[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.

A Dual-Modality System for Both Multi-Color Ultrasound-Switchable Fluorescence and Ultrasound Imaging

PubMed Central

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

2017-01-01

Simultaneous imaging of multiple targets (SIMT) in opaque biological tissues is an important goal for molecular imaging in the future. Multi-color fluorescence imaging in deep tissues is a promising technology to reach this goal. In this work, we developed a dual-modality imaging system by combining our recently developed ultrasound-switchable fluorescence (USF) imaging technology with the conventional ultrasound (US) B-mode imaging. This dual-modality system can simultaneously image tissue acoustic structure information and multi-color fluorophores in centimeter-deep tissue with comparable spatial resolutions. To conduct USF imaging on the same plane (i.e., x-z plane) as US imaging, we adopted two 90°-crossed ultrasound transducers with an overlapped focal region, while the US transducer (the third one) was positioned at the center of these two USF transducers. Thus, the axial resolution of USF is close to the lateral resolution, which allows a point-by-point USF scanning on the same plane as the US imaging. Both multi-color USF and ultrasound imaging of a tissue phantom were demonstrated. PMID:28165390

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

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

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.

A novel automated method for doing registration and 3D reconstruction from multi-modal RGB/IR image sequences

NASA Astrophysics Data System (ADS)

Kirby, Richard; Whitaker, Ross

2016-09-01

In recent years, the use of multi-modal camera rigs consisting of an RGB sensor and an infrared (IR) sensor have become increasingly popular for use in surveillance and robotics applications. The advantages of using multi-modal camera rigs include improved foreground/background segmentation, wider range of lighting conditions under which the system works, and richer information (e.g. visible light and heat signature) for target identification. However, the traditional computer vision method of mapping pairs of images using pixel intensities or image features is often not possible with an RGB/IR image pair. We introduce a novel method to overcome the lack of common features in RGB/IR image pairs by using a variational methods optimization algorithm to map the optical flow fields computed from different wavelength images. This results in the alignment of the flow fields, which in turn produce correspondences similar to those found in a stereo RGB/RGB camera rig using pixel intensities or image features. In addition to aligning the different wavelength images, these correspondences are used to generate dense disparity and depth maps. We obtain accuracies similar to other multi-modal image alignment methodologies as long as the scene contains sufficient depth variations, although a direct comparison is not possible because of the lack of standard image sets from moving multi-modal camera rigs. We test our method on synthetic optical flow fields and on real image sequences that we created with a multi-modal binocular stereo RGB/IR camera rig. We determine our method's accuracy by comparing against a ground truth.

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

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.

Dual-modality imaging

NASA Astrophysics Data System (ADS)

Hasegawa, Bruce; Tang, H. Roger; Da Silva, Angela J.; Wong, Kenneth H.; Iwata, Koji; Wu, Max C.

2001-09-01

In comparison to conventional medical imaging techniques, dual-modality imaging offers the advantage of correlating anatomical information from X-ray computed tomography (CT) with functional measurements from single-photon emission computed tomography (SPECT) or with positron emission tomography (PET). The combined X-ray/radionuclide images from dual-modality imaging can help the clinician to differentiate disease from normal uptake of radiopharmaceuticals, and to improve diagnosis and staging of disease. In addition, phantom and animal studies have demonstrated that a priori structural information from CT can be used to improve quantification of tissue uptake and organ function by correcting the radionuclide data for errors due to photon attenuation, partial volume effects, scatter radiation, and other physical effects. Dual-modality imaging therefore is emerging as a method of improving the visual quality and the quantitative accuracy of radionuclide imaging for diagnosis of patients with cancer and heart disease.

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

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.

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

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

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

vECTlab—A fully integrated multi-modality Monte Carlo simulation framework for the radiological imaging sciences

NASA Astrophysics Data System (ADS)

Peter, Jörg; Semmler, Wolfhard

2007-10-01

Alongside and in part motivated by recent advances in molecular diagnostics, the development of dual-modality instruments for patient and dedicated small animal imaging has gained attention by diverse research groups. The desire for such systems is high not only to link molecular or functional information with the anatomical structures, but also for detecting multiple molecular events simultaneously at shorter total acquisition times. While PET and SPECT have been integrated successfully with X-ray CT, the advance of optical imaging approaches (OT) and the integration thereof into existing modalities carry a high application potential, particularly for imaging small animals. A multi-modality Monte Carlo (MC) simulation approach at present has been developed that is able to trace high-energy (keV) as well as optical (eV) photons concurrently within identical phantom representation models. We show that the involved two approaches for ray-tracing keV and eV photons can be integrated into a unique simulation framework which enables both photon classes to be propagated through various geometry models representing both phantoms and scanners. The main advantage of such integrated framework for our specific application is the investigation of novel tomographic multi-modality instrumentation intended for in vivo small animal imaging through time-resolved MC simulation upon identical phantom geometries. Design examples are provided for recently proposed SPECT-OT and PET-OT imaging systems.

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

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

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

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.

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.

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.

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.

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.

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.

Quantitative multi-modal MRI of the Hippocampus and cognitive ability in community-dwelling older subjects.

PubMed

Aribisala, Benjamin S; Royle, Natalie A; Maniega, Susana Muñoz; Valdés Hernández, Maria C; Murray, Catherine; Penke, Lars; Gow, Alan; Starr, John M; Bastin, Mark E; Deary, Ian J; Wardlaw, Joanna M

2014-04-01

Hippocampal structural integrity is commonly quantified using volumetric measurements derived from brain magnetic resonance imaging (MRI). Previously reported associations with cognitive decline have not been consistent. We investigate hippocampal integrity using quantitative MRI techniques and its association with cognitive abilities in older age. Participants from the Lothian Birth Cohort 1936 underwent brain MRI at mean age 73 years. Longitudinal relaxation time (T1), magnetization transfer ratio (MTR), fractional anisotropy (FA) and mean diffusivity (MD) were measured in the hippocampus. General factors of fluid-type intelligence (g), cognitive processing speed (speed) and memory were obtained at age 73 years, as well as childhood IQ test results at age 11 years. Amongst 565 older adults, multivariate linear regression showed that, after correcting for ICV, gender and age 11 IQ, larger left hippocampal volume was significantly associated with better memory ability (β = .11, p = .003), but not with speed or g. Using quantitative MRI and after correcting for multiple testing, higher T1 and MD were significantly associated with lower scores of g (β range = -.11 to -.14, p < .001), speed (β range = -.15 to -.20, p < .001) and memory (β range = -.10 to -.12, p < .001). Higher MTR and FA in the hippocampus were also significantly associated with higher scores of g (β range = .17 to .18, p < .0001) and speed (β range = .10 to .15, p < .0001), but not memory. Quantitative multi-modal MRI assessments were more sensitive at detecting cognition-hippocampal integrity associations than volumetric measurements, resulting in stronger associations between MRI biomarkers and age-related cognition changes. Copyright © 2014. Published by Elsevier Ltd.

Quantitative phase-digital holographic microscopy: a new imaging modality to identify original cellular biomarkers of diseases

NASA Astrophysics Data System (ADS)

Marquet, P.; Rothenfusser, K.; Rappaz, B.; Depeursinge, C.; Jourdain, P.; Magistretti, P. J.

2016-03-01

Quantitative phase microscopy (QPM) has recently emerged as a powerful label-free technique in the field of living cell imaging allowing to non-invasively measure with a nanometric axial sensitivity cell structure and dynamics. Since the phase retardation of a light wave when transmitted through the observed cells, namely the quantitative phase signal (QPS), is sensitive to both cellular thickness and intracellular refractive index related to the cellular content, its accurate analysis allows to derive various cell parameters and monitor specific cell processes, which are very likely to identify new cell biomarkers. Specifically, quantitative phase-digital holographic microscopy (QP-DHM), thanks to its numerical flexibility facilitating parallelization and automation processes, represents an appealing imaging modality to both identify original cellular biomarkers of diseases as well to explore the underlying pathophysiological processes.

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.

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

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

A prototype hand-held tri-modal instrument for in vivo ultrasound, photoacoustic, and fluorescence imaging

NASA Astrophysics Data System (ADS)

Kang, Jeeun; Chang, Jin Ho; Wilson, Brian C.; Veilleux, Israel; Bai, Yanhui; DaCosta, Ralph; Kim, Kang; Ha, Seunghan; Lee, Jong Gun; Kim, Jeong Seok; Lee, Sang-Goo; Kim, Sun Mi; Lee, Hak Jong; Ahn, Young Bok; Han, Seunghee; Yoo, Yangmo; Song, Tai-Kyong

2015-03-01

Multi-modality imaging is beneficial for both preclinical and clinical applications as it enables complementary information from each modality to be obtained in a single procedure. In this paper, we report the design, fabrication, and testing of a novel tri-modal in vivo imaging system to exploit molecular/functional information from fluorescence (FL) and photoacoustic (PA) imaging as well as anatomical information from ultrasound (US) imaging. The same ultrasound transducer was used for both US and PA imaging, bringing the pulsed laser light into a compact probe by fiberoptic bundles. The FL subsystem is independent of the acoustic components but the front end that delivers and collects the light is physically integrated into the same probe. The tri-modal imaging system was implemented to provide each modality image in real time as well as co-registration of the images. The performance of the system was evaluated through phantom and in vivo animal experiments. The results demonstrate that combining the modalities does not significantly compromise the performance of each of the separate US, PA, and FL imaging techniques, while enabling multi-modality registration. The potential applications of this novel approach to multi-modality imaging range from preclinical research to clinical diagnosis, especially in detection/localization and surgical guidance of accessible solid tumors.

Development of a Multi-modal Tissue Diagnostic System Combining High Frequency Ultrasound and Photoacoustic Imaging with Lifetime Fluorescence Spectroscopy

PubMed Central

Sun, Yang; Stephens, Douglas N.; Park, Jesung; Sun, Yinghua; Marcu, Laura; Cannata, Jonathan M.; Shung, K. Kirk

2010-01-01

We report the development and validate a multi-modal tissue diagnostic technology, which combines three complementary techniques into one system including ultrasound backscatter microscopy (UBM), photoacoustic imaging (PAI), and time-resolved laser-induced fluorescence spectroscopy (TR-LIFS). UBM enables the reconstruction of the tissue microanatomy. PAI maps the optical absorption heterogeneity of the tissue associated with structure information and has the potential to provide functional imaging of the tissue. Examination of the UBM and PAI images allows for localization of regions of interest for TR-LIFS evaluation of the tissue composition. The hybrid probe consists of a single element ring transducer with concentric fiber optics for multi-modal data acquisition. Validation and characterization of the multi-modal system and ultrasonic, photoacoustic, and spectroscopic data coregistration were conducted in a physical phantom with properties of ultrasound scattering, optical absorption, and fluorescence. The UBM system with the 41 MHz ring transducer can reach the axial and lateral resolution of 30 and 65 μm, respectively. The PAI system with 532 nm excitation light from a Nd:YAG laser shows great contrast for the distribution of optical absorbers. The TR-LIFS system records the fluorescence decay with the time resolution of ~300 ps and a high sensitivity of nM concentration range. Biological phantom constructed with different types of tissues (tendon and fat) was used to demonstrate the complementary information provided by the three modalities. Fluorescence spectra and lifetimes were compared to differentiate chemical composition of tissues at the regions of interest determined by the coregistered high resolution UBM and PAI image. Current results demonstrate that the fusion of these techniques enables sequentially detection of functional, morphological, and compositional features of biological tissue, suggesting potential applications in diagnosis of tumors

Development of a Multi-modal Tissue Diagnostic System Combining High Frequency Ultrasound and Photoacoustic Imaging with Lifetime Fluorescence Spectroscopy.

