degrees. Diffusely scattered light from each orientation of the source fiber is collected via the fiber bundle, with a frame of data representing spectra collected at a range of distances from the OIR source point. Initial results with intralipid phantoms show good agreement to published data over the 550-650 nm spectral range. We successfully imaged and measured the optical properties of rodent cardiac muscle.

Imaging findings in a case of Gorlin-Goltz syndrome: a survey using advanced modalities.

PubMed

Bronoosh, Pegah; Shakibafar, Ali Reza; Houshyar, Maneli; Nafarzade, Shima

2011-12-01

Gorlin-Goltz syndrome is an infrequent multi-systemic disease which is characterized by multiple keratocysts in the jaws, calcification of falx cerebri, and basal cell carcinomas. We report a case of Gorlin-Goltz syndrome in a 23-year-old man with emphasis on image findings of keratocyctic odontogenic tumors (KCOTs) on panoramic radiograph, computed tomography, magnetic resonance (MR) imaging, and Ultrasonography (US). In this case, pericoronal lesions were mostly orthokeratinized odontogenic cyst (OOC) concerning the MR and US study, which tended to recur less. The aim of this report was to clarify the characteristic imaging features of the syndrome-related keratocysts that can be used to differentiate KCOT from OOC. Also, our findings suggested that the recurrence rate of KCOTs might be predicted based on their association to teeth.

MO-E-12A-01: Quantitative Imaging: Techniques, Applications, and Challenges

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

Jackson, E; Jeraj, R; McNitt-Gray, M

The first symposium in the Quantitative Imaging Track focused on the introduction of quantitative imaging (QI) by illustrating the potential of QI in diagnostic and therapeutic applications in research and patient care, highlighting key challenges in implementation of such QI applications, and reviewing QI efforts of selected national and international agencies and organizations, including the FDA, NCI, NIST, and RSNA. This second QI symposium will focus more specifically on the techniques, applications, and challenges of QI. The first talk of the session will focus on modalityagnostic challenges of QI, beginning with challenges of the development and implementation of QI applicationsmore » in single-center, single-vendor settings and progressing to the challenges encountered in the most general setting of multi-center, multi-vendor settings. The subsequent three talks will focus on specific QI challenges and opportunities in the modalityspecific settings of CT, PET/CT, and MR. Each talk will provide information on modality-specific QI techniques, applications, and challenges, including current efforts focused on solutions to such challenges. Learning Objectives: Understand key general challenges of QI application development and implementation, regardless of modality. Understand selected QI techniques and applications in CT, PET/CT, and MR. Understand challenges, and potential solutions for such challenges, for the applications presented for each modality.« less

Residual Shuffling Convolutional Neural Networks for Deep Semantic Image Segmentation Using Multi-Modal Data

NASA Astrophysics Data System (ADS)

Chen, K.; Weinmann, M.; Gao, X.; Yan, M.; Hinz, S.; Jutzi, B.; Weinmann, M.

2018-05-01

In this paper, we address the deep semantic segmentation of aerial imagery based on multi-modal data. Given multi-modal data composed of true orthophotos and the corresponding Digital Surface Models (DSMs), we extract a variety of hand-crafted radiometric and geometric features which are provided separately and in different combinations as input to a modern deep learning framework. The latter is represented by a Residual Shuffling Convolutional Neural Network (RSCNN) combining the characteristics of a Residual Network with the advantages of atrous convolution and a shuffling operator to achieve a dense semantic labeling. Via performance evaluation on a benchmark dataset, we analyze the value of different feature sets for the semantic segmentation task. The derived results reveal that the use of radiometric features yields better classification results than the use of geometric features for the considered dataset. Furthermore, the consideration of data on both modalities leads to an improvement of the classification results. However, the derived results also indicate that the use of all defined features is less favorable than the use of selected features. Consequently, data representations derived via feature extraction and feature selection techniques still provide a gain if used as the basis for deep semantic segmentation.

RadMAP: The Radiological Multi-sensor Analysis Platform

NASA Astrophysics Data System (ADS)

Bandstra, Mark S.; Aucott, Timothy J.; Brubaker, Erik; Chivers, Daniel H.; Cooper, Reynold J.; Curtis, Joseph C.; Davis, John R.; Joshi, Tenzing H.; Kua, John; Meyer, Ross; Negut, Victor; Quinlan, Michael; Quiter, Brian J.; Srinivasan, Shreyas; Zakhor, Avideh; Zhang, Richard; Vetter, Kai

2016-12-01

The variability of gamma-ray and neutron background during the operation of a mobile detector system greatly limits the ability of the system to detect weak radiological and nuclear threats. The natural radiation background measured by a mobile detector system is the result of many factors, including the radioactivity of nearby materials, the geometric configuration of those materials and the system, the presence of absorbing materials, and atmospheric conditions. Background variations tend to be highly non-Poissonian, making it difficult to set robust detection thresholds using knowledge of the mean background rate alone. The Radiological Multi-sensor Analysis Platform (RadMAP) system is designed to allow the systematic study of natural radiological background variations and to serve as a development platform for emerging concepts in mobile radiation detection and imaging. To do this, RadMAP has been used to acquire extensive, systematic background measurements and correlated contextual data that can be used to test algorithms and detector modalities at low false alarm rates. By combining gamma-ray and neutron detector systems with data from contextual sensors, the system enables the fusion of data from multiple sensors into novel data products. The data are curated in a common format that allows for rapid querying across all sensors, creating detailed multi-sensor datasets that are used to study correlations between radiological and contextual data, and develop and test novel techniques in mobile detection and imaging. In this paper we will describe the instruments that comprise the RadMAP system, the effort to curate and provide access to multi-sensor data, and some initial results on the fusion of contextual and radiological data.

A virtual surgical environment for rehearsal of tympanomastoidectomy.

PubMed

Chan, Sonny; Li, Peter; Lee, Dong Hoon; Salisbury, J Kenneth; Blevins, Nikolas H

2011-01-01

This article presents a virtual surgical environment whose purpose is to assist the surgeon in preparation for individual cases. The system constructs interactive anatomical models from patient-specific, multi-modal preoperative image data, and incorporates new methods for visually and haptically rendering the volumetric data. Evaluation of the system's ability to replicate temporal bone dissections for tympanomastoidectomy, using intraoperative video of the same patients as guides, showed strong correlations between virtual and intraoperative anatomy. The result is a portable and cost-effective tool that may prove highly beneficial for the purposes of surgical planning and rehearsal.

A high-speed network for cardiac image review.

PubMed

Elion, J L; Petrocelli, R R

1994-01-01

A high-speed fiber-based network for the transmission and display of digitized full-motion cardiac images has been developed. Based on Asynchronous Transfer Mode (ATM), the network is scaleable, meaning that the same software and hardware is used for a small local area network or for a large multi-institutional network. The system can handle uncompressed digital angiographic images, considered to be at the "high-end" of the bandwidth requirements. Along with the networking, a general-purpose multi-modality review station has been implemented without specialized hardware. This station can store a full injection sequence in "loop RAM" in a 512 x 512 format, then interpolate to 1024 x 1024 while displaying at 30 frames per second. The network and review stations connect to a central file server that uses a virtual file system to make a large high-speed RAID storage disk and associated off-line storage tapes and cartridges all appear as a single large file system to the software. In addition to supporting archival storage and review, the system can also digitize live video using high-speed Direct Memory Access (DMA) from the frame grabber to present uncompressed data to the network. Fully functional prototypes have provided the proof of concept, with full deployment in the institution planned as the next stage.

A high-speed network for cardiac image review.

PubMed Central

Elion, J. L.; Petrocelli, R. R.

1994-01-01

A high-speed fiber-based network for the transmission and display of digitized full-motion cardiac images has been developed. Based on Asynchronous Transfer Mode (ATM), the network is scaleable, meaning that the same software and hardware is used for a small local area network or for a large multi-institutional network. The system can handle uncompressed digital angiographic images, considered to be at the "high-end" of the bandwidth requirements. Along with the networking, a general-purpose multi-modality review station has been implemented without specialized hardware. This station can store a full injection sequence in "loop RAM" in a 512 x 512 format, then interpolate to 1024 x 1024 while displaying at 30 frames per second. The network and review stations connect to a central file server that uses a virtual file system to make a large high-speed RAID storage disk and associated off-line storage tapes and cartridges all appear as a single large file system to the software. In addition to supporting archival storage and review, the system can also digitize live video using high-speed Direct Memory Access (DMA) from the frame grabber to present uncompressed data to the network. Fully functional prototypes have provided the proof of concept, with full deployment in the institution planned as the next stage. PMID:7949964

Real-time dynamic display of registered 4D cardiac MR and ultrasound images using a GPU

NASA Astrophysics Data System (ADS)

Zhang, Q.; Huang, X.; Eagleson, R.; Guiraudon, G.; Peters, T. M.

2007-03-01

In minimally invasive image-guided surgical interventions, different imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and real-time three-dimensional (3D) ultrasound (US), can provide complementary, multi-spectral image information. Multimodality dynamic image registration is a well-established approach that permits real-time diagnostic information to be enhanced by placing lower-quality real-time images within a high quality anatomical context. For the guidance of cardiac procedures, it would be valuable to register dynamic MRI or CT with intraoperative US. However, in practice, either the high computational cost prohibits such real-time visualization of volumetric multimodal images in a real-world medical environment, or else the resulting image quality is not satisfactory for accurate guidance during the intervention. Modern graphics processing units (GPUs) provide the programmability, parallelism and increased computational precision to begin to address this problem. In this work, we first outline our research on dynamic 3D cardiac MR and US image acquisition, real-time dual-modality registration and US tracking. Then we describe image processing and optimization techniques for 4D (3D + time) cardiac image real-time rendering. We also present our multimodality 4D medical image visualization engine, which directly runs on a GPU in real-time by exploiting the advantages of the graphics hardware. In addition, techniques such as multiple transfer functions for different imaging modalities, dynamic texture binding, advanced texture sampling and multimodality image compositing are employed to facilitate the real-time display and manipulation of the registered dual-modality dynamic 3D MR and US cardiac datasets.

Integration of Sparse Multi-modality Representation and Geometrical Constraint for Isointense Infant Brain Segmentation

PubMed Central

Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H.; Shen, Dinggang

2014-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6–8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a novel segmentation method to address the above-mentioned challenge based on the sparse representation of the complementary tissue distribution information from T1, T2 and diffusion-weighted images. Specifically, we first derive an initial segmentation from a library of aligned multi-modality images with ground-truth segmentations by using sparse representation in a patch-based fashion. The segmentation is further refined by the integration of the geometrical constraint information. The proposed method was evaluated on 22 6-month-old training subjects using leave-one-out cross-validation, as well as 10 additional infant testing subjects, showing superior results in comparison to other state-of-the-art methods. PMID:24505729

Integration of sparse multi-modality representation and geometrical constraint for isointense infant brain segmentation.

PubMed

Wang, Li; Shi, Feng; Li, Gang; Lin, Weili; Gilmore, John H; Shen, Dinggang

2013-01-01

Segmentation of infant brain MR images is challenging due to insufficient image quality, severe partial volume effect, and ongoing maturation and myelination process. During the first year of life, the signal contrast between white matter (WM) and gray matter (GM) in MR images undergoes inverse changes. In particular, the inversion of WM/GM signal contrast appears around 6-8 months of age, where brain tissues appear isointense and hence exhibit extremely low tissue contrast, posing significant challenges for automated segmentation. In this paper, we propose a novel segmentation method to address the above-mentioned challenge based on the sparse representation of the complementary tissue distribution information from T1, T2 and diffusion-weighted images. Specifically, we first derive an initial segmentation from a library of aligned multi-modality images with ground-truth segmentations by using sparse representation in a patch-based fashion. The segmentation is further refined by the integration of the geometrical constraint information. The proposed method was evaluated on 22 6-month-old training subjects using leave-one-out cross-validation, as well as 10 additional infant testing subjects, showing superior results in comparison to other state-of-the-art methods.

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

Larner, J.

In this interactive session, lung SBRT patient cases will be presented to highlight real-world considerations for ensuring safe and accurate treatment delivery. An expert panel of speakers will discuss challenges specific to lung SBRT including patient selection, patient immobilization techniques, 4D CT simulation and respiratory motion management, target delineation for treatment planning, online treatment alignment, and established prescription regimens and OAR dose limits. Practical examples of cases, including the patient flow thought the clinical process are presented and audience participation will be encouraged. This panel session is designed to provide case demonstration and review for lung SBRT in terms ofmore » (1) clinical appropriateness in patient selection, (2) strategies for simulation, including 4D and respiratory motion management, and (3) applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent, and (4) image guidance in treatment delivery. Learning Objectives: Understand the established requirements for patient selection in lung SBRT Become familiar with the various immobilization strategies for lung SBRT, including technology for respiratory motion management Understand the benefits and pitfalls of applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent determination for lung SBRT Understand established prescription regimes and OAR dose limits.« less

Failure Analysis of a Complex Learning Framework Incorporating Multi-Modal and Semi-Supervised Learning

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

Pullum, Laura L; Symons, Christopher T

2011-01-01

Machine learning is used in many applications, from machine vision to speech recognition to decision support systems, and is used to test applications. However, though much has been done to evaluate the performance of machine learning algorithms, little has been done to verify the algorithms or examine their failure modes. Moreover, complex learning frameworks often require stepping beyond black box evaluation to distinguish between errors based on natural limits on learning and errors that arise from mistakes in implementation. We present a conceptual architecture, failure model and taxonomy, and failure modes and effects analysis (FMEA) of a semi-supervised, multi-modal learningmore » system, and provide specific examples from its use in a radiological analysis assistant system. The goal of the research described in this paper is to provide a foundation from which dependability analysis of systems using semi-supervised, multi-modal learning can be conducted. The methods presented provide a first step towards that overall goal.« less

Multiscale multimodal fusion of histological and MRI volumes for characterization of lung inflammation

NASA Astrophysics Data System (ADS)

Rusu, Mirabela; Wang, Haibo; Golden, Thea; Gow, Andrew; Madabhushi, Anant

2013-03-01

Mouse lung models facilitate the investigation of conditions such as chronic inflammation which are associated with common lung diseases. The multi-scale manifestation of lung inflammation prompted us to use multi-scale imaging - both in vivo, ex vivo MRI along with ex vivo histology, for its study in a new quantitative way. Some imaging modalities, such as MRI, are non-invasive and capture macroscopic features of the pathology, while others, e.g. ex vivo histology, depict detailed structures. Registering such multi-modal data to the same spatial coordinates will allow the construction of a comprehensive 3D model to enable the multi-scale study of diseases. Moreover, it may facilitate the identification and definition of quantitative of in vivo imaging signatures for diseases and pathologic processes. We introduce a quantitative, image analytic framework to integrate in vivo MR images of the entire mouse with ex vivo histology of the lung alone, using lung ex vivo MRI as conduit to facilitate their co-registration. In our framework, we first align the MR images by registering the in vivo and ex vivo MRI of the lung using an interactive rigid registration approach. Then we reconstruct the 3D volume of the ex vivo histological specimen by efficient group wise registration of the 2D slices. The resulting 3D histologic volume is subsequently registered to the MRI volumes by interactive rigid registration, directly to the ex vivo MRI, and implicitly to in vivo MRI. Qualitative evaluation of the registration framework was performed by comparing airway tree structures in ex vivo MRI and ex vivo histology where airways are visible and may be annotated. We present a use case for evaluation of our co-registration framework in the context of studying chronic inammation in a diseased mouse.

Computer-aided-diagnosis (CAD) for colposcopy

NASA Astrophysics Data System (ADS)

Lange, Holger; Ferris, Daron G.

2005-04-01

Uterine cervical cancer is the second most common cancer among women worldwide. Colposcopy is a diagnostic method, whereby a physician (colposcopist) visually inspects the lower genital tract (cervix, vulva and vagina), with special emphasis on the subjective appearance of metaplastic epithelium comprising the transformation zone on the cervix. Cervical cancer precursor lesions and invasive cancer exhibit certain distinctly abnormal morphologic features. Lesion characteristics such as margin; color or opacity; blood vessel caliber, intercapillary spacing and distribution; and contour are considered by colposcopists to derive a clinical diagnosis. Clinicians and academia have suggested and shown proof of concept that automated image analysis of cervical imagery can be used for cervical cancer screening and diagnosis, having the potential to have a direct impact on improving women"s health care and reducing associated costs. STI Medical Systems is developing a Computer-Aided-Diagnosis (CAD) system for colposcopy -- ColpoCAD. At the heart of ColpoCAD is a complex multi-sensor, multi-data and multi-feature image analysis system. A functional description is presented of the envisioned ColpoCAD system, broken down into: Modality Data Management System, Image Enhancement, Feature Extraction, Reference Database, and Diagnosis and directed Biopsies. The system design and development process of the image analysis system is outlined. The system design provides a modular and open architecture built on feature based processing. The core feature set includes the visual features used by colposcopists. This feature set can be extended to include new features introduced by new instrument technologies, like fluorescence and impedance, and any other plausible feature that can be extracted from the cervical data. Preliminary results of our research on detecting the three most important features: blood vessel structures, acetowhite regions and lesion margins are shown. As this is a new and very complex field in medical image processing, the hope is that this paper can provide a framework and basis to encourage and facilitate collaboration and discussion between industry, academia, and medical practitioners.

A framework for optimizing micro-CT in dual-modality micro-CT/XFCT small-animal imaging system

NASA Astrophysics Data System (ADS)

Vedantham, Srinivasan; Shrestha, Suman; Karellas, Andrew; Cho, Sang Hyun

2017-09-01

Dual-modality Computed Tomography (CT)/X-ray Fluorescence Computed Tomography (XFCT) can be a valuable tool for imaging and quantifying the organ and tissue distribution of small concentrations of high atomic number materials in small-animal system. In this work, the framework for optimizing the micro-CT imaging system component of the dual-modality system is described, either when the micro-CT images are concurrently acquired with XFCT and using the x-ray spectral conditions for XFCT, or when the micro-CT images are acquired sequentially and independently of XFCT. This framework utilizes the cascaded systems analysis for task-specific determination of the detectability index using numerical observer models at a given radiation dose, where the radiation dose is determined using Monte Carlo simulations.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Energy Logic (EL): a novel fusion engine of multi-modality multi-agent data/information fusion for intelligent surveillance systems

NASA Astrophysics Data System (ADS)

Rababaah, Haroun; Shirkhodaie, Amir

2009-04-01

The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.

Whole mouse cryo-imaging

NASA Astrophysics Data System (ADS)

Wilson, David; Roy, Debashish; Steyer, Grant; Gargesha, Madhusudhana; Stone, Meredith; McKinley, Eliot

2008-03-01

The Case cryo-imaging system is a section and image system which allows one to acquire micron-scale, information rich, whole mouse color bright field and molecular fluorescence images of an entire mouse. Cryo-imaging is used in a variety of applications, including mouse and embryo anatomical phenotyping, drug delivery, imaging agents, metastastic cancer, stem cells, and very high resolution vascular imaging, among many. Cryo-imaging fills the gap between whole animal in vivo imaging and histology, allowing one to image a mouse along the continuum from the mouse -> organ -> tissue structure -> cell -> sub-cellular domains. In this overview, we describe the technology and a variety of exciting applications. Enhancements to the system now enable tiled acquisition of high resolution images to cover an entire mouse. High resolution fluorescence imaging, aided by a novel subtraction processing algorithm to remove sub-surface fluorescence, makes it possible to detect fluorescently-labeled single cells. Multi-modality experiments in Magnetic Resonance Imaging and Cryo-imaging of a whole mouse demonstrate superior resolution of cryo-images and efficiency of registration techniques. The 3D results demonstrate the novel true-color volume visualization tools we have developed and the inherent advantage of cryo-imaging in providing unlimited depth of field and spatial resolution. The recent results continue to demonstrate the value cryo-imaging provides in the field of small animal imaging research.

Simultaneous multi-scale microscopy as a potential dedicated tool for intra-operative parathyroid identification during thyroid surgery (Conference Presentation)

NASA Astrophysics Data System (ADS)

De Montigny, Étienne; Goulamhoussen, Nadir; Madore, Wendy-Julie; Strupler, Mathias; Maniakas, Anastasios; Ayad, Tareck; Boudoux, Caroline

2016-02-01

While thyroidectomy is considered a safe surgery, dedicated tools facilitating tissue identification during surgery could improve its outcome. The most common complication following surgery is hypocalcaemia, which results from iatrogenic removal or damage to parathyroid glands. This research project aims at developing and validating an instrument based on optical microscopy modalities to identify tissues in real time during surgery. Our approach is based on a combination of reflectance confocal microscopy (RCM) and optical coherence tomography (OCT) to obtain multi-scale morphological contrast images. The orthogonal field of views provide information to navigate through the sample. To allow simultaneous, synchronized video-rate imaging in both modalities, we designed and built a dual-band wavelength-swept laser which scans a 30 nm band centered at 780 nm and a 90 nm band centered at 1310 nm. We built an imaging setup integrating a custom-made objective lens and a double-clad fibre coupler optimized for confocal microscopy. It features high resolutions in RCM (2µm lateral and 20 µm axial) in a 500 µm x 500 µm field-of-view and a larger field-of-view of 2 mm (lateral) x 5 mm (axial) with 20 µm lateral and axial resolutions in OCT. Imaging of ex vivo animal samples is demonstrated on a bench-top system. Tissues that are visually difficult to distinguish from each other intra-operatively such as parathyroid gland, lymph nodes and adipose tissue are imaged to show the potential of this approach in differentiating neck tissues. We will also provide an update on our ongoing clinical pilot study on patients undergoing thyroidectomy.

Identification of Amnestic Mild Cognitive Impairment Using Multi-Modal Brain Features: A Combined Structural MRI and Diffusion Tensor Imaging Study.

PubMed

Xie, Yunyan; Cui, Zaixu; Zhang, Zhongmin; Sun, Yu; Sheng, Can; Li, Kuncheng; Gong, Gaolang; Han, Ying; Jia, Jianping

2015-01-01

Identifying amnestic mild cognitive impairment (aMCI) is of great clinical importance because aMCI is a putative prodromal stage of Alzheimer's disease. The present study aimed to explore the feasibility of accurately identifying aMCI with a magnetic resonance imaging (MRI) biomarker. We integrated measures of both gray matter (GM) abnormalities derived from structural MRI and white matter (WM) alterations acquired from diffusion tensor imaging at the voxel level across the entire brain. In particular, multi-modal brain features, including GM volume, WM fractional anisotropy, and mean diffusivity, were extracted from a relatively large sample of 64 Han Chinese aMCI patients and 64 matched controls. Then, support vector machine classifiers for GM volume, FA, and MD were fused to distinguish the aMCI patients from the controls. The fused classifier was evaluated with the leave-one-out and the 10-fold cross-validations, and the classifier had an accuracy of 83.59% and an area under the curve of 0.862. The most discriminative regions of GM were mainly located in the medial temporal lobe, temporal lobe, precuneus, cingulate gyrus, parietal lobe, and frontal lobe, whereas the most discriminative regions of WM were mainly located in the corpus callosum, cingulum, corona radiata, frontal lobe, and parietal lobe. Our findings suggest that aMCI is characterized by a distributed pattern of GM abnormalities and WM alterations that represent discriminative power and reflect relevant pathological changes in the brain, and these changes further highlight the advantage of multi-modal feature integration for identifying aMCI.

Hand hygiene and healthcare system change within multi-modal promotion: a narrative review.

PubMed

Allegranzi, B; Sax, H; Pittet, D

2013-02-01

Many factors may influence the level of compliance with hand hygiene recommendations by healthcare workers. Lack of products and facilities as well as their inappropriate and non-ergonomic location represent important barriers. Targeted actions aimed at making hand hygiene practices feasible during healthcare delivery by ensuring that the necessary infrastructure is in place, defined as 'system change', are essential to improve hand hygiene in healthcare. In particular, access to alcohol-based hand rubs (AHRs) enables appropriate and timely hand hygiene performance at the point of care. The feasibility and impact of system change within multi-modal strategies have been demonstrated both at institutional level and on a large scale. The introduction of AHRs overcomes some important barriers to best hand hygiene practices and is associated with higher compliance, especially when integrated within multi-modal strategies. Several studies demonstrated the association between AHR consumption and reduction in healthcare-associated infection, in particular, meticillin-resistant Staphylococcus aureus bacteraemia. Recent reports demonstrate the feasibility and success of system change implementation on a large scale. The World Health Organization and other investigators have reported the challenges and encouraging results of implementing hand hygiene improvement strategies, including AHR introduction, in settings with limited resources. This review summarizes the available evidence demonstrating the need for system change and its importance within multi-modal hand hygiene improvement strategies. This topic is also discussed in a global perspective and highlights some controversial issues. Copyright © 2013 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Anatomical and metabolic small-animal whole-body imaging using ring-shaped confocal photoacoustic computed tomography

NASA Astrophysics Data System (ADS)

Xia, Jun; Chatni, Muhammad; Maslov, Konstantin; Wang, Lihong V.

2013-03-01

Due to the wide use of animals for human disease studies, small animal whole-body imaging plays an increasingly important role in biomedical research. Currently, none of the existing imaging modalities can provide both anatomical and glucose metabolic information, leading to higher costs of building dual-modality systems. Even with image coregistration, the spatial resolution of the metabolic imaging modality is not improved. We present a ring-shaped confocal photoacoustic computed tomography (RC-PACT) system that can provide both assessments in a single modality. Utilizing the novel design of confocal full-ring light delivery and ultrasound transducer array detection, RC-PACT provides full-view cross-sectional imaging with high spatial resolution. Scanning along the orthogonal direction provides three-dimensional imaging. While the mouse anatomy was imaged with endogenous hemoglobin contrast, the glucose metabolism was imaged with a near-infrared dye-labeled 2-deoxyglucose. Through mouse tumor models, we demonstrate that RC-PACT may be a paradigm shifting imaging method for preclinical research.

A novel phoswich imaging detector for simultaneous beta and coincidence-gamma imaging of plant leaves.

PubMed

Wu, Heyu; Tai, Yuan-Chuan

2011-09-07

To meet the growing demand for functional imaging technology for use in studying plant biology, we are developing a novel technique that permits simultaneous imaging of escaped positrons and coincidence gammas from annihilation of positrons within an intake leaf. The multi-modality imaging system will include two planar detectors: one is a typical PET detector array and the other is a phoswich imaging detector that detects both beta and gamma. The novel phoswich detector is made of a plastic scintillator, a lutetium oxyorthosilicate (LSO) array, and a position sensitive photomultiplier tube (PS-PMT). The plastic scintillator serves as a beta detector, while the LSO array serves as a gamma detector and light guide that couples scintillation light from the plastic detector to the PMT. In our prototype, the PMT signal was fed into the Siemens QuickSilver electronics to achieve shaping and waveform sampling. Pulse-shape discrimination based on the detectors' decay times (2.1 ns for plastic and 40 ns for LSO) was used to differentiate beta and gamma events using the common PMT signals. Using our prototype phoswich detector, we simultaneously measured a beta image and gamma events (in single mode). The beta image showed a resolution of 1.6 mm full-width-at-half-maximum using F-18 line sources. Because this shows promise for plant-scale imaging, our future plans include development of a fully functional simultaneous beta-and-coincidence-gamma imager with sub-millimeter resolution imaging capability for both modalities.

Human factors evaluation of the effectiveness of multi-modality displays in advanced traveler information systems

DOT National Transportation Integrated Search

1999-12-01

To achieve the goals for Advanced Traveler Information Systems (ATIS), significant information will necessarily be provided to the driver. A primary ATIS design issue is the display modality (i.e., visual, auditory, or the combination) selected for p...

Deep Photoacoustic/Luminescence/Magnetic Resonance Multimodal Imaging in Living Subjects Using High-Efficiency Upconversion Nanocomposites.

PubMed

Liu, Yu; Kang, Ning; Lv, Jing; Zhou, Zijian; Zhao, Qingliang; Ma, Lingceng; Chen, Zhong; Ren, Lei; Nie, Liming

2016-08-01

A gadolinium-doped multi-shell upconversion nanoparticle under 800 nm excitation is synthesized with a 10-fold fluorescence-intensity enhancement over that under 980 nm. The nanoformulations exhibit excellent photoacoustic/luminescence/magnetic resonance tri-modal imaging capabilities, enabling visualization of tumor morphology and microvessel distribution at a new imaging depth. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

PubMed

Vergara, Victor M; Ulloa, Alvaro; Calhoun, Vince D; Boutte, David; Chen, Jiayu; Liu, Jingyu

2014-09-01

Multi-modal data analysis techniques, such as the Parallel Independent Component Analysis (pICA), are essential in neuroscience, medical imaging and genetic studies. The pICA algorithm allows the simultaneous decomposition of up to two data modalities achieving better performance than separate ICA decompositions and enabling the discovery of links between modalities. However, advances in data acquisition techniques facilitate the collection of more than two data modalities from each subject. Examples of commonly measured modalities include genetic information, structural magnetic resonance imaging (MRI) and functional MRI. In order to take full advantage of the available data, this work extends the pICA approach to incorporate three modalities in one comprehensive analysis. Simulations demonstrate the three-way pICA performance in identifying pairwise links between modalities and estimating independent components which more closely resemble the true sources than components found by pICA or separate ICA analyses. In addition, the three-way pICA algorithm is applied to real experimental data obtained from a study that investigate genetic effects on alcohol dependence. Considered data modalities include functional MRI (contrast images during alcohol exposure paradigm), gray matter concentration images from structural MRI and genetic single nucleotide polymorphism (SNP). The three-way pICA approach identified links between a SNP component (pointing to brain function and mental disorder associated genes, including BDNF, GRIN2B and NRG1), a functional component related to increased activation in the precuneus area, and a gray matter component comprising part of the default mode network and the caudate. Although such findings need further verification, the simulation and in-vivo results validate the three-way pICA algorithm presented here as a useful tool in biomedical data fusion applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Fully Scalable Porous Metal Electrospray Propulsion

DTIC Science & Technology

2012-03-20

particular emphasis on the variation of specific impulse for multi-modal propulsion is currently carried out by MIT and the Busek Company under an...Beam profile distributions in the negative (left) and positive (center) modes as visualized directly thorough a multi-channel plate and phosphor...screen. These profiles are parabolic (right) indicating the non-thermal character of these type of ion beams. Microscopic Image of pattern imprinted on Si

High-intensity focused ultrasound (HIFU) array system for image-guided ablative therapy (IGAT)

NASA Astrophysics Data System (ADS)

Kaczkowski, Peter J.; Keilman, George W.; Cunitz, Bryan W.; Martin, Roy W.; Vaezy, Shahram; Crum, Lawrence A.

2003-06-01

Recent interest in using High Intensity Focused Ultrasound (HIFU) for surgical applications such as hemostasis and tissue necrosis has stimulated the development of image-guided systems for non-invasive HIFU therapy. Seeking an all-ultrasound therapeutic modality, we have developed a clinical HIFU system comprising an integrated applicator that permits precisely registered HIFU therapy delivery and high quality ultrasound imaging using two separate arrays, a multi-channel signal generator and RF amplifier system, and a software program that provides the clinician with a graphical overlay of the ultrasound image and therapeutic protocol controls. Electronic phasing of a 32 element 2 MHz HIFU annular array allows adjusting the focus within the range of about 4 to 12 cm from the face. A central opening in the HIFU transducer permits mounting a commercial medical imaging scanhead (ATL P7-4) that is held in place within a special housing. This mechanical fixture ensures precise coaxial registration between the HIFU transducer and the image plane of the imaging probe. Recent enhancements include development of an acoustic lens using numerical simulations for use with a 5-element array. Our image-guided therapy system is very flexible and enables exploration of a variety of new HIFU therapy delivery and monitoring approaches in the search for safe, effective, and efficient treatment protocols.

Magnetoacoustic microscopic imaging of conductive objects and nanoparticles distribution

NASA Astrophysics Data System (ADS)

Liu, Siyu; Zhang, Ruochong; Luo, Yunqi; Zheng, Yuanjin

2017-09-01

Magnetoacoustic tomography has been demonstrated as a powerful and low-cost multi-wave imaging modality. However, due to limited spatial resolution and detection efficiency of magnetoacoustic signal, full potential of the magnetoacoustic imaging remains to be tapped. Here we report a high-resolution magnetoacoustic microscopy method, where magnetic stimulation is provided by a compact solenoid resonance coil connected with a matching network, and acoustic reception is realized by using a high-frequency focused ultrasound transducer. Scanning the magnetoacoustic microscopy system perpendicularly to the acoustic axis of the focused transducer would generate a two-dimensional microscopic image with acoustically determined lateral resolution. It is analyzed theoretically and demonstrated experimentally that magnetoacoustic generation in this microscopic system depends on the conductivity profile of conductive objects and localized distribution of superparamagnetic iron magnetic nanoparticles, based on two different but related implementations. The lateral resolution is characterized. Directional nature of magnetoacoustic vibration and imaging sensitivity for mapping magnetic nanoparticles are also discussed. The proposed microscopy system offers a high-resolution method that could potentially map intrinsic conductivity distribution in biological tissue and extraneous magnetic nanoparticles.

Abdominal Organ Location, Morphology, and Rib Coverage for the 5(th), 50(th), and 95(th) Percentile Males and Females in the Supine and Seated Posture using Multi-Modality Imaging.

PubMed

Hayes, Ashley R; Gayzik, F Scott; Moreno, Daniel P; Martin, R Shayn; Stitzel, Joel D

The purpose of this study was to use data from a multi-modality image set of males and females representing the 5(th), 50(th), and 95(th) percentile (n=6) to examine abdominal organ location, morphology, and rib coverage variations between supine and seated postures. Medical images were acquired from volunteers in three image modalities including Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and upright MRI (uMRI). A manual and semi-automated segmentation method was used to acquire data and a registration technique was employed to conduct a comparative analysis between abdominal organs (liver, spleen, and kidneys) in both postures. Location of abdominal organs, defined by center of gravity movement, varied between postures and was found to be significant (p=0.002 to p=0.04) in multiple directions for each organ. In addition, morphology changes, including compression and expansion, were seen in each organ as a result of postural changes. Rib coverage, defined as the projected area of the ribs onto the abdominal organs, was measured in frontal, lateral, and posterior projections, and also varied between postures. A significant change in rib coverage between postures was measured for the spleen and right kidney (p=0.03 and p=0.02). The results indicate that posture affects the location, morphology and rib coverage area of abdominal organs and these implications should be noted in computational modeling efforts focused on a seated posture.

Quantitative Image Informatics for Cancer Research (QIICR) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

Imaging has enormous untapped potential to improve cancer research through software to extract and process morphometric and functional biomarkers. In the era of non-cytotoxic treatment agents, multi- modality image-guided ablative therapies and rapidly evolving computational resources, quantitative imaging software can be transformative in enabling minimally invasive, objective and reproducible evaluation of cancer treatment response. Post-processing algorithms are integral to high-throughput analysis and fine- grained differentiation of multiple molecular targets.

Gamma-Ray imaging for nuclear security and safety: Towards 3-D gamma-ray vision

NASA Astrophysics Data System (ADS)

Vetter, Kai; Barnowksi, Ross; Haefner, Andrew; Joshi, Tenzing H. Y.; Pavlovsky, Ryan; Quiter, Brian J.

2018-01-01

The development of portable gamma-ray imaging instruments in combination with the recent advances in sensor and related computer vision technologies enable unprecedented capabilities in the detection, localization, and mapping of radiological and nuclear materials in complex environments relevant for nuclear security and safety. Though multi-modal imaging has been established in medicine and biomedical imaging for some time, the potential of multi-modal data fusion for radiological localization and mapping problems in complex indoor and outdoor environments remains to be explored in detail. In contrast to the well-defined settings in medical or biological imaging associated with small field-of-view and well-constrained extension of the radiation field, in many radiological search and mapping scenarios, the radiation fields are not constrained and objects and sources are not necessarily known prior to the measurement. The ability to fuse radiological with contextual or scene data in three dimensions, in analog to radiological and functional imaging with anatomical fusion in medicine, provides new capabilities enhancing image clarity, context, quantitative estimates, and visualization of the data products. We have developed new means to register and fuse gamma-ray imaging with contextual data from portable or moving platforms. These developments enhance detection and mapping capabilities as well as provide unprecedented visualization of complex radiation fields, moving us one step closer to the realization of gamma-ray vision in three dimensions.

Diagnostic accuracy of integrated intravascular ultrasound and optical coherence tomography (IVUS-OCT) system for coronary plaque characterization

NASA Astrophysics Data System (ADS)

Li, Jiawen; Ma, Teng; Mohar, Dilbahar; Correa, Adrian; Minami, Hataka; Jing, Joseph; Zhou, Qifa; Patel, Pranav M.; Chen, Zhongping

2014-03-01

Intravascular ultrasound (IVUS) imaging and optical coherence tomography (OCT), two commonly used intracoronary imaging modalities, play important roles in plaque evaluation. The combined use of IVUS (to visualize the entire plaque volume) and OCT (to quantify the thickness of the plaque cap, if any) is hypothesized to increase plaque diagnostic accuracy. Our group has developed a fully-integrated dual-modality IVUS-OCT imaging system and 3.6F catheter for simultaneous IVUS-OCT imaging with a high resolution and deep penetration depth. However, the diagnostic accuracy of an integrated IVUS-OCT system has not been investigated. In this study, we imaged 175 coronary artery sites (241 regions of interest) from 20 cadavers using our previous reported integrated IVUS-OCT system. IVUS-OCT images were read by two skilled interventional cardiologists. Each region of interest was classified as either calcification, lipid pool or fibrosis. Comparing the diagnosis by cardiologists using IVUSOCT images with the diagnosis by the pathologist, we calculated the sensitivity and specificity for characterization of calcification, lipid pool or fibrosis with this integrated system. In vitro imaging of cadaver coronary specimens demonstrated the complementary nature of these two modalities for plaques classification. A higher accuracy was shown than using a single modality alone.

α-Information Based Registration of Dynamic Scans for Magnetic Resonance Cystography

PubMed Central

Han, Hao; Lin, Qin; Li, Lihong; Duan, Chaijie; Lu, Hongbing; Li, Haifang; Yan, Zengmin; Fitzgerald, John

2015-01-01

To continue our effort on developing magnetic resonance (MR) cystography, we introduce a novel non–rigid 3D registration method to compensate for bladder wall motion and deformation in dynamic MR scans, which are impaired by relatively low signal–to–noise ratio in each time frame. The registration method is developed on the similarity measure of α–information, which has the potential of achieving higher registration accuracy than the commonly-used mutual information (MI) measure for either mono-modality or multi-modality image registration. The α–information metric was also demonstrated to be superior to both the mean squares and the cross-correlation metrics in multi-modality scenarios. The proposed α–registration method was applied for bladder motion compensation via real patient studies, and its effect to the automatic and accurate segmentation of bladder wall was also evaluated. Compared with the prevailing MI-based image registration approach, the presented α–information based registration was more effective to capture the bladder wall motion and deformation, which ensured the success of the following bladder wall segmentation to achieve the goal of evaluating the entire bladder wall for detection and diagnosis of abnormality. PMID:26087506

Imaging findings in a case of Gorlin-Goltz syndrome: a survey using advanced modalities

PubMed Central

Shakibafar, Ali Reza; Houshyar, Maneli; Nafarzade, Shima

2011-01-01

Gorlin-Goltz syndrome is an infrequent multi-systemic disease which is characterized by multiple keratocysts in the jaws, calcification of falx cerebri, and basal cell carcinomas. We report a case of Gorlin-Goltz syndrome in a 23-year-old man with emphasis on image findings of keratocyctic odontogenic tumors (KCOTs) on panoramic radiograph, computed tomography, magnetic resonance (MR) imaging, and Ultrasonography (US). In this case, pericoronal lesions were mostly orthokeratinized odontogenic cyst (OOC) concerning the MR and US study, which tended to recur less. The aim of this report was to clarify the characteristic imaging features of the syndrome-related keratocysts that can be used to differentiate KCOT from OOC. Also, our findings suggested that the recurrence rate of KCOTs might be predicted based on their association to teeth. PMID:22232727

Whole-brain ex-vivo quantitative MRI of the cuprizone mouse model

PubMed Central

Hurley, Samuel A.; Vernon, Anthony C.; Torres, Joel; Dell’Acqua, Flavio; Williams, Steve C.R.; Cash, Diana

2016-01-01

Myelin is a critical component of the nervous system and a major contributor to contrast in Magnetic Resonance (MR) images. However, the precise contribution of myelination to multiple MR modalities is still under debate. The cuprizone mouse is a well-established model of demyelination that has been used in several MR studies, but these have often imaged only a single slice and analysed a small region of interest in the corpus callosum. We imaged and analyzed the whole brain of the cuprizone mouse ex-vivo using high-resolution quantitative MR methods (multi-component relaxometry, Diffusion Tensor Imaging (DTI) and morphometry) and found changes in multiple regions, including the corpus callosum, cerebellum, thalamus and hippocampus. The presence of inflammation, confirmed with histology, presents difficulties in isolating the sensitivity and specificity of these MR methods to demyelination using this model. PMID:27833805

Imaging assessment of penetrating injury of the neck and face.

PubMed

Offiah, Curtis; Hall, Edward

2012-10-01

Penetrating trauma of the neck and face is a frequent presentation to acute emergency, trauma and critical care units. There remains a steady incidence of both gunshot penetrating injury to the neck and face as well as non-missile penetrating injury-largely, but not solely, knife-related. Optimal imaging assessment of such injuries therefore remains an on-going requirement of the general and specialised radiologist. The anatomy of the neck and face-in particular, vascular, pharyngo-oesophageal, laryngo-tracheal and neural anatomy-demands a more specialised and selective management plan which incorporates specific imaging techniques. The current treatment protocol of injuries of the neck and face has seen a radical shift away from expectant surgical exploration in the management of such injuries, largely as a result of advances in the diagnostic capabilities of multi-detector computed tomography angiography (MDCTA), which is now the first-line imaging modality of choice in such cases. This review aims to highlight ballistic considerations, differing imaging modalities, including MDCTA, that might be utilised to assist in the accurate assessment of these injuries as well as the specific radiological features and patterns of specific organ-system injuries that should be considered and communicated to surgical and critical care teams. TEACHING POINTS : • MDCTA is the first-line imaging modality in penetrating trauma of the neck and, often, of the face • The inherent deformability of a bullet is a significant factor in its tissue-damaging capabilities • MDCTA can provide accurate assessment of visceral injury of the neck as well as vascular injury • Penetrating facial trauma warrants radiological assessment of key adjacent anatomical structures • In-driven fragments of native bone potentiate tissue damage in projectile penetrating facial trauma.

Richard Mazurchuk, PhD | Division of Cancer Prevention

Cancer.gov

Dr. Richard Mazurchuk received a BS in Physics and MS and PhD in Biophysics from SUNY Buffalo. His research focused on developing novel multi-modality imaging techniques, contrast (enhancing) agents and methods to assess the efficacy of experimental therapeutics. |

Spatial accessibility to healthcare services in Shenzhen, China: improving the multi-modal two-step floating catchment area method by estimating travel time via online map APIs.

PubMed

Tao, Zhuolin; Yao, Zaoxing; Kong, Hui; Duan, Fei; Li, Guicai

2018-05-09

Shenzhen has rapidly grown into a megacity in the recent decades. It is a challenging task for the Shenzhen government to provide sufficient healthcare services. The spatial configuration of healthcare services can influence the convenience for the consumers to obtain healthcare services. Spatial accessibility has been widely adopted as a scientific measurement for evaluating the rationality of the spatial configuration of healthcare services. The multi-modal two-step floating catchment area (2SFCA) method is an important advance in the field of healthcare accessibility modelling, which enables the simultaneous assessment of spatial accessibility via multiple transport modes. This study further develops the multi-modal 2SFCA method by introducing online map APIs to improve the estimation of travel time by public transit or by car respectively. As the results show, the distribution of healthcare accessibility by multi-modal 2SFCA shows significant spatial disparity. Moreover, by dividing the multi-modal accessibility into car-mode and transit-mode accessibility, this study discovers that the transit-mode subgroup is disadvantaged in the competition for healthcare services with the car-mode subgroup. The disparity in transit-mode accessibility is the main reason of the uneven pattern of healthcare accessibility in Shenzhen. The findings suggest improving the public transit conditions for accessing healthcare services to reduce the disparity of healthcare accessibility. More healthcare services should be allocated in the eastern and western Shenzhen, especially sub-districts in Dapeng District and western Bao'an District. As these findings cannot be drawn by the traditional single-modal 2SFCA method, the advantage of the multi-modal 2SFCA method is significant to both healthcare studies and healthcare system planning.

Accurate determination of imaging modality using an ensemble of text- and image-based classifiers.

PubMed

Kahn, Charles E; Kalpathy-Cramer, Jayashree; Lam, Cesar A; Eldredge, Christina E

2012-02-01

Imaging modality can aid retrieval of medical images for clinical practice, research, and education. We evaluated whether an ensemble classifier could outperform its constituent individual classifiers in determining the modality of figures from radiology journals. Seventeen automated classifiers analyzed 77,495 images from two radiology journals. Each classifier assigned one of eight imaging modalities--computed tomography, graphic, magnetic resonance imaging, nuclear medicine, positron emission tomography, photograph, ultrasound, or radiograph-to each image based on visual and/or textual information. Three physicians determined the modality of 5,000 randomly selected images as a reference standard. A "Simple Vote" ensemble classifier assigned each image to the modality that received the greatest number of individual classifiers' votes. A "Weighted Vote" classifier weighted each individual classifier's vote based on performance over a training set. For each image, this classifier's output was the imaging modality that received the greatest weighted vote score. We measured precision, recall, and F score (the harmonic mean of precision and recall) for each classifier. Individual classifiers' F scores ranged from 0.184 to 0.892. The simple vote and weighted vote classifiers correctly assigned 4,565 images (F score, 0.913; 95% confidence interval, 0.905-0.921) and 4,672 images (F score, 0.934; 95% confidence interval, 0.927-0.941), respectively. The weighted vote classifier performed significantly better than all individual classifiers. An ensemble classifier correctly determined the imaging modality of 93% of figures in our sample. The imaging modality of figures published in radiology journals can be determined with high accuracy, which will improve systems for image retrieval.

Medical image diagnoses by artificial neural networks with image correlation, wavelet transform, simulated annealing

NASA Astrophysics Data System (ADS)

Szu, Harold H.

1993-09-01

Classical artificial neural networks (ANN) and neurocomputing are reviewed for implementing a real time medical image diagnosis. An algorithm known as the self-reference matched filter that emulates the spatio-temporal integration ability of the human visual system might be utilized for multi-frame processing of medical imaging data. A Cauchy machine, implementing a fast simulated annealing schedule, can determine the degree of abnormality by the degree of orthogonality between the patient imagery and the class of features of healthy persons. An automatic inspection process based on multiple modality image sequences is simulated by incorporating the following new developments: (1) 1-D space-filling Peano curves to preserve the 2-D neighborhood pixels' relationship; (2) fast simulated Cauchy annealing for the global optimization of self-feature extraction; and (3) a mini-max energy function for the intra-inter cluster-segregation respectively useful for top-down ANN designs.

Multi-modal automatic montaging of adaptive optics retinal images

PubMed Central

Chen, Min; Cooper, Robert F.; Han, Grace K.; Gee, James; Brainard, David H.; Morgan, Jessica I. W.

2016-01-01

We present a fully automated adaptive optics (AO) retinal image montaging algorithm using classic scale invariant feature transform with random sample consensus for outlier removal. Our approach is capable of using information from multiple AO modalities (confocal, split detection, and dark field) and can accurately detect discontinuities in the montage. The algorithm output is compared to manual montaging by evaluating the similarity of the overlapping regions after montaging, and calculating the detection rate of discontinuities in the montage. Our results show that the proposed algorithm has high alignment accuracy and a discontinuity detection rate that is comparable (and often superior) to manual montaging. In addition, we analyze and show the benefits of using multiple modalities in the montaging process. We provide the algorithm presented in this paper as open-source and freely available to download. PMID:28018714

TU-G-303-03: Machine Learning to Improve Human Learning From Longitudinal Image Sets

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

Veeraraghavan, H.

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with othermore » biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)« less

Correlative imaging across microscopy platforms using the fast and accurate relocation of microscopic experimental regions (FARMER) method

NASA Astrophysics Data System (ADS)

Huynh, Toan; Daddysman, Matthew K.; Bao, Ying; Selewa, Alan; Kuznetsov, Andrey; Philipson, Louis H.; Scherer, Norbert F.

2017-05-01

Imaging specific regions of interest (ROIs) of nanomaterials or biological samples with different imaging modalities (e.g., light and electron microscopy) or at subsequent time points (e.g., before and after off-microscope procedures) requires relocating the ROIs. Unfortunately, relocation is typically difficult and very time consuming to achieve. Previously developed techniques involve the fabrication of arrays of features, the procedures for which are complex, and the added features can interfere with imaging the ROIs. We report the Fast and Accurate Relocation of Microscopic Experimental Regions (FARMER) method, which only requires determining the coordinates of 3 (or more) conspicuous reference points (REFs) and employs an algorithm based on geometric operators to relocate ROIs in subsequent imaging sessions. The 3 REFs can be quickly added to various regions of a sample using simple tools (e.g., permanent markers or conductive pens) and do not interfere with the ROIs. The coordinates of the REFs and the ROIs are obtained in the first imaging session (on a particular microscope platform) using an accurate and precise encoded motorized stage. In subsequent imaging sessions, the FARMER algorithm finds the new coordinates of the ROIs (on the same or different platforms), using the coordinates of the manually located REFs and the previously recorded coordinates. FARMER is convenient, fast (3-15 min/session, at least 10-fold faster than manual searches), accurate (4.4 μm average error on a microscope with a 100x objective), and precise (almost all errors are <8 μm), even with deliberate rotating and tilting of the sample well beyond normal repositioning accuracy. We demonstrate this versatility by imaging and re-imaging a diverse set of samples and imaging methods: live mammalian cells at different time points; fixed bacterial cells on two microscopes with different imaging modalities; and nanostructures on optical and electron microscopes. FARMER can be readily adapted to any imaging system with an encoded motorized stage and can facilitate multi-session and multi-platform imaging experiments in biology, materials science, photonics, and nanoscience.

Label-free, multi-contrast optical coherence tomography for study of skin melanoma mice in vivo

NASA Astrophysics Data System (ADS)

Lai, Pei-Yu; Lin, Tim-Han; Chou, Ya-Shuan; Chang, Chung-Hsing; Kuo, Wen-Chuan

2018-02-01

The lymphatic system plays an important role in inflammation and cancer such as melanoma. Due to the limitations of current developed imaging techniques, visualization of lymphatic vessels within the tissue in vivo has been challenging. Optical imaging of lymphatic vessel is gaining increased interests because it does not involve any radiation and can achieve very high resolution. Here, we developed a multi-contrast, label-free optical coherence tomography (OCT) imaging technology with an axial resolution of 5 μm and lateral resolution of 7 μm, which is capable of providing microstructural information and microcirculatory system including blood and lymphatic vessels simultaneously. Using this technique, we observed the melanoma mice in vivo. Mice were treated topically on the ear with (Z)-4- Hydroxytamoxifen(4-OHT) to elicit BRAFV600E and to silence Pten expression. Also, to observing the structural information, angiogenesis and lymphangiogenesis in the ear of the induced melanoma mouse can be done. The advantage of using OCT over other imaging modalities is its ability to assess label-free blood flow along with lymphatic vessels simultaneously for imaging the microcirculatory system within tissue beds without any exogenous agents. Because the metastasis of melanoma is highly related to the lymphatic vessels, our findings can be a powerful tool to help the diagnosis of the metastasis melanoma. In the future, this may become a helpful tool for better understanding pathologic mechanisms and treatment technique development in some diseases.

Deeply learnt hashing forests for content based image retrieval in prostate MR images

NASA Astrophysics Data System (ADS)

Shah, Amit; Conjeti, Sailesh; Navab, Nassir; Katouzian, Amin

2016-03-01

Deluge in the size and heterogeneity of medical image databases necessitates the need for content based retrieval systems for their efficient organization. In this paper, we propose such a system to retrieve prostate MR images which share similarities in appearance and content with a query image. We introduce deeply learnt hashing forests (DL-HF) for this image retrieval task. DL-HF effectively leverages the semantic descriptiveness of deep learnt Convolutional Neural Networks. This is used in conjunction with hashing forests which are unsupervised random forests. DL-HF hierarchically parses the deep-learnt feature space to encode subspaces with compact binary code words. We propose a similarity preserving feature descriptor called Parts Histogram which is derived from DL-HF. Correlation defined on this descriptor is used as a similarity metric for retrieval from the database. Validations on publicly available multi-center prostate MR image database established the validity of the proposed approach. The proposed method is fully-automated without any user-interaction and is not dependent on any external image standardization like image normalization and registration. This image retrieval method is generalizable and is well-suited for retrieval in heterogeneous databases other imaging modalities and anatomies.

Angiogram, fundus, and oxygen saturation optic nerve head image fusion

NASA Astrophysics Data System (ADS)

Cao, Hua; Khoobehi, Bahram

2009-02-01

A novel multi-modality optic nerve head image fusion approach has been successfully designed. The new approach has been applied on three ophthalmologic modalities: angiogram, fundus, and oxygen saturation retinal optic nerve head images. It has achieved an excellent result by giving the visualization of fundus or oxygen saturation images with a complete angiogram overlay. During this study, two contributions have been made in terms of novelty, efficiency, and accuracy. The first contribution is the automated control point detection algorithm for multi-sensor images. The new method employs retina vasculature and bifurcation features by identifying the initial good-guess of control points using the Adaptive Exploratory Algorithm. The second contribution is the heuristic optimization fusion algorithm. In order to maximize the objective function (Mutual-Pixel-Count), the iteration algorithm adjusts the initial guess of the control points at the sub-pixel level. A refinement of the parameter set is obtained at the end of each loop, and finally an optimal fused image is generated at the end of the iteration. It is the first time that Mutual-Pixel-Count concept has been introduced into biomedical image fusion area. By locking the images in one place, the fused image allows ophthalmologists to match the same eye over time and get a sense of disease progress and pinpoint surgical tools. The new algorithm can be easily expanded to human or animals' 3D eye, brain, or body image registration and fusion.

Evaluation of PACS in a multihospital environment

NASA Astrophysics Data System (ADS)

Siegel, Eliot L.; Reiner, Bruce I.; Protopapas, Zenon

1998-07-01

Although a number of authors have described the challenges and benefits of filmless operation using a hospital-wide Picture Archival and Communication System (PACS), there have been few descriptions of a multi-hospital wide area PACS. The purpose of this paper is to describe our two and a half year experience with PACS in an integrated multi-facility health care environment, the Veterans Affairs Maryland Health Care System (VAMHCS). On June 17, 1995 the Radiology and Nuclear Medicine services became integrated for four medical centers forming the VA Maryland Health Care System creating a single multi-facility imaging department. The facilities consisted of the Baltimore VA (acute and outpatient care, tertiary referral center), Ft. Howard (primarily long term care), Perry Point (primarily psychiatric care), and the Baltimore Rehabilitation and extended care facility (nursing home). The combined number of studies at all four sites is slightly more than 80,000 examinations per year. In addition to residents and fellows, the number of radiologists at Baltimore was approximately seven, with two at Perry Point, one at Ft. Howard, and no radiologists at the Rehabilitation and Extended Care facility. A single HIS/RIS, which is located physically at the Baltimore VAMC is utilized for all four medical centers. The multi- facility image management and communication system utilizes two separate PAC Systems that are physically located at the Baltimore VA Medical Center (BVAMC). The commercial system (GE Medical Systems) has been in place in Baltimore for more than 41/2 years and is utilized primarily in the acquisition, storage, distribution and display of radiology and nuclear medicine studies. The second PACS is the VISTA Imaging System, which has been developed as a module of the VA's HIS/RIS by and for the Department of Veterans Affairs. All of the radiology images obtained on the commercial PACS are requested by the VISTA Imaging System using DICOM query/retrieve commands and are stored on a separate server and optical jukebox. Additionally, the VISTA system is used to store all images obtained by all specialties in the medical center including pathology, dermatology, GI medicine, surgery, podiatry, ophthalmology, etc. Using this two PAC system approach, the hospital is able to achieve redundancy with regard to image storage, retrieval, and display of radiology images. The transition to a 'virtual' multi-facility imaging department was accomplished over a period of two years. Initially, Perry Point and Ft. Howard replaced their general radiographic film processors with Computed Radiography (CR) units. The CR units and subsequently, the CT and Ultrasound systems at Perry Point were interfaced (DeJarnette Research Systems) with the commercial PACS located in Baltimore. A HIS/RIS to modality interface was developed (DeJarnette and Fuji Medical Systems) between the computed radiography and CT units and VISTA Information System at Baltimore. A digital dictation system was recently implemented across the multi- facility network. The integration of the three radiology departments into a single virtual imaging department serving four medical centers has resulted in a number of benefits. Economically, there has been the elimination via attrition of one and a half radiologist FTE's (full time equivalents) and an administrative position resulting in an annual savings of more than $375,000 per year. Additionally, the expenditures for moonlighter coverage for vacation, meeting, and sick leave have been eliminated. There is now subspecialty coverage for primary or secondary interpretation and for peer review.

Neural network for intelligent query of an FBI forensic database

NASA Astrophysics Data System (ADS)

Uvanni, Lee A.; Rainey, Timothy G.; Balasubramanian, Uma; Brettle, Dean W.; Weingard, Fred; Sibert, Robert W.; Birnbaum, Eric

1997-02-01

Examiner is an automated fired cartridge case identification system utilizing a dual-use neural network pattern recognition technology, called the statistical-multiple object detection and location system (S-MODALS) developed by Booz(DOT)Allen & Hamilton, Inc. in conjunction with Rome Laboratory. S-MODALS was originally designed for automatic target recognition (ATR) of tactical and strategic military targets using multisensor fusion [electro-optical (EO), infrared (IR), and synthetic aperture radar (SAR)] sensors. Since S-MODALS is a learning system readily adaptable to problem domains other than automatic target recognition, the pattern matching problem of microscopic marks for firearms evidence was analyzed using S-MODALS. The physics; phenomenology; discrimination and search strategies; robustness requirements; error level and confidence level propagation that apply to the pattern matching problem of military targets were found to be applicable to the ballistic domain as well. The Examiner system uses S-MODALS to rank a set of queried cartridge case images from the most similar to the least similar image in reference to an investigative fired cartridge case image. The paper presents three independent tests and evaluation studies of the Examiner system utilizing the S-MODALS technology for the Federal Bureau of Investigation.

Photoacoustic tomography guided diffuse optical tomography for small-animal model

NASA Astrophysics Data System (ADS)

Wang, Yihan; Gao, Feng; Wan, Wenbo; Zhang, Yan; Li, Jiao

2015-03-01

Diffuse optical tomography (DOT) is a biomedical imaging technology for noninvasive visualization of spatial variation about the optical properties of tissue, which can be applied to in vivo small-animal disease model. However, traditional DOT suffers low spatial resolution due to tissue scattering. To overcome this intrinsic shortcoming, multi-modal approaches that incorporate DOT with other imaging techniques have been intensively investigated, where a priori information provided by the other modalities is normally used to reasonably regularize the inverse problem of DOT. Nevertheless, these approaches usually consider the anatomical structure, which is different from the optical structure. Photoacoustic tomography (PAT) is an emerging imaging modality that is particularly useful for visualizing lightabsorbing structures embedded in soft tissue with higher spatial resolution compared with pure optical imaging. Thus, we present a PAT-guided DOT approach, to obtain the location a priori information of optical structure provided by PAT first, and then guide DOT to reconstruct the optical parameters quantitatively. The results of reconstruction of phantom experiments demonstrate that both quantification and spatial resolution of DOT could be highly improved by the regularization of feasible-region information provided by PAT.

Nanox: a miniature mechanical stress rig designed for near-field X-ray diffraction imaging techniques.

PubMed

Gueninchault, N; Proudhon, H; Ludwig, W

2016-11-01

Multi-modal characterization of polycrystalline materials by combined use of three-dimensional (3D) X-ray diffraction and imaging techniques may be considered as the 3D equivalent of surface studies in the electron microscope combining diffraction and other imaging modalities. Since acquisition times at synchrotron sources are nowadays compatible with four-dimensional (time lapse) studies, suitable mechanical testing devices are needed which enable switching between these different imaging modalities over the course of a mechanical test. Here a specifically designed tensile device, fulfilling severe space constraints and permitting to switch between X-ray (holo)tomography, diffraction contrast tomography and topotomography, is presented. As a proof of concept the 3D characterization of an Al-Li alloy multicrystal by means of diffraction contrast tomography is presented, followed by repeated topotomography characterization of one selected grain at increasing levels of deformation. Signatures of slip bands and sudden lattice rotations inside the grain have been shown by means of in situ topography carried out during the load ramps, and diffraction spot peak broadening has been monitored throughout the experiment.

Nanox: a miniature mechanical stress rig designed for near-field X-ray diffraction imaging techniques

PubMed Central

Gueninchault, N.; Proudhon, H.; Ludwig, W.

2016-01-01

Multi-modal characterization of polycrystalline materials by combined use of three-dimensional (3D) X-ray diffraction and imaging techniques may be considered as the 3D equivalent of surface studies in the electron microscope combining diffraction and other imaging modalities. Since acquisition times at synchrotron sources are nowadays compatible with four-dimensional (time lapse) studies, suitable mechanical testing devices are needed which enable switching between these different imaging modalities over the course of a mechanical test. Here a specifically designed tensile device, fulfilling severe space constraints and permitting to switch between X-ray (holo)tomography, diffraction contrast tomography and topotomography, is presented. As a proof of concept the 3D characterization of an Al–Li alloy multicrystal by means of diffraction contrast tomography is presented, followed by repeated topotomography characterization of one selected grain at increasing levels of deformation. Signatures of slip bands and sudden lattice rotations inside the grain have been shown by means of in situ topography carried out during the load ramps, and diffraction spot peak broadening has been monitored throughout the experiment. PMID:27787253

SU-E-J-218: Novel Validation Paradigm of MRI to CT Deformation of Prostate

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

Padgett, K; University of Miami School of Medicine - Radiology, Miami, FL; Pirozzi, S

2015-06-15

Purpose: Deformable registration algorithms are inherently difficult to characterize in the multi-modality setting due to a significant differences in the characteristics of the different modalities (CT and MRI) as well as tissue deformations. We present a unique paradigm where this is overcome by utilizing a planning-MRI acquired within an hour of the planning-CT serving as a surrogate for quantifying MRI to CT deformation by eliminating the issues of multi-modality comparisons. Methods: For nine subjects, T2 fast-spin-echo images were acquired at two different time points, the first several weeks prior to planning (diagnostic-MRI) and the second on the same day asmore » the planning-CT (planning-MRI). Significant effort in patient positioning and bowel/bladder preparation was undertaken to minimize distortion of the prostate in all datasets. The diagnostic-MRI was rigidly and deformably aligned to the planning-CT utilizing a commercially available deformable registration algorithm synthesized from local registrations. Additionally, the quality of rigid alignment was ranked by an imaging physicist. The distances between corresponding anatomical landmarks on rigid and deformed registrations (diagnostic-MR to planning-CT) were evaluated. Results: It was discovered that in cases where the rigid registration was of acceptable quality the deformable registration didn’t improve the alignment, this was true of all metrics employed. If the analysis is separated into cases where the rigid alignment was ranked as unacceptable the deformable registration significantly improved the alignment, 4.62mm residual error in landmarks as compared to 5.72mm residual error in rigid alignments with a p-value of 0.0008. Conclusion: This paradigm provides an ideal testing ground for MR to CT deformable registration algorithms by allowing for inter-modality comparisons of multi-modality registrations. Consistent positioning, bowel and bladder preparation may Result in higher quality rigid registrations than typically achieved which limits the impact of deformable registrations. In this study cases where significant differences exist, deformable registrations provide significant value.« less

MO-E-BRB-03: Panel Member

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

Salter, B.

2016-06-15

In this interactive session, lung SBRT patient cases will be presented to highlight real-world considerations for ensuring safe and accurate treatment delivery. An expert panel of speakers will discuss challenges specific to lung SBRT including patient selection, patient immobilization techniques, 4D CT simulation and respiratory motion management, target delineation for treatment planning, online treatment alignment, and established prescription regimens and OAR dose limits. Practical examples of cases, including the patient flow thought the clinical process are presented and audience participation will be encouraged. This panel session is designed to provide case demonstration and review for lung SBRT in terms ofmore » (1) clinical appropriateness in patient selection, (2) strategies for simulation, including 4D and respiratory motion management, and (3) applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent, and (4) image guidance in treatment delivery. Learning Objectives: Understand the established requirements for patient selection in lung SBRT Become familiar with the various immobilization strategies for lung SBRT, including technology for respiratory motion management Understand the benefits and pitfalls of applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent determination for lung SBRT Understand established prescription regimes and OAR dose limits.« less

MO-E-BRB-01: Panel Member

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

Benedict, S.