PubMed

Sun, Yang; Stephens, Douglas N; Park, Jesung; Sun, Yinghua; Marcu, Laura; Cannata, Jonathan M; Shung, K Kirk

2008-01-01

We report the development and validate a multi-modal tissue diagnostic technology, which combines three complementary techniques into one system including ultrasound backscatter microscopy (UBM), photoacoustic imaging (PAI), and time-resolved laser-induced fluorescence spectroscopy (TR-LIFS). UBM enables the reconstruction of the tissue microanatomy. PAI maps the optical absorption heterogeneity of the tissue associated with structure information and has the potential to provide functional imaging of the tissue. Examination of the UBM and PAI images allows for localization of regions of interest for TR-LIFS evaluation of the tissue composition. The hybrid probe consists of a single element ring transducer with concentric fiber optics for multi-modal data acquisition. Validation and characterization of the multi-modal system and ultrasonic, photoacoustic, and spectroscopic data coregistration were conducted in a physical phantom with properties of ultrasound scattering, optical absorption, and fluorescence. The UBM system with the 41 MHz ring transducer can reach the axial and lateral resolution of 30 and 65 μm, respectively. The PAI system with 532 nm excitation light from a Nd:YAG laser shows great contrast for the distribution of optical absorbers. The TR-LIFS system records the fluorescence decay with the time resolution of ~300 ps and a high sensitivity of nM concentration range. Biological phantom constructed with different types of tissues (tendon and fat) was used to demonstrate the complementary information provided by the three modalities. Fluorescence spectra and lifetimes were compared to differentiate chemical composition of tissues at the regions of interest determined by the coregistered high resolution UBM and PAI image. Current results demonstrate that the fusion of these techniques enables sequentially detection of functional, morphological, and compositional features of biological tissue, suggesting potential applications in diagnosis of tumors

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.

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.

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.

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-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.

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.

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.

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.

Quantitative multi-modality imaging analysis of a bioabsorbable poly-L-lactic acid stent design in the acute phase: a comparison between 2- and 3D-QCA, QCU and QMSCT-CA.

PubMed

Bruining, Nico; Tanimoto, Shuzou; Otsuka, Masato; Weustink, Annick; Ligthart, Jurgen; de Winter, Sebastiaan; van Mieghem, Carlos; Nieman, Koen; de Feyter, Pim J; van Domburg, Ron T; Serruys, Patrick W

2008-08-01

To investigate if three-dimensional (3D) based quantitative techniques are comparable to each other and to explore possible differences with respect to the reference method of 2D-QCA in the acute phase and to study whether non-invasive MSCT could potentially be applied to quantify luminal dimensions of a stented coronary segment with a novel bioabsorable drug-eluting stent made of poly-l-lactic-acid (PLLA). Quantitative imaging data derived from 16 patients enrolled at our institution in a first-in-man trial (ABSORB) receiving a biodegradable stent and who were imaged with standard coronary angiography and intravascular ultrasound were compared. Shortly, after stenting the patients also underwent a MSCT procedure. Standard 2D-QCA showed significant smaller stent lengths (p < 0.01). Although, the absolute measured stent diameters and areas by 2D-QCA tend to be smaller, the differences failed to be statistically different when compared to the 3D based quantitative modalities. Measurements made by non-invasive QMSCT-CA of implanted PLLA stents appeared to be comparable to the other 3D modalities without significant differences. Three-dimensional based quantitative analyses showed similar results quantifying luminal dimensions as compared to 2D-QCA during an evaluation of a new bioabsorbable coronary stent design in the acute phase. Furthermore, in biodegradable stents made of PLLA, non-invasive QMSCT-CA can be used to quantify luminal dimensions.

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.

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.

Smartphone-Based Dual-Modality Imaging System for Quantitative Detection of Color or Fluorescent Lateral Flow Immunochromatographic Strips

NASA Astrophysics Data System (ADS)

Hou, Yafei; Wang, Kan; Xiao, Kun; Qin, Weijian; Lu, Wenting; Tao, Wei; Cui, Daxiang

2017-04-01

Nowadays, lateral flow immunochromatographic assays are increasingly popular as a diagnostic tool for point-of-care (POC) test based on their simplicity, specificity, and sensitivity. Hence, quantitative detection and pluralistic popular application are urgently needed in medical examination. In this study, a smartphone-based dual-modality imaging system was developed for quantitative detection of color or fluorescent lateral flow test strips, which can be operated anywhere at any time. In this system, the white and ultra-violet (UV) light of optical device was designed, which was tunable with different strips, and the Sobel operator algorithm was used in the software, which could enhance the identification ability to recognize the test area from the background boundary information. Moreover, this technology based on extraction of the components from RGB format (red, green, and blue) of color strips or only red format of the fluorescent strips can obviously improve the high-signal intensity and sensitivity. Fifty samples were used to evaluate the accuracy of this system, and the ideal detection limit was calculated separately from detection of human chorionic gonadotropin (HCG) and carcinoembryonic antigen (CEA). The results indicated that smartphone-controlled dual-modality imaging system could provide various POC diagnoses, which becomes a potential technology for developing the next-generation of portable system in the near future.

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.

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.

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

Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

PubMed

Zuluaga, Maria A; Rodionov, Roman; Nowell, Mark; Achhala, Sufyan; Zombori, Gergely; Mendelson, Alex F; Cardoso, M Jorge; Miserocchi, Anna; McEvoy, Andrew W; Duncan, John S; Ourselin, Sébastien

2015-08-01

Brain vessels are among the most critical landmarks that need to be assessed for mitigating surgical risks in stereo-electroencephalography (SEEG) implantation. Intracranial haemorrhage is the most common complication associated with implantation, carrying significantly associated morbidity. SEEG planning is done pre-operatively to identify avascular trajectories for the electrodes. In current practice, neurosurgeons have no assistance in the planning of electrode trajectories. There is great interest in developing computer-assisted planning systems that can optimise the safety profile of electrode trajectories, maximising the distance to critical structures. This paper presents a method that integrates the concepts of scale, neighbourhood structure and feature stability with the aim of improving robustness and accuracy of vessel extraction within a SEEG planning system. The developed method accounts for scale and vicinity of a voxel by formulating the problem within a multi-scale tensor voting framework. Feature stability is achieved through a similarity measure that evaluates the multi-modal consistency in vesselness responses. The proposed measurement allows the combination of multiple images modalities into a single image that is used within the planning system to visualise critical vessels. Twelve paired data sets from two image modalities available within the planning system were used for evaluation. The mean Dice similarity coefficient was 0.89 ± 0.04, representing a statistically significantly improvement when compared to a semi-automated single human rater, single-modality segmentation protocol used in clinical practice (0.80 ± 0.03). Multi-modal vessel extraction is superior to semi-automated single-modality segmentation, indicating the possibility of safer SEEG planning, with reduced patient morbidity.

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

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

Musculoskeletal ultrasound and other imaging modalities in rheumatoid arthritis.

PubMed

Ohrndorf, Sarah; Werner, Stephanie G; Finzel, Stephanie; Backhaus, Marina

2013-05-01

This review refers to the use of musculoskeletal ultrasound in patients with rheumatoid arthritis (RA) both in clinical practice and research. Furthermore, other novel sensitive imaging modalities (high resolution peripheral quantitative computed tomography and fluorescence optical imaging) are introduced in this article. Recently published ultrasound studies presented power Doppler activity by ultrasound highly predictive for later radiographic erosions in patients with RA. Another study presented synovitis detected by ultrasound being predictive of subsequent structural radiographic destruction irrespective of the ultrasound modality (grayscale ultrasound/power Doppler ultrasound). Further studies are currently under way which prove ultrasound findings as imaging biomarkers in the destructive process of RA. Other introduced novel imaging modalities are in the validation process to prove their impact and significance in inflammatory joint diseases. The introduced imaging modalities show different sensitivities and specificities as well as strength and weakness belonging to the assessment of inflammation, differentiation of the involved structures and radiological progression. The review tries to give an answer regarding how to best integrate them into daily clinical practice with the aim to improve the diagnostic algorithms, the daily patient care and, furthermore, the disease's outcome.

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...

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

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

Multi-modal diffuse optical techniques for breast cancer neoadjuvant chemotherapy monitoring (Conference Presentation)

NASA Astrophysics Data System (ADS)

Cochran, Jeffrey M.; Busch, David R.; Ban, Han Y.; Kavuri, Venkaiah C.; Schweiger, Martin J.; Arridge, Simon R.; Yodh, Arjun G.

2017-02-01

We present high spatial density, multi-modal, parallel-plate Diffuse Optical Tomography (DOT) imaging systems for the purpose of breast tumor detection. One hybrid instrument provides time domain (TD) and continuous wave (CW) DOT at 64 source fiber positions. The TD diffuse optical spectroscopy with PMT- detection produces low-resolution images of absolute tissue scattering and absorption while the spatially dense array of CCD-coupled detector fibers (108 detectors) provides higher-resolution CW images of relative tissue optical properties. Reconstruction of the tissue optical properties, along with total hemoglobin concentration and tissue oxygen saturation, is performed using the TOAST software suite. Comparison of the spatially-dense DOT images and MR images allows for a robust validation of DOT against an accepted clinical modality. Additionally, the structural information from co-registered MR images is used as a spatial prior to improve the quality of the functional optical images and provide more accurate quantification of the optical and hemodynamic properties of tumors. We also present an optical-only imaging system that provides frequency domain (FD) DOT at 209 source positions with full CCD detection and incorporates optical fringe projection profilometry to determine the breast boundary. This profilometry serves as a spatial constraint, improving the quality of the DOT reconstructions while retaining the benefits of an optical-only device. We present initial images from both human subjects and phantoms to display the utility of high spatial density data and multi-modal information in DOT reconstruction with the two systems.

Combined multi-modal photoacoustic tomography, optical coherence tomography (OCT) and OCT angiography system with an articulated probe for in vivo human skin structure and vasculature imaging

PubMed Central

Liu, Mengyang; Chen, Zhe; Zabihian, Behrooz; Sinz, Christoph; Zhang, Edward; Beard, Paul C.; Ginner, Laurin; Hoover, Erich; Minneman, Micheal P.; Leitgeb, Rainer A.; Kittler, Harald; Drexler, Wolfgang

2016-01-01

Cutaneous blood flow accounts for approximately 5% of cardiac output in human and plays a key role in a number of a physiological and pathological processes. We show for the first time a multi-modal photoacoustic tomography (PAT), optical coherence tomography (OCT) and OCT angiography system with an articulated probe to extract human cutaneous vasculature in vivo in various skin regions. OCT angiography supplements the microvasculature which PAT alone is unable to provide. Co-registered volumes for vessel network is further embedded in the morphologic image provided by OCT. This multi-modal system is therefore demonstrated as a valuable tool for comprehensive non-invasive human skin vasculature and morphology imaging in vivo. PMID:27699106

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.

Quantitative imaging methods in osteoporosis.

PubMed

Oei, Ling; Koromani, Fjorda; Rivadeneira, Fernando; Zillikens, M Carola; Oei, Edwin H G

2016-12-01

Osteoporosis is characterized by a decreased bone mass and quality resulting in an increased fracture risk. Quantitative imaging methods are critical in the diagnosis and follow-up of treatment effects in osteoporosis. Prior radiographic vertebral fractures and bone mineral density (BMD) as a quantitative parameter derived from dual-energy X-ray absorptiometry (DXA) are among the strongest known predictors of future osteoporotic fractures. Therefore, current clinical decision making relies heavily on accurate assessment of these imaging features. Further, novel quantitative techniques are being developed to appraise additional characteristics of osteoporosis including three-dimensional bone architecture with quantitative computed tomography (QCT). Dedicated high-resolution (HR) CT equipment is available to enhance image quality. At the other end of the spectrum, by utilizing post-processing techniques such as the trabecular bone score (TBS) information on three-dimensional architecture can be derived from DXA images. Further developments in magnetic resonance imaging (MRI) seem promising to not only capture bone micro-architecture but also characterize processes at the molecular level. This review provides an overview of various quantitative imaging techniques based on different radiological modalities utilized in clinical osteoporosis care and research.

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.

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

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

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

Antibody Drug Conjugates: Application of Quantitative Pharmacology in Modality Design and Target Selection.

PubMed

Sadekar, S; Figueroa, I; Tabrizi, M

2015-07-01

Antibody drug conjugates (ADCs) are a multi-component modality comprising of an antibody targeting a cell-specific antigen, a potent drug/payload, and a linker that can be processed within cellular compartments to release payload upon internalization. Numerous ADCs are being evaluated in both research and clinical settings within the academic and pharmaceutical industry due to their ability to selectively deliver potent payloads. Hence, there is a clear need to incorporate quantitative approaches during early stages of drug development for effective modality design and target selection. In this review, we describe a quantitative approach and framework for evaluation of the interplay between drug- and systems-dependent properties (i.e., target expression, density, localization, turnover, and affinity) in order to deliver a sufficient amount of a potent payload into the relevant target cells. As discussed, theoretical approaches with particular considerations given to various key properties for the target and modality suggest that delivery of the payload into particular effect cells to be more sensitive to antigen concentrations for targets with slow turnover rates as compared to those with faster internalization rates. Further assessments also suggest that increasing doses beyond the threshold of the target capacity (a function of target internalization and expression) may not impact the maximum amount of payload delivered to the intended effect cells. This article will explore the important application of quantitative sciences in selection of the target and design of ADC modalities.

Multi-Sensory, Multi-Modal Concepts for Information Understanding

DTIC Science & Technology

2004-04-01

September 20022-2 Outline • The modern dilemma of knowledge acquisition • A vision for information access and understanding • Emerging concepts for...Multi-Sensory, Multi-Modal Concepts for Information Understanding David L. Hall, Ph.D. School of Information Sciences and Technology The... understanding . INTRODUCTION Historically, information displays for display and understanding of data fusion products have focused on the use of vision

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.

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 findings of huge intrachoroidal cavitation and myopic peripapillary sinkhole.

PubMed

Chen, Yutong; Ma, Xiaoli; Hua, Rui

2018-02-02

Peripapillary intrachoroidal cavitation was described as the presence of an asymptomatic, well-circumscribed, yellow-orange, peripapillary lesion at the inferior border of the myopic conus in eyes with high myopia. A 66-year-old myopic Chinese man was enrolled and his multi-color imaging examination showed a well-circumscribed, caesious, peripapillary lesion coalesced with the optic nerve head vertically rotated and obliquely tilted, together with an inferotemporal sinkhole in the myopic conus. The optical coherence tomography images showed an intrachoroidal hyporeflective space, schisis, an intracavitary septum located below the retinal pigment epithelium and inserted beneath the optic nerve head, as well as a sinkhole between the peripapillary intrachoroidal cavitation and the vitreous space. Both myopic colobomas and sinkhole in myopic conus may contribute the coalescence of intrachoroidal cavitation with optic nerve head. These qualitative and quantitative new findings will be beneficial for understanding its pathomorphological mechanism, and the impact on optic nerve tissue of myopic patients.

Multi-observation PET image analysis for patient follow-up quantitation and therapy assessment

NASA Astrophysics Data System (ADS)

David, S.; Visvikis, D.; Roux, C.; Hatt, M.

2011-09-01

In positron emission tomography (PET) imaging, an early therapeutic response is usually characterized by variations of semi-quantitative parameters restricted to maximum SUV measured in PET scans during the treatment. Such measurements do not reflect overall tumor volume and radiotracer uptake variations. The proposed approach is based on multi-observation image analysis for merging several PET acquisitions to assess tumor metabolic volume and uptake variations. The fusion algorithm is based on iterative estimation using a stochastic expectation maximization (SEM) algorithm. The proposed method was applied to simulated and clinical follow-up PET images. We compared the multi-observation fusion performance to threshold-based methods, proposed for the assessment of the therapeutic response based on functional volumes. On simulated datasets the adaptive threshold applied independently on both images led to higher errors than the ASEM fusion and on clinical datasets it failed to provide coherent measurements for four patients out of seven due to aberrant delineations. The ASEM method demonstrated improved and more robust estimation of the evaluation leading to more pertinent measurements. Future work will consist in extending the methodology and applying it to clinical multi-tracer datasets in order to evaluate its potential impact on the biological tumor volume definition for radiotherapy applications.

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.

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

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.

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 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.

Multi-modality imaging of tumor phenotype and response to therapy

NASA Astrophysics Data System (ADS)

Nyflot, Matthew J.

2011-12-01

Imaging and radiation oncology have historically been closely linked. However, the vast majority of techniques used in the clinic involve anatomical imaging. Biological imaging offers the potential for innovation in the areas of cancer diagnosis and staging, radiotherapy target definition, and treatment response assessment. Some relevant imaging techniques are FDG PET (for imaging cellular metabolism), FLT PET (proliferation), CuATSM PET (hypoxia), and contrast-enhanced CT (vasculature and perfusion). Here, a technique for quantitative spatial correlation of tumor phenotype is presented for FDG PET, FLT PET, and CuATSM PET images. Additionally, multimodality imaging of treatment response with FLT PET, CuATSM, and dynamic contrast-enhanced CT is presented, in a trial of patients receiving an antiangiogenic agent (Avastin) combined with cisplatin and radiotherapy. Results are also presented for translational applications in animal models, including quantitative assessment of proliferative response to cetuximab with FLT PET and quantification of vascular volume with a blood-pool contrast agent (Fenestra). These techniques have clear applications to radiobiological research and optimized treatment strategies, and may eventually be used for personalized therapy for patients.

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.

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.

Imaging Breast Density: Established and Emerging Modalities1

PubMed Central

Chen, Jeon-Hor; Gulsen, Gultekin; Su, Min-Ying

2015-01-01

Mammographic density has been proven as an independent risk factor for breast cancer. Women with dense breast tissue visible on a mammogram have a much higher cancer risk than women with little density. A great research effort has been devoted to incorporate breast density into risk prediction models to better estimate each individual’s cancer risk. In recent years, the passage of breast density notification legislation in many states in USA requires that every mammography report should provide information regarding the patient’s breast density. Accurate definition and measurement of breast density are thus important, which may allow all the potential clinical applications of breast density to be implemented. Because the two-dimensional mammography-based measurement is subject to tissue overlapping and thus not able to provide volumetric information, there is an urgent need to develop reliable quantitative measurements of breast density. Various new imaging technologies are being developed. Among these new modalities, volumetric mammographic density methods and three-dimensional magnetic resonance imaging are the most well studied. Besides, emerging modalities, including different x-ray–based, optical imaging, and ultrasound-based methods, have also been investigated. All these modalities may either overcome some fundamental problems related to mammographic density or provide additional density and/or compositional information. The present review article aimed to summarize the current established and emerging imaging techniques for the measurement of breast density and the evidence of the clinical use of these density methods from the literature. PMID:26692524

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.

A wireless modular multi-modal multi-node patch platform for robust biosignal monitoring.

PubMed

Pantelopoulos, Alexandros; Saldivar, Enrique; Roham, Masoud

2011-01-01

In this paper a wireless modular, multi-modal, multi-node patch platform is described. The platform comprises low-cost semi-disposable patch design aiming at unobtrusive ambulatory monitoring of multiple physiological parameters. Owing to its modular design it can be interfaced with various low-power RF communication and data storage technologies, while the data fusion of multi-modal and multi-node features facilitates measurement of several biosignals from multiple on-body locations for robust feature extraction. Preliminary results of the patch platform are presented which illustrate the capability to extract respiration rate from three different independent metrics, which combined together can give a more robust estimate of the actual respiratory rate.

Continuous monitoring of arthritis in animal models using optical imaging modalities

NASA Astrophysics Data System (ADS)

Son, Taeyoon; Yoon, Hyung-Ju; Lee, Saseong; Jang, Won Seuk; Jung, Byungjo; Kim, Wan-Uk

2014-10-01

Given the several difficulties associated with histology, including difficulty in continuous monitoring, this study aimed to investigate the feasibility of optical imaging modalities-cross-polarization color (CPC) imaging, erythema index (EI) imaging, and laser speckle contrast (LSC) imaging-for continuous evaluation and monitoring of arthritis in animal models. C57BL/6 mice, used for the evaluation of arthritis, were divided into three groups: arthritic mice group (AMG), positive control mice group (PCMG), and negative control mice group (NCMG). Complete Freund's adjuvant, mineral oil, and saline were injected into the footpad for AMG, PCMG, and NCMG, respectively. LSC and CPC images were acquired from 0 through 144 h after injection for all groups. EI images were calculated from CPC images. Variations in feet area, EI, and speckle index for each mice group over time were calculated for quantitative evaluation of arthritis. Histological examinations were performed, and the results were found to be consistent with those from optical imaging analysis. Thus, optical imaging modalities may be successfully applied for continuous evaluation and monitoring of arthritis in animal models.

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.

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

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

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

Sensei: A Multi-Modal Framework for Assessing Stress Resiliency

DTIC Science & Technology

2013-04-30

DATE MAY2013 2. REPORT TYPE 4. TITLE AND SUBTITLE Sensei: A Multi-Modal Framework for Assessing Stress Resiliency 6. AUTHOR(S) 7. PERFORMING...Report: Distribution A Page 1 of 3 SRI International (Sarnoff) Document Sensei: A Multi-Modal Framework for Assessing Stress Resiliency (April... Stress Markers in Real-Time in Lab Environment with graded exposure to ICT’s scenarios MAC 1-6 During this reporting period, we established

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 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

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

Cerenkov imaging - a new modality for molecular imaging

PubMed Central

Thorek, Daniel LJ; Robertson, Robbie; Bacchus, Wassifa A; Hahn, Jaeseung; Rothberg, Julie; Beattie, Bradley J; Grimm, Jan

2012-01-01

Cerenkov luminescence imaging (CLI) is an emerging hybrid modality that utilizes the light emission from many commonly used medical isotopes. Cerenkov radiation (CR) is produced when charged particles travel through a dielectric medium faster than the speed of light in that medium. First described in detail nearly 100 years ago, CR has only recently applied for biomedical imaging purposes. The modality is of considerable interest as it enables the use of widespread luminescence imaging equipment to visualize clinical diagnostic (all PET radioisotopes) and many therapeutic radionuclides. The amount of light detected in CLI applications is significantly lower than other that in other optical imaging techniques such as bioluminescence and fluorescence. However, significant advantages include the use of approved radiotracers and lack of an incident light source, resulting in high signal to background ratios. As well, multiple subjects may be imaged concurrently (up to 5 in common bioluminescent equipment), conferring both cost and time benefits. This review summarizes the field of Cerenkov luminescence imaging to date. Applications of CLI discussed include intraoperative radionuclide-guided surgery, monitoring of therapeutic efficacy, tomographic optical imaging capabilities, and the ability to perform multiplexed imaging using fluorophores excited by the Cerenkov radiation. While technical challenges still exist, Cerenkov imaging has materialized as an important molecular imaging modality. PMID:23133811

Quantitative Vectorial Magnetic Imaging of Multi Domain Rock Forming Minerals using Nitrogen-Vacancy Centers in Diamond

NASA Astrophysics Data System (ADS)

Shaar, R.; Farchi, E.; Farfurnik, D.; Ebert, Y.; Haim, G.; Bar-Gill, N.