2016-06-15

In this interactive session, lung SBRT patient cases will be presented to highlight real-world considerations for ensuring safe and accurate treatment delivery. An expert panel of speakers will discuss challenges specific to lung SBRT including patient selection, patient immobilization techniques, 4D CT simulation and respiratory motion management, target delineation for treatment planning, online treatment alignment, and established prescription regimens and OAR dose limits. Practical examples of cases, including the patient flow thought the clinical process are presented and audience participation will be encouraged. This panel session is designed to provide case demonstration and review for lung SBRT in terms ofmore » (1) clinical appropriateness in patient selection, (2) strategies for simulation, including 4D and respiratory motion management, and (3) applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent, and (4) image guidance in treatment delivery. Learning Objectives: Understand the established requirements for patient selection in lung SBRT Become familiar with the various immobilization strategies for lung SBRT, including technology for respiratory motion management Understand the benefits and pitfalls of applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent determination for lung SBRT Understand established prescription regimes and OAR dose limits.« less

MO-E-BRB-00: PANEL DISCUSSION: SBRT/SRS Case Studies - Lung

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

NONE

2016-06-15

In this interactive session, lung SBRT patient cases will be presented to highlight real-world considerations for ensuring safe and accurate treatment delivery. An expert panel of speakers will discuss challenges specific to lung SBRT including patient selection, patient immobilization techniques, 4D CT simulation and respiratory motion management, target delineation for treatment planning, online treatment alignment, and established prescription regimens and OAR dose limits. Practical examples of cases, including the patient flow thought the clinical process are presented and audience participation will be encouraged. This panel session is designed to provide case demonstration and review for lung SBRT in terms ofmore » (1) clinical appropriateness in patient selection, (2) strategies for simulation, including 4D and respiratory motion management, and (3) applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent, and (4) image guidance in treatment delivery. Learning Objectives: Understand the established requirements for patient selection in lung SBRT Become familiar with the various immobilization strategies for lung SBRT, including technology for respiratory motion management Understand the benefits and pitfalls of applying multi imaging modality (4D CT imaging, MRI, PET) for tumor volume delineation and motion extent determination for lung SBRT Understand established prescription regimes and OAR dose limits.« less

Multi-pass transmission electron microscopy

DOE PAGES

Juffmann, Thomas; Koppell, Stewart A.; Klopfer, Brannon B.; ...

2017-05-10

Feynman once asked physicists to build better electron microscopes to be able to watch biology at work. While electron microscopes can now provide atomic resolution, electron beam induced specimen damage precludes high resolution imaging of sensitive materials, such as single proteins or polymers. Here, we use simulations to show that an electron microscope based on a multi-pass measurement protocol enables imaging of single proteins, without averaging structures over multiple images. While we demonstrate the method for particular imaging targets, the approach is broadly applicable and is expected to improve resolution and sensitivity for a range of electron microscopy imaging modalities,more » including, for example, scanning and spectroscopic techniques. The approach implements a quantum mechanically optimal strategy which under idealized conditions can be considered interaction-free.« less

Multi-task linear programming discriminant analysis for the identification of progressive MCI individuals.

PubMed

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method.

Multi-Task Linear Programming Discriminant Analysis for the Identification of Progressive MCI Individuals

PubMed Central

Yu, Guan; Liu, Yufeng; Thung, Kim-Han; Shen, Dinggang

2014-01-01

Accurately identifying mild cognitive impairment (MCI) individuals who will progress to Alzheimer's disease (AD) is very important for making early interventions. Many classification methods focus on integrating multiple imaging modalities such as magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET). However, the main challenge for MCI classification using multiple imaging modalities is the existence of a lot of missing data in many subjects. For example, in the Alzheimer's Disease Neuroimaging Initiative (ADNI) study, almost half of the subjects do not have PET images. In this paper, we propose a new and flexible binary classification method, namely Multi-task Linear Programming Discriminant (MLPD) analysis, for the incomplete multi-source feature learning. Specifically, we decompose the classification problem into different classification tasks, i.e., one for each combination of available data sources. To solve all different classification tasks jointly, our proposed MLPD method links them together by constraining them to achieve the similar estimated mean difference between the two classes (under classification) for those shared features. Compared with the state-of-the-art incomplete Multi-Source Feature (iMSF) learning method, instead of constraining different classification tasks to choose a common feature subset for those shared features, MLPD can flexibly and adaptively choose different feature subsets for different classification tasks. Furthermore, our proposed MLPD method can be efficiently implemented by linear programming. To validate our MLPD method, we perform experiments on the ADNI baseline dataset with the incomplete MRI and PET images from 167 progressive MCI (pMCI) subjects and 226 stable MCI (sMCI) subjects. We further compared our method with the iMSF method (using incomplete MRI and PET images) and also the single-task classification method (using only MRI or only subjects with both MRI and PET images). Experimental results show very promising performance of our proposed MLPD method. PMID:24820966

TU-G-303-04: Radiomics and the Coming Pan-Omics Revolution

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

El Naqa, I.

‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with othermore » biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding requirements for reliable radiomic models, including robustness of metrics, adequate predictive accuracy, and generalizability. Understanding the methodology behind radiomic-genomic (’radiogenomics’) correlations. Research supported by NIH (US), CIHR (Canada), and NSERC (Canada)« less

Mechanically assisted 3D ultrasound for pre-operative assessment and guiding percutaneous treatment of focal liver tumors

NASA Astrophysics Data System (ADS)

Sadeghi Neshat, Hamid; Bax, Jeffery; Barker, Kevin; Gardi, Lori; Chedalavada, Jason; Kakani, Nirmal; Fenster, Aaron

2014-03-01

Image-guided percutaneous ablation is the standard treatment for focal liver tumors deemed inoperable and is commonly used to maintain eligibility for patients on transplant waitlists. Radiofrequency (RFA), microwave (MWA) and cryoablation technologies are all delivered via one or a number of needle-shaped probes inserted directly into the tumor. Planning is mostly based on contrast CT/MRI. While intra-procedural CT is commonly used to confirm the intended probe placement, 2D ultrasound (US) remains the main, and in some centers the only imaging modality used for needle guidance. Corresponding intraoperative 2D US with planning and other intra-procedural imaging modalities is essential for accurate needle placement. However, identification of matching features of interest among these images is often challenging given the limited field-of-view (FOV) and low quality of 2D US images. We have developed a passive tracking arm with a motorized scan-head and software tools to improve guiding capabilities of conventional US by large FOV 3D US scans that provides more anatomical landmarks that can facilitate registration of US with both planning and intra-procedural images. The tracker arm is used to scan the whole liver with a high geometrical accuracy that facilitates multi-modality landmark based image registration. Software tools are provided to assist with the segmentation of the ablation probes and tumors, find the 2D view that best shows the probe(s) from a 3D US image, and to identify the corresponding image from planning CT scans. In this paper, evaluation results from laboratory testing and a phase 1 clinical trial for planning and guiding RFA and MWA procedures using the developed system will be presented. Early clinical results show a comparable performance to intra-procedural CT that suggests 3D US as a cost-effective alternative with no side-effects in centers where CT is not available.

Integrating Iris and Signature Traits for Personal Authentication Using User-Specific Weighting

PubMed Central

Viriri, Serestina; Tapamo, Jules R.

2012-01-01

Biometric systems based on uni-modal traits are characterized by noisy sensor data, restricted degrees of freedom, non-universality and are susceptible to spoof attacks. Multi-modal biometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, a user-score-based weighting technique for integrating the iris and signature traits is presented. This user-specific weighting technique has proved to be an efficient and effective fusion scheme which increases the authentication accuracy rate of multi-modal biometric systems. The weights are used to indicate the importance of matching scores output by each biometrics trait. The experimental results show that our biometric system based on the integration of iris and signature traits achieve a false rejection rate (FRR) of 0.08% and a false acceptance rate (FAR) of 0.01%. PMID:22666032

Integrated adaptive optics optical coherence tomography and adaptive optics scanning laser ophthalmoscope system for simultaneous cellular resolution in vivo retinal imaging

PubMed Central

Zawadzki, Robert J.; Jones, Steven M.; Pilli, Suman; Balderas-Mata, Sandra; Kim, Dae Yu; Olivier, Scot S.; Werner, John S.

2011-01-01

We describe an ultrahigh-resolution (UHR) retinal imaging system that combines adaptive optics Fourier-domain optical coherence tomography (AO-OCT) with an adaptive optics scanning laser ophthalmoscope (AO-SLO) to allow simultaneous data acquisition by the two modalities. The AO-SLO subsystem was integrated into the previously described AO-UHR OCT instrument with minimal changes to the latter. This was done in order to ensure optimal performance and image quality of the AO- UHR OCT. In this design both imaging modalities share most of the optical components including a common AO-subsystem and vertical scanner. One of the benefits of combining Fd-OCT with SLO includes automatic co-registration between two acquisition channels for direct comparison between retinal structures imaged by both modalities (e.g., photoreceptor mosaics or microvasculature maps). Because of differences in the detection scheme of the two systems, this dual imaging modality instrument can provide insight into retinal morphology and potentially function, that could not be accessed easily by a single system. In this paper we describe details of the components and parameters of the combined instrument, including incorporation of a novel membrane magnetic deformable mirror with increased stroke and actuator count used as a single wavefront corrector. We also discuss laser safety calculations for this multimodal system. Finally, retinal images acquired in vivo with this system are presented. PMID:21698028

Selection and implementation of a distributed phased archive for a multivendor incremental approach to PACS

NASA Astrophysics Data System (ADS)

Smith, Edward M.; Wandtke, John; Robinson, Arvin E.

1999-07-01

The selection criteria for the archive were based on the objectives of the Medical Information, Communication and Archive System (MICAS), a multi-vendor incremental approach to PACS. These objectives include interoperability between all components, seamless integration of the Radiology Information System (RIS) with MICAS and eventually other hospital databases, all components must demonstrate DICOM compliance prior to acceptance and automated workflow that can be programmed to meet changes in the healthcare environment. The long-term multi-modality archive is being implemented in 3 or more phases with the first phase designed to provide a 12 to 18 month storage solution. This decision was made because the cost per GB of storage is rapidly decreasing and the speed at which data can be retrieved is increasing with time. The open-solution selected allows incorporation of leading edge, 'best of breed' hardware and software and provides maximum jukeboxes, provides maximum flexibility of workflow both within and outside of radiology. The selected solution is media independent, supports multiple jukeboxes, provides expandable storage capacity and will provide redundancy and fault tolerance at minimal cost. Some of the required attributes of the archive include scalable archive strategy, virtual image database with global query and object-oriented database. The selection process took approximately 10 months with Cemax-Icon being the vendor selected. Prior to signing a purchase order, Cemax-Icon performed a site survey, agreed upon the acceptance test protocol and provided a written guarantee of connectivity between their archive and the imaging modalities and other MICAS components.

On modal cross-coupling in the asymptotic modal limit

NASA Astrophysics Data System (ADS)

Culver, Dean; Dowell, Earl

2018-03-01

The conditions under which significant modal cross-coupling occurs in dynamical systems responding to high-frequency, broadband forcing that excites many modes is studied. The modal overlap factor plays a key role in the analysis of these systems as the modal density (the ratio of number of modes to the frequency bandwidth) becomes large. The modal overlap factor is effectively the ratio of the width of a resonant peak (the damping ratio times the resonant frequency) to the average frequency interval between resonant peaks (or rather, the inverse of the modal density). It is shown that this parameter largely determines whether substantial modal cross-coupling occurs in a given system's response. Here, two prototypical systems are considered. The first is a simple rectangular plate whose significant modal cross-coupling is the exception rather than the norm. The second is a pair of rectangular plates attached at a point where significant modal cross-coupling is more likely to occur. We show that, for certain cases of modal density and damping, non-negligible cross coupling occurs in both systems. Under similar circumstances, the constraint force between the two plates in the latter system becomes broadband. The implications of this for using Asymptotic Modal Analysis (AMA) in multi-component systems are discussed.

About CIB | Division of Cancer Prevention

Cancer.gov

The Consortium was created to improve cancer screening, early detection of aggressive cancer, assessment of cancer risk and cancer diagnosis aimed at integrating multi-modality imaging strategies and multiplexed biomarker methodologies into a singular complementary approach. Investigator perform collaborative studies, exchange information, share knowledge and leverage common

Multispectral photoacoustic characterization of ICG and porcine blood using an LED-based photoacoustic imaging system

NASA Astrophysics Data System (ADS)

Shigeta, Yusuke; Sato, Naoto; Kuniyil Ajith Singh, Mithun; Agano, Toshitaka

2018-02-01

Photoacoustic imaging is a hybrid biomedical imaging modality that has emerged over the last decade. In photoacoustic imaging, pulsed-light absorbed by the target emits ultrasound that can be detected using a conventional ultrasound array. This ultrasound data can be used to reconstruct the location and spatial details of the intrinsic/extrinsic light absorbers in the tissue. Recently we reported on the development of a multi-wavelength high frame-rate LED-based photoacoustic/ultrasound imaging system (AcousticX). In this work, we photoacoustically characterize the absorption spectrum of ICG and porcine blood using LED arrays with multiple wavelengths (405, 420, 470, 520, 620, 660, 690, 750, 810, 850, 925, 980 nm). Measurements were performed in a simple reflection mode configuration in which LED arrays where fixed on both sides of the linear array ultrasound probe. Phantom used consisted of micro-test tubes filled with ICG and porcine blood, which were placed in a tank filled with water. The photoacoustic spectrum obtained from our measurements matches well with the reference absorption spectrum. These results demonstrate the potential capability of our system in performing clinical/pre-clinical multispectral photoacoustic imaging.

Hierarchical patch-based co-registration of differently stained histopathology slides

NASA Astrophysics Data System (ADS)

Yigitsoy, Mehmet; Schmidt, Günter

2017-03-01

Over the past decades, digital pathology has emerged as an alternative way of looking at the tissue at subcellular level. It enables multiplexed analysis of different cell types at micron level. Information about cell types can be extracted by staining sections of a tissue block using different markers. However, robust fusion of structural and functional information from different stains is necessary for reproducible multiplexed analysis. Such a fusion can be obtained via image co-registration by establishing spatial correspondences between tissue sections. Spatial correspondences can then be used to transfer various statistics about cell types between sections. However, the multi-modal nature of images and sparse distribution of interesting cell types pose several challenges for the registration of differently stained tissue sections. In this work, we propose a co-registration framework that efficiently addresses such challenges. We present a hierarchical patch-based registration of intensity normalized tissue sections. Preliminary experiments demonstrate the potential of the proposed technique for the fusion of multi-modal information from differently stained digital histopathology sections.

Fully integrated optical coherence tomography, ultrasound, and indocyanine green based fluorescence tri-modality system for intravascular imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Li, Yan; Jing, Joseph C.; Qu, Yueqiao; Miao, Yusi; Ma, Teng; Yu, Mingyue; Zhou, Qifa; Chen, Zhongping

2017-02-01

The rupture of atherosclerotic plaques is the leading cause of acute coronary events, so accurate assessment of plaque is critical. A large lipid pool, thin fibrous cap, and inflammatory reaction are the crucial characteristics for identifying vulnerable plaques. In our study, a tri-modality imaging system for intravascular imaging was designed and implemented. The tri-modality imaging system with a 1-mm probe diameter is able to simultaneously acquire optical coherence tomography (OCT), intravascular ultrasound (IVUS), and fluorescence imaging. Moreover, for fluorescence imaging, we used the FDA-approved indocyanine green (ICG) dye as the contrast agent to target lipid-loaded macrophages. Firstly, IVUS is used as the first step for identifying plaque since IVUS enables the visualization of the layered structures of the artery wall. Due to low soft-tissue contrast, IVUS only provides initial identification of the lipid plaque. Then OCT is used for differentiating fibrosis and lipid pool based on its relatively higher soft tissue contrast and high sensitivity/specificity. Last, fluorescence imaging is used for identifying inflammatory reaction to further confirm whether the plaque is vulnerable or not. Ex vivo experiment of a male New Zealand white rabbit aorta was performed to validate the performance of our tri-modality system. H and E histology results of the rabbit aorta were also presented to check assessment accuracy. The miniature tri-modality probe, together with the use of ICG dye suggest that the system is of great potential for providing a more accurate assessment of vulnerable plaques in clinical applications.

Neurocognitive insights on conceptual knowledge and its breakdown

PubMed Central

Lambon Ralph, Matthew A.

2014-01-01

Conceptual knowledge reflects our multi-modal ‘semantic database’. As such, it brings meaning to all verbal and non-verbal stimuli, is the foundation for verbal and non-verbal expression and provides the basis for computing appropriate semantic generalizations. Multiple disciplines (e.g. philosophy, cognitive science, cognitive neuroscience and behavioural neurology) have striven to answer the questions of how concepts are formed, how they are represented in the brain and how they break down differentially in various neurological patient groups. A long-standing and prominent hypothesis is that concepts are distilled from our multi-modal verbal and non-verbal experience such that sensation in one modality (e.g. the smell of an apple) not only activates the intramodality long-term knowledge, but also reactivates the relevant intermodality information about that item (i.e. all the things you know about and can do with an apple). This multi-modal view of conceptualization fits with contemporary functional neuroimaging studies that observe systematic variation of activation across different modality-specific association regions dependent on the conceptual category or type of information. A second vein of interdisciplinary work argues, however, that even a smorgasbord of multi-modal features is insufficient to build coherent, generalizable concepts. Instead, an additional process or intermediate representation is required. Recent multidisciplinary work, which combines neuropsychology, neuroscience and computational models, offers evidence that conceptualization follows from a combination of modality-specific sources of information plus a transmodal ‘hub’ representational system that is supported primarily by regions within the anterior temporal lobe, bilaterally. PMID:24324236

Improving lateral resolution and image quality of optical coherence tomography by the multi-frame superresolution technique for 3D tissue imaging.

PubMed

Shen, Kai; Lu, Hui; Baig, Sarfaraz; Wang, Michael R

2017-11-01

The multi-frame superresolution technique is introduced to significantly improve the lateral resolution and image quality of spectral domain optical coherence tomography (SD-OCT). Using several sets of low resolution C-scan 3D images with lateral sub-spot-spacing shifts on different sets, the multi-frame superresolution processing of these sets at each depth layer reconstructs a higher resolution and quality lateral image. Layer by layer processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution processing including deconvolution can solve the diffraction limit, lateral scan density and background noise problems together. In experiment, the improved lateral resolution by ~3 times reaching 7.81 µm and 2.19 µm using sample arm optics of 0.015 and 0.05 numerical aperture respectively as well as doubling the image quality has been confirmed by imaging a known resolution test target. Improved lateral resolution on in vitro skin C-scan images has been demonstrated. For in vivo 3D SD-OCT imaging of human skin, fingerprint and retina layer, we used the multi-modal volume registration method to effectively estimate the lateral image shifts among different C-scans due to random minor unintended live body motion. Further processing of these images generated high lateral resolution 3D images as well as high quality B-scan images of these in vivo tissues.

A novel multimodal optical imaging system for early detection of oral cancer

PubMed Central

Malik, Bilal H.; Jabbour, Joey M.; Cheng, Shuna; Cuenca, Rodrigo; Cheng, Yi-Shing Lisa; Wright, John M.; Jo, Javier A.; Maitland, Kristen C.

2015-01-01

Objectives Several imaging techniques have been advocated as clinical adjuncts to improve identification of suspicious oral lesions. However, these have not yet shown superior sensitivity or specificity over conventional oral examination techniques. We developed a multimodal, multi-scale optical imaging system that combines macroscopic biochemical imaging of fluorescence lifetime imaging (FLIM) with subcellular morphologic imaging of reflectance confocal microscopy (RCM) for early detection of oral cancer. We tested our system on excised human oral tissues. Study Design A total of four tissue specimen were imaged. These specimens were diagnosed as one each: clinically normal, oral lichen planus, gingival hyperplasia, and superficially-invasive squamous cell carcinoma (SCC). The optical and fluorescence lifetime properties of each specimen were recorded. Results Both quantitative and qualitative differences between normal, benign and SCC lesions can be resolved with FLIM-RCM imaging. The results demonstrate that an integrated approach based on these two methods can potentially enable rapid screening and evaluation of large areas of oral epithelial tissue. Conclusions Early results from ongoing studies of imaging human oral cavity illustrate the synergistic combination of the two modalities. An adjunct device based on such optical characterization of oral mucosa can potentially be used to detect oral carcinogenesis in early stages. PMID:26725720

Noninvasive imaging of oral premalignancy and malignancy

NASA Astrophysics Data System (ADS)

Wilder-Smith, Petra; Krasieva, T.; Jung, W.; You, J. S.; Chen, Z.; Osann, K.; Tromberg, B.

2005-04-01

Objectives: Early detection of cancer and its curable precursors remains the best way to ensure patient survival and quality of life. Despite significant advances in treatment, oral cancer still results in 10,000 U.S. deaths annually, mainly due to the late detection of most oral lesions. Specific aim was to use a combination of non-invasive optical in vivo technologies to test a multi-modality approach to non-invasive diagnostics of oral premalignancy and malignancy. Methods: In the hamster cheek pouch model (120 hamsters), in vivo optical coherence tomography (OCT) and optical Doppler tomography (ODT) mapped epithelial, subepithelial and vascular change throughout carcinogenesis in specific, marked sites. In vivo multi-wavelength multi-photon (MPM) and second harmonic generated (SHG) fluorescence techniques provided parallel data on surface and subsurface tissue structure, specifically collagen presence and structure, cellular presence, and vasculature. Images were diagnosed by 2 blinded, pre-standardized investigators using a standardized scale from 0-6 for all modalities. After sacrifice, histopathological sections were prepared and pathology evaluated on a scale of 0-6. ANOVA techniques compared imaging diagnostics with histopathology. 95% confidence limits of the sensitivity and specificity were established for the diagnostic capability of OCT/ODT+ MPM/SHG using ROC curves and kappa statistics. Results: Imaging data were reproducibly obtained with good accuracy. Carcinogenesis-related structural and vascular changes were clearly visible to tissue depths of 2mm. Sensitivity (OCT/ODT alone: 71-88%; OCT+MPM/SHG: 79-91%) and specificity (OCT alone: 62-83%;OCT+MPM/SHG: 67-90%) compared well with conventional techniques. Conclusions: OCT/ODT and MPM/SHG are promising non-invasive in vivo diagnostic modalities for oral dysplasia and malignancy. Supported by CRFA 30003, CCRP 00-01391V-20235, NIH (LAMMP) RR01192, DOE DE903-91ER 61227, NIH EB-00293 CA91717, NSF BES-86924, AFOSR FA 9550-04-1-0101.

Random Forest Algorithm for the Classification of Neuroimaging Data in Alzheimer's Disease: A Systematic Review.

PubMed

Sarica, Alessia; Cerasa, Antonio; Quattrone, Aldo

2017-01-01

Objective: Machine learning classification has been the most important computational development in the last years to satisfy the primary need of clinicians for automatic early diagnosis and prognosis. Nowadays, Random Forest (RF) algorithm has been successfully applied for reducing high dimensional and multi-source data in many scientific realms. Our aim was to explore the state of the art of the application of RF on single and multi-modal neuroimaging data for the prediction of Alzheimer's disease. Methods: A systematic review following PRISMA guidelines was conducted on this field of study. In particular, we constructed an advanced query using boolean operators as follows: ("random forest" OR "random forests") AND neuroimaging AND ("alzheimer's disease" OR alzheimer's OR alzheimer) AND (prediction OR classification) . The query was then searched in four well-known scientific databases: Pubmed, Scopus, Google Scholar and Web of Science. Results: Twelve articles-published between the 2007 and 2017-have been included in this systematic review after a quantitative and qualitative selection. The lesson learnt from these works suggest that when RF was applied on multi-modal data for prediction of Alzheimer's disease (AD) conversion from the Mild Cognitive Impairment (MCI), it produces one of the best accuracies to date. Moreover, the RF has important advantages in terms of robustness to overfitting, ability to handle highly non-linear data, stability in the presence of outliers and opportunity for efficient parallel processing mainly when applied on multi-modality neuroimaging data, such as, MRI morphometric, diffusion tensor imaging, and PET images. Conclusions: We discussed the strengths of RF, considering also possible limitations and by encouraging further studies on the comparisons of this algorithm with other commonly used classification approaches, particularly in the early prediction of the progression from MCI to AD.

Windows on the Human Body – in Vivo High-Field Magnetic Resonance Research and Applications in Medicine and Psychology

PubMed Central

Moser, Ewald; Meyerspeer, Martin; Fischmeister, Florian Ph. S.; Grabner, Günther; Bauer, Herbert; Trattnig, Siegfried

2010-01-01

Analogous to the evolution of biological sensor-systems, the progress in “medical sensor-systems”, i.e., diagnostic procedures, is paradigmatically described. Outstanding highlights of this progress are magnetic resonance imaging (MRI) and spectroscopy (MRS), which enable non-invasive, in vivo acquisition of morphological, functional, and metabolic information from the human body with unsurpassed quality. Recent achievements in high and ultra-high field MR (at 3 and 7 Tesla) are described, and representative research applications in Medicine and Psychology in Austria are discussed. Finally, an overview of current and prospective research in multi-modal imaging, potential clinical applications, as well as current limitations and challenges is given. PMID:22219684

Partnering for transportation safety : human-centered systems : operator fatigue management conference

DOT National Transportation Integrated Search

2000-01-01

This Conference was intended to enlist support for, and participation in, a new multi-modal DOT safety initiative. This initiative builds on the modal agency programs within DOT to develop techniques that transportation operating companies can employ...

Multi-Modal Traveler Information System - VMS/HAR State-of-the-Practice

DOT National Transportation Integrated Search

1997-05-30

The Gary-Chicago-Milwaukee (GCM) Corridor is one of the four "Priority Corridors" established by the United States Congress in the Inter-Modal Surface Transportation Efficiency Act (ISTEA). These corridors have been selected for special federal trans...

Detailed description of the Mayo/IBM PACS

NASA Astrophysics Data System (ADS)

Gehring, Dale G.; Persons, Kenneth R.; Rothman, Melvyn L.; Salutz, James R.; Morin, Richard L.

1991-07-01

The Mayo Clinic and IBM/Rochester have jointly developed a picture archiving system (PACS) for use with Mayo's MRI and Neuro-CT imaging modalities. The system was developed to replace the imaging system's vendor-supplied magnetic tape archiving capability. The system consists of seven MR imagers and nine CT scanners, each interfaced to the PACS via IBM Personal System/2(tm) (PS/2) computers, which act as gateways from the imaging modality to the PACS network. The PAC system operates on the token-ring component of Mayo's city-wide local area network. Also on the PACS network are four optical storage subsystems used for image archival, three optical subsystems used for image retrieval, an IBM Application System/400(tm) (AS/400) computer used for database management and multiple PS/2-based image display systems and their image servers.

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

PubMed Central

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

2015-01-01

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

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Real-time photoacoustic and ultrasound dual-modality imaging system facilitated with graphics processing unit and code parallel optimization.

PubMed

Yuan, Jie; Xu, Guan; Yu, Yao; Zhou, Yu; Carson, Paul L; Wang, Xueding; Liu, Xiaojun

2013-08-01

Photoacoustic tomography (PAT) offers structural and functional imaging of living biological tissue with highly sensitive optical absorption contrast and excellent spatial resolution comparable to medical ultrasound (US) imaging. We report the development of a fully integrated PAT and US dual-modality imaging system, which performs signal scanning, image reconstruction, and display for both photoacoustic (PA) and US imaging all in a truly real-time manner. The back-projection (BP) algorithm for PA image reconstruction is optimized to reduce the computational cost and facilitate parallel computation on a state of the art graphics processing unit (GPU) card. For the first time, PAT and US imaging of the same object can be conducted simultaneously and continuously, at a real-time frame rate, presently limited by the laser repetition rate of 10 Hz. Noninvasive PAT and US imaging of human peripheral joints in vivo were achieved, demonstrating the satisfactory image quality realized with this system. Another experiment, simultaneous PAT and US imaging of contrast agent flowing through an artificial vessel, was conducted to verify the performance of this system for imaging fast biological events. The GPU-based image reconstruction software code for this dual-modality system is open source and available for download from http://sourceforge.net/projects/patrealtime.

Two-dimensional multi-frequency imaging of a tumor inclusion in a homogeneous breast phantom using the harmonic motion Doppler imaging method.

PubMed

Tafreshi, Azadeh Kamali; Top, Can Barış; Gençer, Nevzat Güneri

2017-06-21

Harmonic motion microwave Doppler imaging (HMMDI) is a novel imaging modality for imaging the coupled electrical and mechanical properties of body tissues. In this paper, we used two experimental systems with different receiver configurations to obtain HMMDI images from tissue-mimicking phantoms at multiple vibration frequencies between 15 Hz and 35 Hz. In the first system, we used a spectrum analyzer to obtain the Doppler data in the frequency domain, while in the second one, we used a homodyne receiver that was designed to acquire time-domain data. The developed phantoms mimicked the elastic and dielectric properties of breast fat tissue, and included a [Formula: see text] mm cylindrical inclusion representing the tumor. A focused ultrasound probe was mechanically scanned in two lateral dimensions to obtain two-dimensional HMMDI images of the phantoms. The inclusions were resolved inside the fat phantom using both experimental setups. The image resolution increased with increasing vibration frequency. The designed receiver showed higher sensitivity than the spectrum analyzer measurements. The results also showed that time-domain data acquisition should be used to fully exploit the potential of the HMMDI method.

Two-dimensional multi-frequency imaging of a tumor inclusion in a homogeneous breast phantom using the harmonic motion Doppler imaging method

NASA Astrophysics Data System (ADS)

Kamali Tafreshi, Azadeh; Barış Top, Can; Güneri Gençer, Nevzat

2017-06-01

Harmonic motion microwave Doppler imaging (HMMDI) is a novel imaging modality for imaging the coupled electrical and mechanical properties of body tissues. In this paper, we used two experimental systems with different receiver configurations to obtain HMMDI images from tissue-mimicking phantoms at multiple vibration frequencies between 15 Hz and 35 Hz. In the first system, we used a spectrum analyzer to obtain the Doppler data in the frequency domain, while in the second one, we used a homodyne receiver that was designed to acquire time-domain data. The developed phantoms mimicked the elastic and dielectric properties of breast fat tissue, and included a 14~\\text{mm}× 9 mm cylindrical inclusion representing the tumor. A focused ultrasound probe was mechanically scanned in two lateral dimensions to obtain two-dimensional HMMDI images of the phantoms. The inclusions were resolved inside the fat phantom using both experimental setups. The image resolution increased with increasing vibration frequency. The designed receiver showed higher sensitivity than the spectrum analyzer measurements. The results also showed that time-domain data acquisition should be used to fully exploit the potential of the HMMDI method.

In vivo time-serial multi-modality optical imaging in a mouse model of ovarian tumorigenesis

PubMed Central

Watson, Jennifer M; Marion, Samuel L; Rice, Photini F; Bentley, David L; Besselsen, David G; Utzinger, Urs; Hoyer, Patricia B; Barton, Jennifer K

2014-01-01

Identification of the early microscopic changes associated with ovarian cancer may lead to development of a diagnostic test for high-risk women. In this study we use optical coherence tomography (OCT) and multiphoton microscopy (MPM) (collecting both two photon excited fluorescence [TPEF] and second harmonic generation [SHG]) to image mouse ovaries in vivo at multiple time points. We demonstrate the feasibility of imaging mouse ovaries in vivo during a long-term survival study and identify microscopic changes associated with early tumor development. These changes include alterations in tissue microstructure, as seen by OCT, alterations in cellular fluorescence and morphology, as seen by TPEF, and remodeling of collagen structure, as seen by SHG. These results suggest that a combined OCT-MPM system may be useful for early detection of ovarian cancer. PMID:24145178

Fabricating optical phantoms to simulate skin tissue properties and microvasculatures

NASA Astrophysics Data System (ADS)

Sheng, Shuwei; Wu, Qiang; Han, Yilin; Dong, Erbao; Xu, Ronald

2015-03-01

This paper introduces novel methods to fabricate optical phantoms that simulate the morphologic, optical, and microvascular characteristics of skin tissue. The multi-layer skin-simulating phantom was fabricated by a light-cured 3D printer that mixed and printed the colorless light-curable ink with the absorption and the scattering ingredients for the designated optical properties. The simulated microvascular network was fabricated by a soft lithography process to embed microchannels in polydimethylsiloxane (PDMS) phantoms. The phantoms also simulated vascular anomalies and hypoxia commonly observed in cancer. A dual-modal multispectral and laser speckle imaging system was used for oxygen and perfusion imaging of the tissue-simulating phantoms. The light-cured 3D printing technique and the soft lithography process may enable freeform fabrication of skin-simulating phantoms that embed microvessels for image and drug delivery applications.