2017-12-01

Magnetization in rock samples is crucial for paleomagnetometry research, as it harbors valuable geological information on long term processes, such as tectonic movements and the formation of oceans and continents. Nevertheless, current techniques are limited in their ability to measure high spatial resolution and high-sensitivity quantitative vectorial magnetic signatures from individual minerals and micrometer scale samples. As a result, our understanding of bulk rock magnetization is limited, specifically for the case of multi-domain minerals. In this work we use a newly developed nitrogen-vacancy magnetic microscope, capable of quantitative vectorial magnetic imaging with optical resolution. We demonstrate direct imaging of the vectorial magnetic field of a single, multi-domain dendritic magnetite, as well as the measurement and calculation of the weak magnetic moments of an individual grain on the micron scale. Our results were measured in a standoff distance of 3-10 μm, with 350 nm spatial resolution, magnetic sensitivity of 6 μT/√(Hz) and a field of view of 35 μm. The results presented here show the capabilities and the future potential of NV microscopy in measuring the magnetic signals of individual micrometer scale grains. These outcomes pave the way for future applications in paleomagnetometry, and for the fundamental understanding of magnetization in multi-domain samples.

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

PubMed

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

2013-08-01

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

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.

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

Adaptive Diffeomorphic Multiresolution Demons and Their Application to Same Modality Medical Image Registration with Large Deformation

PubMed Central

Wang, Chang; Ren, Qiongqiong; Qin, Xin

2018-01-01

Diffeomorphic demons can guarantee smooth and reversible deformation and avoid unreasonable deformation. However, the number of iterations needs to be set manually, and this greatly influences the registration result. In order to solve this problem, we proposed adaptive diffeomorphic multiresolution demons in this paper. We used an optimized framework with nonrigid registration and diffeomorphism strategy, designed a similarity energy function based on grey value, and stopped iterations adaptively. This method was tested by synthetic image and same modality medical image. Large deformation was simulated by rotational distortion and extrusion transform, medical image registration with large deformation was performed, and quantitative analyses were conducted using the registration evaluation indexes, and the influence of different driving forces and parameters on the registration result was analyzed. The registration results of same modality medical images were compared with those obtained using active demons, additive demons, and diffeomorphic demons. Quantitative analyses showed that the proposed method's normalized cross-correlation coefficient and structural similarity were the highest and mean square error was the lowest. Medical image registration with large deformation could be performed successfully; evaluation indexes remained stable with an increase in deformation strength. The proposed method is effective and robust, and it can be applied to nonrigid registration of same modality medical images with large deformation.

Adaptive Diffeomorphic Multiresolution Demons and Their Application to Same Modality Medical Image Registration with Large Deformation.

PubMed

Wang, Chang; Ren, Qiongqiong; Qin, Xin; Yu, Yi

2018-01-01

Diffeomorphic demons can guarantee smooth and reversible deformation and avoid unreasonable deformation. However, the number of iterations needs to be set manually, and this greatly influences the registration result. In order to solve this problem, we proposed adaptive diffeomorphic multiresolution demons in this paper. We used an optimized framework with nonrigid registration and diffeomorphism strategy, designed a similarity energy function based on grey value, and stopped iterations adaptively. This method was tested by synthetic image and same modality medical image. Large deformation was simulated by rotational distortion and extrusion transform, medical image registration with large deformation was performed, and quantitative analyses were conducted using the registration evaluation indexes, and the influence of different driving forces and parameters on the registration result was analyzed. The registration results of same modality medical images were compared with those obtained using active demons, additive demons, and diffeomorphic demons. Quantitative analyses showed that the proposed method's normalized cross-correlation coefficient and structural similarity were the highest and mean square error was the lowest. Medical image registration with large deformation could be performed successfully; evaluation indexes remained stable with an increase in deformation strength. The proposed method is effective and robust, and it can be applied to nonrigid registration of same modality medical images with large deformation.

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

Multi-modal image registration: matching MRI with histology

NASA Astrophysics Data System (ADS)

Alic, Lejla; Haeck, Joost C.; Klein, Stefan; Bol, Karin; van Tiel, Sandra T.; Wielopolski, Piotr A.; Bijster, Magda; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.; de Jong, Marion

2010-03-01

Spatial correspondence between histology and multi sequence MRI can provide information about the capabilities of non-invasive imaging to characterize cancerous tissue. However, shrinkage and deformation occurring during the excision of the tumor and the histological processing complicate the co registration of MR images with histological sections. This work proposes a methodology to establish a detailed 3D relation between histology sections and in vivo MRI tumor data. The key features of the methodology are a very dense histological sampling (up to 100 histology slices per tumor), mutual information based non-rigid B-spline registration, the utilization of the whole 3D data sets, and the exploitation of an intermediate ex vivo MRI. In this proof of concept paper, the methodology was applied to one tumor. We found that, after registration, the visual alignment of tumor borders and internal structures was fairly accurate. Utilizing the intermediate ex vivo MRI, it was possible to account for changes caused by the excision of the tumor: we observed a tumor expansion of 20%. Also the effects of fixation, dehydration and histological sectioning could be determined: 26% shrinkage of the tumor was found. The annotation of viable tissue, performed in histology and transformed to the in vivo MRI, matched clearly with high intensity regions in MRI. With this methodology, histological annotation can be directly related to the corresponding in vivo MRI. This is a vital step for the evaluation of the feasibility of multi-spectral MRI to depict histological groundtruth.

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.

Quantitative Medical Image Analysis for Clinical Development of Therapeutics

NASA Astrophysics Data System (ADS)

Analoui, Mostafa

There has been significant progress in development of therapeutics for prevention and management of several disease areas in recent years, leading to increased average life expectancy, as well as of quality of life, globally. However, due to complexity of addressing a number of medical needs and financial burden of development of new class of therapeutics, there is a need for better tools for decision making and validation of efficacy and safety of new compounds. Numerous biological markers (biomarkers) have been proposed either as adjunct to current clinical endpoints or as surrogates. Imaging biomarkers are among rapidly increasing biomarkers, being examined to expedite effective and rational drug development. Clinical imaging often involves a complex set of multi-modality data sets that require rapid and objective analysis, independent of reviewer's bias and training. In this chapter, an overview of imaging biomarkers for drug development is offered, along with challenges that necessitate quantitative and objective image analysis. Examples of automated and semi-automated analysis approaches are provided, along with technical review of such methods. These examples include the use of 3D MRI for osteoarthritis, ultrasound vascular imaging, and dynamic contrast enhanced MRI for oncology. Additionally, a brief overview of regulatory requirements is discussed. In conclusion, this chapter highlights key challenges and future directions in this area.

Quantitative assessment of ischemia and reactive hyperemia of the dermal layers using multi - spectral imaging on the human arm

NASA Astrophysics Data System (ADS)

Kainerstorfer, Jana M.; Amyot, Franck; Demos, Stavros G.; Hassan, Moinuddin; Chernomordik, Victor; Hitzenberger, Christoph K.; Gandjbakhche, Amir H.; Riley, Jason D.

2009-07-01

Quantitative assessment of skin chromophores in a non-invasive fashion is often desirable. Especially pixel wise assessment of blood volume and blood oxygenation is beneficial for improved diagnostics. We utilized a multi-spectral imaging system for acquiring diffuse reflectance images of healthy volunteers' lower forearm. Ischemia and reactive hyperemia was introduced by occluding the upper arm with a pressure cuff for 5min with 180mmHg. Multi-spectral images were taken every 30s, before, during and after occlusion. Image reconstruction for blood volume and blood oxygenation was performed, using a two layered skin model. As the images were taken in a non-contact way, strong artifacts related to the shape (curvature) of the arms were observed, making reconstruction of optical / physiological parameters highly inaccurate. We developed a curvature correction method, which is based on extracting the curvature directly from the intensity images acquired and does not require any additional measures on the object imaged. The effectiveness of the algorithm was demonstrated, on reconstruction results of blood volume and blood oxygenation for in vivo data during occlusion of the arm. Pixel wise assessment of blood volume and blood oxygenation was made possible over the entire image area and comparison of occlusion effects between veins and surrounding skin was performed. Induced ischemia during occlusion and reactive hyperemia afterwards was observed and quantitatively assessed. Furthermore, the influence of epidermal thickness on reconstruction results was evaluated and the exact knowledge of this parameter for fully quantitative assessment was pointed out.

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.

Quantitative image fusion in infrared radiometry

NASA Astrophysics Data System (ADS)

Romm, Iliya; Cukurel, Beni

2018-05-01

Towards high-accuracy infrared radiance estimates, measurement practices and processing techniques aimed to achieve quantitative image fusion using a set of multi-exposure images of a static scene are reviewed. The conventional non-uniformity correction technique is extended, as the original is incompatible with quantitative fusion. Recognizing the inherent limitations of even the extended non-uniformity correction, an alternative measurement methodology, which relies on estimates of the detector bias using self-calibration, is developed. Combining data from multi-exposure images, two novel image fusion techniques that ultimately provide high tonal fidelity of a photoquantity are considered: ‘subtract-then-fuse’, which conducts image subtraction in the camera output domain and partially negates the bias frame contribution common to both the dark and scene frames; and ‘fuse-then-subtract’, which reconstructs the bias frame explicitly and conducts image fusion independently for the dark and the scene frames, followed by subtraction in the photoquantity domain. The performances of the different techniques are evaluated for various synthetic and experimental data, identifying the factors contributing to potential degradation of the image quality. The findings reflect the superiority of the ‘fuse-then-subtract’ approach, conducting image fusion via per-pixel nonlinear weighted least squares optimization.

Imaging investigations in Spine Trauma: The value of commonly used imaging modalities and emerging imaging modalities.

PubMed

Tins, Bernhard J

2017-01-01

Traumatic spine injuries can be devastating for patients affected and for health care professionals if preventable neurological deterioration occurs. This review discusses the imaging options for the diagnosis of spinal trauma. It lays out when imaging is appropriate and when it is not. It discusses strength and weakness of available imaging modalities. Advanced techniques for spinal injury imaging will be explored. The review concludes with a review of imaging protocols adjusted to clinical circumstances.

Investigation of a dual modal method for bone pathologies using quantitative ultrasound and photoacoustics

NASA Astrophysics Data System (ADS)

Steinberg, Idan; Gannot, Israel; Eyal, Avishay

2015-03-01

Osteoporosis is a widespread disease that has a catastrophic impact on patient's lives and overwhelming related healthcare costs. In recent works, we have developed a multi-spectral, frequency domain photoacoustic method for the evaluation of bone pathologies. This method has great advantages over pure ultrasonic or optical methods as it provides both molecular information from the bone absorption spectrum and bone mechanical status from the characteristics of the ultrasound propagation. These characteristics include both the Speed of Sound (SOS) and Broadband Ultrasonic Attenuation (BUA). To test the method's quantitative predictions, we have constructed a combined ultrasound and photoacoustic setup. Here, we experimentally present a dual modality system, and compares between the methods on bone samples in-vitro. The differences between the two modalities are shown to provide valuable insight into the bone structure and functional status.