Survey on the use of smart and adaptive engineering systems in medicine.

PubMed

Abbod, M F; Linkens, D A; Mahfouf, M; Dounias, G

2002-11-01

In this paper, the current published knowledge about smart and adaptive engineering systems in medicine is reviewed. The achievements of frontier research in this particular field within medical engineering are described. A multi-disciplinary approach to the applications of adaptive systems is observed from the literature surveyed. The three modalities of diagnosis, imaging and therapy are considered to be an appropriate classification method for the analysis of smart systems being applied to specified medical sub-disciplines. It is expected that future research in biomedicine should identify subject areas where more advanced intelligent systems could be applied than is currently evident. The literature provides evidence of hybridisation of different types of adaptive and smart systems with applications in different areas of medical specifications. Copyright 2002 Elsevier Science B.V.

A multi-modal stereo microscope based on a spatial light modulator.

PubMed

Lee, M P; Gibson, G M; Bowman, R; Bernet, S; Ritsch-Marte, M; Phillips, D B; Padgett, M J

2013-07-15

Spatial Light Modulators (SLMs) can emulate the classic microscopy techniques, including differential interference (DIC) contrast and (spiral) phase contrast. Their programmability entails the benefit of flexibility or the option to multiplex images, for single-shot quantitative imaging or for simultaneous multi-plane imaging (depth-of-field multiplexing). We report the development of a microscope sharing many of the previously demonstrated capabilities, within a holographic implementation of a stereo microscope. Furthermore, we use the SLM to combine stereo microscopy with a refocusing filter and with a darkfield filter. The instrument is built around a custom inverted microscope and equipped with an SLM which gives various imaging modes laterally displaced on the same camera chip. In addition, there is a wide angle camera for visualisation of a larger region of the sample.

Enhancing resource coordination for multi-modal evacuation planning.

DOT National Transportation Integrated Search

2013-01-01

This research project seeks to increase knowledge about coordinating effective multi-modal evacuation for disasters. It does so by identifying, evaluating, and assessing : current transportation management approaches for multi-modal evacuation planni...

Mutual information-based template matching scheme for detection of breast masses: from mammography to digital breast tomosynthesis

PubMed Central

Mazurowski, Maciej A; Lo, Joseph Y; Harrawood, Brian P; Tourassi, Georgia D

2011-01-01

Development of a computational decision aid for a new medical imaging modality typically is a long and complicated process. It consists of collecting data in the form of images and annotations, development of image processing and pattern recognition algorithms for analysis of the new images and finally testing of the resulting system. Since new imaging modalities are developed more rapidly than ever before, any effort for decreasing the time and cost of this development process could result in maximizing the benefit of the new imaging modality to patients by making the computer aids quickly available to radiologists that interpret the images. In this paper, we make a step in this direction and investigate the possibility of translating the knowledge about the detection problem from one imaging modality to another. Specifically, we present a computer-aided detection (CAD) system for mammographic masses that uses a mutual information-based template matching scheme with intelligently selected templates. We presented principles of template matching with mutual information for mammography before. In this paper, we present an implementation of those principles in a complete computer-aided detection system. The proposed system, through an automatic optimization process, chooses the most useful templates (mammographic regions of interest) using a large database of previously collected and annotated mammograms. Through this process, the knowledge about the task of detecting masses in mammograms is incorporated in the system. Then we evaluate whether our system developed for screen-film mammograms can be successfully applied not only to other mammograms but also to digital breast tomosynthesis (DBT) reconstructed slices without adding any DBT cases for training. Our rationale is that since mutual information is known to be a robust intermodality image similarity measure, it has high potential of transferring knowledge between modalities in the context of the mass detection task. Experimental evaluation of the system on mammograms showed competitive performance compared to other mammography CAD systems recently published in the literature. When the system was applied “as-is” to DBT, its performance was notably worse than that for mammograms. However, with a simple additional preprocessing step, the performance of the system reached levels similar to that obtained for mammograms. In conclusion, the presented CAD system not only performed competitively on screen-film mammograms but it also performed robustly on DBT showing that direct transfer of knowledge across breast imaging modalities for mass detection is in fact possible. PMID:21554985

Potential of PET-MRI for imaging of non-oncologic musculoskeletal disease.

PubMed

Kogan, Feliks; Fan, Audrey P; Gold, Garry E

2016-12-01

Early detection of musculoskeletal disease leads to improved therapies and patient outcomes, and would benefit greatly from imaging at the cellular and molecular level. As it becomes clear that assessment of multiple tissues and functional processes are often necessary to study the complex pathogenesis of musculoskeletal disorders, the role of multi-modality molecular imaging becomes increasingly important. New positron emission tomography-magnetic resonance imaging (PET-MRI) systems offer to combine high-resolution MRI with simultaneous molecular information from PET to study the multifaceted processes involved in numerous musculoskeletal disorders. In this article, we aim to outline the potential clinical utility of hybrid PET-MRI to these non-oncologic musculoskeletal diseases. We summarize current applications of PET molecular imaging in osteoarthritis (OA), rheumatoid arthritis (RA), metabolic bone diseases and neuropathic peripheral pain. Advanced MRI approaches that reveal biochemical and functional information offer complementary assessment in soft tissues. Additionally, we discuss technical considerations for hybrid PET-MR imaging including MR attenuation correction, workflow, radiation dose, and quantification.

Photoacoustic and ultrasound dual-modality imaging of human peripheral joints

NASA Astrophysics Data System (ADS)

Xu, Guan; Rajian, Justin R.; Girish, Gandikota; Kaplan, Mariana J.; Fowlkes, J. Brian; Carson, Paul L.; Wang, Xueding

2013-01-01

A photoacoustic (PA) and ultrasound (US) dual modality system, for imaging human peripheral joints, is introduced. The system utilizes a commercial US unit for both US control imaging and PA signal acquisition. Preliminary in vivo evaluation of the system, on normal volunteers, revealed that this system can recover both the structural and functional information of intra- and extra-articular tissues. Confirmed by the control US images, the system, on the PA mode, can differentiate tendon from surrounding soft tissue based on the endogenous optical contrast. Presenting both morphological and pathological information in joint, this system holds promise for diagnosis and characterization of inflammatory joint diseases such as rheumatoid arthritis.

Multi Modal Anticipation in Fuzzy Space

NASA Astrophysics Data System (ADS)

Asproth, Viveca; Holmberg, Stig C.; Hâkansson, Anita

2006-06-01

We are all stakeholders in the geographical space, which makes up our common living and activity space. This means that a careful, creative, and anticipatory planning, design, and management of that space will be of paramount importance for our sustained life on earth. Here it is shown that the quality of such planning could be significantly increased with help of a computer based modelling and simulation tool. Further, the design and implementation of such a tool ought to be guided by the conceptual integration of some core concepts like anticipation and retardation, multi modal system modelling, fuzzy space modelling, and multi actor interaction.

An image based vibration sensor for soft tissue modal analysis in a Digital Image Elasto Tomography (DIET) system.

PubMed

Feng, Sheng; Lotz, Thomas; Chase, J Geoffrey; Hann, Christopher E

2010-01-01

Digital Image Elasto Tomography (DIET) is a non-invasive elastographic breast cancer screening technology, based on image-based measurement of surface vibrations induced on a breast by mechanical actuation. Knowledge of frequency response characteristics of a breast prior to imaging is critical to maximize the imaging signal and diagnostic capability of the system. A feasibility analysis for a non-invasive image based modal analysis system is presented that is able to robustly and rapidly identify resonant frequencies in soft tissue. Three images per oscillation cycle are enough to capture the behavior at a given frequency. Thus, a sweep over critical frequency ranges can be performed prior to imaging to determine critical imaging settings of the DIET system to optimize its tumor detection performance.

Radiation dose reduction and new image modalities development for interventional C-arm imaging system

NASA Astrophysics Data System (ADS)

Niu, Kai

Cardiovascular disease and stroke are the leading health problems and causes of death in the US. Due to the minimally invasive nature of the evolution of image guided techniques, interventional radiological procedures are becoming more common and are preferred in treating many cardiovascular diseases and strokes. In addition, with the recent advances in hardware and device technology, the speed and efficacy of interventional treatment has significantly improved. This implies that more image modalities can be developed based on the current C-arm system and patients treated in interventional suites can potentially experience better health outcomes. However, during the treatment patients are irradiated with substantial amounts of ionizing radiation with a high dose rate (digital subtraction angiography (DSA) with 3muGy/frame and 3D cone beam CT image with 0.36muGy/frame for a Siemens Artis Zee biplane system) and/or a long irradiation time (a roadmapping image sequence can be as long as one hour during aneurysm embolization). As a result, the patient entrance dose is extremely high. Despite the fact that the radiation dose is already substantial, image quality is not always satisfactory. By default a temporal average is used in roadmapping images to overcome poor image quality, but this technique can result in motion blurred images. Therefore, reducing radiation dose while maintaining or even improving the image quality is an important area for continued research. This thesis is focused on improving the clinical applications of C-arm cone beam CT systems in two ways: (1) Improve the performance of current image modalities on the C-arm system. (2) Develop new image modalities based on the current system. To be more specific, the objectives are to reduce radiation dose for current modalities (e.g., DSA, fluoroscopy, roadmapping, and cone beam CT) and enable cone beam CT perfusion and time resolved cone beam CT angiography that can be used to diagnose and triage acute ischemic stroke patients more efficiently compared with the current clinical work-flow. The animal and patient cases presented in this thesis are focused towards but not limited to neurointerventional applications.

Hybrid-modality ocular imaging using a clinical ultrasound system and nanosecond pulsed laser.

PubMed

Lim, Hoong-Ta; Matham, Murukeshan Vadakke

2015-07-01

Hybrid optical modality imaging is a special type of multimodality imaging significantly used in the recent past in order to harness the strengths of different imaging methods as well as to furnish complementary information beyond that provided by any individual method. We present a hybrid-modality imaging system based on a commercial clinical ultrasound imaging (USI) system using a linear array ultrasound transducer (UST) and a tunable nanosecond pulsed laser as the source. The integrated system uses photoacoustic imaging (PAI) and USI for ocular imaging to provide the complementary absorption and structural information of the eye. In this system, B-mode images from PAI and USI are acquired at 10 Hz and about 40 Hz, respectively. A linear array UST makes the system much faster compared to other ocular imaging systems using a single-element UST to form B-mode images. The results show that the proposed instrumentation is able to incorporate PAI and USI in a single setup. The feasibility and efficiency of this developed probe system was illustrated by using enucleated pig eyes as test samples. It was demonstrated that PAI could successfully capture photoacoustic signals from the iris, anterior lens surface, and posterior pole, while USI could accomplish the mapping of the eye to reveal the structures like the cornea, anterior chamber, lens, iris, and posterior pole. This system and the proposed methodology are expected to enable ocular disease diagnostic applications and can be used as a preclinical imaging system.

Correlation of morphological and molecular parameters for colon cancer

NASA Astrophysics Data System (ADS)

Yuan, Shuai; Roney, Celeste A.; Li, Qian; Jiang, James; Cable, Alex; Summers, Ronald M.; Chen, Yu

2010-02-01

Colorectal cancer (CRC) is the second leading cause of cancer death in the United States. There is great interest in studying the relationship among microstructures and molecular processes of colorectal cancer during its progression at early stages. In this study, we use our multi-modality optical system that could obtain co-registered optical coherence tomography (OCT) and fluorescence molecular imaging (FMI) images simultaneously to study CRC. The overexpressed carbohydrate α-L-fucose on the surfaces of polyps facilitates the bond of adenomatous polyps with UEA-1 and is used as biomarker. Tissue scattering coefficient derived from OCT axial scan is used as quantitative value of structural information. Both structural images from OCT and molecular images show spatial heterogeneity of tumors. Correlations between those values are analyzed and demonstrate that scattering coefficients are positively correlated with FMI signals in conjugated. In UEA-1 conjugated samples (8 polyps and 8 control regions), the correlation coefficient is ranged from 0.45 to 0.99. These findings indicate that the microstructure of polyps is changed gradually during cancer progression and the change is well correlated with certain molecular process. Our study demonstrated that multi-parametric imaging is able to simultaneously detect morphology and molecular information and it can enable spatially and temporally correlated studies of structure-function relationships during tumor progression.

Mobile, Multi-modal, Label-Free Imaging Probe Analysis of Choroidal Oximetry and Retinal Hypoxia

DTIC Science & Technology

2016-10-01

Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Coherent anti-stokes Raman spectroscopy ( CARS ) can be used to detect differences in the oxygen content...oxygen, eye, retina, photoreceptor, neuron, TRPM7, neurodegeneration, neurotoxicity, coherent anti-Stokes Raman spectroscopy, CARS , mouse 16...ANSI Std. Z39.18 Section 1: Introduction The study is based on the premise that Coherent Anti-Stokes Raman scattering ( CARS ) imaging provides a

Single-Step Assembly of Multi-Modal Imaging Nanocarriers: MRI and Long-Wavelength Fluorescence Imaging

PubMed Central

Pinkerton, Nathalie M.; Gindy, Marian E.; Calero-DdelC, Victoria L.; Wolfson, Theodore; Pagels, Robert F.; Adler, Derek; Gao, Dayuan; Li, Shike; Wang, Ruobing; Zevon, Margot; Yao, Nan; Pacheco, Carlos; Therien, Michael J.; Rinaldi, Carlos; Sinko, Patrick J.

2015-01-01

MRI and NIR-active, multi-modal Composite NanoCarriers (CNCs) are prepared using a simple, one-step process, Flash NanoPrecipitation (FNP). The FNP process allows for the independent control of the hydrodynamic diameter, co-core excipient and NIR dye loading, and iron oxide-based nanocrystal (IONC) content of the CNCs. In the controlled precipitation process, 10 nm IONCs are encapsulated into poly(ethylene glycol) stabilized CNCs to make biocompatible T2 contrast agents. By adjusting the formulation, CNC size is tuned between 80 and 360 nm. Holding the CNC size constant at an intensity weighted average diameter of 99 ± 3 nm (PDI width 28 nm), the particle relaxivity varies linearly with encapsulated IONC content ranging from 66 to 533 mM-1s-1 for CNCs formulated with 4 to 16 wt% IONC. To demonstrate the use of CNCs as in vivo MRI contrast agents, CNCs are surface functionalized with liver targeting hydroxyl groups. The CNCs enable the detection of 0.8 mm3 non-small cell lung cancer metastases in mice livers via MRI. Incorporating the hydrophobic, NIR dye PZn3 into CNCs enables complementary visualization with long-wavelength fluorescence at 800 nm. In vivo imaging demonstrates the ability of CNCs to act both as MRI and fluorescent imaging agents. PMID:25925128

Enterprise-scale image distribution with a Web PACS.

PubMed

Gropper, A; Doyle, S; Dreyer, K

1998-08-01

The integration of images with existing and new health care information systems poses a number of challenges in a multi-facility network: image distribution to clinicians; making DICOM image headers consistent across information systems; and integration of teleradiology into PACS. A novel, Web-based enterprise PACS architecture introduced at Massachusetts General Hospital provides a solution. Four AMICAS Web/Intranet Image Servers were installed as the default DICOM destination of 10 digital modalities. A fifth AMICAS receives teleradiology studies via the Internet. Each AMICAS includes: a Java-based interface to the IDXrad radiology information system (RIS), a DICOM autorouter to tape-library archives and to the Agfa PACS, a wavelet image compressor/decompressor that preserves compatibility with DICOM workstations, a Web server to distribute images throughout the enterprise, and an extensible interface which permits links between other HIS and AMICAS. Using wavelet compression and Internet standards as its native formats, AMICAS creates a bridge to the DICOM networks of remote imaging centers via the Internet. This teleradiology capability is integrated into the DICOM network and the PACS thereby eliminating the need for special teleradiology workstations. AMICAS has been installed at MGH since March of 1997. During that time, it has been a reliable component of the evolving digital image distribution system. As a result, the recently renovated neurosurgical ICU will be filmless and use only AMICAS workstations for mission-critical patient care.

Development of an electromagnetic imaging system for well bore integrity inspection

NASA Astrophysics Data System (ADS)

Plotnikov, Yuri; Wheeler, Frederick W.; Mandal, Sudeep; Climent, Helene C.; Kasten, A. Matthias; Ross, William

2017-02-01

State-of-the-art imaging technologies for monitoring the integrity of oil and gas well bores are typically limited to the inspection of metal casings and cement bond interfaces close to the first casing region. The objective of this study is to develop and evaluate a novel well-integrity inspection system that is capable of providing enhanced information about the flaw structure and topology of hydrocarbon producing well bores. In order to achieve this, we propose the development of a multi-element electromagnetic (EM) inspection tool that can provide information about material loss in the first and second casing structure as well as information about eccentricity between multiple casing strings. Furthermore, the information gathered from the EM inspection tool will be combined with other imaging modalities (e.g. data from an x-ray backscatter imaging device). The independently acquired data are then fused to achieve a comprehensive assessment of integrity with greater accuracy. A test rig composed of several concentric metal casings with various defect structures was assembled and imaged. Initial test results were obtained with a scanning system design that includes a single transmitting coil and several receiving coils mounted on a single rod. A mechanical linear translation stage was used to move the EM sensors in the axial direction during data acquisition. For simplicity, a single receiving coil and repetitive scans were employed to simulate performance of the designed receiving sensor array system. The resulting electromagnetic images enable the detection of the metal defects in the steel pipes. Responses from several sensors were used to assess the location and amount of material loss in the first and second metal pipe as well as the relative eccentric position between these two pipes. The results from EM measurements and x-ray backscatter simulations demonstrate that data fusion from several sensing modalities can provide an enhanced assessment of flaw structures in producing well bores and potentially allow for early detection of anomalies that if undetected might lead to catastrophic failures.

ACIR: automatic cochlea image registration

NASA Astrophysics Data System (ADS)

Al-Dhamari, Ibraheem; Bauer, Sabine; Paulus, Dietrich; Lissek, Friedrich; Jacob, Roland

2017-02-01

Efficient Cochlear Implant (CI) surgery requires prior knowledge of the cochlea's size and its characteristics. This information helps to select suitable implants for different patients. To get these measurements, a segmentation method of cochlea medical images is needed. An important pre-processing step for good cochlea segmentation involves efficient image registration. The cochlea's small size and complex structure, in addition to the different resolutions and head positions during imaging, reveals a big challenge for the automated registration of the different image modalities. In this paper, an Automatic Cochlea Image Registration (ACIR) method for multi- modal human cochlea images is proposed. This method is based on using small areas that have clear structures from both input images instead of registering the complete image. It uses the Adaptive Stochastic Gradient Descent Optimizer (ASGD) and Mattes's Mutual Information metric (MMI) to estimate 3D rigid transform parameters. The use of state of the art medical image registration optimizers published over the last two years are studied and compared quantitatively using the standard Dice Similarity Coefficient (DSC). ACIR requires only 4.86 seconds on average to align cochlea images automatically and to put all the modalities in the same spatial locations without human interference. The source code is based on the tool elastix and is provided for free as a 3D Slicer plugin. Another contribution of this work is a proposed public cochlea standard dataset which can be downloaded for free from a public XNAT server.

Fourier Spectral Filter Array for Optimal Multispectral Imaging.

PubMed

Jia, Jie; Barnard, Kenneth J; Hirakawa, Keigo

2016-04-01

Limitations to existing multispectral imaging modalities include speed, cost, range, spatial resolution, and application-specific system designs that lack versatility of the hyperspectral imaging modalities. In this paper, we propose a novel general-purpose single-shot passive multispectral imaging modality. Central to this design is a new type of spectral filter array (SFA) based not on the notion of spatially multiplexing narrowband filters, but instead aimed at enabling single-shot Fourier transform spectroscopy. We refer to this new SFA pattern as Fourier SFA, and we prove that this design solves the problem of optimally sampling the hyperspectral image data.

The year 2013 in the European Heart Journal--Cardiovascular Imaging: Part II.

PubMed

Plein, Sven; Edvardsen, Thor; Pierard, Luc A; Saraste, Antti; Knuuti, Juhani; Maurer, Gerald; Lancellotti, Patrizio

2014-08-01

The new multi-modality cardiovascular imaging journal, European Heart Journal - Cardiovascular Imaging, was created in 2012. Here we summarize the most important studies from the journal's second year in two articles. Part I of the review has summarized studies in myocardial function, myocardial ischaemia, and emerging techniques in cardiovascular imaging. Part II is focussed on valvular heart diseases, heart failure, cardiomyopathies, and congenital heart diseases. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.

Changing Utilization of Noninvasive Diagnostic Imaging Over 2 Decades: An Examination Family-Focused Analysis of Medicare Claims Using the Neiman Imaging Types of Service Categorization System.

PubMed

Rosman, David A; Duszak, Richard; Wang, Wenyi; Hughes, Danny R; Rosenkrantz, Andrew B

2018-02-01

The objective of our study was to use a new modality and body region categorization system to assess changing utilization of noninvasive diagnostic imaging in the Medicare fee-for-service population over a recent 20-year period (1994-2013). All Medicare Part B Physician Fee Schedule services billed between 1994 and 2013 were identified using Physician/Supplier Procedure Summary master files. Billed codes for diagnostic imaging were classified using the Neiman Imaging Types of Service (NITOS) coding system by both modality and body region. Utilization rates per 1000 beneficiaries were calculated for families of services. Among all diagnostic imaging modalities, growth was greatest for MRI (+312%) and CT (+151%) and was lower for ultrasound, nuclear medicine, and radiography and fluoroscopy (range, +1% to +31%). Among body regions, service growth was greatest for brain (+126%) and spine (+74%) imaging; showed milder growth (range, +18% to +67%) for imaging of the head and neck, breast, abdomen and pelvis, and extremity; and showed slight declines (range, -2% to -7%) for cardiac and chest imaging overall. The following specific imaging service families showed massive (> +100%) growth: cardiac CT, cardiac MRI, and breast MRI. NITOS categorization permits identification of temporal shifts in noninvasive diagnostic imaging by specific modality- and region-focused families, providing a granular understanding and reproducible analysis of global changes in imaging overall. Service family-level perspectives may help inform ongoing policy efforts to optimize imaging utilization and appropriateness.

Initial tests of a prototype MRI-compatible PET imager

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Lemieux, Susan; Velan, S. Sendhil; Kross, Brain; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.; Wojcik, Randy

2006-12-01

Multi-modality imaging is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET fused with anatomical structure images created by MRI, will allow the correlation of form with function. Our group (a collaboration of West Virginia University and Jefferson Lab) is developing a system to acquire MRI and PET images contemporaneously. The prototype device consists of two opposed detector heads, operating in coincidence mode with an active FOV of 5×5×4 cm 3. Each MRI-PET detector module consists of an array of LSO detector elements (2.5×2.5×15 mm 3) coupled through a long fiber optic light guide to a single Hamamatsu flat panel PSPMT. The fiber optic light guide is made of a glued assembly of 2 mm diameter acrylic fibers with a total length of 2.5 m. The use of a light guides allows the PSPMTs to be positioned outside the bore of the 3 T General Electric MRI scanner used in the tests. Photon attenuation in the light guides resulted in an energy resolution of ˜60% FWHM, interaction of the magnetic field with PSPMT further reduced energy resolution to ˜85% FWHM. Despite this effect, excellent multi-plane PET and MRI images of a simple disk phantom were acquired simultaneously. Future work includes improved light guides, optimized magnetic shielding for the PSPMTs, construction of specialized coils to permit high-resolution MRI imaging, and use of the system to perform simultaneous PET and MRI or MR-spectroscopy .

An X-Ray computed tomography/positron emission tomography system designed specifically for breast imaging.

PubMed

Boone, John M; Yang, Kai; Burkett, George W; Packard, Nathan J; Huang, Shih-ying; Bowen, Spencer; Badawi, Ramsey D; Lindfors, Karen K

2010-02-01

Mammography has served the population of women who are at-risk for breast cancer well over the past 30 years. While mammography has undergone a number of changes as digital detector technology has advanced, other modalities such as computed tomography have experienced technological sophistication over this same time frame as well. The advent of large field of view flat panel detector systems enable the development of breast CT and several other niche CT applications, which rely on cone beam geometry. The breast, it turns out, is well suited to cone beam CT imaging because the lack of bones reduces artifacts, and the natural tapering of the breast anteriorly reduces the x-ray path lengths through the breast at large cone angle, reducing cone beam artifacts as well. We are in the process of designing a third prototype system which will enable the use of breast CT for image guided interventional procedures. This system will have several copies fabricated so that several breast CT scanners can be used in a multi-institutional clinical trial to better understand the role that this technology can bring to breast imaging.

Large focal nodular hyperplasia and extrahepatic portosystemic shunt in a male patient: multi-modality imaging features.

PubMed

Kitzing, Yu Xuan; Gallagher, James; Waugh, Richard

2011-10-01

Congenital extrahepatic portocaval shunt is a rare condition that is described mostly in female patients. We report an unusual case of a young adult male patient with type 1 congenital extrahepatic portocaval shunt with associated development of a focal nodular hyperplasia on a background of regenerative nodules. With multi-slice CT utilisation, there is increased detection of portocaval malformation in asymptomatic patients. This congenital variant is clinically significant with associated development of hepatocellular lesions, hepatic dysfunction and/or encephalopathy. © 2011 The Authors. Journal of Medical Imaging and Radiation Oncology © 2011 The Royal Australian and New Zealand College of Radiologists.

Combined optical tomographic and magnetic resonance imaging of tumor bearing mice

NASA Astrophysics Data System (ADS)

Masciotti, J.; Abdoulaev, G.; Hur, J.; Papa, J.; Bae, J.; Huang, J.; Yamashiro, D.; Kandel, J.; Hielscher, A. H.

2005-04-01

With the advent of small animal imaging systems, it has become possible to non-invasively monitor the progression of diseases in living small animals and study the efficacy of drugs and treatment protocols. Magnetic resonance imaging (MRI) is an established imaging modality capable of obtaining high resolution anatomical images as well as studying cerebral blood volume (CBV), cerebral blood flow (CBF), and cerebral metabolic rate of oxygen (CMRO2). Optical tomography, on the other hand, is an emerging imaging modality, which, while much lower in spatial resolution and insensitive to CBF, can separate the effects of oxyhemoglobin, deoxyhemoglobin, and CBV with high temporal resolution. In this study we present our first results concerning coregistration of MRI and optical data. By applying both modalities to imaging of kidney tumors in mice that undergo VEGF treatment, we illustrate how these imaging modalities can supplement each other and cross validation can be performed.

A dual-modality optical coherence tomography and selective plane illumination microscopy system for mouse embryonic imaging

NASA Astrophysics Data System (ADS)

Wu, Chen; Ran, Shihao; Le, Henry; Singh, Manmohan; Larina, Irina V.; Mayerich, David; Dickinson, Mary E.; Larin, Kirill V.

2017-02-01

Both optical coherence tomography (OCT) and selective plane illumination microscopy (SPIM) are frequently used in mouse embryonic research for high-resolution three-dimensional imaging. However, each of these imaging methods provide a unique and independent advantage: SPIM provides morpho-functional information through immunofluorescence and OCT provides a method for whole-embryo 3D imaging. In this study, we have combined rotational imaging OCT and SPIM into a single, dual-modality device to image E9.5 mouse embryos. The results demonstrate that the dual-modality setup is able to provide both anatomical and functional information simultaneously for more comprehensive tissue characterization.

Development of an Anthropomorphic Breast Phantom for Combined PET, B-Mode Ultrasound and Elastographic Imaging

NASA Astrophysics Data System (ADS)

Dang, Jun; Frisch, Benjamin; Lasaygues, Philippe; Zhang, Dachun; Tavernier, Stefaan; Felix, Nicolas; Lecoq, Paul; Auffray, Etiennette; Varela, Joao; Mensah, Serge; Wan, Mingxi

2011-06-01

Combining the advantages of different imaging modalities leads to improved clinical results. For example, ultrasound provides good real-time structural information without any radiation and PET provides sensitive functional information. For the ongoing ClearPEM-Sonic project combining ultrasound and PET for breast imaging, we developed a dual-modality PET/Ultrasound (US) phantom. The phantom reproduces the acoustic and elastic properties of human breast tissue and allows labeling the different tissues in the phantom with different concentrations of FDG. The phantom was imaged with a whole-body PET/CT and with the Supersonic Imagine Aixplorer system. This system allows both B-mode US and shear wave elastographic imaging. US elastography is a new imaging method for displaying the tissue elasticity distribution. It was shown to be useful in breast imaging. We also tested the phantom with static elastography. A 6D magnetic positioning system allows fusing the images obtained with the two modalities. ClearPEM-Sonic is a project of the Crystal Clear Collaboration and the European Centre for Research on Medical Imaging (CERIMED).

Numerical study on simultaneous emission and transmission tomography in the MRI framework

NASA Astrophysics Data System (ADS)

Gjesteby, Lars; Cong, Wenxiang; Wang, Ge

2017-09-01

Multi-modality imaging methods are instrumental for advanced diagnosis and therapy. Specifically, a hybrid system that combines computed tomography (CT), nuclear imaging, and magnetic resonance imaging (MRI) will be a Holy Grail of medical imaging, delivering complementary structural/morphological, functional, and molecular information for precision medicine. A novel imaging method was recently demonstrated that takes advantage of radiotracer polarization to combine MRI principles with nuclear imaging. This approach allows the concentration of a polarized Υ-ray emitting radioisotope to be imaged with MRI resolution potentially outperforming the standard nuclear imaging mode at a sensitivity significantly higher than that of MRI. In our work, we propose to acquire MRI-modulated nuclear data for simultaneous image reconstruction of both emission and transmission parameters, suggesting the potential for simultaneous CT-SPECT-MRI. The synchronized diverse datasets allow excellent spatiotemporal registration and unique insight into physiological and pathological features. Here we describe the methodology involving the system design with emphasis on the formulation for tomographic images, even when significant radiotracer signals are limited to a region of interest (ROI). Initial numerical results demonstrate the feasibility of our approach for reconstructing concentration and attenuation images through a head phantom with various radio-labeled ROIs. Additional considerations regarding the radioisotope characteristics are also discussed.

Left ventricular mass and hypertrophy by echocardiography and cardiac magnetic resonance: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

Armstrong, Anderson C.; Gjesdal, Ola; Almeida, André; Nacif, Marcelo; Wu, Colin; Bluemke, David A.; Brumback, Lyndia; Lima, João A. C.

2013-01-01

BACKGROUND Left ventricular mass (LVM) and hypertrophy (LVH) are important parameters, but their use is surrounded by controversies. We compare LVM by echocardiography and cardiac magnetic resonance (CMR), investigating reproducibility aspects and the effect of echocardiography image quality. We also compare indexing methods within and between imaging modalities for classification of LVH and cardiovascular risk. METHODS MESA enrolled 880 participants in Baltimore City; 146 had echocardiograms and CMR on the same day. LVM was then assessed using standard techniques. Echocardiography image quality was rated (good/limited) according to the parasternal view. LVH was defined after indexing LVM to body surface area, height1.7, height2.7, or by the predicted LVM from a reference group. Participants were classified for cardiovascular risk according to Framingham score. Pearson’s correlation, Bland-Altman plots, percent agreement, and kappa coefficient assessed agreement within and between modalities. RESULTS LVM by echocardiography (140 ± 40 g) and by CMR were correlated (r = 0.8, p < 0.001) regardless of the echocardiography image quality. The reproducibility profile had strong correlations and agreement for both modalities. Image quality groups had similar characteristics; those with good images compared to CMR slightly superiorly. The prevalence of LVH tended to be higher with higher cardiovascular risk. The agreement for LVH between imaging modalities ranged from 77% to 98% and the kappa coefficient from 0.10 to 0.76. CONCLUSIONS Echocardiography has a reliable performance for LVM assessment and classification of LVH, with limited influence of image quality. Echocardiography and CMR differ in the assessment of LVH, and additional differences rise from the indexing methods. PMID:23930739

Near-IR multi-modal imaging of natural occlusal lesions

NASA Astrophysics Data System (ADS)

Lee, Dustin; Fried, Daniel; Darling, Cynthia L.

2009-02-01

Reflectance and transillumination imaging show demineralization with high contrast in the near-IR. The objective of this study is to use lesion size and contrast acquired in reflectance and transillumination near-infrared imaging modes to estimate the severity of natural occlusal caries lesions. Previous studies have shown that near-infrared (NIR) light can be used to effectively image artificial carious lesions. However, its efficacy on natural lesions requires further exploration. Fifty extracted teeth with varying amounts of occlusal decay were examined using a NIR imaging system operating at 1310-nm. Image analysis software was used to calculate contrast values between sound and carious tooth structure. After imaging, teeth were histologically sampled at 1-mm intervals in order to determine lesion depth. Lesion contrast in transillumination mode significantly increased with lesion depth (p<0.001), while lesion contrast in reflectance mode did not increase. The lesion area demonstrated a significant increase with lesion severity in both imaging modes. These results suggest that lesion contrast and area can be used to estimate lesion severity in NIR images.

Simultaneous MRI and PET imaging of a rat brain

NASA Astrophysics Data System (ADS)

Raylman, Raymond R.; Majewski, Stan; Lemieux, Susan K.; Sendhil Velan, S.; Kross, Brian; Popov, Vladimir; Smith, Mark F.; Weisenberger, Andrew G.; Zorn, Carl; Marano, Gary D.

2006-12-01

Multi-modality imaging is rapidly becoming a valuable tool in the diagnosis of disease and in the development of new drugs. Functional images produced with PET fused with anatomical structure images created by MRI will allow the correlation of form with function. Our group is developing a system to acquire MRI and PET images contemporaneously. The prototype device consists of two opposed detector heads, operating in coincidence mode. Each MRI-PET detector module consists of an array of LSO detector elements coupled through a long fibre optic light guide to a single Hamamatsu flat panel position-sensitive photomultiplier tube (PSPMT). The use of light guides allows the PSPMTs to be positioned outside the bore of a 3T MRI scanner where the magnetic field is relatively small. To test the device, simultaneous MRI and PET images of the brain of a male Sprague Dawley rat injected with FDG were successfully obtained. The images revealed no noticeable artefacts in either image set. Future work includes the construction of a full ring PET scanner, improved light guides and construction of a specialized MRI coil to permit higher quality MRI imaging.

Operando Multi-modal Synchrotron Investigation for Structural and Chemical Evolution of Cupric Sulfide (CuS) Additive in Li-S battery

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

Sun, Ke; Zhao, Chonghang; Lin, Cheng-Hung

Conductive metal sulfides are promising multi-functional additives for future lithium-sulfur (Li-S) batteries. These can increase the sulfur cathode’s electrical conductivity to improve the battery’s power capability, as well as contribute to the overall cell-discharge capacity. This multi-functional electrode design showed initial promise; however, complicated interactions at the system level are accompanied by some detrimental side effects. The metal sulfide additives with a chemical conversion as the reaction mechanism, e.g., CuS and FeS 2, can increase the theoretical capacity of the Li-S system. However, these additives may cause undesired parasitic reactions, such as the dissolution of the additive in the electrolyte.more » Studying such complex reactions presents a challenge because it requires experimental methods that can track the chemical and structural evolution of the system during an electrochemical process. To address the fundamental mechanisms in these systems, we employed an operando multimodal x-ray characterization approach to study the structural and chemical evolution of the metal sulfide—utilizing powder diffraction and fluorescence imaging to resolve the former and absorption spectroscopy the latter—during lithiation and de-lithiation of a Li-S battery with CuS as the multi-functional cathode additive. The resulting elucidation of the structural and chemical evolution of the system leads to a new description of the reaction mechanism.« less

Operando Multi-modal Synchrotron Investigation for Structural and Chemical Evolution of Cupric Sulfide (CuS) Additive in Li-S battery

DOE PAGES

Sun, Ke; Zhao, Chonghang; Lin, Cheng-Hung; ...

2017-10-11

Conductive metal sulfides are promising multi-functional additives for future lithium-sulfur (Li-S) batteries. These can increase the sulfur cathode’s electrical conductivity to improve the battery’s power capability, as well as contribute to the overall cell-discharge capacity. This multi-functional electrode design showed initial promise; however, complicated interactions at the system level are accompanied by some detrimental side effects. The metal sulfide additives with a chemical conversion as the reaction mechanism, e.g., CuS and FeS 2, can increase the theoretical capacity of the Li-S system. However, these additives may cause undesired parasitic reactions, such as the dissolution of the additive in the electrolyte.more » Studying such complex reactions presents a challenge because it requires experimental methods that can track the chemical and structural evolution of the system during an electrochemical process. To address the fundamental mechanisms in these systems, we employed an operando multimodal x-ray characterization approach to study the structural and chemical evolution of the metal sulfide—utilizing powder diffraction and fluorescence imaging to resolve the former and absorption spectroscopy the latter—during lithiation and de-lithiation of a Li-S battery with CuS as the multi-functional cathode additive. The resulting elucidation of the structural and chemical evolution of the system leads to a new description of the reaction mechanism.« less

MIDG-Emerging grid technologies for multi-site preclinical molecular imaging research communities.

PubMed

Lee, Jasper; Documet, Jorge; Liu, Brent; Park, Ryan; Tank, Archana; Huang, H K

2011-03-01

Molecular imaging is the visualization and identification of specific molecules in anatomy for insight into metabolic pathways, tissue consistency, and tracing of solute transport mechanisms. This paper presents the Molecular Imaging Data Grid (MIDG) which utilizes emerging grid technologies in preclinical molecular imaging to facilitate data sharing and discovery between preclinical molecular imaging facilities and their collaborating investigator institutions to expedite translational sciences research. Grid-enabled archiving, management, and distribution of animal-model imaging datasets help preclinical investigators to monitor, access and share their imaging data remotely, and promote preclinical imaging facilities to share published imaging datasets as resources for new investigators. The system architecture of the Molecular Imaging Data Grid is described in a four layer diagram. A data model for preclinical molecular imaging datasets is also presented based on imaging modalities currently used in a molecular imaging center. The MIDG system components and connectivity are presented. And finally, the workflow steps for grid-based archiving, management, and retrieval of preclincial molecular imaging data are described. Initial performance tests of the Molecular Imaging Data Grid system have been conducted at the USC IPILab using dedicated VMware servers. System connectivity, evaluated datasets, and preliminary results are presented. The results show the system's feasibility, limitations, direction of future research. Translational and interdisciplinary research in medicine is increasingly interested in cellular and molecular biology activity at the preclinical levels, utilizing molecular imaging methods on animal models. The task of integrated archiving, management, and distribution of these preclinical molecular imaging datasets at preclinical molecular imaging facilities is challenging due to disparate imaging systems and multiple off-site investigators. A Molecular Imaging Data Grid design, implementation, and initial evaluation is presented to demonstrate the secure and novel data grid solution for sharing preclinical molecular imaging data across the wide-area-network (WAN).

Future Directions in Medical Physics: Models, Technology, and Translation to Medicine

NASA Astrophysics Data System (ADS)

Siewerdsen, Jeffrey

The application of physics in medicine has been integral to major advances in diagnostic and therapeutic medicine. Two primary areas represent the mainstay of medical physics research in the last century: in radiation therapy, physicists have propelled advances in conformal radiation treatment and high-precision image guidance; and in diagnostic imaging, physicists have advanced an arsenal of multi-modality imaging that includes CT, MRI, ultrasound, and PET as indispensible tools for noninvasive screening, diagnosis, and assessment of treatment response. In addition to their role in building such technologically rich fields of medicine, physicists have also become integral to daily clinical practice in these areas. The future suggests new opportunities for multi-disciplinary research bridging physics, biology, engineering, and computer science, and collaboration in medical physics carries a strong capacity for identification of significant clinical needs, access to clinical data, and translation of technologies to clinical studies. In radiation therapy, for example, the extraction of knowledge from large datasets on treatment delivery, image-based phenotypes, genomic profile, and treatment outcome will require innovation in computational modeling and connection with medical physics for the curation of large datasets. Similarly in imaging physics, the demand for new imaging technology capable of measuring physical and biological processes over orders of magnitude in scale (from molecules to whole organ systems) and exploiting new contrast mechanisms for greater sensitivity to molecular agents and subtle functional / morphological change will benefit from multi-disciplinary collaboration in physics, biology, and engineering. Also in surgery and interventional radiology, where needs for increased precision and patient safety meet constraints in cost and workflow, development of new technologies for imaging, image registration, and robotic assistance can leverage collaboration in physics, biomedical engineering, and computer science. In each area, there is major opportunity for multi-disciplinary collaboration with medical physics to accelerate the translation of such technologies to clinical use. Research supported by the National Institutes of Health, Siemens Healthcare, and Carestream Health.

Advanced Interactive Display Formats for Terminal Area Traffic Control

NASA Technical Reports Server (NTRS)

Grunwald, Arthur J.; Shaviv, G. E.

1999-01-01

This research project deals with an on-line dynamic method for automated viewing parameter management in perspective displays. Perspective images are optimized such that a human observer will perceive relevant spatial geometrical features with minimal errors. In order to compute the errors at which observers reconstruct spatial features from perspective images, a visual spatial-perception model was formulated. The model was employed as the basis of an optimization scheme aimed at seeking the optimal projection parameter setting. These ideas are implemented in the context of an air traffic control (ATC) application. A concept, referred to as an active display system, was developed. This system uses heuristic rules to identify relevant geometrical features of the three-dimensional air traffic situation. Agile, on-line optimization was achieved by a specially developed and custom-tailored genetic algorithm (GA), which was to deal with the multi-modal characteristics of the objective function and exploit its time-evolving nature.

Multi-segment detector array for hybrid reflection-mode ultrasound and optoacoustic tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Merčep, Elena; Burton, Neal C.; Deán-Ben, Xosé Luís.; Razansky, Daniel

2017-02-01

The complementary contrast of the optoacoustic (OA) and pulse-echo ultrasound (US) modalities makes the combined usage of these imaging technologies highly advantageous. Due to the different physical contrast mechanisms development of a detector array optimally suited for both modalities is one of the challenges to efficient implementation of a single OA-US imaging device. We demonstrate imaging performance of the first hybrid detector array whose novel design, incorporating array segments of linear and concave geometry, optimally supports image acquisition in both reflection-mode ultrasonography and optoacoustic tomography modes. Hybrid detector array has a total number of 256 elements and three segments of different geometry and variable pitch size: a central 128-element linear segment with pitch of 0.25mm, ideally suited for pulse-echo US imaging, and two external 64-elements segments with concave geometry and 0.6mm pitch optimized for OA image acquisition. Interleaved OA and US image acquisition with up to 25 fps is facilitated through a custom-made multiplexer unit. Spatial resolution of the transducer was characterized in numerical simulations and validated in phantom experiments and comprises 230 and 300 μm in the respective OA and US imaging modes. Imaging performance of the multi-segment detector array was experimentally shown in a series of imaging sessions with healthy volunteers. Employing mixed array geometries allows at the same time achieving excellent OA contrast with a large field of view, and US contrast for complementary structural features with reduced side-lobes and improved resolution. The newly designed hybrid detector array that comprises segments of linear and concave geometries optimally fulfills requirements for efficient US and OA imaging and may expand the applicability of the developed hybrid OPUS imaging technology and accelerate its clinical translation.

Simultaneous dual modality optical and MR imaging of mouse dorsal skin-fold window chamber

NASA Astrophysics Data System (ADS)

Salek, Mir Farrokh; Pagel, Mark D.; Gmitro, Arthur F.

2011-02-01

Optical imaging and MRI have both been used extensively to study tumor microenvironment. The two imaging modalities are complementary and can be used to cross-validate one another for specific measurements. We have developed a modular platform that is capable of doing optical microscopy inside an MRI instrument. To do this, an optical relay system transfers the image to outside of the MR bore to a commercial grade CCD camera. This enables simultaneous optical and MR imaging of the same tissue and thus creates the ideal situation for comparative or complementary studies using both modalities. Initial experiments have been done using GFP labeled prostate cancer cells implanted in mouse dorsal skin fold window chamber. Vascular hemodynamics and vascular permeability were studied using our imaging system. Towards this goal, we developed a dual MR-Optical contrast agent by labeling BSA with both Gd-DTPA and Alexa Fluor. Overall system design and results of these preliminary vascular studies are presented.

Improving lateral resolution and image quality of optical coherence tomography by the multi-frame superresolution technique for 3D tissue imaging

PubMed Central

Shen, Kai; Lu, Hui; Baig, Sarfaraz; Wang, Michael R.

2017-01-01

The multi-frame superresolution technique is introduced to significantly improve the lateral resolution and image quality of spectral domain optical coherence tomography (SD-OCT). Using several sets of low resolution C-scan 3D images with lateral sub-spot-spacing shifts on different sets, the multi-frame superresolution processing of these sets at each depth layer reconstructs a higher resolution and quality lateral image. Layer by layer processing yields an overall high lateral resolution and quality 3D image. In theory, the superresolution processing including deconvolution can solve the diffraction limit, lateral scan density and background noise problems together. In experiment, the improved lateral resolution by ~3 times reaching 7.81 µm and 2.19 µm using sample arm optics of 0.015 and 0.05 numerical aperture respectively as well as doubling the image quality has been confirmed by imaging a known resolution test target. Improved lateral resolution on in vitro skin C-scan images has been demonstrated. For in vivo 3D SD-OCT imaging of human skin, fingerprint and retina layer, we used the multi-modal volume registration method to effectively estimate the lateral image shifts among different C-scans due to random minor unintended live body motion. Further processing of these images generated high lateral resolution 3D images as well as high quality B-scan images of these in vivo tissues. PMID:29188089

Multi-modal cockpit interface for improved airport surface operations

NASA Technical Reports Server (NTRS)

Arthur, Jarvis J. (Inventor); Bailey, Randall E. (Inventor); Prinzel, III, Lawrence J. (Inventor); Kramer, Lynda J. (Inventor); Williams, Steven P. (Inventor)

2010-01-01

A system for multi-modal cockpit interface during surface operation of an aircraft comprises a head tracking device, a processing element, and a full-color head worn display. The processing element is configured to receive head position information from the head tracking device, to receive current location information of the aircraft, and to render a virtual airport scene corresponding to the head position information and the current aircraft location. The full-color head worn display is configured to receive the virtual airport scene from the processing element and to display the virtual airport scene. The current location information may be received from one of a global positioning system or an inertial navigation system.

DICOM index tracker enterprise: advanced system for enterprise-wide quality assurance and patient safety monitoring

NASA Astrophysics Data System (ADS)

Zhang, Min; Pavlicek, William; Panda, Anshuman; Langer, Steve G.; Morin, Richard; Fetterly, Kenneth A.; Paden, Robert; Hanson, James; Wu, Lin-Wei; Wu, Teresa

2015-03-01

DICOM Index Tracker (DIT) is an integrated platform to harvest rich information available from Digital Imaging and Communications in Medicine (DICOM) to improve quality assurance in radiology practices. It is designed to capture and maintain longitudinal patient-specific exam indices of interests for all diagnostic and procedural uses of imaging modalities. Thus, it effectively serves as a quality assurance and patient safety monitoring tool. The foundation of DIT is an intelligent database system which stores the information accepted and parsed via a DICOM receiver and parser. The database system enables the basic dosimetry analysis. The success of DIT implementation at Mayo Clinic Arizona calls for the DIT deployment at the enterprise level which requires significant improvements. First, for geographically distributed multi-site implementation, the first bottleneck is the communication (network) delay; the second is the scalability of the DICOM parser to handle the large volume of exams from different sites. To address this issue, DICOM receiver and parser are separated and decentralized by site. To facilitate the enterprise wide Quality Assurance (QA), a notable challenge is the great diversities of manufacturers, modalities and software versions, as the solution DIT Enterprise provides the standardization tool for device naming, protocol naming, physician naming across sites. Thirdly, advanced analytic engines are implemented online which support the proactive QA in DIT Enterprise.

Highlights lecture EANM 2016: "Embracing molecular imaging and multi-modal imaging: a smart move for nuclear medicine towards personalized medicine".

PubMed

Aboagye, Eric O; Kraeber-Bodéré, Françoise

2017-08-01

The 2016 EANM Congress took place in Barcelona, Spain, from 15 to 19 October under the leadership of Prof. Wim Oyen, chair of the EANM Scientific Committee. With more than 6,000 participants, this congress was the most important European event in nuclear medicine, bringing together a multidisciplinary community involved in the different fields of nuclear medicine. There were over 600 oral and 1,200 poster or e-Poster presentations with an overwhelming focus on development and application of imaging for personalized care, which is timely for the community. Beyond FDG PET, major highlights included progress in the use of PSMA and SSTR receptor-targeted radiopharmaceuticals and associated theranostics in oncology. Innovations in radiopharmaceuticals for imaging pathologies of the brain and cardiovascular system, as well as infection and inflammation, were also highlighted. In the areas of physics and instrumentation, multimodality imaging and radiomics were highlighted as promising areas of research.

Viewpoints on Medical Image Processing: From Science to Application

PubMed Central

Deserno (né Lehmann), Thomas M.; Handels, Heinz; Maier-Hein (né Fritzsche), Klaus H.; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

2013-01-01

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment. PMID:24078804

Viewpoints on Medical Image Processing: From Science to Application.

PubMed

Deserno Né Lehmann, Thomas M; Handels, Heinz; Maier-Hein Né Fritzsche, Klaus H; Mersmann, Sven; Palm, Christoph; Tolxdorff, Thomas; Wagenknecht, Gudrun; Wittenberg, Thomas

2013-05-01

Medical image processing provides core innovation for medical imaging. This paper is focused on recent developments from science to applications analyzing the past fifteen years of history of the proceedings of the German annual meeting on medical image processing (BVM). Furthermore, some members of the program committee present their personal points of views: (i) multi-modality for imaging and diagnosis, (ii) analysis of diffusion-weighted imaging, (iii) model-based image analysis, (iv) registration of section images, (v) from images to information in digital endoscopy, and (vi) virtual reality and robotics. Medical imaging and medical image computing is seen as field of rapid development with clear trends to integrated applications in diagnostics, treatment planning and treatment.

Multimodal Image Registration through Simultaneous Segmentation.

PubMed

Aganj, Iman; Fischl, Bruce

2017-11-01

Multimodal image registration facilitates the combination of complementary information from images acquired with different modalities. Most existing methods require computation of the joint histogram of the images, while some perform joint segmentation and registration in alternate iterations. In this work, we introduce a new non-information-theoretical method for pairwise multimodal image registration, in which the error of segmentation - using both images - is considered as the registration cost function. We empirically evaluate our method via rigid registration of multi-contrast brain magnetic resonance images, and demonstrate an often higher registration accuracy in the results produced by the proposed technique, compared to those by several existing methods.

Implementation of DICOM Modality Worklist at Patient Registration Systems in Radiology Unit

NASA Astrophysics Data System (ADS)

Kartawiguna, Daniel; Georgiana, Vina

2014-03-01

Currently, the information and communication technology is developing very rapidly. A lot of hospitals have digital radiodiagnostic modality that supports the DICOM protocol. However, the implementation of integrated radiology information system with medical imaging equipment is still very limited until now, especially in developing countries like Indonesia. One of the obstacles is high prices for radiology information system. Whereas the radiology information systems can be widely used by radiologists to provide many benefit for patient, hospitals, and the doctors themselves. This study aims to develop a system that integrates the radiology administration information system with radiodiagnostic imaging modalities. Such a system would give some benefits that the information obtained is more accurate, timely, relevant, and accelerate the workflow of healthcare workers. This research used direct observation method to some hospital radiology unit. Data was collected through interviews, questionnaires, and surveys directly to some of the hospital's radiology department in Jakarta, and supported by the literature study. Based on the observations, the prototype of integrated patient registration systems in radiology unit is developed and interfaced to imaging equipment radiodiagnostic using standard DICOM communications. The prototype of radiology patient registration system is tested with the modality MRI and CT scan.

Combinatorial Markov Random Fields and Their Applications to Information Organization

DTIC Science & Technology

2008-02-01

titles, part-of- speech tags; • Image processing: images, colors, texture, blobs, interest points, caption words; • Video processing: video signal, audio...McGurk and MacDonald published their pioneering work [80] that revealed the multi-modal nature of speech perception: sound and moving lips compose one... Speech (POS) n-grams (that correspond to the syntactic structure of text). POS n-grams are extracted from sentences in an incremental manner: the first n

Non-invasive and Non-destructive Characterization of Tissue Engineered Constructs Using Ultrasound Imaging Technologies: A Review.

PubMed

Kim, Kang; Wagner, William R

2016-03-01

With the rapid expansion of biomaterial development and coupled efforts to translate such advances toward the clinic, non-invasive and non-destructive imaging tools to evaluate implants in situ in a timely manner are critically needed. The required multi-level information is comprehensive, including structural, mechanical, and biological changes such as scaffold degradation, mechanical strength, cell infiltration, extracellular matrix formation and vascularization to name a few. With its inherent advantages of non-invasiveness and non-destructiveness, ultrasound imaging can be an ideal tool for both preclinical and clinical uses. In this review, currently available ultrasound imaging technologies that have been applied in vitro and in vivo for tissue engineering and regenerative medicine are discussed and some new emerging ultrasound technologies and multi-modality approaches utilizing ultrasound are introduced.

Real-time ultrasound image classification for spine anesthesia using local directional Hadamard features.

PubMed

Pesteie, Mehran; Abolmaesumi, Purang; Ashab, Hussam Al-Deen; Lessoway, Victoria A; Massey, Simon; Gunka, Vit; Rohling, Robert N

2015-06-01

Injection therapy is a commonly used solution for back pain management. This procedure typically involves percutaneous insertion of a needle between or around the vertebrae, to deliver anesthetics near nerve bundles. Most frequently, spinal injections are performed either blindly using palpation or under the guidance of fluoroscopy or computed tomography. Recently, due to the drawbacks of the ionizing radiation of such imaging modalities, there has been a growing interest in using ultrasound imaging as an alternative. However, the complex spinal anatomy with different wave-like structures, affected by speckle noise, makes the accurate identification of the appropriate injection plane difficult. The aim of this study was to propose an automated system that can identify the optimal plane for epidural steroid injections and facet joint injections. A multi-scale and multi-directional feature extraction system to provide automated identification of the appropriate plane is proposed. Local Hadamard coefficients are obtained using the sequency-ordered Hadamard transform at multiple scales. Directional features are extracted from local coefficients which correspond to different regions in the ultrasound images. An artificial neural network is trained based on the local directional Hadamard features for classification. The proposed method yields distinctive features for classification which successfully classified 1032 images out of 1090 for epidural steroid injection and 990 images out of 1052 for facet joint injection. In order to validate the proposed method, a leave-one-out cross-validation was performed. The average classification accuracy for leave-one-out validation was 94 % for epidural and 90 % for facet joint targets. Also, the feature extraction time for the proposed method was 20 ms for a native 2D ultrasound image. A real-time machine learning system based on the local directional Hadamard features extracted by the sequency-ordered Hadamard transform for detecting the laminae and facet joints in ultrasound images has been proposed. The system has the potential to assist the anesthesiologists in quickly finding the target plane for epidural steroid injections and facet joint injections.

Joint detection and localization of multiple anatomical landmarks through learning

NASA Astrophysics Data System (ADS)

Dikmen, Mert; Zhan, Yiqiang; Zhou, Xiang Sean

2008-03-01

Reliable landmark detection in medical images provides the essential groundwork for successful automation of various open problems such as localization, segmentation, and registration of anatomical structures. In this paper, we present a learning-based system to jointly detect (is it there?) and localize (where?) multiple anatomical landmarks in medical images. The contributions of this work exist in two aspects. First, this method takes the advantage from the learning scenario that is able to automatically extract the most distinctive features for multi-landmark detection. Therefore, it is easily adaptable to detect arbitrary landmarks in various kinds of imaging modalities, e.g., CT, MRI and PET. Second, the use of multi-class/cascaded classifier architecture in different phases of the detection stage combined with robust features that are highly efficient in terms of computation time enables a seemingly real time performance, with very high localization accuracy. This method is validated on CT scans of different body sections, e.g., whole body scans, chest scans and abdominal scans. Aside from improved robustness (due to the exploitation of spatial correlations), it gains a run time efficiency in landmark detection. It also shows good scalability performance under increasing number of landmarks.

Enhanced Visualization of Subtle Outer Retinal Pathology by En Face Optical Coherence Tomography and Correlation with Multi-Modal Imaging

PubMed Central

Chew, Avenell L.; Lamey, Tina; McLaren, Terri; De Roach, John

2016-01-01

Purpose To present en face optical coherence tomography (OCT) images generated by graph-search theory algorithm-based custom software and examine correlation with other imaging modalities. Methods En face OCT images derived from high density OCT volumetric scans of 3 healthy subjects and 4 patients using a custom algorithm (graph-search theory) and commercial software (Heidelberg Eye Explorer software (Heidelberg Engineering)) were compared and correlated with near infrared reflectance, fundus autofluorescence, adaptive optics flood-illumination ophthalmoscopy (AO-FIO) and microperimetry. Results Commercial software was unable to generate accurate en face OCT images in eyes with retinal pigment epithelium (RPE) pathology due to segmentation error at the level of Bruch’s membrane (BM). Accurate segmentation of the basal RPE and BM was achieved using custom software. The en face OCT images from eyes with isolated interdigitation or ellipsoid zone pathology were of similar quality between custom software and Heidelberg Eye Explorer software in the absence of any other significant outer retinal pathology. En face OCT images demonstrated angioid streaks, lesions of acute macular neuroretinopathy, hydroxychloroquine toxicity and Bietti crystalline deposits that correlated with other imaging modalities. Conclusions Graph-search theory algorithm helps to overcome the limitations of outer retinal segmentation inaccuracies in commercial software. En face OCT images can provide detailed topography of the reflectivity within a specific layer of the retina which correlates with other forms of fundus imaging. Our results highlight the need for standardization of image reflectivity to facilitate quantification of en face OCT images and longitudinal analysis. PMID:27959968

Imaging system for creating 3D block-face cryo-images of whole mice

NASA Astrophysics Data System (ADS)

Roy, Debashish; Breen, Michael; Salvado, Olivier; Heinzel, Meredith; McKinley, Eliot; Wilson, David

2006-03-01

We developed a cryomicrotome/imaging system that provides high resolution, high sensitivity block-face images of whole mice or excised organs, and applied it to a variety of biological applications. With this cryo-imaging system, we sectioned cryo-preserved tissues at 2-40 μm thickness and acquired high resolution brightfield and fluorescence images with microscopic in-plane resolution (as good as 1.2 μm). Brightfield images of normal and pathological anatomy show exquisite detail, especially in the abdominal cavity. Multi-planar reformatting and 3D renderings allow one to interrogate 3D structures. In this report, we present brightfield images of mouse anatomy, as well as 3D renderings of organs. For BPK mice model of polycystic kidney disease, we compared brightfield cryo-images and kidney volumes to MRI. The color images provided greater contrast and resolution of cysts as compared to in vivo MRI. We note that color cryo-images are closer to what a researcher sees in dissection, making it easier for them to interpret image data. The combination of field of view, depth of field, ultra high resolution and color/fluorescence contrast enables cryo-image volumes to provide details that cannot be found through in vivo imaging or other ex vivo optical imaging approaches. We believe that this novel imaging system will have applications that include identification of mouse phenotypes, characterization of diseases like blood vessel disease, kidney disease, and cancer, assessment of drug and gene therapy delivery and efficacy and validation of other imaging modalities.

Designing a Website to Support Students' Academic Writing Process

ERIC Educational Resources Information Center

Åberg, Eva Svärdemo; Ståhle, Ylva; Engdahl, Ingrid; Knutes-Nyqvist, Helen

2016-01-01

Academic writing skills are crucial when students, e.g., in teacher education programs, write their undergraduate theses. A multi-modal web-based and self-regulated learning resource on academic writing was developed, using texts, hypertext, moving images, podcasts and templates. A study, using surveys and a focus group, showed that students used…

Articulatory Mediation of Speech Perception: A Causal Analysis of Multi-Modal Imaging Data

ERIC Educational Resources Information Center

Gow, David W., Jr.; Segawa, Jennifer A.

2009-01-01

The inherent confound between the organization of articulation and the acoustic-phonetic structure of the speech signal makes it exceptionally difficult to evaluate the competing claims of motor and acoustic-phonetic accounts of how listeners recognize coarticulated speech. Here we use Granger causation analysis of high spatiotemporal resolution…

Development of Convergence Nanoparticles for Multi-Modal Bio-Medical Imaging

DTIC Science & Technology

2008-09-18

Synthesized nanoparticles (1 mg /ml ( Mn +Fe)) are mixed with cancer cell (MCF7) and heat generation efficacy was measured with the cell viability under...fabrication of MnFe2O4 which has superior magnetic property compared to other types of metal ferrites . Figure 1. Magnetic nanoparticle for disease

Dynamic characteristics of the blisk with synchronized switch damping based on negative capacitor

NASA Astrophysics Data System (ADS)

Liu, J.; Li, L.; Huang, X.; Jezequel, L.

2017-10-01

In this paper, we propose a method to suppress the vibration of the integral bladed disk ('blisk' for short) in aero-engines using synchronized switch damping based on negative capacitor (SSDNC). Different from the classical piezoelectric shunt damping, SSDNC is a type of nonlinear piezoelectric damping. A multi-harmonic balance method combined with the alternating frequency/time method (MHBM-AFT) is used to predict and further analyze the dynamic characteristics of the electromechanical system, and an arc-length continuation technique is used to improve the convergence of the method. In order to validate the algorithm as well as to recognize the characteristics of the system with SSDNC, a two degree-of-freedom (2-DOF) system with SSDNC is studied at first. The nonlinear complex modal information is calculated and compared with those of the corresponding system with a linear RL shunt circuit. The results indicate that the natural frequencies and modal damping ratio do not change with the modal amplitude, which means that SSDNC has the same modal damping corresponding to different system energy levels. In addition, SSDNC can improve the damping level of all the modes nearly without affecting the natural frequencies of the system. Then, the forced response of the blisk with SSDNC in the frequency domain is calculated and analyzed, including a tuned blisk, which is excited by the traveling wave excitation with a single harmonic and multi-harmonic, and a mistuned blisk, which is excited by traveling wave excitation with a single harmonic and multi-harmonic. We present two advantages of the SSDNC technique when compared with piezoelectric shunt damping. First, SSDNC can suppress the vibration of the blisk under a multi-harmonic wideband the traveling wave, and second, the vibration suppression performance of SSDNC is insensitive to the mistuning of mechanical parameters of the blisk. The results will be of great significance in overcoming the problem of the amplitude magnification induced by the inevitable mistuning of the blisk in aero-engines.

Multi-modal in vivo imaging of brain blood oxygenation, blood flow and neural calcium dynamics during acute seizures

NASA Astrophysics Data System (ADS)

Ringuette, Dene; Jeffrey, Melanie A.; Carlen, Peter L.; Levi, Ofer

2016-03-01

Dysfunction of the vascular endothelium has been implicated in the development of epilepsy. To better understand the relation between vascular function and seizure and provide a foundation for interpreting results from functional imaging in chronic disease models, we investigate the relationship between intracellular calcium dynamics and local cerebral blood flow and blood oxygen saturation during acute seizure-like events and pharmacological seizure rescue. To probe the relation between the aforementioned physiological markers in an acute model of epilepsy in rats, we integrated three different optical modalities together with electrophysiological recordings: Laser speckle contrast imaging (LSCI) was used to study changes in flow speeds, Intrinsic optical signal imaging (IOSI) was used to monitor changes in oxygenated, de-oxygenated, and total hemoglobin concentration, and Calcium-sensitive dye imaging was used to monitor intracellular calcium dynamics. We designed a dedicated cortical flow chamber to remove superficial blood and dye resulting from the injection procedure, which reduced spurious artifacts. The near infrared light used for IOSI and LSCI was delivered via a light pipe integrated with the flow chamber to minimize the effect of fluid surface movement on illumination stability. Calcium-sensitive dye was injected via a glass electrode used for recording the local field potential. Our system allowed us to observe and correlate increases in intracellular calcium, blood flow and blood volume during seizure-like events and provide a quantitative analysis of neurovascular coupling changes associated with seizure rescue via injection of an anti-convulsive agent.