Multi-scale spectrally resolved quantitative fluorescence imaging system: towards neurosurgical guidance in glioma resection

NASA Astrophysics Data System (ADS)

Xie, Yijing; Thom, Maria; Miserocchi, Anna; McEvoy, Andrew W.; Desjardins, Adrien; Ourselin, Sebastien; Vercauteren, Tom

2017-02-01

In glioma resection surgery, the detection of tumour is often guided by using intraoperative fluorescence imaging notably with 5-ALA-PpIX, providing fluorescent contrast between normal brain tissue and the gliomas tissue to achieve improved tumour delineation and prolonged patient survival compared with the conventional white-light guided resection. However, the commercially available fluorescence imaging system relies on surgeon's eyes to visualise and distinguish the fluorescence signals, which unfortunately makes the resection subjective. In this study, we developed a novel multi-scale spectrally-resolved fluorescence imaging system and a computational model for quantification of PpIX concentration. The system consisted of a wide-field spectrally-resolved quantitative imaging device and a fluorescence endomicroscopic imaging system enabling optical biopsy. Ex vivo animal tissue experiments as well as human tumour sample studies demonstrated that the system was capable of specifically detecting the PpIX fluorescent signal and estimate the true concentration of PpIX in brain specimen.

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.

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

PubMed

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

2016-01-01

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

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.

Quantitative photoacoustic elasticity and viscosity imaging for cirrhosis detection

NASA Astrophysics Data System (ADS)

Wang, Qian; Shi, Yujiao; Yang, Fen; Yang, Sihua

2018-05-01

Elasticity and viscosity assessments are essential for understanding and characterizing the physiological and pathological states of tissue. In this work, by establishing a photoacoustic (PA) shear wave model, an approach for quantitative PA elasticity imaging based on measurement of the rise time of the thermoelastic displacement was developed. Thus, using an existing PA viscoelasticity imaging method that features a phase delay measurement, quantitative PA elasticity imaging and viscosity imaging can be obtained in a simultaneous manner. The method was tested and validated by imaging viscoelastic agar phantoms prepared at different agar concentrations, and the imaging data were in good agreement with rheometry results. Ex vivo experiments on liver pathological models demonstrated the capability for cirrhosis detection, and the results were consistent with the corresponding histological results. This method expands the scope of conventional PA imaging and has potential to become an important alternative imaging modality.

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.

Perspectives on How Human Simultaneous Multi-Modal Imaging Adds Directionality to Spread Models of Alzheimer’s Disease

PubMed Central

Neitzel, Julia; Nuttall, Rachel; Sorg, Christian

2018-01-01

Previous animal research suggests that the spread of pathological agents in Alzheimer’s disease (AD) follows the direction of signaling pathways. Specifically, tau pathology has been suggested to propagate in an infection-like mode along axons, from transentorhinal cortices to medial temporal lobe cortices and consequently to other cortical regions, while amyloid-beta (Aβ) pathology seems to spread in an activity-dependent manner among and from isocortical regions into limbic and then subcortical regions. These directed connectivity-based spread models, however, have not been tested directly in AD patients due to the lack of an in vivo method to identify directed connectivity in humans. Recently, a new method—metabolic connectivity mapping (MCM)—has been developed and validated in healthy participants that uses simultaneous FDG-PET and resting-state fMRI data acquisition to identify directed intrinsic effective connectivity (EC). To this end, postsynaptic energy consumption (FDG-PET) is used to identify regions with afferent input from other functionally connected brain regions (resting-state fMRI). Here, we discuss how this multi-modal imaging approach allows quantitative, whole-brain mapping of signaling direction in AD patients, thereby pointing out some of the advantages it offers compared to other EC methods (i.e., Granger causality, dynamic causal modeling, Bayesian networks). Most importantly, MCM provides the basis on which models of pathology spread, derived from animal studies, can be tested in AD patients. In particular, future work should investigate whether tau and Aβ in humans propagate along the trajectories of directed connectivity in order to advance our understanding of the neuropathological mechanisms causing disease progression. PMID:29434570

Multimodal Image Alignment via Linear Mapping between Feature Modalities.

PubMed

Jiang, Yanyun; Zheng, Yuanjie; Hou, Sujuan; Chang, Yuchou; Gee, James

2017-01-01

We propose a novel landmark matching based method for aligning multimodal images, which is accomplished uniquely by resolving a linear mapping between different feature modalities. This linear mapping results in a new measurement on similarity of images captured from different modalities. In addition, our method simultaneously solves this linear mapping and the landmark correspondences by minimizing a convex quadratic function. Our method can estimate complex image relationship between different modalities and nonlinear nonrigid spatial transformations even in the presence of heavy noise, as shown in our experiments carried out by using a variety of image modalities.

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.

Quantitative imaging of the human upper airway: instrument design and clinical studies

NASA Astrophysics Data System (ADS)

Leigh, M. S.; Armstrong, J. J.; Paduch, A.; Sampson, D. D.; Walsh, J. H.; Hillman, D. R.; Eastwood, P. R.

2006-08-01

Imaging of the human upper airway is widely used in medicine, in both clinical practice and research. Common imaging modalities include video endoscopy, X-ray CT, and MRI. However, no current modality is both quantitative and safe to use for extended periods of time. Such a capability would be particularly valuable for sleep research, which is inherently reliant on long observation sessions. We have developed an instrument capable of quantitative imaging of the human upper airway, based on endoscopic optical coherence tomography. There are no dose limits for optical techniques, and the minimally invasive imaging probe is safe for use in overnight studies. We report on the design of the instrument and its use in preliminary clinical studies, and we present results from a range of initial experiments. The experiments show that the instrument is capable of imaging during sleep, and that it can record dynamic changes in airway size and shape. This information is useful for research into sleep disorders, and potentially for clinical diagnosis and therapies.

Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

PubMed Central

Wang, Ge; Zhang, Jie; Gao, Hao; Weir, Victor; Yu, Hengyong; Cong, Wenxiang; Xu, Xiaochen; Shen, Haiou; Bennett, James; Furth, Mark; Wang, Yue; Vannier, Michael

2012-01-01

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine. PMID:22768108

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

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.

Integration of XNAT/PACS, DICOM, and Research Software for Automated Multi-modal Image Analysis.

PubMed

Gao, Yurui; Burns, Scott S; Lauzon, Carolyn B; Fong, Andrew E; James, Terry A; Lubar, Joel F; Thatcher, Robert W; Twillie, David A; Wirt, Michael D; Zola, Marc A; Logan, Bret W; Anderson, Adam W; Landman, Bennett A

2013-03-29

Traumatic brain injury (TBI) is an increasingly important public health concern. While there are several promising avenues of intervention, clinical assessments are relatively coarse and comparative quantitative analysis is an emerging field. Imaging data provide potentially useful information for evaluating TBI across functional, structural, and microstructural phenotypes. Integration and management of disparate data types are major obstacles. In a multi-institution collaboration, we are collecting electroencephalogy (EEG), structural MRI, diffusion tensor MRI (DTI), and single photon emission computed tomography (SPECT) from a large cohort of US Army service members exposed to mild or moderate TBI who are undergoing experimental treatment. We have constructed a robust informatics backbone for this project centered on the DICOM standard and eXtensible Neuroimaging Archive Toolkit (XNAT) server. Herein, we discuss (1) optimization of data transmission, validation and storage, (2) quality assurance and workflow management, and (3) integration of high performance computing with research software.

Integration of XNAT/PACS, DICOM, and research software for automated multi-modal image analysis

NASA Astrophysics Data System (ADS)

Gao, Yurui; Burns, Scott S.; Lauzon, Carolyn B.; Fong, Andrew E.; James, Terry A.; Lubar, Joel F.; Thatcher, Robert W.; Twillie, David A.; Wirt, Michael D.; Zola, Marc A.; Logan, Bret W.; Anderson, Adam W.; Landman, Bennett A.

2013-03-01

Traumatic brain injury (TBI) is an increasingly important public health concern. While there are several promising avenues of intervention, clinical assessments are relatively coarse and comparative quantitative analysis is an emerging field. Imaging data provide potentially useful information for evaluating TBI across functional, structural, and microstructural phenotypes. Integration and management of disparate data types are major obstacles. In a multi-institution collaboration, we are collecting electroencephalogy (EEG), structural MRI, diffusion tensor MRI (DTI), and single photon emission computed tomography (SPECT) from a large cohort of US Army service members exposed to mild or moderate TBI who are undergoing experimental treatment. We have constructed a robust informatics backbone for this project centered on the DICOM standard and eXtensible Neuroimaging Archive Toolkit (XNAT) server. Herein, we discuss (1) optimization of data transmission, validation and storage, (2) quality assurance and workflow management, and (3) integration of high performance computing with research software.

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 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 Interaction for Robotic Mules

DTIC Science & Technology

2014-02-26

Multi-Modal Interaction for Robotic Mules Glenn Taylor, Mike Quist, Matt Lanting, Cory Dunham , Patrick Theisen, Paul Muench Abstract...Taylor, Mike Quist, Matt Lanting, Cory Dunham , and Patrick Theisen are with Soar Technology, Inc. (corresponding author: 734-887- 7620; email: glenn...soartech.com; quist@soartech.com; matt.lanting@soartech.com; dunham @soartech.com; patrick.theisen@soartech.com Paul Muench is with US Army TARDEC

NOTE: An innovative phantom for quantitative and qualitative investigation of advanced x-ray imaging technologies

NASA Astrophysics Data System (ADS)

Chiarot, C. B.; Siewerdsen, J. H.; Haycocks, T.; Moseley, D. J.; Jaffray, D. A.

2005-11-01

Development, characterization, and quality assurance of advanced x-ray imaging technologies require phantoms that are quantitative and well suited to such modalities. This note reports on the design, construction, and use of an innovative phantom developed for advanced imaging technologies (e.g., multi-detector CT and the numerous applications of flat-panel detectors in dual-energy imaging, tomosynthesis, and cone-beam CT) in diagnostic and image-guided procedures. The design addresses shortcomings of existing phantoms by incorporating criteria satisfied by no other single phantom: (1) inserts are fully 3D—spherically symmetric rather than cylindrical; (2) modules are quantitative, presenting objects of known size and contrast for quality assurance and image quality investigation; (3) features are incorporated in ideal and semi-realistic (anthropomorphic) contexts; and (4) the phantom allows devices to be inserted and manipulated in an accessible module (right lung). The phantom consists of five primary modules: (1) head, featuring contrast-detail spheres approximate to brain lesions; (2) left lung, featuring contrast-detail spheres approximate to lung modules; (3) right lung, an accessible hull in which devices may be placed and manipulated; (4) liver, featuring conrast-detail spheres approximate to metastases; and (5) abdomen/pelvis, featuring simulated kidneys, colon, rectum, bladder, and prostate. The phantom represents a two-fold evolution in design philosophy—from 2D (cylindrically symmetric) to fully 3D, and from exclusively qualitative or quantitative to a design accommodating quantitative study within an anatomical context. It has proven a valuable tool in investigations throughout our institution, including low-dose CT, dual-energy radiography, and cone-beam CT for image-guided radiation therapy and surgery.

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…

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

Alternative Fuels Data Center: Multi-Modal Transportation

Science.gov Websites

examples of resources to help travelers use multi-modal transportation. OpenTripPlanner Map - an online transportation modes including transit (bus or train), walking, and bicycling 511 - a one-stop source from the of alternative transportation modes. A 2010 evaluation by the Oregon Transportation Research and

Quantitative imaging features: extension of the oncology medical image database

NASA Astrophysics Data System (ADS)

Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

2015-03-01

Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

Comparison of quantitative Y-90 SPECT and non-time-of-flight PET imaging in post-therapy radioembolization of liver cancer

PubMed Central

Yue, Jianting; Mauxion, Thibault; Reyes, Diane K.; Lodge, Martin A.; Hobbs, Robert F.; Rong, Xing; Dong, Yinfeng; Herman, Joseph M.; Wahl, Richard L.; Geschwind, Jean-François H.; Frey, Eric C.