Using consumer-grade devices for multi-imager non-contact imaging photoplethysmography

NASA Astrophysics Data System (ADS)

Blackford, Ethan B.; Estepp, Justin R.

2017-02-01

Imaging photoplethysmography is a technique through which the morphology of the blood volume pulse can be obtained through non-contact video recordings of exposed skin with superficial vasculature. The acceptance of such a convenient modality for use in everyday applications may well depend upon the availability of consumer-grade imagers that facilitate ease-of-adoption. Multiple imagers have been used previously in concept demonstrations, showing improvements in quality of the extracted blood volume pulse signal. However, the use of multi-imager sensors requires synchronization of the frame exposures between the individual imagers, a capability that has only recently been available without creating custom solutions. In this work, we consider the use of multiple, commercially-available, synchronous imagers for use in imaging photoplethysmography. A commercially-available solution for adopting multi-imager synchronization was analyzed for 21 stationary, seated participants while ground-truth physiological signals were simultaneously measured. A total of three imagers were used, facilitating a comparison between fused data from all three imagers versus data from the single, central imager in the array. The within-subjects design included analyses of pulse rate and pulse signal-to-noise ratio. Using the fused data from the triple-imager array, mean absolute error in pulse rate measurement was reduced to 3.8 as compared to 7.4 beats per minute with the single imager. While this represents an overall improvement in the multi-imager case, it is also noted that these errors are substantially higher than those obtained in comparable studies. We further discuss these results and their implications for using readily-available commercial imaging solutions for imaging photoplethysmography applications.

Time-resolved multi-mass ion imaging: Femtosecond UV-VUV pump-probe spectroscopy with the PImMS camera.

PubMed

Forbes, Ruaridh; Makhija, Varun; Veyrinas, Kévin; Stolow, Albert; Lee, Jason W L; Burt, Michael; Brouard, Mark; Vallance, Claire; Wilkinson, Iain; Lausten, Rune; Hockett, Paul

2017-07-07

The Pixel-Imaging Mass Spectrometry (PImMS) camera allows for 3D charged particle imaging measurements, in which the particle time-of-flight is recorded along with (x, y) position. Coupling the PImMS camera to an ultrafast pump-probe velocity-map imaging spectroscopy apparatus therefore provides a route to time-resolved multi-mass ion imaging, with both high count rates and large dynamic range, thus allowing for rapid measurements of complex photofragmentation dynamics. Furthermore, the use of vacuum ultraviolet wavelengths for the probe pulse allows for an enhanced observation window for the study of excited state molecular dynamics in small polyatomic molecules having relatively high ionization potentials. Herein, preliminary time-resolved multi-mass imaging results from C 2 F 3 I photolysis are presented. The experiments utilized femtosecond VUV and UV (160.8 nm and 267 nm) pump and probe laser pulses in order to demonstrate and explore this new time-resolved experimental ion imaging configuration. The data indicate the depth and power of this measurement modality, with a range of photofragments readily observed, and many indications of complex underlying wavepacket dynamics on the excited state(s) prepared.

3D optical imagery for motion compensation in a limb ultrasound system

NASA Astrophysics Data System (ADS)

Ranger, Bryan J.; Feigin, Micha; Zhang, Xiang; Mireault, Al; Raskar, Ramesh; Herr, Hugh M.; Anthony, Brian W.

2016-04-01

Conventional processes for prosthetic socket fabrication are heavily subjective, often resulting in an interface to the human body that is neither comfortable nor completely functional. With nearly 100% of amputees reporting that they experience discomfort with the wearing of their prosthetic limb, designing an effective interface to the body can significantly affect quality of life and future health outcomes. Active research in medical imaging and biomechanical tissue modeling of residual limbs has led to significant advances in computer aided prosthetic socket design, demonstrating an interest in moving toward more quantifiable processes that are still patient-specific. In our work, medical ultrasonography is being pursued to acquire data that may quantify and improve the design process and fabrication of prosthetic sockets while greatly reducing cost compared to an MRI-based framework. This paper presents a prototype limb imaging system that uses a medical ultrasound probe, mounted to a mechanical positioning system and submerged in a water bath. The limb imaging is combined with three-dimensional optical imaging for motion compensation. Images are collected circumferentially around the limb and combined into cross-sectional axial image slices, resulting in a compound image that shows tissue distributions and anatomical boundaries similar to magnetic resonance imaging. In this paper we provide a progress update on our system development, along with preliminary results as we move toward full volumetric imaging of residual limbs for prosthetic socket design. This demonstrates a novel multi-modal approach to residual limb imaging.

A Digital Preclinical PET/MRI Insert and Initial Results.

PubMed

Weissler, Bjoern; Gebhardt, Pierre; Dueppenbecker, Peter M; Wehner, Jakob; Schug, David; Lerche, Christoph W; Goldschmidt, Benjamin; Salomon, Andre; Verel, Iris; Heijman, Edwin; Perkuhn, Michael; Heberling, Dirk; Botnar, Rene M; Kiessling, Fabian; Schulz, Volkmar

2015-11-01

Combining Positron Emission Tomography (PET) with Magnetic Resonance Imaging (MRI) results in a promising hybrid molecular imaging modality as it unifies the high sensitivity of PET for molecular and cellular processes with the functional and anatomical information from MRI. Digital Silicon Photomultipliers (dSiPMs) are the digital evolution in scintillation light detector technology and promise high PET SNR. DSiPMs from Philips Digital Photon Counting (PDPC) were used to develop a preclinical PET/RF gantry with 1-mm scintillation crystal pitch as an insert for clinical MRI scanners. With three exchangeable RF coils, the hybrid field of view has a maximum size of 160 mm × 96.6 mm (transaxial × axial). 0.1 ppm volume-root-mean-square B 0-homogeneity is kept within a spherical diameter of 96 mm (automatic volume shimming). Depending on the coil, MRI SNR is decreased by 13% or 5% by the PET system. PET count rates, energy resolution of 12.6% FWHM, and spatial resolution of 0.73 mm (3) (isometric volume resolution at isocenter) are not affected by applied MRI sequences. PET time resolution of 565 ps (FWHM) degraded by 6 ps during an EPI sequence. Timing-optimized settings yielded 260 ps time resolution. PET and MR images of a hot-rod phantom show no visible differences when the other modality was in operation and both resolve 0.8-mm rods. Versatility of the insert is shown by successfully combining multi-nuclei MRI ((1)H/(19)F) with simultaneously measured PET ((18)F-FDG). A longitudinal study of a tumor-bearing mouse verifies the operability, stability, and in vivo capabilities of the system. Cardiac- and respiratory-gated PET/MRI motion-capturing (CINE) images of the mouse heart demonstrate the advantage of simultaneous acquisition for temporal and spatial image registration.

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech.

PubMed

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances.

Thermal-to-visible face recognition using partial least squares.

PubMed

Hu, Shuowen; Choi, Jonghyun; Chan, Alex L; Schwartz, William Robson

2015-03-01

Although visible face recognition has been an active area of research for several decades, cross-modal face recognition has only been explored by the biometrics community relatively recently. Thermal-to-visible face recognition is one of the most difficult cross-modal face recognition challenges, because of the difference in phenomenology between the thermal and visible imaging modalities. We address the cross-modal recognition problem using a partial least squares (PLS) regression-based approach consisting of preprocessing, feature extraction, and PLS model building. The preprocessing and feature extraction stages are designed to reduce the modality gap between the thermal and visible facial signatures, and facilitate the subsequent one-vs-all PLS-based model building. We incorporate multi-modal information into the PLS model building stage to enhance cross-modal recognition. The performance of the proposed recognition algorithm is evaluated on three challenging datasets containing visible and thermal imagery acquired under different experimental scenarios: time-lapse, physical tasks, mental tasks, and subject-to-camera range. These scenarios represent difficult challenges relevant to real-world applications. We demonstrate that the proposed method performs robustly for the examined scenarios.

Diagnostic Imaging of the Hepatobiliary System: An Update.

PubMed

Marolf, Angela J

2017-05-01

Recent advances in diagnostic imaging of the hepatobiliary system include MRI, computed tomography (CT), contrast-enhanced ultrasound, and ultrasound elastography. With the advent of multislice CT scanners, sedated examinations in veterinary patients are feasible, increasing the utility of this imaging modality. CT and MRI provide additional information for dogs and cats with hepatobiliary diseases due to lack of superimposition of structures, operator dependence, and through intravenous contrast administration. Advanced ultrasound methods can offer complementary information to standard ultrasound imaging. These newer imaging modalities assist clinicians by aiding diagnosis, prognostication, and surgical planning. Copyright © 2016 Elsevier Inc. All rights reserved.

Large-area photogrammetry based testing of wind turbine blades

NASA Astrophysics Data System (ADS)

Poozesh, Peyman; Baqersad, Javad; Niezrecki, Christopher; Avitabile, Peter; Harvey, Eric; Yarala, Rahul

2017-03-01

An optically based sensing system that can measure the displacement and strain over essentially the entire area of a utility-scale blade leads to a measurement system that can significantly reduce the time and cost associated with traditional instrumentation. This paper evaluates the performance of conventional three dimensional digital image correlation (3D DIC) and three dimensional point tracking (3DPT) approaches over the surface of wind turbine blades and proposes a multi-camera measurement system using dynamic spatial data stitching. The potential advantages for the proposed approach include: (1) full-field measurement distributed over a very large area, (2) the elimination of time-consuming wiring and expensive sensors, and (3) the need for large-channel data acquisition systems. There are several challenges associated with extending the capability of a standard 3D DIC system to measure entire surface of utility scale blades to extract distributed strain, deflection, and modal parameters. This paper only tries to address some of the difficulties including: (1) assessing the accuracy of the 3D DIC system to measure full-field distributed strain and displacement over the large area, (2) understanding the geometrical constraints associated with a wind turbine testing facility (e.g. lighting, working distance, and speckle pattern size), (3) evaluating the performance of the dynamic stitching method to combine two different fields of view by extracting modal parameters from aligned point clouds, and (4) determining the feasibility of employing an output-only system identification to estimate modal parameters of a utility scale wind turbine blade from optically measured data. Within the current work, the results of an optical measurement (one stereo-vision system) performed on a large area over a 50-m utility-scale blade subjected to quasi-static and cyclic loading are presented. The blade certification and testing is typically performed using International Electro-Technical Commission standard (IEC 61400-23). For static tests, the blade is pulled in either flap-wise or edge-wise directions to measure deflection or distributed strain at a few limited locations of a large-sized blade. Additionally, the paper explores the error associated with using a multi-camera system (two stereo-vision systems) in measuring 3D displacement and extracting structural dynamic parameters on a mock set up emulating a utility-scale wind turbine blade. The results obtained in this paper reveal that the multi-camera measurement system has the potential to identify the dynamic characteristics of a very large structure.

Cross-modal face recognition using multi-matcher face scores

NASA Astrophysics Data System (ADS)

Zheng, Yufeng; Blasch, Erik

2015-05-01

The performance of face recognition can be improved using information fusion of multimodal images and/or multiple algorithms. When multimodal face images are available, cross-modal recognition is meaningful for security and surveillance applications. For example, a probe face is a thermal image (especially at nighttime), while only visible face images are available in the gallery database. Matching a thermal probe face onto the visible gallery faces requires crossmodal matching approaches. A few such studies were implemented in facial feature space with medium recognition performance. In this paper, we propose a cross-modal recognition approach, where multimodal faces are cross-matched in feature space and the recognition performance is enhanced with stereo fusion at image, feature and/or score level. In the proposed scenario, there are two cameras for stereo imaging, two face imagers (visible and thermal images) in each camera, and three recognition algorithms (circular Gaussian filter, face pattern byte, linear discriminant analysis). A score vector is formed with three cross-matched face scores from the aforementioned three algorithms. A classifier (e.g., k-nearest neighbor, support vector machine, binomial logical regression [BLR]) is trained then tested with the score vectors by using 10-fold cross validations. The proposed approach was validated with a multispectral stereo face dataset from 105 subjects. Our experiments show very promising results: ACR (accuracy rate) = 97.84%, FAR (false accept rate) = 0.84% when cross-matching the fused thermal faces onto the fused visible faces by using three face scores and the BLR classifier.

Towards Development of a Field-Deployable Imaging Device for TBI

DTIC Science & Technology

2012-03-01

accompany TBI, and that ultrasound-based ‘sonoelastic’ imaging modalities responsive to some measure of stiffness might offer a useful means for imaging the...changes to brain due to TBI. Use of such systems in and near the field should improve clinical outcome for patients suffering from TBI. Our long...sonoelastic’ imaging modalities responsive to some measure of stiffness might offer a useful means for imaging the gross and subtle changes to brain

Dual-modality imaging with a ultrasound-gamma device for oncology

NASA Astrophysics Data System (ADS)

Polito, C.; Pellegrini, R.; Cinti, M. N.; De Vincentis, G.; Lo Meo, S.; Fabbri, A.; Bennati, P.; Cencelli, V. Orsolini; Pani, R.

2018-06-01

Recently, dual-modality systems have been developed, aimed to correlate anatomical and functional information, improving disease localization and helping oncological or surgical treatments. Moreover, due to the growing interest in handheld detectors for preclinical trials or small animal imaging, in this work a new dual modality integrated device, based on a Ultrasounds probe and a small Field of View Single Photon Emission gamma camera, is proposed.

Magnetic resonance spectroscopy of fiber tracts in children with traumatic brain injury: A combined MRS - Diffusion MRI study.

PubMed

Dennis, Emily L; Babikian, Talin; Alger, Jeffry; Rashid, Faisal; Villalon-Reina, Julio E; Jin, Yan; Olsen, Alexander; Mink, Richard; Babbitt, Christopher; Johnson, Jeffrey; Giza, Christopher C; Thompson, Paul M; Asarnow, Robert F

2018-05-10

Traumatic brain injury can cause extensive damage to the white matter (WM) of the brain. These disruptions can be especially damaging in children, whose brains are still maturing. Diffusion magnetic resonance imaging (dMRI) is the most commonly used method to assess WM organization, but it has limited resolution to differentiate causes of WM disruption. Magnetic resonance spectroscopy (MRS) yields spectra showing the levels of neurometabolites that can indicate neuronal/axonal health, inflammation, membrane proliferation/turnover, and other cellular processes that are on-going post-injury. Previous analyses on this dataset revealed a significant division within the msTBI patient group, based on interhemispheric transfer time (IHTT); one subgroup of patients (TBI-normal) showed evidence of recovery over time, while the other showed continuing degeneration (TBI-slow). We combined dMRI with MRS to better understand WM disruptions in children with moderate-severe traumatic brain injury (msTBI). Tracts with poorer WM organization, as shown by lower FA and higher MD and RD, also showed lower N-acetylaspartate (NAA), a marker of neuronal and axonal health and myelination. We did not find lower NAA in tracts with normal WM organization. Choline, a marker of inflammation, membrane turnover, or gliosis, did not show such associations. We further show that multi-modal imaging can improve outcome prediction over a single modality, as well as over earlier cognitive function measures. Our results suggest that demyelination plays an important role in WM disruption post-injury in a subgroup of msTBI children and indicate the utility of multi-modal imaging. © 2018 Wiley Periodicals, Inc.

Diffusion magnetic resonance imaging: A molecular imaging tool caught between hope, hype and the real world of “personalized oncology”

PubMed Central

Mahajan, Abhishek; Deshpande, Sneha S; Thakur, Meenakshi H

2017-01-01

“Personalized oncology” is a multi-disciplinary science, which requires inputs from various streams for optimal patient management. Humongous progress in the treatment modalities available and the increasing need to provide functional information in addition to the morphological data; has led to leaping progress in the field of imaging. Magnetic resonance imaging has undergone tremendous progress with various newer MR techniques providing vital functional information and is becoming the cornerstone of “radiomics/radiogenomics”. Diffusion-weighted imaging is one such technique which capitalizes on the tendency of water protons to diffuse randomly in a given system. This technique has revolutionized oncological imaging, by giving vital qualitative and quantitative information regarding tumor biology which helps in detection, characterization and post treatment surveillance of the lesions and challenging the notion that “one size fits all”. It has been applied at various sites with different clinical experience. We hereby present a brief review of this novel functional imaging tool, with its application in “personalized oncology”. PMID:28717412

Compensation of spectral artifacts in dual-modality intravascular optical coherence tomography and near-infrared spectroscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Fard, Ali M.; Gardecki, Joseph A.; Ughi, Giovanni J.; Hyun, Chulho; Tearney, Guillermo J.

2016-02-01

Intravascular optical coherence tomography (OCT) is a high-resolution catheter-based imaging method that provides three-dimensional microscopic images of coronary artery in vivo, facilitating coronary artery disease treatment decisions based on detailed morphology. Near-infrared spectroscopy (NIRS) has proven to be a powerful tool for identification of lipid-rich plaques inside the coronary walls. We have recently demonstrated a dual-modality intravascular imaging technology that integrates OCT and NIRS into one imaging catheter using a two-fiber arrangement and a custom-made dual-channel fiber rotary junction. It therefore enables simultaneous acquisition of microstructural and composition information at 100 frames/second for improved diagnosis of coronary lesions. The dual-modality OCT-NIRS system employs a single wavelength-swept light source for both OCT and NIRS modalities. It subsequently uses a high-speed photoreceiver to detect the NIRS spectrum in the time domain. Although use of one light source greatly simplifies the system configuration, such light source exhibits pulse-to-pulse wavelength and intensity variation due to mechanical scanning of the wavelength. This can be in particular problematic for NIRS modality and sacrifices the reliability of the acquired spectra. In order to address this challenge, here we developed a robust data acquisition and processing method that compensates for the spectral variations of the wavelength-swept light source. The proposed method extracts the properties of the light source, i.e., variation period and amplitude from a reference spectrum and subsequently calibrates the NIRS datasets. We have applied this method on datasets obtained from cadaver human coronary arteries using a polygon-scanning (1230-1350nm) OCT system, operating at 100,000 sweeps per second. The results suggest that our algorithm accurately and robustly compensates the spectral variations and visualizes the dual-modality OCT-NIRS images. These findings are therefore crucial for the practical application and clinical translation of dual-modality intravascular OCT-NIRS imaging when the same swept sources are used for both OCT and spectroscopy.

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features

PubMed Central

Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-01-01

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization. PMID:28599282

Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

PubMed

Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

2017-07-18

Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

Enabling Low-Power, Multi-Modal Neural Interfaces Through a Common, Low-Bandwidth Feature Space.

PubMed

Irwin, Zachary T; Thompson, David E; Schroeder, Karen E; Tat, Derek M; Hassani, Ali; Bullard, Autumn J; Woo, Shoshana L; Urbanchek, Melanie G; Sachs, Adam J; Cederna, Paul S; Stacey, William C; Patil, Parag G; Chestek, Cynthia A

2016-05-01

Brain-Machine Interfaces (BMIs) have shown great potential for generating prosthetic control signals. Translating BMIs into the clinic requires fully implantable, wireless systems; however, current solutions have high power requirements which limit their usability. Lowering this power consumption typically limits the system to a single neural modality, or signal type, and thus to a relatively small clinical market. Here, we address both of these issues by investigating the use of signal power in a single narrow frequency band as a decoding feature for extracting information from electrocorticographic (ECoG), electromyographic (EMG), and intracortical neural data. We have designed and tested the Multi-modal Implantable Neural Interface (MINI), a wireless recording system which extracts and transmits signal power in a single, configurable frequency band. In prerecorded datasets, we used the MINI to explore low frequency signal features and any resulting tradeoff between power savings and decoding performance losses. When processing intracortical data, the MINI achieved a power consumption 89.7% less than a more typical system designed to extract action potential waveforms. When processing ECoG and EMG data, the MINI achieved similar power reductions of 62.7% and 78.8%. At the same time, using the single signal feature extracted by the MINI, we were able to decode all three modalities with less than a 9% drop in accuracy relative to using high-bandwidth, modality-specific signal features. We believe this system architecture can be used to produce a viable, cost-effective, clinical BMI.

Multimodality imaging of ovarian cystic lesions: Review with an imaging based algorithmic approach

PubMed Central

Wasnik, Ashish P; Menias, Christine O; Platt, Joel F; Lalchandani, Usha R; Bedi, Deepak G; Elsayes, Khaled M

2013-01-01

Ovarian cystic masses include a spectrum of benign, borderline and high grade malignant neoplasms. Imaging plays a crucial role in characterization and pretreatment planning of incidentally detected or suspected adnexal masses, as diagnosis of ovarian malignancy at an early stage is correlated with a better prognosis. Knowledge of differential diagnosis, imaging features, management trends and an algorithmic approach of such lesions is important for optimal clinical management. This article illustrates a multi-modality approach in the diagnosis of a spectrum of ovarian cystic masses and also proposes an algorithmic approach for the diagnosis of these lesions. PMID:23671748

Rapid multi-modality preregistration based on SIFT descriptor.

PubMed

Chen, Jian; Tian, Jie

2006-01-01

This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration.

Multidisciplinary HIS DICOM interfaces at the Department of Veterans Affairs

NASA Astrophysics Data System (ADS)

Kuzmak, Peter M.; Dayhoff, Ruth E.

2000-05-01

The U.S. Department of Veterans Affairs (VA) is using the Digital Imaging and Communications in Medicine (DICOM) standard to integrate image data objects from multiple systems for use across the healthcare enterprise. DICOM uses a structured representation of image data and a communication mechanism that allows the VA to easily acquire images from multiple sources and store them directly into the online patient record. The VA can obtain both radiology and non- radiology images using DICOM, and can display them on low-cost clinician's color workstations throughout the medical center. High-resolution gray-scale diagnostic quality multi-monitor workstations with specialized viewing software can be used for reading radiology images. The VA's DICOM capabilities can interface six different commercial Picture Archiving and Communication Systems (PACS) and over twenty different image acquisition modalities. The VA is advancing its use of DICOM beyond radiology. New color imaging applications for Gastrointestinal Endoscopy and Ophthalmology using DICOM are under development. These are the first DICOM offerings for the vendors, who are planning to support the recently passed DICOM Visible Light and Structured Reporting service classes. Implementing these in VistA is a challenge because of the different workflow and software support for these disciplines within the VA HIS environment.

MO-D-BRB-02: SBRT Treatment Planning and Delivery

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

Yang, Y.

2016-06-15

Increased use of SBRT and hypofractionation in radiation oncology practice has posted a number of challenges to medical physicist, ranging from planning, image-guided patient setup and on-treatment monitoring, to quality assurance (QA) and dose delivery. This symposium is designed to provide current knowledge necessary for the safe and efficient implementation of SBRT in various linac platforms, including the emerging digital linacs equipped with high dose rate FFF beams. Issues related to 4D CT, PET and MRI simulations, 3D/4D CBCT guided patient setup, real-time image guidance during SBRT dose delivery using gated/un-gated VMAT/IMRT, and technical advancements in QA of SBRT (inmore » particular, strategies dealing with high dose rate FFF beams) will be addressed. The symposium will help the attendees to gain a comprehensive understanding of the SBRT workflow and facilitate their clinical implementation of the state-of-art imaging and planning techniques. Learning Objectives: Present background knowledge of SBRT, describe essential requirements for safe implementation of SBRT, and discuss issues specific to SBRT treatment planning and QA. Update on the use of multi-dimensional and multi-modality imaging for reliable guidance of SBRT. Discuss treatment planning and QA issues specific to SBRT. Provide a comprehensive overview of emerging digital linacs and summarize the key geometric and dosimetric features of the new generation of linacs for substantially improved SBRT. NIH/NCI; Varian Medical Systems; F. Yin, Duke University has a research agreement with Varian Medical Systems. In addition to research grant, I had a technology license agreement with Varian Medical Systems.« less

Hilar cholangiocarcinoma: Cross sectional evaluation of disease spectrum

PubMed Central

Mahajan, Mangal S; Moorthy, Srikanth; Karumathil, Sreekumar P; Rajeshkannan, R; Pothera, Ramchandran

2015-01-01

Although hilar cholangiocarcinoma is relatively rare, it can be diagnosed on imaging by identifying its typical pattern. In most cases, the tumor appears to be centered on the right or left hepatic duct with involvement of the ipsilateral portal vein, atrophy of hepatic lobe on that side, and invasion of adjacent liver parenchyma. Multi-detector computed tomography (MDCT) and magnetic resonance cholangiopancreatography (MRCP) are commonly used imaging modalities to assess the longitudinal and horizontal spread of tumor. PMID:25969643

Dose factor entry and display tool for BNCT radiotherapy

DOEpatents

Wessol, Daniel E.; Wheeler, Floyd J.; Cook, Jeremy L.

1999-01-01

A system for use in Boron Neutron Capture Therapy (BNCT) radiotherapy planning where a biological distribution is calculated using a combination of conversion factors and a previously calculated physical distribution. Conversion factors are presented in a graphical spreadsheet so that a planner can easily view and modify the conversion factors. For radiotherapy in multi-component modalities, such as Fast-Neutron and BNCT, it is necessary to combine each conversion factor component to form an effective dose which is used in radiotherapy planning and evaluation. The Dose Factor Entry and Display System is designed to facilitate planner entry of appropriate conversion factors in a straightforward manner for each component. The effective isodose is then immediately computed and displayed over the appropriate background (e.g. digitized image).

PDE based scheme for multi-modal medical image watermarking.

PubMed

Aherrahrou, N; Tairi, H

2015-11-25

This work deals with copyright protection of digital images, an issue that needs protection of intellectual property rights. It is an important issue with a large number of medical images interchanged on the Internet every day. So, it is a challenging task to ensure the integrity of received images as well as authenticity. Digital watermarking techniques have been proposed as valid solution for this problem. It is worth mentioning that the Region Of Interest (ROI)/Region Of Non Interest (RONI) selection can be seen as a significant limitation from which suffers most of ROI/RONI based watermarking schemes and that in turn affects and limit their applicability in an effective way. Generally, the ROI/RONI is defined by a radiologist or a computer-aided selection tool. And thus, this will not be efficient for an institute or health care system, where one has to process a large number of images. Therefore, developing an automatic ROI/RONI selection is a challenge task. The major aim of this work is to develop an automatic selection algorithm of embedding region based on the so called Partial Differential Equation (PDE) method. Thus avoiding ROI/RONI selection problems including: (1) computational overhead, (2) time consuming, and (3) modality dependent selection. The algorithm is evaluated in terms of imperceptibility, robustness, tamper localization and recovery using MRI, Ultrasound, CT and X-ray grey scale medical images. From experimental results that we have conducted on a database of 100 medical images of four modalities, it can be inferred that our method can achieve high imperceptibility, while showing good robustness against attacks. Furthermore, the experiment results confirm the effectiveness of the proposed algorithm in detecting and recovering the various types of tampering. The highest PSNR value reached over the 100 images is 94,746 dB, while the lowest PSNR value is 60,1272 dB, which demonstrates the higher imperceptibility nature of the proposed method. Moreover, the Normalized Correlation (NC) between the original watermark and the corresponding extracted watermark for 100 images is computed. We get a NC value greater than or equal to 0.998. This indicates that the extracted watermark is very similar to the original watermark for all modalities. The key features of our proposed method are to (1) increase the robustness of the watermark against attacks; (2) provide more transparency to the embedded watermark. (3) provide more authenticity and integrity protection of the content of medical images. (4) provide minimum ROI/RONI selection complexity.

Optics clustered to output unique solutions: A multi-laser facility for combined single molecule and ensemble microscopy

NASA Astrophysics Data System (ADS)

Clarke, David T.; Botchway, Stanley W.; Coles, Benjamin C.; Needham, Sarah R.; Roberts, Selene K.; Rolfe, Daniel J.; Tynan, Christopher J.; Ward, Andrew D.; Webb, Stephen E. D.; Yadav, Rahul; Zanetti-Domingues, Laura; Martin-Fernandez, Marisa L.

2011-09-01

Optics clustered to output unique solutions (OCTOPUS) is a microscopy platform that combines single molecule and ensemble imaging methodologies. A novel aspect of OCTOPUS is its laser excitation system, which consists of a central core of interlocked continuous wave and pulsed laser sources, launched into optical fibres and linked via laser combiners. Fibres are plugged into wall-mounted patch panels that reach microscopy end-stations in adjacent rooms. This allows multiple tailor-made combinations of laser colours and time characteristics to be shared by different end-stations minimising the need for laser duplications. This setup brings significant benefits in terms of cost effectiveness, ease of operation, and user safety. The modular nature of OCTOPUS also facilitates the addition of new techniques as required, allowing the use of existing lasers in new microscopes while retaining the ability to run the established parts of the facility. To date, techniques interlinked are multi-photon/multicolour confocal fluorescence lifetime imaging for several modalities of fluorescence resonance energy transfer (FRET) and time-resolved anisotropy, total internal reflection fluorescence, single molecule imaging of single pair FRET, single molecule fluorescence polarisation, particle tracking, and optical tweezers. Here, we use a well-studied system, the epidermal growth factor receptor network, to illustrate how OCTOPUS can aid in the investigation of complex biological phenomena.

Laser scanning saturated structured illumination microscopy based on phase modulation

NASA Astrophysics Data System (ADS)

Huang, Yujia; Zhu, Dazhao; Jin, Luhong; Kuang, Cuifang; Xu, Yingke; Liu, Xu

2017-08-01

Wide-field saturated structured illumination microscopy has not been widely used due to the requirement of high laser power. We propose a novel method called laser scanning saturated structured illumination microscopy (LS-SSIM), which introduces high order of harmonics frequency and greatly reduces the required laser power for SSIM imaging. To accomplish that, an excitation PSF with two peaks is generated and scanned along different directions on the sample. Raw images are recorded cumulatively by a CCD detector and then reconstructed to form a high-resolution image with extended optical transfer function (OTF). Our theoretical analysis and simulation results show that LS-SSIM method reaches a resolution of 0.16 λ, equivalent to 2.7-fold resolution than conventional wide-field microscopy. In addition, LS-SSIM greatly improves the optical sectioning capability of conventional wide-field illumination system by diminishing our-of-focus light. Furthermore, this modality has the advantage of implementation in multi-photon microscopy with point scanning excitation to image samples in greater depths.

Multi-modal and targeted imaging improves automated mid-brain segmentation

NASA Astrophysics Data System (ADS)

Plassard, Andrew J.; D'Haese, Pierre F.; Pallavaram, Srivatsan; Newton, Allen T.; Claassen, Daniel O.; Dawant, Benoit M.; Landman, Bennett A.

2017-02-01

The basal ganglia and limbic system, particularly the thalamus, putamen, internal and external globus pallidus, substantia nigra, and sub-thalamic nucleus, comprise a clinically relevant signal network for Parkinson's disease. In order to manually trace these structures, a combination of high-resolution and specialized sequences at 7T are used, but it is not feasible to scan clinical patients in those scanners. Targeted imaging sequences at 3T such as F-GATIR, and other optimized inversion recovery sequences, have been presented which enhance contrast in a select group of these structures. In this work, we show that a series of atlases generated at 7T can be used to accurately segment these structures at 3T using a combination of standard and optimized imaging sequences, though no one approach provided the best result across all structures. In the thalamus and putamen, a median Dice coefficient over 0.88 and a mean surface distance less than 1.0mm was achieved using a combination of T1 and an optimized inversion recovery imaging sequences. In the internal and external globus pallidus a Dice over 0.75 and a mean surface distance less than 1.2mm was achieved using a combination of T1 and FGATIR imaging sequences. In the substantia nigra and sub-thalamic nucleus a Dice coefficient of over 0.6 and a mean surface distance of less than 1.0mm was achieved using the optimized inversion recovery imaging sequence. On average, using T1 and optimized inversion recovery together produced significantly improved segmentation results than any individual modality (p<0.05 wilcox sign-rank test).

Multi-Modal Traveler Information System - Corridor User Needs and Data Exchange Elements

DOT National Transportation Integrated Search

1997-07-30

Intended as a resource for the members of the GCM Deployment Committee, : Architecture Communication and Information Work Group, project managers, system : designers, system developers and system integrators, this Working Paper supports : the design,...

infoRAD: computers for clinical practice and education in radiology. Teleradiology, information transfer, and PACS: implications for diagnostic imaging in the 1990s.