2016-01-01

Purpose: Radioembolization with yttrium-90 microspheres may be optimized with patient-specific pretherapy treatment planning. Dose verification and validation of treatment planning methods require quantitative imaging of the post-therapy distribution of yttrium-90 (Y-90). Methods for quantitative imaging of Y-90 using both bremsstrahlung SPECT and PET have previously been described. The purpose of this study was to compare the two modalities quantitatively in humans. Methods: Calibration correction factors for both quantitative Y-90 bremsstrahlung SPECT and a non-time-of-flight PET system without compensation for prompt coincidences were developed by imaging three phantoms. The consistency of these calibration correction factors for the different phantoms was evaluated. Post-therapy images from both modalities were obtained from 15 patients with hepatocellular carcinoma who underwent hepatic radioembolization using Y-90 glass microspheres. Quantitative SPECT and PET images were rigidly registered and the total liver activities and activity distributions estimated for each modality were compared. The activity distributions were compared using profiles, voxel-by-voxel correlation and Bland–Altman analyses, and activity-volume histograms. Results: The mean ± standard deviation of difference in the total activity in the liver between the two modalities was 0% ± 9% (range −21%–18%). Voxel-by-voxel comparisons showed a good agreement in regions corresponding roughly to treated tumor and treated normal liver; the agreement was poorer in regions with low or no expected activity, where PET appeared to overestimate the activity. The correlation coefficients between intrahepatic voxel pairs for the two modalities ranged from 0.86 to 0.94. Cumulative activity volume histograms were in good agreement. Conclusions: These data indicate that, with appropriate reconstruction methods and measured calibration correction factors, either Y-90 SPECT/CT or Y-90 PET/CT can be used

Comparison of quantitative Y-90 SPECT and non-time-of-flight PET imaging in post-therapy radioembolization of liver cancer.

PubMed

Yue, Jianting; Mauxion, Thibault; Reyes, Diane K; Lodge, Martin A; Hobbs, Robert F; Rong, Xing; Dong, Yinfeng; Herman, Joseph M; Wahl, Richard L; Geschwind, Jean-François H; Frey, Eric C

2016-10-01

Radioembolization with yttrium-90 microspheres may be optimized with patient-specific pretherapy treatment planning. Dose verification and validation of treatment planning methods require quantitative imaging of the post-therapy distribution of yttrium-90 (Y-90). Methods for quantitative imaging of Y-90 using both bremsstrahlung SPECT and PET have previously been described. The purpose of this study was to compare the two modalities quantitatively in humans. Calibration correction factors for both quantitative Y-90 bremsstrahlung SPECT and a non-time-of-flight PET system without compensation for prompt coincidences were developed by imaging three phantoms. The consistency of these calibration correction factors for the different phantoms was evaluated. Post-therapy images from both modalities were obtained from 15 patients with hepatocellular carcinoma who underwent hepatic radioembolization using Y-90 glass microspheres. Quantitative SPECT and PET images were rigidly registered and the total liver activities and activity distributions estimated for each modality were compared. The activity distributions were compared using profiles, voxel-by-voxel correlation and Bland-Altman analyses, and activity-volume histograms. The mean ± standard deviation of difference in the total activity in the liver between the two modalities was 0% ± 9% (range -21%-18%). Voxel-by-voxel comparisons showed a good agreement in regions corresponding roughly to treated tumor and treated normal liver; the agreement was poorer in regions with low or no expected activity, where PET appeared to overestimate the activity. The correlation coefficients between intrahepatic voxel pairs for the two modalities ranged from 0.86 to 0.94. Cumulative activity volume histograms were in good agreement. These data indicate that, with appropriate reconstruction methods and measured calibration correction factors, either Y-90 SPECT/CT or Y-90 PET/CT can be used for quantitative post-therapy monitoring of Y

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.

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.

Integration of XNAT/PACS, DICOM, and Research Software for Automated Multi-modal Image Analysis

PubMed Central

Gao, Yurui; Burns, Scott S.; Lauzon, Carolyn B.; Fong, Andrew E.; James, Terry A.; Lubar, Joel F.; Thatcher, Robert W.; Twillie, David A.; Wirt, Michael D.; Zola, Marc A.; Logan, Bret W.; Anderson, Adam W.; Landman, Bennett A.

2013-01-01

Traumatic brain injury (TBI) is an increasingly important public health concern. While there are several promising avenues of intervention, clinical assessments are relatively coarse and comparative quantitative analysis is an emerging field. Imaging data provide potentially useful information for evaluating TBI across functional, structural, and microstructural phenotypes. Integration and management of disparate data types are major obstacles. In a multi-institution collaboration, we are collecting electroencephalogy (EEG), structural MRI, diffusion tensor MRI (DTI), and single photon emission computed tomography (SPECT) from a large cohort of US Army service members exposed to mild or moderate TBI who are undergoing experimental treatment. We have constructed a robust informatics backbone for this project centered on the DICOM standard and eXtensible Neuroimaging Archive Toolkit (XNAT) server. Herein, we discuss (1) optimization of data transmission, validation and storage, (2) quality assurance and workflow management, and (3) integration of high performance computing with research software. PMID:24386548

Novel minimally invasive multi-modality monitoring modalities in neurocritical care.

PubMed

Al-Mufti, Fawaz; Smith, Brendan; Lander, Megan; Damodara, Nitesh; Nuoman, Rolla; El-Ghanem, Mohammad; Kamal, Naveed; Al-Marsoummi, Sarmad; Alzubaidi, Basim; Nuoaman, Halla; Foreman, Brandon; Amuluru, Krishna; Gandhi, Chirag D

2018-07-15

Elevated intracranial pressure (ICP) following brain injury contributes to poor outcomes for patients, primarily by reducing the caliber of cerebral vasculature, and thereby reducing cerebral blood flow. Careful monitoring of ICP is critical in these patients in order to determine prognosis, implement treatment when ICP becomes elevated, and to judge responsiveness to treatment. Currently, the gold standard for monitoring is invasive pressure transducers, usually an intraventricular monitor, which presents significant risk of infection and hemorrhage. These risks made discovering non-invasive methods for monitoring ICP and cerebral perfusion a priority for researchers. Herein we sought to review recent publications on novel minimally invasive multi-modality monitoring techniques that provide surrogate data on ICP, cerebral oxygenation, metabolism and blood flow. While limitations in various forms preclude them from supplanting the use of invasive monitors, these modalities represent useful screening tools within our armamentarium that may be invaluable when the risks of invasive monitoring outweigh the associated benefits. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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.

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

In vivo, label-free, three-dimensional quantitative imaging of liver surface using multi-photon microscopy

NASA Astrophysics Data System (ADS)

Zhuo, Shuangmu; Yan, Jie; Kang, Yuzhan; Xu, Shuoyu; Peng, Qiwen; So, Peter T. C.; Yu, Hanry

2014-07-01

Various structural features on the liver surface reflect functional changes in the liver. The visualization of these surface features with molecular specificity is of particular relevance to understanding the physiology and diseases of the liver. Using multi-photon microscopy (MPM), we have developed a label-free, three-dimensional quantitative and sensitive method to visualize various structural features of liver surface in living rat. MPM could quantitatively image the microstructural features of liver surface with respect to the sinuosity of collagen fiber, the elastic fiber structure, the ratio between elastin and collagen, collagen content, and the metabolic state of the hepatocytes that are correlative with the pathophysiologically induced changes in the regions of interest. This study highlights the potential of this technique as a useful tool for pathophysiological studies and possible diagnosis of the liver diseases with further development.

In vivo, label-free, three-dimensional quantitative imaging of liver surface using multi-photon microscopy

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

Zhuo, Shuangmu, E-mail: shuangmuzhuo@gmail.com, E-mail: hanry-yu@nuhs.edu.sg; Institute of Laser and Optoelectronics Technology, Fujian Normal University, Fuzhou 350007; Yan, Jie

2014-07-14

Various structural features on the liver surface reflect functional changes in the liver. The visualization of these surface features with molecular specificity is of particular relevance to understanding the physiology and diseases of the liver. Using multi-photon microscopy (MPM), we have developed a label-free, three-dimensional quantitative and sensitive method to visualize various structural features of liver surface in living rat. MPM could quantitatively image the microstructural features of liver surface with respect to the sinuosity of collagen fiber, the elastic fiber structure, the ratio between elastin and collagen, collagen content, and the metabolic state of the hepatocytes that are correlativemore » with the pathophysiologically induced changes in the regions of interest. This study highlights the potential of this technique as a useful tool for pathophysiological studies and possible diagnosis of the liver diseases with further development.« less

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.

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.

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...

Utilizing Multi-Modal Literacies in Middle Grades Science

ERIC Educational Resources Information Center

Saurino, Dan; Ogletree, Tamra; Saurino, Penelope

2010-01-01

The nature of literacy is changing. Increased student use of computer-mediated, digital, and visual communication spans our understanding of adolescent multi-modal capabilities that reach beyond the traditional conventions of linear speech and written text in the science curriculum. Advancing technology opens doors to learning that involve…

Automatized image processing of bovine blastocysts produced in vitro for quantitative variable determination

NASA Astrophysics Data System (ADS)

Rocha, José Celso; Passalia, Felipe José; Matos, Felipe Delestro; Takahashi, Maria Beatriz; Maserati, Marc Peter, Jr.; Alves, Mayra Fernanda; de Almeida, Tamie Guibu; Cardoso, Bruna Lopes; Basso, Andrea Cristina; Nogueira, Marcelo Fábio Gouveia

2017-12-01

There is currently no objective, real-time and non-invasive method for evaluating the quality of mammalian embryos. In this study, we processed images of in vitro produced bovine blastocysts to obtain a deeper comprehension of the embryonic morphological aspects that are related to the standard evaluation of blastocysts. Information was extracted from 482 digital images of blastocysts. The resulting imaging data were individually evaluated by three experienced embryologists who graded their quality. To avoid evaluation bias, each image was related to the modal value of the evaluations. Automated image processing produced 36 quantitative variables for each image. The images, the modal and individual quality grades, and the variables extracted could potentially be used in the development of artificial intelligence techniques (e.g., evolutionary algorithms and artificial neural networks), multivariate modelling and the study of defined structures of the whole blastocyst.

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...

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.

Quantitative, depth-resolved determination of particle motion using multi-exposure, spatial frequency domain laser speckle imaging.

PubMed

Rice, Tyler B; Kwan, Elliott; Hayakawa, Carole K; Durkin, Anthony J; Choi, Bernard; Tromberg, Bruce J

2013-01-01

Laser Speckle Imaging (LSI) is a simple, noninvasive technique for rapid imaging of particle motion in scattering media such as biological tissue. LSI is generally used to derive a qualitative index of relative blood flow due to unknown impact from several variables that affect speckle contrast. These variables may include optical absorption and scattering coefficients, multi-layer dynamics including static, non-ergodic regions, and systematic effects such as laser coherence length. In order to account for these effects and move toward quantitative, depth-resolved LSI, we have developed a method that combines Monte Carlo modeling, multi-exposure speckle imaging (MESI), spatial frequency domain imaging (SFDI), and careful instrument calibration. Monte Carlo models were used to generate total and layer-specific fractional momentum transfer distributions. This information was used to predict speckle contrast as a function of exposure time, spatial frequency, layer thickness, and layer dynamics. To verify with experimental data, controlled phantom experiments with characteristic tissue optical properties were performed using a structured light speckle imaging system. Three main geometries were explored: 1) diffusive dynamic layer beneath a static layer, 2) static layer beneath a diffuse dynamic layer, and 3) directed flow (tube) submerged in a dynamic scattering layer. Data fits were performed using the Monte Carlo model, which accurately reconstructed the type of particle flow (diffusive or directed) in each layer, the layer thickness, and absolute flow speeds to within 15% or better.

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.

Monitoring and quantitative assessment of tumor burden using in vivo bioluminescence imaging

NASA Astrophysics Data System (ADS)

Chen, Chia-Chi; Hwang, Jeng-Jong; Ting, Gann; Tseng, Yun-Long; Wang, Shyh-Jen; Whang-Peng, Jaqueline

2007-02-01

In vivo bioluminescence imaging (BLI) is a sensitive imaging modality that is rapid and accessible, and may comprise an ideal tool for evaluating tumor growth. In this study, the kinetic of tumor growth has been assessed in C26 colon carcinoma bearing BALB/c mouse model. The ability of BLI to noninvasively quantitate the growth of subcutaneous tumors transplanted with C26 cells genetically engineered to stably express firefly luciferase and herpes simplex virus type-1 thymidine kinase (C26/ tk-luc). A good correlation ( R2=0.998) of photon emission to the cell number was found in vitro. Tumor burden and tumor volume were monitored in vivo over time by quantitation of photon emission using Xenogen IVIS 50 and standard external caliper measurement, respectively. At various time intervals, tumor-bearing mice were imaged to determine the correlation of in vivo BLI to tumor volume. However, a correlation of BLI to tumor volume was observed when tumor volume was smaller than 1000 mm 3 ( R2=0.907). γ Scintigraphy combined with [ 131I]FIAU was another imaging modality used for verifying the previous results. In conclusion, this study showed that bioluminescence imaging is a powerful and quantitative tool for the direct assay to monitor tumor growth in vivo. The dual reporter genes transfected tumor-bearing animal model can be applied in the evaluation of the efficacy of new developed anti-cancer drugs.

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

Quantitative comparison of 3D third harmonic generation and fluorescence microscopy images.

PubMed

Zhang, Zhiqing; Kuzmin, Nikolay V; Groot, Marie Louise; de Munck, Jan C

2018-01-01

Third harmonic generation (THG) microscopy is a label-free imaging technique that shows great potential for rapid pathology of brain tissue during brain tumor surgery. However, the interpretation of THG brain images should be quantitatively linked to images of more standard imaging techniques, which so far has been done qualitatively only. We establish here such a quantitative link between THG images of mouse brain tissue and all-nuclei-highlighted fluorescence images, acquired simultaneously from the same tissue area. For quantitative comparison of a substantial pair of images, we present here a segmentation workflow that is applicable for both THG and fluorescence images, with a precision of 91.3 % and 95.8 % achieved respectively. We find that the correspondence between the main features of the two imaging modalities amounts to 88.9 %, providing quantitative evidence of the interpretation of dark holes as brain cells. Moreover, 80 % bright objects in THG images overlap with nuclei highlighted in the fluorescence images, and they are 2 times smaller than the dark holes, showing that cells of different morphologies can be recognized in THG images. We expect that the described quantitative comparison is applicable to other types of brain tissue and with more specific staining experiments for cell type identification. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A correlative imaging based methodology for accurate quantitative assessment of bone formation in additive manufactured implants.

PubMed

Geng, Hua; Todd, Naomi M; Devlin-Mullin, Aine; Poologasundarampillai, Gowsihan; Kim, Taek Bo; Madi, Kamel; Cartmell, Sarah; Mitchell, Christopher A; Jones, Julian R; Lee, Peter D

2016-06-01

A correlative imaging methodology was developed to accurately quantify bone formation in the complex lattice structure of additive manufactured implants. Micro computed tomography (μCT) and histomorphometry were combined, integrating the best features from both, while demonstrating the limitations of each imaging modality. This semi-automatic methodology registered each modality using a coarse graining technique to speed the registration of 2D histology sections to high resolution 3D μCT datasets. Once registered, histomorphometric qualitative and quantitative bone descriptors were directly correlated to 3D quantitative bone descriptors, such as bone ingrowth and bone contact. The correlative imaging allowed the significant volumetric shrinkage of histology sections to be quantified for the first time (~15 %). This technique demonstrated the importance of location of the histological section, demonstrating that up to a 30 % offset can be introduced. The results were used to quantitatively demonstrate the effectiveness of 3D printed titanium lattice implants.

Calibration of Wide-Field Deconvolution Microscopy for Quantitative Fluorescence Imaging

PubMed Central

Lee, Ji-Sook; Wee, Tse-Luen (Erika); Brown, Claire M.

2014-01-01

Deconvolution enhances contrast in fluorescence microscopy images, especially in low-contrast, high-background wide-field microscope images, improving characterization of features within the sample. Deconvolution can also be combined with other imaging modalities, such as confocal microscopy, and most software programs seek to improve resolution as well as contrast. Quantitative image analyses require instrument calibration and with deconvolution, necessitate that this process itself preserves the relative quantitative relationships between fluorescence intensities. To ensure that the quantitative nature of the data remains unaltered, deconvolution algorithms need to be tested thoroughly. This study investigated whether the deconvolution algorithms in AutoQuant X3 preserve relative quantitative intensity data. InSpeck Green calibration microspheres were prepared for imaging, z-stacks were collected using a wide-field microscope, and the images were deconvolved using the iterative deconvolution algorithms with default settings. Afterwards, the mean intensities and volumes of microspheres in the original and the deconvolved images were measured. Deconvolved data sets showed higher average microsphere intensities and smaller volumes than the original wide-field data sets. In original and deconvolved data sets, intensity means showed linear relationships with the relative microsphere intensities given by the manufacturer. Importantly, upon normalization, the trend lines were found to have similar slopes. In original and deconvolved images, the volumes of the microspheres were quite uniform for all relative microsphere intensities. We were able to show that AutoQuant X3 deconvolution software data are quantitative. In general, the protocol presented can be used to calibrate any fluorescence microscope or image processing and analysis procedure. PMID:24688321

Neonatal brain resting-state functional connectivity imaging modalities.

PubMed

Mohammadi-Nejad, Ali-Reza; Mahmoudzadeh, Mahdi; Hassanpour, Mahlegha S; Wallois, Fabrice; Muzik, Otto; Papadelis, Christos; Hansen, Anne; Soltanian-Zadeh, Hamid; Gelovani, Juri; Nasiriavanaki, Mohammadreza

2018-06-01

Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

Quantitative analysis of vascular parameters for micro-CT imaging of vascular networks with multi-resolution.

PubMed

Zhao, Fengjun; Liang, Jimin; Chen, Xueli; Liu, Junting; Chen, Dongmei; Yang, Xiang; Tian, Jie

2016-03-01

Previous studies showed that all the vascular parameters from both the morphological and topological parameters were affected with the altering of imaging resolutions. However, neither the sensitivity analysis of the vascular parameters at multiple resolutions nor the distinguishability estimation of vascular parameters from different data groups has been discussed. In this paper, we proposed a quantitative analysis method of vascular parameters for vascular networks of multi-resolution, by analyzing the sensitivity of vascular parameters at multiple resolutions and estimating the distinguishability of vascular parameters from different data groups. Combining the sensitivity and distinguishability, we designed a hybrid formulation to estimate the integrated performance of vascular parameters in a multi-resolution framework. Among the vascular parameters, degree of anisotropy and junction degree were two insensitive parameters that were nearly irrelevant with resolution degradation; vascular area, connectivity density, vascular length, vascular junction and segment number were five parameters that could better distinguish the vascular networks from different groups and abide by the ground truth. Vascular area, connectivity density, vascular length and segment number not only were insensitive to multi-resolution but could also better distinguish vascular networks from different groups, which provided guidance for the quantification of the vascular networks in multi-resolution frameworks.

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.

Online Multi-Modal Robust Non-Negative Dictionary Learning for Visual Tracking

PubMed Central

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality. PMID:25961715

Online multi-modal robust non-negative dictionary learning for visual tracking.

PubMed

Zhang, Xiang; Guan, Naiyang; Tao, Dacheng; Qiu, Xiaogang; Luo, Zhigang

2015-01-01

Dictionary learning is a method of acquiring a collection of atoms for subsequent signal representation. Due to its excellent representation ability, dictionary learning has been widely applied in multimedia and computer vision. However, conventional dictionary learning algorithms fail to deal with multi-modal datasets. In this paper, we propose an online multi-modal robust non-negative dictionary learning (OMRNDL) algorithm to overcome this deficiency. Notably, OMRNDL casts visual tracking as a dictionary learning problem under the particle filter framework and captures the intrinsic knowledge about the target from multiple visual modalities, e.g., pixel intensity and texture information. To this end, OMRNDL adaptively learns an individual dictionary, i.e., template, for each modality from available frames, and then represents new particles over all the learned dictionaries by minimizing the fitting loss of data based on M-estimation. The resultant representation coefficient can be viewed as the common semantic representation of particles across multiple modalities, and can be utilized to track the target. OMRNDL incrementally learns the dictionary and the coefficient of each particle by using multiplicative update rules to respectively guarantee their non-negativity constraints. Experimental results on a popular challenging video benchmark validate the effectiveness of OMRNDL for visual tracking in both quantity and quality.

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

NASA Astrophysics Data System (ADS)

Yuan, Zhen; Li, Xiaoqi; Xi, Lei

2014-06-01

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

MMX-I: A data-processing software for multi-modal X-ray imaging and tomography

NASA Astrophysics Data System (ADS)

Bergamaschi, A.; Medjoubi, K.; Messaoudi, C.; Marco, S.; Somogyi, A.

2017-06-01

Scanning hard X-ray imaging allows simultaneous acquisition of multimodal information, including X-ray fluorescence, absorption, phase and dark-field contrasts, providing structural and chemical details of the samples. Combining these scanning techniques with the infrastructure developed for fast data acquisition at Synchrotron Soleil permits to perform multimodal imaging and tomography during routine user experiments at the Nanoscopium beamline. A main challenge of such imaging techniques is the online processing and analysis of the generated very large volume (several hundreds of Giga Bytes) multimodal data-sets. This is especially important for the wide user community foreseen at the user oriented Nanoscopium beamline (e.g. from the fields of Biology, Life Sciences, Geology, Geobiology), having no experience in such data-handling. MMX-I is a new multi-platform open-source freeware for the processing and reconstruction of scanning multi-technique X-ray imaging and tomographic datasets. The MMX-I project aims to offer, both expert users and beginners, the possibility of processing and analysing raw data, either on-site or off-site. Therefore we have developed a multi-platform (Mac, Windows and Linux 64bit) data processing tool, which is easy to install, comprehensive, intuitive, extendable and user-friendly. MMX-I is now routinely used by the Nanoscopium user community and has demonstrated its performance in treating big data.

Dual-modality wide-field photothermal quantitative phase microscopy and depletion of cell populations

NASA Astrophysics Data System (ADS)

Turko, Nir A.; Barnea, Itay; Blum, Omry; Korenstein, Rafi; Shaked, Natan T.