PubMed

Schilling, R B

1993-05-01

Picture archiving and communication systems (PACS) provide image viewing at diagnostic, reporting, consultation, and remote workstations; archival on magnetic or optical media by means of short- or long-term storage devices; communications by means of local or wide area networks or public communication services; and integrated systems with modality interfaces and gateways to health care facilities and departmental information systems. Research indicates three basic needs for image and report management: (a) improved communication and turnaround time between radiologists and other imaging specialists and referring physicians, (b) fast reliable access to both current and previously obtained images and reports, and (c) space-efficient archival support. Although PACS considerations are much more complex than those associated with single modalities, the same basic purchase criteria apply. These criteria include technical leadership, image quality, throughput, life cost (eg, initial cost, maintenance, upgrades, and depreciation), and total service. Because a PACS takes much longer to implement than a single modality, the customer and manufacturer must develop a closer working relationship than has been necessary in the past.

Towards an intelligent framework for multimodal affective data analysis.

PubMed

Poria, Soujanya; Cambria, Erik; Hussain, Amir; Huang, Guang-Bin

2015-03-01

An increasingly large amount of multimodal content is posted on social media websites such as YouTube and Facebook everyday. In order to cope with the growth of such so much multimodal data, there is an urgent need to develop an intelligent multi-modal analysis framework that can effectively extract information from multiple modalities. In this paper, we propose a novel multimodal information extraction agent, which infers and aggregates the semantic and affective information associated with user-generated multimodal data in contexts such as e-learning, e-health, automatic video content tagging and human-computer interaction. In particular, the developed intelligent agent adopts an ensemble feature extraction approach by exploiting the joint use of tri-modal (text, audio and video) features to enhance the multimodal information extraction process. In preliminary experiments using the eNTERFACE dataset, our proposed multi-modal system is shown to achieve an accuracy of 87.95%, outperforming the best state-of-the-art system by more than 10%, or in relative terms, a 56% reduction in error rate. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dual modality virtual colonoscopy workstation: design, implementation, and preliminary evaluation

NASA Astrophysics Data System (ADS)

Chen, Dongqing; Meissner, Michael

2006-03-01

The aim of this study is to develop a virtual colonoscopy (VC) workstation that supports both CT (computed tomography) and MR (magnetic resonance) imaging procedures. The workflow should be optimized and be able to take advantage of both image modalities. The technological break through is at the real-time volume rendering of spatial-intensity-inhomogeneous MR images to achieve high quality 3D endoluminal view. VC aims at visualizing CT or MR tomography images for detection of colonic polyp and lesion. It is also called as CT/MR colonography based on the imaging modality that is employed. The published results of large scale clinical trial demonstrated more than 90% of sensitivity on polyp detection for certain CT colonography (CTC) workstation. A drawback of the CT colonoscopy is the radiation exposure. MR colonography (MRC) is free from the X-ray radiation. It achieved almost 100% specificity for polyp detection in published trials. The better tissue contrast in MR image allows the accurate diagnosis of inflammatory bowel disease also, which is usually difficult in CTC. At present, most of the VC workstations are designed for CT examination. They are not able to display multi-sequence MR series concurrently in a single application. The automatic correlation between 2D and 3D view is not available due to the difficulty of 3D model building for MR images. This study aims at enhancing a commercial VC product that was successfully used for CTC to equally support dark-lumen protocol MR procedure also.

Implementation and assessment of an animal management system for small-animal micro-CT / micro-SPECT imaging

NASA Astrophysics Data System (ADS)

Holdsworth, David W.; Detombe, Sarah A.; Chiodo, Chris; Fricke, Stanley T.; Drangova, Maria

2011-03-01

Advances in laboratory imaging systems for CT, SPECT, MRI, and PET facilitate routine micro-imaging during pre-clinical investigations. Challenges still arise when dealing with immune-compromised animals, biohazardous agents, and multi-modality imaging. These challenges can be overcome with an appropriate animal management system (AMS), with the capability for supporting and monitoring a rat or mouse during micro-imaging. We report the implementation and assessment of a new AMS system for mice (PRA-3000 / AHS-2750, ASI Instruments, Warren MI), designed to be compatible with a commercial micro-CT / micro-SPECT imaging system (eXplore speCZT, GE Healthcare, London ON). The AMS was assessed under the following criteria: 1) compatibility with the imaging system (i.e. artifact generation, geometric dimensions); 2) compatibility with live animals (i.e. positioning, temperature regulation, anesthetic supply); 3) monitoring capabilities (i.e. rectal temperature, respiratory and cardiac monitoring); 4) stability of co-registration; and 5) containment. Micro-CT scans performed using a standardized live-animal protocol (90 kVp, 40 mA, 900 views, 16 ms per view) exhibited low noise (+/-19 HU) and acceptable artifact from high-density components within the AMS (e.g. ECG pad contacts). Live mice were imaged repeatedly (with removal and replacement of the AMS) and spatial registration was found to be stable to within +/-0.07 mm. All animals tolerated enclosure within the AMS for extended periods (i.e. > one hour) without distress, based on continuous recordings of rectal temperature, ECG waveform and respiratory rate. A sealed AMS system extends the capability of a conventional micro-imaging system to include immune-compromised and biosafety level 2 mouse-imaging protocols.

Spinal fusion-hardware construct: Basic concepts and imaging review

PubMed Central

Nouh, Mohamed Ragab

2012-01-01

The interpretation of spinal images fixed with metallic hardware forms an increasing bulk of daily practice in a busy imaging department. Radiologists are required to be familiar with the instrumentation and operative options used in spinal fixation and fusion procedures, especially in his or her institute. This is critical in evaluating the position of implants and potential complications associated with the operative approaches and spinal fixation devices used. Thus, the radiologist can play an important role in patient care and outcome. This review outlines the advantages and disadvantages of commonly used imaging methods and reports on the best yield for each modality and how to overcome the problematic issues associated with the presence of metallic hardware during imaging. Baseline radiographs are essential as they are the baseline point for evaluation of future studies should patients develop symptoms suggesting possible complications. They may justify further imaging workup with computed tomography, magnetic resonance and/or nuclear medicine studies as the evaluation of a patient with a spinal implant involves a multi-modality approach. This review describes imaging features of potential complications associated with spinal fusion surgery as well as the instrumentation used. This basic knowledge aims to help radiologists approach everyday practice in clinical imaging. PMID:22761979

Contemporary Multi-Modal Historical Representations and the Teaching of Disciplinary Understandings in History

ERIC Educational Resources Information Center

Donnelly, Debra J.

2018-01-01

Traditional privileging of the printed text has been considerably eroded by rapid technological advancement and in Australia, as elsewhere, many History teaching programs feature an array of multi-modal historical representations. Research suggests that engagement with the visual and multi-modal constructs has the potential to enrich the pedagogy…

Phantom Preparation and Optical Property Determination

NASA Astrophysics Data System (ADS)

He, Di; He, Jie; Mao, Heng

2018-12-01

Tissue-like optical phantoms are important in testing new imaging algorithms. Homogeneous optical phantoms with determined optical properties are the first step of making a proper heterogeneous phantom for multi-modality imaging. Typical recipes for such phantoms consist of epoxy resin, hardener, India ink and titanium oxide. By altering the concentration of India ink and titanium oxide, we are able to get multiple homogeneous phantoms with different absorption and scattering coefficients by carefully mixing all the ingredients. After fabricating the phantoms, we need to find their individual optical properties including the absorption and scattering coefficients. This is achieved by solving diffusion equation of each phantom as a homogeneous slab under canonical illumination. We solve the diffusion equation of homogeneous slab in frequency domain and get the formula for theoretical measurements. Under our steady-state diffused optical tomography (DOT) imaging system, we are able to obtain the real distribution of the incident light produced by a laser. With this source distribution we got and the formula we derived, numerical experiments show how measurements change while varying the value of absorption and scattering coefficients. Then we notice that the measurements alone will not be enough for us to get unique optical properties for steady-state DOT problem. Thus in order to determine the optical properties of a homogeneous slab we want to fix one of the coefficients first and use optimization methods to find another one. Then by assemble multiple homogeneous slab phantoms with different optical properties, we are able to obtain a heterogeneous phantom suitable for testing multi-modality imaging algorithms. In this paper, we describe how to make phantoms, derive a formula to solve the diffusion equation, demonstrate the non-uniqueness of steady-state DOT problem by analysing some numerical results of our formula, and finally propose a possible way to determine optical properties for homogeneous slab for our future work.

Laser-driven x-ray and neutron source development for industrial applications of plasma accelerators

NASA Astrophysics Data System (ADS)

Brenner, C. M.; Mirfayzi, S. R.; Rusby, D. R.; Armstrong, C.; Alejo, A.; Wilson, L. A.; Clarke, R.; Ahmed, H.; Butler, N. M. H.; Haddock, D.; Higginson, A.; McClymont, A.; Murphy, C.; Notley, M.; Oliver, P.; Allott, R.; Hernandez-Gomez, C.; Kar, S.; McKenna, P.; Neely, D.

2016-01-01

Pulsed beams of energetic x-rays and neutrons from intense laser interactions with solid foils are promising for applications where bright, small emission area sources, capable of multi-modal delivery are ideal. Possible end users of laser-driven multi-modal sources are those requiring advanced non-destructive inspection techniques in industry sectors of high value commerce such as aerospace, nuclear and advanced manufacturing. We report on experimental work that demonstrates multi-modal operation of high power laser-solid interactions for neutron and x-ray beam generation. Measurements and Monte Carlo radiation transport simulations show that neutron yield is increased by a factor ~2 when a 1 mm copper foil is placed behind a 2 mm lithium foil, compared to using a 2 cm block of lithium only. We explore x-ray generation with a 10 picosecond drive pulse in order to tailor the spectral content for radiography with medium density alloy metals. The impact of using  >1 ps pulse duration on laser-accelerated electron beam generation and transport is discussed alongside the optimisation of subsequent bremsstrahlung emission in thin, high atomic number target foils. X-ray spectra are deconvolved from spectrometer measurements and simulation data generated using the GEANT4 Monte Carlo code. We also demonstrate the unique capability of laser-driven x-rays in being able to deliver single pulse high spatial resolution projection imaging of thick metallic objects. Active detector radiographic imaging of industrially relevant sample objects with a 10 ps drive pulse is presented for the first time, demonstrating that features of 200 μm size are resolved when projected at high magnification.

Combined multi-spectrum and orthogonal Laplacianfaces for fast CB-XLCT imaging with single-view data

NASA Astrophysics Data System (ADS)

Zhang, Haibo; Geng, Guohua; Chen, Yanrong; Qu, Xuan; Zhao, Fengjun; Hou, Yuqing; Yi, Huangjian; He, Xiaowei

2017-12-01

Cone-beam X-ray luminescence computed tomography (CB-XLCT) is an attractive hybrid imaging modality, which has the potential of monitoring the metabolic processes of nanophosphors-based drugs in vivo. Single-view data reconstruction as a key issue of CB-XLCT imaging promotes the effective study of dynamic XLCT imaging. However, it suffers from serious ill-posedness in the inverse problem. In this paper, a multi-spectrum strategy is adopted to relieve the ill-posedness of reconstruction. The strategy is based on the third-order simplified spherical harmonic approximation model. Then, an orthogonal Laplacianfaces-based method is proposed to reduce the large computational burden without degrading the imaging quality. Both simulated data and in vivo experimental data were used to evaluate the efficiency and robustness of the proposed method. The results are satisfactory in terms of both location and quantitative recovering with computational efficiency, indicating that the proposed method is practical and promising for single-view CB-XLCT imaging.

A Review of Multivariate Methods for Multimodal Fusion of Brain Imaging Data

PubMed Central

Adali, Tülay; Yu, Qingbao; Calhoun, Vince D.

2011-01-01

The development of various neuroimaging techniques is rapidly improving the measurements of brain function/structure. However, despite improvements in individual modalities, it is becoming increasingly clear that the most effective research approaches will utilize multi-modal fusion, which takes advantage of the fact that each modality provides a limited view of the brain. The goal of multimodal fusion is to capitalize on the strength of each modality in a joint analysis, rather than a separate analysis of each. This is a more complicated endeavor that must be approached more carefully and efficient methods should be developed to draw generalized and valid conclusions from high dimensional data with a limited number of subjects. Numerous research efforts have been reported in the field based on various statistical approaches, e.g. independent component analysis (ICA), canonical correlation analysis (CCA) and partial least squares (PLS). In this review paper, we survey a number of multivariate methods appearing in previous reports, which are performed with or without prior information and may have utility for identifying potential brain illness biomarkers. We also discuss the possible strengths and limitations of each method, and review their applications to brain imaging data. PMID:22108139

Multimodal digital color imaging system for facial skin lesion analysis

NASA Astrophysics Data System (ADS)

Bae, Youngwoo; Lee, Youn-Heum; Jung, Byungjo

2008-02-01

In dermatology, various digital imaging modalities have been used as an important tool to quantitatively evaluate the treatment effect of skin lesions. Cross-polarization color image was used to evaluate skin chromophores (melanin and hemoglobin) information and parallel-polarization image to evaluate skin texture information. In addition, UV-A induced fluorescent image has been widely used to evaluate various skin conditions such as sebum, keratosis, sun damages, and vitiligo. In order to maximize the evaluation efficacy of various skin lesions, it is necessary to integrate various imaging modalities into an imaging system. In this study, we propose a multimodal digital color imaging system, which provides four different digital color images of standard color image, parallel and cross-polarization color image, and UV-A induced fluorescent color image. Herein, we describe the imaging system and present the examples of image analysis. By analyzing the color information and morphological features of facial skin lesions, we are able to comparably and simultaneously evaluate various skin lesions. In conclusion, we are sure that the multimodal color imaging system can be utilized as an important assistant tool in dermatology.

The Mind Research Network - Mental Illness Neuroscience Discovery Grant

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

Roberts, J.; Calhoun, V.

The scientific and technological programs of the Mind Research Network (MRN), reflect DOE missions in basic science and associated instrumentation, computational modeling, and experimental techniques. MRN's technical goals over the course of this project have been to develop and apply integrated, multi-modality functional imaging techniques derived from a decade of DOE-support research and technology development.

Math Snacks: Using Animations and Games to Fill the Gaps in Mathematics

ERIC Educational Resources Information Center

Valdiz, Alfred; Trujillo, Karen; Wiburg, Karin

2013-01-01

Math Snacks animations and support materials were developed for use on the web and mobile technologies to teach ratio, proportion, scale factor, and number line concepts using a multi-modal approach. Included in Math Snacks are: Animations which promote the visualization of a concept image; written lessons which provide cognitive complexity for…

Validation of a new modal performance measure for flexible controllers design

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

Simo, J.B.; Tahan, S.A.; Kamwa, I.

1996-05-01

A new modal performance measure for power system stabilizer (PSS) optimization is proposed in this paper. The new method is based on modifying the square envelopes of oscillating modes, in order to take into account their damping ratios while minimizing the performance index. This criteria is applied to flexible controllers optimal design, on a multi-input-multi-output (MIMO) reduced-order model of a prototype power system. The multivariable model includes four generators, each having one input and one output. Linear time-response simulation and transient stability analysis with a nonlinear package confirm the superiority of the proposed criteria and illustrate its effectiveness in decentralizedmore » control.« less

Preliminary clinical results: an analyzing tool for 2D optical imaging in detection of active inflammation in rheumatoid arthritis

NASA Astrophysics Data System (ADS)

Adi Aizudin Bin Radin Nasirudin, Radin; Meier, Reinhard; Ahari, Carmen; Sievert, Matti; Fiebich, Martin; Rummeny, Ernst J.; No"l, Peter B.

2011-03-01

Optical imaging (OI) is a relatively new method in detecting active inflammation of hand joints of patients suffering from rheumatoid arthritis (RA). With the high number of people affected by this disease especially in western countries, the availability of OI as an early diagnostic imaging method is clinically highly relevant. In this paper, we present a newly in-house developed OI analyzing tool and a clinical evaluation study. Our analyzing tool extends the capability of existing OI tools. We include many features in the tool, such as region-based image analysis, hyper perfusion curve analysis, and multi-modality image fusion to aid clinicians in localizing and determining the intensity of inflammation in joints. Additionally, image data management options, such as the full integration of PACS/RIS, are included. In our clinical study we demonstrate how OI facilitates the detection of active inflammation in rheumatoid arthritis. The preliminary clinical results indicate a sensitivity of 43.5%, a specificity of 80.3%, an accuracy of 65.7%, a positive predictive value of 76.6%, and a negative predictive value of 64.9% in relation to clinical results from MRI. The accuracy of inflammation detection serves as evidence to the potential of OI as a useful imaging modality for early detection of active inflammation in patients with rheumatoid arthritis. With our in-house developed tool we extend the usefulness of OI imaging in the clinical arena. Overall, we show that OI is a fast, inexpensive, non-invasive and nonionizing yet highly sensitive and accurate imaging modality.-

Quantitative magnetic resonance imaging phantoms: A review and the need for a system phantom.

PubMed

Keenan, Kathryn E; Ainslie, Maureen; Barker, Alex J; Boss, Michael A; Cecil, Kim M; Charles, Cecil; Chenevert, Thomas L; Clarke, Larry; Evelhoch, Jeffrey L; Finn, Paul; Gembris, Daniel; Gunter, Jeffrey L; Hill, Derek L G; Jack, Clifford R; Jackson, Edward F; Liu, Guoying; Russek, Stephen E; Sharma, Samir D; Steckner, Michael; Stupic, Karl F; Trzasko, Joshua D; Yuan, Chun; Zheng, Jie

2018-01-01

The MRI community is using quantitative mapping techniques to complement qualitative imaging. For quantitative imaging to reach its full potential, it is necessary to analyze measurements across systems and longitudinally. Clinical use of quantitative imaging can be facilitated through adoption and use of a standard system phantom, a calibration/standard reference object, to assess the performance of an MRI machine. The International Society of Magnetic Resonance in Medicine AdHoc Committee on Standards for Quantitative Magnetic Resonance was established in February 2007 to facilitate the expansion of MRI as a mainstream modality for multi-institutional measurements, including, among other things, multicenter trials. The goal of the Standards for Quantitative Magnetic Resonance committee was to provide a framework to ensure that quantitative measures derived from MR data are comparable over time, between subjects, between sites, and between vendors. This paper, written by members of the Standards for Quantitative Magnetic Resonance committee, reviews standardization attempts and then details the need, requirements, and implementation plan for a standard system phantom for quantitative MRI. In addition, application-specific phantoms and implementation of quantitative MRI are reviewed. Magn Reson Med 79:48-61, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

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

Computational Intelligence Techniques for Tactile Sensing Systems

PubMed Central

Gastaldo, Paolo; Pinna, Luigi; Seminara, Lucia; Valle, Maurizio; Zunino, Rodolfo

2014-01-01

Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach. PMID:24949646

Computational intelligence techniques for tactile sensing systems.

PubMed

Gastaldo, Paolo; Pinna, Luigi; Seminara, Lucia; Valle, Maurizio; Zunino, Rodolfo

2014-06-19

Tactile sensing helps robots interact with humans and objects effectively in real environments. Piezoelectric polymer sensors provide the functional building blocks of the robotic electronic skin, mainly thanks to their flexibility and suitability for detecting dynamic contact events and for recognizing the touch modality. The paper focuses on the ability of tactile sensing systems to support the challenging recognition of certain qualities/modalities of touch. The research applies novel computational intelligence techniques and a tensor-based approach for the classification of touch modalities; its main results consist in providing a procedure to enhance system generalization ability and architecture for multi-class recognition applications. An experimental campaign involving 70 participants using three different modalities in touching the upper surface of the sensor array was conducted, and confirmed the validity of the approach.

A networked modular hardware and software system for MRI-guided robotic prostate interventions

NASA Astrophysics Data System (ADS)

Su, Hao; Shang, Weijian; Harrington, Kevin; Camilo, Alex; Cole, Gregory; Tokuda, Junichi; Hata, Nobuhiko; Tempany, Clare; Fischer, Gregory S.

2012-02-01

Magnetic resonance imaging (MRI) provides high resolution multi-parametric imaging, large soft tissue contrast, and interactive image updates making it an ideal modality for diagnosing prostate cancer and guiding surgical tools. Despite a substantial armamentarium of apparatuses and systems has been developed to assist surgical diagnosis and therapy for MRI-guided procedures over last decade, the unified method to develop high fidelity robotic systems in terms of accuracy, dynamic performance, size, robustness and modularity, to work inside close-bore MRI scanner still remains a challenge. In this work, we develop and evaluate an integrated modular hardware and software system to support the surgical workflow of intra-operative MRI, with percutaneous prostate intervention as an illustrative case. Specifically, the distinct apparatuses and methods include: 1) a robot controller system for precision closed loop control of piezoelectric motors, 2) a robot control interface software that connects the 3D Slicer navigation software and the robot controller to exchange robot commands and coordinates using the OpenIGTLink open network communication protocol, and 3) MRI scan plane alignment to the planned path and imaging of the needle as it is inserted into the target location. A preliminary experiment with ex-vivo phantom validates the system workflow, MRI-compatibility and shows that the robotic system has a better than 0.01mm positioning accuracy.

Multi-Modal Hallucinations and Cognitive Function in Parkinson's Disease

PubMed Central

Katzen, Heather; Myerson, Connie; Papapetropoulos, Spiridon; Nahab, Fatta; Gallo, Bruno; Levin, Bonnie

2010-01-01

Background/Aims Hallucinations have been linked to a constellation of cognitive deficits in Parkinson's disease (PD), but it is not known whether multi-modal hallucinations are associated with greater neuropsychological dysfunction. Methods 152 idiopathic PD patients were categorized based on the presence or absence of hallucinations and then were further subdivided into visual-only (VHonly; n = 35) or multi-modal (VHplus; n = 12) hallucination groups. All participants underwent detailed neuropsychological assessment. Results Participants with hallucinations performed more poorly on select neuropsychological measures and exhibited more mood symptoms. There were no differences between VHonly and VHplus groups. Conclusions PD patients with multi-modal hallucinations are not at greater risk for neuropsychological impairment than those with single-modal hallucinations. PMID:20689283

Multi-modality Imaging: Bird's eye view from the 2015 American Heart Association Scientific Sessions.

PubMed

Einstein, Andrew J; Lloyd, Steven G; Chaudhry, Farooq A; AlJaroudi, Wael A; Hage, Fadi G

2016-04-01

Multiple novel studies were presented at the 2015 American Heart Association Scientific Sessions which was considered a successful conference at many levels. In this review, we will summarize key studies in nuclear cardiology, cardiac magnetic resonance, echocardiography, and cardiac computed tomography that were presented at the Sessions. We hope that this bird's eye view will keep readers updated on the newest imaging studies presented at the meeting whether or not they were able to attend the meeting.

Use of Multi-Modal Media and Tools in an Online Information Literacy Course: College Students' Attitudes and Perceptions

ERIC Educational Resources Information Center

Chen, Hsin-Liang; Williams, James Patrick

2009-01-01

This project studies the use of multi-modal media objects in an online information literacy class. One hundred sixty-two undergraduate students answered seven surveys. Significant relationships are found among computer skills, teaching materials, communication tools and learning experience. Multi-modal media objects and communication tools are…

Intelligent Transportation Systems for Commercial Vehicle Operations

DOT National Transportation Integrated Search

1997-10-15

What is TransLink? - Public/private partnership - Multi-modal initiative - Focused on linking elements of transportation system - Laboratory using real world data - Looking toward the next generation of transportation operations and management

Combining Raman spectroscopy and digital holographic microscopy for label-free classification of human immune cells (Conference Presentation)

NASA Astrophysics Data System (ADS)

McReynolds, Naomi; Cooke, Fiona G. M.; Chen, Mingzhou; Powis, Simon J.; Dholakia, Kishan

2017-02-01

Moving towards label-free techniques for cell identification is essential for many clinical and research applications. Raman spectroscopy and digital holographic microscopy (DHM) are both label-free, non-destructive optical techniques capable of providing complimentary information. We demonstrate a multi-modal system which may simultaneously take Raman spectra and DHM images to provide both a molecular and a morphological description of our sample. In this study we use Raman spectroscopy and DHM to discriminate between three immune cell populations CD4+ T cells, B cells, and monocytes, which together comprise key functional immune cell subsets in immune responses to invading pathogens. Various parameters that may be used to describe the phase images are also examined such as pixel value histograms or texture analysis. Using our system it is possible to consider each technique individually or in combination. Principal component analysis is used on the data set to discriminate between cell types and leave-one-out cross-validation is used to estimate the efficiency of our method. Raman spectroscopy provides specific chemical information but requires relatively long acquisition times, combining this with a faster modality such as DHM could help achieve faster throughput rates. The combination of these two complimentary optical techniques provides a wealth of information for cell characterisation which is a step towards achieving label free technology for the identification of human immune cells.

The design and application of a multi-band IR imager

NASA Astrophysics Data System (ADS)

Li, Lijuan

2018-02-01

Multi-band IR imaging system has many applications in security, national defense, petroleum and gas industry, etc. So the relevant technologies are getting more and more attention in rent years. As we know, when used in missile warning and missile seeker systems, multi-band IR imaging technology has the advantage of high target recognition capability and low false alarm rate if suitable spectral bands are selected. Compared with traditional single band IR imager, multi-band IR imager can make use of spectral features in addition to space and time domain features to discriminate target from background clutters and decoys. So, one of the key work is to select the right spectral bands in which the feature difference between target and false target is evident and is well utilized. Multi-band IR imager is a useful instrument to collect multi-band IR images of target, backgrounds and decoys for spectral band selection study at low cost and with adjustable parameters and property compared with commercial imaging spectrometer. In this paper, a multi-band IR imaging system is developed which is suitable to collect 4 spectral band images of various scenes at every turn and can be expanded to other short-wave and mid-wave IR spectral bands combination by changing filter groups. The multi-band IR imaging system consists of a broad band optical system, a cryogenic InSb large array detector, a spinning filter wheel and electronic processing system. The multi-band IR imaging system's performance is tested in real data collection experiments.

Time-Of-Flight Camera, Optical Tracker and Computed Tomography in Pairwise Data Registration.

PubMed

Pycinski, Bartlomiej; Czajkowska, Joanna; Badura, Pawel; Juszczyk, Jan; Pietka, Ewa

2016-01-01

A growing number of medical applications, including minimal invasive surgery, depends on multi-modal or multi-sensors data processing. Fast and accurate 3D scene analysis, comprising data registration, seems to be crucial for the development of computer aided diagnosis and therapy. The advancement of surface tracking system based on optical trackers already plays an important role in surgical procedures planning. However, new modalities, like the time-of-flight (ToF) sensors, widely explored in non-medical fields are powerful and have the potential to become a part of computer aided surgery set-up. Connection of different acquisition systems promises to provide a valuable support for operating room procedures. Therefore, the detailed analysis of the accuracy of such multi-sensors positioning systems is needed. We present the system combining pre-operative CT series with intra-operative ToF-sensor and optical tracker point clouds. The methodology contains: optical sensor set-up and the ToF-camera calibration procedures, data pre-processing algorithms, and registration technique. The data pre-processing yields a surface, in case of CT, and point clouds for ToF-sensor and marker-driven optical tracker representation of an object of interest. An applied registration technique is based on Iterative Closest Point algorithm. The experiments validate the registration of each pair of modalities/sensors involving phantoms of four various human organs in terms of Hausdorff distance and mean absolute distance metrics. The best surface alignment was obtained for CT and optical tracker combination, whereas the worst for experiments involving ToF-camera. The obtained accuracies encourage to further develop the multi-sensors systems. The presented substantive discussion concerning the system limitations and possible improvements mainly related to the depth information produced by the ToF-sensor is useful for computer aided surgery developers.

Pre-Motor Response Time Benefits in Multi-Modal Displays

DTIC Science & Technology

2013-11-12

when animals are presented with stimuli from two sensory modalities as compared with stimulation from only one modality. The combinations of two...modality attention and orientation behaviors (see also Wallace, Meredith, & Stein, 609 !998). Multi-modal stimulation in the world is not always...perceptually when the stimuli are congruent. In another study, Craig (2006) had participants judge the direction of apparent motion by stimulating

[Guidelines for wise utilization of knee imaging].

PubMed

Finestone, Aharon S; Eshed, Iris; Freedman, Yehuda; Beer, Yiftah; Bar-Sever, Zvi; Kots, Yavvgeni; Adar, Eliyahu; Mann, Gideon

2012-02-01

The knee is a complex structure afflicted with diverse pathologies. Correct management of knee complaints demands wise utilization of imaging modalities, considering their accuracy in the specific clinical situation, the patient's safety and availability and financial issues. Some of these considerations are universal, while others are local, depending on medical and insurance systems. There is controversy and unclearness regarding the best imaging modality in different clinical situations. To develop clinical guidelines for utilizing knee imaging. Leading physicians in specialties associated with knee disease and imaging were invited to participate in a panel on the guidelines. Controversies were settled in the main panel or in sub-panels. The panel agreed on the principles in choosing from the various modalities, primarily medical accuracy, followed by patient safety, availability and cost. There was agreement that the physician is responsible to choose the most appropriate diagnostic tool, consulting, when necessary, on the advantages, limitations and risks of the various imaging modalities. A comprehensive table was compiled with the importance of the different imaging modalities in various clinical situations. For the first time, Israeli guidelines on wise utilization of knee imaging are presented. They take into consideration the clinical situations and also availability and financial issues specific to Israel. These guidelines will serve physicians of several disciplines and medical insurers to improve patient management efficiently.

Multi-atlas segmentation with joint label fusion and corrective learning—an open source implementation

PubMed Central

Wang, Hongzhi; Yushkevich, Paul A.

2013-01-01

Label fusion based multi-atlas segmentation has proven to be one of the most competitive techniques for medical image segmentation. This technique transfers segmentations from expert-labeled images, called atlases, to a novel image using deformable image registration. Errors produced by label transfer are further reduced by label fusion that combines the results produced by all atlases into a consensus solution. Among the proposed label fusion strategies, weighted voting with spatially varying weight distributions derived from atlas-target intensity similarity is a simple and highly effective label fusion technique. However, one limitation of most weighted voting methods is that the weights are computed independently for each atlas, without taking into account the fact that different atlases may produce similar label errors. To address this problem, we recently developed the joint label fusion technique and the corrective learning technique, which won the first place of the 2012 MICCAI Multi-Atlas Labeling Challenge and was one of the top performers in 2013 MICCAI Segmentation: Algorithms, Theory and Applications (SATA) challenge. To make our techniques more accessible to the scientific research community, we describe an Insight-Toolkit based open source implementation of our label fusion methods. Our implementation extends our methods to work with multi-modality imaging data and is more suitable for segmentation problems with multiple labels. We demonstrate the usage of our tools through applying them to the 2012 MICCAI Multi-Atlas Labeling Challenge brain image dataset and the 2013 SATA challenge canine leg image dataset. We report the best results on these two datasets so far. PMID:24319427

RANZCR Body Systems Framework of diagnostic imaging examination descriptors.

PubMed

Pitman, Alexander G; Penlington, Lisa; Doromal, Darren; Slater, Gregory; Vukolova, Natalia

2014-08-01

A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were 'greyed out'. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities. © 2014 The Royal Australian and New Zealand College of Radiologists.

Iconic Gestures for Robot Avatars, Recognition and Integration with Speech

PubMed Central

Bremner, Paul; Leonards, Ute

2016-01-01

Co-verbal gestures are an important part of human communication, improving its efficiency and efficacy for information conveyance. One possible means by which such multi-modal communication might be realized remotely is through the use of a tele-operated humanoid robot avatar. Such avatars have been previously shown to enhance social presence and operator salience. We present a motion tracking based tele-operation system for the NAO robot platform that allows direct transmission of speech and gestures produced by the operator. To assess the capabilities of this system for transmitting multi-modal communication, we have conducted a user study that investigated if robot-produced iconic gestures are comprehensible, and are integrated with speech. Robot performed gesture outcomes were compared directly to those for gestures produced by a human actor, using a within participant experimental design. We show that iconic gestures produced by a tele-operated robot are understood by participants when presented alone, almost as well as when produced by a human. More importantly, we show that gestures are integrated with speech when presented as part of a multi-modal communication equally well for human and robot performances. PMID:26925010

Nanoparticles in practice for molecular-imaging applications: An overview.

PubMed

Padmanabhan, Parasuraman; Kumar, Ajay; Kumar, Sundramurthy; Chaudhary, Ravi Kumar; Gulyás, Balázs

2016-09-01

Nanoparticles (NPs) are playing a progressively more significant role in multimodal and multifunctional molecular imaging. The agents like Superparamagnetic iron oxide (SPIO), manganese oxide (MnO), gold NPs/nanorods and quantum dots (QDs) possess specific properties like paramagnetism, superparamagnetism, surface plasmon resonance (SPR) and photoluminescence respectively. These specific properties make them able for single/multi-modal and single/multi-functional molecular imaging. NPs generally have nanomolar or micromolar sensitivity range and can be detected via imaging instrumentation. The distinctive characteristics of these NPs make them suitable for imaging, therapy and delivery of drugs. Multifunctional nanoparticles (MNPs) can be produced through either modification of shell or surface or by attaching an affinity ligand to the nanoparticles. They are utilized for targeted imaging by magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT), positron emission tomography (PET), computed tomography (CT), photo acoustic imaging (PAI), two photon or fluorescent imaging and ultra sound etc. Toxicity factor of NPs is also a very important concern and toxic effect should be eliminated. First generation NPs have been designed, developed and tested in living subjects and few of them are already in clinical use. In near future, molecular imaging will get advanced with multimodality and multifunctionality to detect diseases like cancer, neurodegenerative diseases, cardiac diseases, inflammation, stroke, atherosclerosis and many others in their early stages. In the current review, we discussed single/multifunctional nanoparticles along with molecular imaging modalities. The present article intends to reveal recent avenues for nanomaterials in multimodal and multifunctional molecular imaging through a review of pertinent literatures. The topic emphasises on the distinctive characteristics of nanomaterial which makes them, suitable for biomedical imaging, therapy and delivery of drugs. This review is more informative of indicative technologies which will be helpful in a way to plan, understand and lead the nanotechnology related work. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Seeing cilia: imaging modalities for ciliary motion and clinical connections.

PubMed

Peabody, Jacelyn E; Shei, Ren-Jay; Bermingham, Brent M; Phillips, Scott E; Turner, Brett; Rowe, Steven M; Solomon, George M

2018-06-01

The respiratory tract is lined with multiciliated epithelial cells that function to move mucus and trapped particles via the mucociliary transport apparatus. Genetic and acquired ciliopathies result in diminished mucociliary clearance, contributing to disease pathogenesis. Recent innovations in imaging technology have advanced our understanding of ciliary motion in health and disease states. Application of imaging modalities including transmission electron microscopy, high-speed video microscopy, and micron-optical coherence tomography could improve diagnostics and be applied for precision medicine. In this review, we provide an overview of ciliary motion, imaging modalities, and ciliopathic diseases of the respiratory system including primary ciliary dyskinesia, cystic fibrosis, chronic obstructive pulmonary disease, and idiopathic pulmonary fibrosis.

Characterization and evaluation of ionizing and non-ionizing imaging systems used in state of the art image-guided radiation therapy techniques

NASA Astrophysics Data System (ADS)

Stanley, Dennis Nichols

With the growing incidence of cancer worldwide, the need for effective cancer treatment is paramount. Currently, radiation therapy exists as one of the few effective, non-invasive methods of reducing tumor size and has the capability for the elimination of localized tumors. Radiation therapy utilizes non-invasive external radiation to treat localized cancers but to be effective, physicians must be able to visualize and monitor the internal anatomy and target displacements. Image-Guided Radiation Therapy frequently utilizes planar and volumetric imaging during a course of radiation therapy to improve the precision and accuracy of the delivered treatment to the internal anatomy. Clinically, visualization of the internal anatomy allows physicians to refine the treatment to include as little healthy tissue as possible. This not only increases the effectiveness of treatment by damaging only the tumor but also increases the quality of life for the patient by decreasing the amount of healthy tissue damaged. Image-Guided Radiation Therapy is commonly used to treat tumors in areas of the body that are prone to movement, such as the lungs, liver, and prostate, as well as tumors located close to critical organs and tissues such as the tumors in the brain and spinal cord. Image-Guided Radiation Therapy can utilize both ionizing modalities, like x-ray based planar radiography and cone-beam CT, and nonionizing modalities like MRI, ultrasound and video-based optical scanning systems. Currently ionizing modalities are most commonly utilized for their ability to visualize and monitor internal anatomy but cause an increase to the total dose to the patient. Nonionizing imaging modalities allow frequent/continuous imaging without the increase in dose; however, they are just beginning to be clinically implemented in radiation oncology. With the growing prevalence and variety of Image-Guided Radiation Therapy imaging modalities the ability to evaluate the overall image quality, monitor the stability of the imaging systems and characterize each system are important to ensuring the consistency and effectiveness of the overall treatment. Image-Guided Radiation Therapy quality assurance allows a method of quantifying the accuracy and stability of the imaging systems. Understanding how the ionizing imaging systems operate and change over time allows for a more effective overall treatment and will be the focus of the first step of this project. In each of the first three aims, different ionizing imaging modalities will be evaluated for their temporal stability and a record of the determined tolerance level will be reported. The Second step of this project will be a characterization of the accuracy and performance of the new C-Rad CatalystHD a video-based, surface-imaging guided patient localization system. The catalyst will be analyzed for it accuracy of setup and patient positing, intra- and inter- fraction motion detection as well as its respiratory gating capabilities. The final step of this project will be to use the well-established accuracy of the XVI volumetric imaging system as a benchmark to assess the accuracy of the C-Rad CatalystHD system for use in pretreatment patient position verification for cranial stereotactic procedures. The treatment of brain lesions generally requires a very high degree of precision due to relatively small target sizes, close proximity to eloquent areas of the brain, and large, ablative doses being delivered. Stringent accuracy in imaging is needed to verify and monitor the correct spatial delivery of radiation throughout treatment. In order to investigate if the CatalystHD system is a capable imaging system for such deliveries, the system will need to be assessed and benchmarked against the XVI in a phantom geometry. By doing so, the currently unproven utility of the CatalystHD system for cranial stereotactic delivery may be established. (Abstract shortened by ProQuest.).

Multi-modal magnetic resonance imaging and histology of vascular function in xenografts using macromolecular contrast agent hyperbranched polyglycerol (HPG-GdF).

PubMed

Baker, Jennifer H E; McPhee, Kelly C; Moosvi, Firas; Saatchi, Katayoun; Häfeli, Urs O; Minchinton, Andrew I; Reinsberg, Stefan A

2016-01-01

Macromolecular gadolinium (Gd)-based contrast agents are in development as blood pool markers for MRI. HPG-GdF is a 583 kDa hyperbranched polyglycerol doubly tagged with Gd and Alexa 647 nm dye, making it both MR and histologically visible. In this study we examined the location of HPG-GdF in whole-tumor xenograft sections matched to in vivo DCE-MR images of both HPG-GdF and Gadovist. Despite its large size, we have shown that HPG-GdF extravasates from some tumor vessels and accumulates over time, but does not distribute beyond a few cell diameters from vessels. Fractional plasma volume (fPV) and apparent permeability-surface area product (aPS) parameters were derived from the MR concentration-time curves of HPG-GdF. Non-viable necrotic tumor tissue was excluded from the analysis by applying a novel bolus arrival time (BAT) algorithm to all voxels. aPS derived from HPG-GdF was the only MR parameter to identify a difference in vascular function between HCT116 and HT29 colorectal tumors. This study is the first to relate low and high molecular weight contrast agents with matched whole-tumor histological sections. These detailed comparisons identified tumor regions that appear distinct from each other using the HPG-GdF biomarkers related to perfusion and vessel leakiness, while Gadovist-imaged parameter measures in the same regions were unable to detect variation in vascular function. We have established HPG-GdF as a biocompatible multi-modal high molecular weight contrast agent with application for examining vascular function in both MR and histological modalities. Copyright © 2015 John Wiley & Sons, Ltd.

Development of an Automated Modality-Independent Elastographic Image Analysis System for Tumor Screening

DTIC Science & Technology

2006-02-01

further develop modality-independent elastography as a system that is able to reproducibly detect regions of increased stiffness within the breast based...tested on a tissue-like polymer phantom. elastography , breast cancer screening, image processing 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...is a map of the breast (or other tissue of interest) that reflects material inhomogeneity, such as in the case of a tumor mass that disrupts the

Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor

NASA Astrophysics Data System (ADS)

Uzkent, Burak; Hoffman, Matthew J.; Vodacek, Anthony

2015-03-01

Object tracking in urban environments is an important and challenging problem that is traditionally tackled using visible and near infrared wavelengths. By inserting extended data such as spectral features of the objects one can improve the reliability of the identification process. However, huge increase in data created by hyperspectral imaging is usually prohibitive. To overcome the complexity problem, we propose a persistent air-to-ground target tracking system inspired by a state-of-the-art, adaptive, multi-modal sensor. The adaptive sensor is capable of providing panchromatic images as well as the spectra of desired pixels. This addresses the data challenge of hyperspectral tracking by only recording spectral data as needed. Spectral likelihoods are integrated into a data association algorithm in a Bayesian fashion to minimize the likelihood of misidentification. A framework for controlling spectral data collection is developed by incorporating motion segmentation information and prior information from a Gaussian Sum filter (GSF) movement predictions from a multi-model forecasting set. An intersection mask of the surveillance area is extracted from OpenStreetMap source and incorporated into the tracking algorithm to perform online refinement of multiple model set. The proposed system is tested using challenging and realistic scenarios generated in an adverse environment.

Using queuing models to aid design and guide research effort for multimodality buried target detection systems

NASA Astrophysics Data System (ADS)

Malof, Jordan M.; Collins, Leslie M.

2016-05-01

Many remote sensing modalities have been developed for buried target detection (BTD), each one offering relative advantages over the others. There has been interest in combining several modalities into a single BTD system that benefits from the advantages of each constituent sensor. Recently an approach was developed, called multi-state management (MSM), that aims to achieve this goal by separating BTD system operation into discrete states, each with different sensor activity and system velocity. Additionally, a modeling approach, called Q-MSM, was developed to quickly analyze multi-modality BTD systems operating with MSM. This work extends previous work by demonstrating how Q-MSM modeling can be used to design BTD systems operating with MSM, and to guide research to yield the most performance benefits. In this work an MSM system is considered that combines a forward-looking infrared (FLIR) camera and a ground penetrating radar (GPR). Experiments are conducted using a dataset of real, field-collected, data which demonstrates how the Q-MSM model can be used to evaluate performance benefits of altering, or improving via research investment, various characteristics of the GPR and FLIR systems. Q-MSM permits fast analysis that can determine where system improvements will have the greatest impact, and can therefore help guide BTD research.

Performance Evaluation Modeling of Network Sensors

NASA Technical Reports Server (NTRS)

Clare, Loren P.; Jennings, Esther H.; Gao, Jay L.

2003-01-01

Substantial benefits are promised by operating many spatially separated sensors collectively. Such systems are envisioned to consist of sensor nodes that are connected by a communications network. A simulation tool is being developed to evaluate the performance of networked sensor systems, incorporating such metrics as target detection probabilities, false alarms rates, and classification confusion probabilities. The tool will be used to determine configuration impacts associated with such aspects as spatial laydown, and mixture of different types of sensors (acoustic, seismic, imaging, magnetic, RF, etc.), and fusion architecture. The QualNet discrete-event simulation environment serves as the underlying basis for model development and execution. This platform is recognized for its capabilities in efficiently simulating networking among mobile entities that communicate via wireless media. We are extending QualNet's communications modeling constructs to capture the sensing aspects of multi-target sensing (analogous to multiple access communications), unimodal multi-sensing (broadcast), and multi-modal sensing (multiple channels and correlated transmissions). Methods are also being developed for modeling the sensor signal sources (transmitters), signal propagation through the media, and sensors (receivers) that are consistent with the discrete event paradigm needed for performance determination of sensor network systems. This work is supported under the Microsensors Technical Area of the Army Research Laboratory (ARL) Advanced Sensors Collaborative Technology Alliance.

Image Guided Biodistribution and Pharmacokinetic Studies of Theranostics

PubMed Central

Ding, Hong; Wu, Fang

2012-01-01

Image guided technique is playing an increasingly important role in the investigation of the biodistribution and pharmacokinetics of drugs or drug delivery systems in various diseases, especially cancers. Besides anatomical imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), molecular imaging strategy including optical imaging, positron emission tomography (PET) and single-photon emission computed tomography (SPECT) will facilitate the localization and quantization of radioisotope or optical probe labeled nanoparticle delivery systems in the category of theranostics. The quantitative measurement of the bio-distribution and pharmacokinetics of theranostics in the fields of new drug/probe development, diagnosis and treatment process monitoring as well as tracking the brain-blood-barrier (BBB) breaking through by high sensitive imaging method, and the applications of the representative imaging modalities are summarized in this review. PMID:23227121

Multi-disciplinary optimization of aeroservoelastic systems

NASA Technical Reports Server (NTRS)

Karpel, Mordechay

1991-01-01

New methods were developed for efficient aeroservoelastic analysis and optimization. The main target was to develop a method for investigating large structural variations using a single set of modal coordinates. This task was accomplished by basing the structural modal coordinates on normal modes calculated with a set of fictitious masses loading the locations of anticipated structural changes. The following subject areas are covered: (1) modal coordinates for aeroelastic analysis with large local structural variations; and (2) time simulation of flutter with large stiffness changes.

Brain-based decoding of mentally imagined film clips and sounds reveals experience-based information patterns in film professionals.

PubMed

de Borst, Aline W; Valente, Giancarlo; Jääskeläinen, Iiro P; Tikka, Pia

2016-04-01

In the perceptual domain, it has been shown that the human brain is strongly shaped through experience, leading to expertise in highly-skilled professionals. What has remained unclear is whether specialization also shapes brain networks underlying mental imagery. In our fMRI study, we aimed to uncover modality-specific mental imagery specialization of film experts. Using multi-voxel pattern analysis we decoded from brain activity of professional cinematographers and sound designers whether they were imagining sounds or images of particular film clips. In each expert group distinct multi-voxel patterns, specific for the modality of their expertise, were found during classification of imagery modality. These patterns were mainly localized in the occipito-temporal and parietal cortex for cinematographers and in the auditory cortex for sound designers. We also found generalized patterns across perception and imagery that were distinct for the two expert groups: they involved frontal cortex for the cinematographers and temporal cortex for the sound designers. Notably, the mental representations of film clips and sounds of cinematographers contained information that went beyond modality-specificity. We were able to successfully decode the implicit presence of film genre from brain activity during mental imagery in cinematographers. The results extend existing neuroimaging literature on expertise into the domain of mental imagery and show that experience in visual versus auditory imagery can alter the representation of information in modality-specific association cortices. Copyright © 2016 Elsevier Inc. All rights reserved.

Evoking Emotions and Unpacking Layered Histories through Young Children's Illustrations of Racial Bus Segregation

ERIC Educational Resources Information Center

Kuby, Candace R.

2013-01-01

Drawing on theories of multi-modality and critical visual literacy, this article focuses on images that five-and six year-olds painted in a class-made book, Voice on the Bus, about racial segregation. The article discusses how children used illustrations to convey their understandings of Rosa Parks' bus arrest in Alabama. A post-structural view…

Design of Open Content Social Learning That Increases Learning Efficiency and Engagement Based on Open Pedagogy

ERIC Educational Resources Information Center

John, Benneaser; Thavavel, V.; Jayaraj, Jayakumar; Muthukumar, A.; Jeevanandam, Poornaselvan Kittu

2016-01-01

Academic writing skills are crucial when students, e.g., in teacher education programs, write their undergraduate theses. A multi-modal web-based and self-regulated learning resource on academic writing was developed, using texts, hypertext, moving images, podcasts and templates. A study, using surveys and a focus group, showed that students used…

Multi-modal porous microstructure for high temperature fuel cell application

NASA Astrophysics Data System (ADS)

Wejrzanowski, T.; Haj Ibrahim, S.; Cwieka, K.; Loeffler, M.; Milewski, J.; Zschech, E.; Lee, C.-G.

2018-01-01

In this study, the effect of microstructure of porous nickel electrode on the performance of high temperature fuel cell is investigated and presented based on a molten carbonate fuel cell (MCFC) cathode. The cathode materials are fabricated from slurry consisting of nickel powder and polymeric binder/solvent mixture, using the tape casting method. The final pore structure is shaped through modifying the slurry composition - with or without the addition of porogen(s). The manufactured materials are extensively characterized by various techniques involving: micro-computed tomography (micro-XCT), scanning electron microscopy (SEM), mercury porosimetry, BET and Archimedes method. Tomographic images are also analyzed and quantified to reveal the evolution of pore space due to nickel in situ oxidation to NiO, and infiltration by the electrolyte. Single-cell performance tests are carried out under MCFC operation conditions to estimate the performance of the manufactured materials. It is found that the multi-modal microstructure of MCFC cathode results in a significant enhancement of the power density generated by the reference cell. To give greater insight into the understanding of the effect of microstructure on the properties of the cathode, a model based on 3D tomography image transformation is proposed.

Image dissemination and archiving.

PubMed

Robertson, Ian

2007-08-01

Images generated as part of the sonographic examination are an integral part of the medical record and must be retained according to local regulations. The standard medical image format, known as DICOM (Digital Imaging and COmmunications in Medicine) makes it possible for images from many different imaging modalities, including ultrasound, to be distributed via a standard internet network to distant viewing workstations and a central archive in an almost seamless fashion. The DICOM standard is a truly universal standard for the dissemination of medical images. When purchasing an ultrasound unit, the consumer should research the unit's capacity to generate images in a DICOM format, especially if one wishes interconnectivity with viewing workstations and an image archive that stores other medical images. PACS, an acronym for Picture Archive and Communication System refers to the infrastructure that links modalities, workstations, the image archive, and the medical record information system into an integrated system, allowing for efficient electronic distribution and storage of medical images and access to medical record data.

Integration of multi-modal public transportation systems.

DOT National Transportation Integrated Search

2013-05-01

Transit ridership may be sensitive to fares, travel times, waiting times, and access times, among other factors. Thus, : elastic demands are considered in formulations for maximizing the system welfare for conventional and flexible bus : services. Tw...

Multi-Modal Transportation System Simulation

DOT National Transportation Integrated Search

1971-01-01

THE PRESENT STATUS OF A LABORATORY BEING DEVELOPED FOR REAL-TIME SIMULATION OF COMMAND AND CONTROL FUNCTIONS IN TRANSPORTATION SYSTEMS IS DISCUSSED. DETAILS ARE GIVEN ON THE SIMULATION MODELS AND ON PROGRAMMING TECHNIQUES USED IN DEFINING AND EVALUAT...

Using online modules is a multi-modality teaching system: a high-touch high-tech approach to geriatric education.

PubMed

Gainor, Sara Jane; Goins, R Turner; Miller, Lee Ann

2004-01-01

Making geriatric education available to rural faculty/preceptors, students, and practitioners presents many challenges. Often the only options considered for educating those in the health professions about geriatrics are either traditional face-to-face courses or distance education programs. The purpose of this paper was to examine the use of Web-based modules or courses and other distance learning technology in concert with traditional learning modalities. The Mountain State Geriatric Education Center explored the use of a multi-modal approach within a high-touch, high-tech framework. Our findings indicate the following: it is important to start where participants are ready to begin; flexibility and variety are needed; soliciting evaluative feedback from participants is valuable; there is a need to integrate distance learning with more traditional modalities; and a high-tech, high-touch approach provides a format which participants find acceptable, accessible, and attractive. This assertion does not rule out the use of technology for distance education but rather encourages educators to take advantage of a wide range of modalities, traditional and technological, to reach rural practitioners, faculty, and students.

In vivo two-photon imaging of macrophage activities in skeletal muscle regeneration

NASA Astrophysics Data System (ADS)

Qin, Zhongya; Long, Yanyang; Sun, Qiqi; He, Sicong; Li, Xuesong; Chen, Congping; Wu, Zhenguo; Qu, Jianan Y.

2018-02-01

Macrophages are essential for the regeneration of skeletal muscle after injury. It has been demonstrated that depletion of macrophages results in delay of necrotic fiber phagocytosis and decreased size of regenerated myofibers. In this work, we developed a multi-modal two-photon microscope system for in vivo study of macrophage activities in the regenerative and fibrotic healing process of injured skeletal muscles. The system is capable to image the muscles based on the second harmonic generation (SHG) and two-photon excited fluorescence (TPEF) signals simultaneously. The dynamic activities of macrophages and muscle satellite cells are recorded in different time windows post the muscle injury. Moreover, we found that infiltrating macrophages emitted strong autofluorescence in the injured skeletal muscle of mouse model, which has not been reported previously. The macrophage autofluorescence was characterized in both spectral and temporal domains. The information extracted from the autofluorescence signals may facilitate the understanding on the formation mechanisms and possible applications in biological research related to skeletal muscle regeneration.

Systems engineering management plan : Dallas Integrated Corridor Management (ICM) demonstration project.

DOT National Transportation Integrated Search

2010-12-01

The purpose of the Dallas ICM System is to implement a multi-modal operations decision support tool enabled by real-time data pertaining to the operation of freeways, arterials, and public transit. The system will be shared between information system...

A dual-modal retinal imaging system with adaptive optics.

PubMed

Meadway, Alexander; Girkin, Christopher A; Zhang, Yuhua

2013-12-02

An adaptive optics scanning laser ophthalmoscope (AO-SLO) is adapted to provide optical coherence tomography (OCT) imaging. The AO-SLO function is unchanged. The system uses the same light source, scanning optics, and adaptive optics in both imaging modes. The result is a dual-modal system that can acquire retinal images in both en face and cross-section planes at the single cell level. A new spectral shaping method is developed to reduce the large sidelobes in the coherence profile of the OCT imaging when a non-ideal source is used with a minimal introduction of noise. The technique uses a combination of two existing digital techniques. The thickness and position of the traditionally named inner segment/outer segment junction are measured from individual photoreceptors. In-vivo images of healthy and diseased human retinas are demonstrated.

Optical imaging modalities: From design to diagnosis of skin cancer

NASA Astrophysics Data System (ADS)

Korde, Vrushali Raj

This study investigates three high resolution optical imaging modalities to better detect and diagnose skin cancer. The ideal high resolution optical imaging system can visualize pre-malignant tissue growth non-invasively with resolution comparable to histology. I examined 3 modalities which approached this goal. The first method examined was high magnification microscopy of thin stained tissue sections, together with a statistical analysis of nuclear chromatin patterns termed Karyometry. This method has subcellular resolution, but it necessitates taking a biopsy at the desired tissue site and imaging the tissue ex-vivo. My part of this study was to develop an automated nuclear segmentation algorithm to segment cell nuclei in skin histology images for karyometric analysis. The results of this algorithm were compared to hand segmented cell nuclei in the same images, and it was concluded that the automated segmentations can be used for karyometric analysis. The second optical imaging modality I investigated was Optical Coherence Tomography (OCT). OCT is analogous to ultrasound, in which sound waves are delivered into the body and the echo time and reflected signal magnitude are measured. Due to the fast speed of light and detector temporal integration times, low coherence interferometry is needed to gate the backscattered light. OCT acquires cross sectional images, and has an axial resolution of 1-15 mum (depending on the source bandwidth) and a lateral resolution of 10-20 mum (depending on the sample arm optics). While it is not capable of achieving subcellular resolution, it is a non-invasive imaging modality. OCT was used in this study to evaluate skin along a continuum from normal to sun damaged to precancer. I developed algorithms to detect statistically significant differences between images of sun protected and sun damaged skin, as well as between undiseased and precancerous skin. An Optical Coherence Microscopy (OCM) endoscope was developed in the third portion of this study. OCM is a high resolution en-face imaging modality. It is a hybrid system that combines the principles of confocal microscopy with coherence gating to provide an increased imaging depth. It can also be described as an OCT system with a high NA objective. Similar to OCT, the axial resolution is determined by the source center wavelength and bandwidth. The NA of the sample arm optics determines the lateral resolution, usually on the order of 1-5 mum. My effort on this system was to develop a handheld endoscope. To my knowledge, an OCM endoscope has not been developed prior to this work. An image of skin was taken as a proof of concept. This rigid handheld OCM endoscope will be useful for applications ranging from minimally invasive surgical imaging to non-invasively assessing dysplasia and sun damage in skin.

Development of gamma-photon/Cerenkov-light hybrid system for simultaneous imaging of I-131 radionuclide

NASA Astrophysics Data System (ADS)

Yamamoto, Seiichi; Suzuki, Mayumi; Kato, Katsuhiko; Watabe, Tadashi; Ikeda, Hayato; Kanai, Yasukazu; Ogata, Yoshimune; Hatazawa, Jun

2016-09-01

Although iodine 131 (I-131) is used for radionuclide therapy, high resolution images are difficult to obtain with conventional gamma cameras because of the high energy of I-131 gamma photons (364 keV). Cerenkov-light imaging is a possible method for beta emitting radionuclides, and I-131 (606 MeV maximum beta energy) is a candidate to obtain high resolution images. We developed a high energy gamma camera system for I-131 radionuclide and combined it with a Cerenkov-light imaging system to form a gamma-photon/Cerenkov-light hybrid imaging system to compare the simultaneously measured images of these two modalities. The high energy gamma imaging detector used 0.85-mm×0.85-mm×10-mm thick GAGG scintillator pixels arranged in a 44×44 matrix with a 0.1-mm thick reflector and optical coupled to a Hamamatsu 2 in. square position sensitive photomultiplier tube (PSPMT: H12700 MOD). The gamma imaging detector was encased in a 2 cm thick tungsten shield, and a pinhole collimator was mounted on its top to form a gamma camera system. The Cerenkov-light imaging system was made of a high sensitivity cooled CCD camera. The Cerenkov-light imaging system was combined with the gamma camera using optical mirrors to image the same area of the subject. With this configuration, we simultaneously imaged the gamma photons and the Cerenkov-light from I-131 in the subjects. The spatial resolution and sensitivity of the gamma camera system for I-131 were respectively 3 mm FWHM and 10 cps/MBq for the high sensitivity collimator at 10 cm from the collimator surface. The spatial resolution of the Cerenkov-light imaging system was 0.64 mm FWHM at 10 cm from the system surface. Thyroid phantom and rat images were successfully obtained with the developed gamma-photon/Cerenkov-light hybrid imaging system, allowing direct comparison of these two modalities. Our developed gamma-photon/Cerenkov-light hybrid imaging system will be useful to evaluate the advantages and disadvantages of these two modalities.

Multi-modal neuroimaging in premanifest and early Huntington's disease: 18 month longitudinal data from the IMAGE-HD study.

PubMed

Domínguez D, Juan F; Egan, Gary F; Gray, Marcus A; Poudel, Govinda R; Churchyard, Andrew; Chua, Phyllis; Stout, Julie C; Georgiou-Karistianis, Nellie

2013-01-01

IMAGE-HD is an Australian based multi-modal longitudinal magnetic resonance imaging (MRI) study in premanifest and early symptomatic Huntington's disease (pre-HD and symp-HD, respectively). In this investigation we sought to determine the sensitivity of imaging methods to detect macrostructural (volume) and microstructural (diffusivity) longitudinal change in HD. We used a 3T MRI scanner to acquire T1 and diffusion weighted images at baseline and 18 months in 31 pre-HD, 31 symp-HD and 29 controls. Volume was measured across the whole brain, and volume and diffusion measures were ascertained for caudate and putamen. We observed a range of significant volumetric and, for the first time, diffusion changes over 18 months in both pre-HD and symp-HD, relative to controls, detectable at the brain-wide level (volume change in grey and white matter) and in caudate and putamen (volume and diffusivity change). Importantly, longitudinal volume change in the caudate was the only measure that discriminated between groups across all stages of disease: far from diagnosis (>15 years), close to diagnosis (<15 years) and after diagnosis. Of the two diffusion metrics (mean diffusivity, MD; fractional anisotropy, FA), only longitudinal FA change was sensitive to group differences, but only after diagnosis. These findings further confirm caudate atrophy as one of the most sensitive and early biomarkers of neurodegeneration in HD. They also highlight that different tissue properties have varying schedules in their ability to discriminate between groups along disease progression and may therefore inform biomarker selection for future therapeutic interventions.

In vivo confirmation of hydration based contrast mechanisms for terahertz medical imaging using MRI

NASA Astrophysics Data System (ADS)

Bajwa, Neha; Sung, Shijun; Garritano, James; Nowroozi, Bryan; Tewari, Priyamvada; Ennis, Daniel B.; Alger, Jeffery; Grundfest, Warren; Taylor, Zachary

2014-09-01

Terahertz (THz) detection has been proposed and applied to a variety of medical imaging applications in view of its unrivaled hydration profiling capabilities. Variations in tissue dielectric function have been demonstrated at THz frequencies to generate high contrast imagery of tissue, however, the source of image contrast remains to be verified using a modality with a comparable sensing scheme. To investigate the primary contrast mechanism, a pilot comparison study was performed in a burn wound rat model, widely known to create detectable gradients in tissue hydration through both injured and surrounding tissue. Parallel T2 weighted multi slice multi echo (T2w MSME) 7T Magnetic Resonance (MR) scans and THz surface reflectance maps were acquired of a full thickness skin burn in a rat model over a 5 hour time period. A comparison of uninjured and injured regions in the full thickness burn demonstrates a 3-fold increase in average T2 relaxation times and a 15% increase in average THz reflectivity, respectively. These results support the sensitivity and specificity of MRI for measuring in vivo burn tissue water content and the use of this modality to verify and understand the hydration sensing capabilities of THz imaging for acute assessments of the onset and evolution of diseases that affect the skin. A starting point for more sophisticated in vivo studies, this preliminary analysis may be used in the future to explore how and to what extent the release of unbound water affects imaging contrast in THz burn sensing.

Neurosurgical confocal endomicroscopy: A review of contrast agents, confocal systems, and future imaging modalities

PubMed Central

Zehri, Aqib H.; Ramey, Wyatt; Georges, Joseph F.; Mooney, Michael A.; Martirosyan, Nikolay L.; Preul, Mark C.; Nakaji, Peter

2014-01-01

Background: The clinical application of fluorescent contrast agents (fluorescein, indocyanine green, and aminolevulinic acid) with intraoperative microscopy has led to advances in intraoperative brain tumor imaging. Their properties, mechanism of action, history of use, and safety are analyzed in this report along with a review of current laser scanning confocal endomicroscopy systems. Additional imaging modalities with potential neurosurgical utility are also analyzed. Methods: A comprehensive literature search was performed utilizing PubMed and key words: In vivo confocal microscopy, confocal endomicroscopy, fluorescence imaging, in vivo diagnostics/neoplasm, in vivo molecular imaging, and optical imaging. Articles were reviewed that discussed clinically available fluorophores in neurosurgery, confocal endomicroscopy instrumentation, confocal microscopy systems, and intraoperative cancer diagnostics. Results: Current clinically available fluorescent contrast agents have specific properties that provide microscopic delineation of tumors when imaged with laser scanning confocal endomicroscopes. Other imaging modalities such as coherent anti-Stokes Raman scattering (CARS) microscopy, confocal reflectance microscopy, fluorescent lifetime imaging (FLIM), two-photon microscopy, and second harmonic generation may also have potential in neurosurgical applications. Conclusion: In addition to guiding tumor resection, intraoperative fluorescence and microscopy have the potential to facilitate tumor identification and complement frozen section analysis during surgery by providing real-time histological assessment. Further research, including clinical trials, is necessary to test the efficacy of fluorescent contrast agents and optical imaging instrumentation in order to establish their role in neurosurgery. PMID:24872922

Imaging for percutaneous renal access and management of renal calculi.

PubMed

Park, Sangtae; Pearle, Margaret S

2006-08-01

Percutaneous renal stone surgery requires detailed imaging to define stone burden and delineate the anatomy of the kidney and nearby organs. It is also essential to carry out safe percutaneous access and to assess postoperative outcomes. The emergence of CT as the imaging modality of choice for detecting renal calculi and the ability of CT urography with or without three-dimensional reconstruction to delineate the collecting system makes this the most versatile and sensitive imaging modality for pre- and postoperative evaluation. At present, intravenous urogram continues to play an important role in the evaluation of patients considered for percutaneous nephrostolithotomy. Fluoroscopy re-mains the mainstay of intraoperative imaging, although ultrasound is a useful alternative. Selection and application of appropriate imaging modalities for patients undergoing per-cutaneous nephrostolithotomy enhances the safety and success of the procedure.