2015-03-01

We review our dual-modality technique for quantitative imaging and selective depletion of populations of cells based on wide-field photothermal (PT) quantitative phase imaging and simultaneous PT cell extermination. The cells are first labeled by plasmonic gold nanoparticles, which evoke local plasmonic resonance when illuminated by light in a wavelength corresponding to their specific plasmonic resonance peak. This reaction creates changes of temperature, resulting in changes of phase. This phase changes are recorded by a quantitative phase microscope (QPM), producing specific imaging contrast, and enabling bio-labeling in phase microscopy. Using this technique, we have shown discrimination of EGFR over-expressing (EGFR+) cancer cells from EGFR under-expressing (EGFR-) cancer cells. Then, we have increased the excitation power in order to evoke greater temperatures, which caused specific cell death, all under real-time phase acquisition using QPM. Close to 100% of all EGFR+ cells were immediately exterminated when illuminated with the strong excitation beam, while all EGFR- cells survived. For the second experiment, in order to simulate a condition where circulating tumor cells (CTCs) are present in blood, we have mixed the EGFR+ cancer cells with white blood cells (WBCs) from a healthy donor. Here too, we have used QPM to observe and record the phase of the cells as they were excited for selective visualization and then exterminated. The WBCs survival rate was over 95%, while the EGFR+ survival rate was under 5%. The technique may be the basis for real-time detection and controlled treatment of CTCs.

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.

Three modality image registration of brain SPECT/CT and MR images for quantitative analysis of dopamine transporter imaging

NASA Astrophysics Data System (ADS)

Yamaguchi, Yuzuho; Takeda, Yuta; Hara, Takeshi; Zhou, Xiangrong; Matsusako, Masaki; Tanaka, Yuki; Hosoya, Kazuhiko; Nihei, Tsutomu; Katafuchi, Tetsuro; Fujita, Hiroshi

2016-03-01

Important features in Parkinson's disease (PD) are degenerations and losses of dopamine neurons in corpus striatum. 123I-FP-CIT can visualize activities of the dopamine neurons. The activity radio of background to corpus striatum is used for diagnosis of PD and Dementia with Lewy Bodies (DLB). The specific activity can be observed in the corpus striatum on SPECT images, but the location and the shape of the corpus striatum on SPECT images only are often lost because of the low uptake. In contrast, MR images can visualize the locations of the corpus striatum. The purpose of this study was to realize a quantitative image analysis for the SPECT images by using image registration technique with brain MR images that can determine the region of corpus striatum. In this study, the image fusion technique was used to fuse SPECT and MR images by intervening CT image taken by SPECT/CT. The mutual information (MI) for image registration between CT and MR images was used for the registration. Six SPECT/CT and four MR scans of phantom materials are taken by changing the direction. As the results of the image registrations, 16 of 24 combinations were registered within 1.3mm. By applying the approach to 32 clinical SPECT/CT and MR cases, all of the cases were registered within 0.86mm. In conclusions, our registration method has a potential in superimposing MR images on SPECT images.

Quantitative analysis of ultrasonic images of fibrotic liver using co-occurrence matrix based on multi-Rayleigh model

NASA Astrophysics Data System (ADS)

Isono, Hiroshi; Hirata, Shinnosuke; Hachiya, Hiroyuki

2015-07-01

In medical ultrasonic images of liver disease, a texture with a speckle pattern indicates a microscopic structure such as nodules surrounded by fibrous tissues in hepatitis or cirrhosis. We have been applying texture analysis based on a co-occurrence matrix to ultrasonic images of fibrotic liver for quantitative tissue characterization. A co-occurrence matrix consists of the probability distribution of brightness of pixel pairs specified with spatial parameters and gives new information on liver disease. Ultrasonic images of different types of fibrotic liver were simulated and the texture-feature contrast was calculated to quantify the co-occurrence matrices generated from the images. The results show that the contrast converges with a value that can be theoretically estimated using a multi-Rayleigh model of echo signal amplitude distribution. We also found that the contrast value increases as liver fibrosis progresses and fluctuates depending on the size of fibrotic structure.

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)

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...

In-vivo quantitative structural imaging of the human midbrain and the superior colliculus at 9.4T.

PubMed

Loureiro, Joana R; Himmelbach, Marc; Ethofer, Thomas; Pohmann, Rolf; Martin, Pascal; Bause, Jonas; Grodd, Wolfgang; Scheffler, Klaus; Hagberg, Gisela E

2018-05-02

We explored anatomical details of the superior colliculus (SC) by in vivo magnetic resonance imaging (MRI) at 9.4T. The high signal-to-noise ratio allowed the acquisition of high resolution, multi-modal images with voxel sizes ranging between 176 × 132 × 600 μm and (800) 3 μm. Quantitative mapping of the longitudinal relaxation rate R1, the effective transverse relaxation rate R2*, and the magnetic susceptibility QSM was performed in 14 healthy volunteers. The images were analyzed in native space as well as after normalization to a common brain space (MNI). The coefficient-of-variation (CoV) across subjects was evaluated in prominent regions of the midbrain, reaching the best reproducibility (CoV of 5%) in the R2* maps of the SC in MNI space, while the CoV in the QSM maps remained high regardless of brain-space. To investigate whether more complex neurobiological architectural features could be detected, depth profiles through the SC layers towards the red nucleus (RN) were evaluated at different levels of the SC along the rostro-caudal axis. This analysis revealed alterations of the quantitative MRI parameters concordant with previous post mortem histology studies of the cyto- and myeloarchitecture of the SC. In general, the R1 maps were hyperintense in areas characterized by the presence of abundant myelinated fibers, and likely enabled detection of the deep white layer VII of the SC adjacent to the periaqueductal gray. While R1 maps failed to reveal finer details, possibly due to the relatively coarse spatial sampling used for this modality, these could be recovered in R2* maps and in QSM. In the central part of the SC along its rostro-caudal axis, increased R2* values and decreased susceptibility values were observed 2 mm below the SC surface, likely reflecting the myelinated fibers in the superficial optic layer (layer III). Towards the deeper layers, a second increase in R2* was paralleled by a paramagnetic shift in QSM suggesting the presence

Limited Angle Dual Modality Breast Imaging

NASA Astrophysics Data System (ADS)

More, Mitali J.; Li, Heng; Goodale, Patricia J.; Zheng, Yibin; Majewski, Stan; Popov, Vladimir; Welch, Benjamin; Williams, Mark B.

2007-06-01

We are developing a dual modality breast scanner that can obtain x-ray transmission and gamma ray emission images in succession at multiple viewing angles with the breast held under mild compression. These views are reconstructed and fused to obtain three-dimensional images that combine structural and functional information. Here, we describe the dual modality system and present results of phantom experiments designed to test the system's ability to obtain fused volumetric dual modality data sets from a limited number of projections, acquired over a limited (less than 180 degrees) angular range. We also present initial results from phantom experiments conducted to optimize the acquisition geometry for gamma imaging. The optimization parameters include the total number of views and the angular range over which these views should be spread, while keeping the total number of detected counts fixed. We have found that in general, for a fixed number of views centered around the direction perpendicular to the direction of compression, in-plane contrast and SNR are improved as the angular range of the views is decreased. The improvement in contrast and SNR with decreasing angular range is much greater for deeper lesions and for a smaller number of views. However, the z-resolution of the lesion is significantly reduced with decreasing angular range. Finally, we present results from limited angle tomography scans using a system with dual, opposing heads.

Multi-object segmentation framework using deformable models for medical imaging analysis.

PubMed

Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

2016-08-01

Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed

Evaluation of the Spies™ modalities image quality

PubMed Central

Emiliani, Esteban; Talso, Michele; Baghdadi, Mohammed; Barreiro, Aarón; Orosa, Andrea; Serviàn, Pol; Gavrilov, Pavel; Proietti, Silvia; Traxer, Olivier

2017-01-01

Introduction The Spies™ system (Karl-Storz®) was introduced into digital ureteroscopy to improve endoscopic vision. To date, there is no data to either indicate which of the Spies modalities is better for improving diagnosis and treatment procedures, nor to compare the modalities in terms of image quality. The aim of this study was to evaluate and compare the image quality of five Spies™ modalities (SM) to the standard white light in an in-vitro model. Materials and Methods Two standardized grids and 3 stones of different composition were recorded in white light and the 5SM (Clara, Chroma, Clara+Chroma), Spectra A and B) using 4 standardized aqueous scenarios. Twelve templates were done in order to simultaneously compare the same objective in the different modalities. Six urologists, five medical students, five urology residents, and five persons not involved with urology evaluated each video on a scale of 1 (very bad) to 5 (very good). Results Comparing white light to SM, subjects scored better the quality of Clara and Clara+Chroma than white light (p=0.0139 and p<0.05) and scored worse Spectra A and B (p=0.0005 and p=0.0023)). When comparing Clara to the other SM, it was ranked equivalent to Clara+Chroma (p=0.67) and obtained a higher rank than Chroma, Spectra A and B (p<0.05, p=0.0001 and p=0.0001). In the multivariate analysis mean scores were higher among urologists. Conclusion In all analyzed scenarios, the subjects ranked Clara and Clara+Chroma as the modalities with better image quality compared to white light. PMID:28338307

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 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...

Inverse transport problems in quantitative PAT for molecular imaging

NASA Astrophysics Data System (ADS)

Ren, Kui; Zhang, Rongting; Zhong, Yimin

2015-12-01

Fluorescence photoacoustic tomography (fPAT) is a molecular imaging modality that combines photoacoustic tomography with fluorescence imaging to obtain high-resolution imaging of fluorescence distributions inside heterogeneous media. The objective of this work is to study inverse problems in the quantitative step of fPAT where we intend to reconstruct physical coefficients in a coupled system of radiative transport equations using internal data recovered from ultrasound measurements. We derive uniqueness and stability results on the inverse problems and develop some efficient algorithms for image reconstructions. Numerical simulations based on synthetic data are presented to validate the theoretical analysis. The results we present here complement these in Ren K and Zhao H (2013 SIAM J. Imaging Sci. 6 2024-49) on the same problem but in the diffusive regime.

Training of polyp staging systems using mixed imaging modalities.

PubMed

Wimmer, Georg; Gadermayr, Michael; Kwitt, Roland; Häfner, Michael; Tamaki, Toru; Yoshida, Shigeto; Tanaka, Shinji; Merhof, Dorit; Uhl, Andreas

2018-05-04

In medical image data sets, the number of images is usually quite small. The small number of training samples does not allow to properly train classifiers which leads to massive overfitting to the training data. In this work, we investigate whether increasing the number of training samples by merging datasets from different imaging modalities can be effectively applied to improve predictive performance. Further, we investigate if the extracted features from the employed image representations differ between different imaging modalities and if domain adaption helps to overcome these differences. We employ twelve feature extraction methods to differentiate between non-neoplastic and neoplastic lesions. Experiments are performed using four different classifier training strategies, each with a different combination of training data. The specifically designed setup for these experiments enables a fair comparison between the four training strategies. Combining high definition with high magnification training data and chromoscopic with non-chromoscopic training data partly improved the results. The usage of domain adaptation has only a small effect on the results compared to just using non-adapted training data. Merging datasets from different imaging modalities turned out to be partially beneficial for the case of combining high definition endoscopic data with high magnification endoscopic data and for combining chromoscopic with non-chromoscopic data. NBI and chromoendoscopy on the other hand are mostly too different with respect to the extracted features to combine images of these two modalities for classifier training. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prospectus on Multi-Modal Aspects of Human Factors in Transportation

DOT National Transportation Integrated Search

1991-02-01

This prospectus identifies and discusses a series of human factors : issues which are critical to transportation safety and productivity, and : examines the potential benefits that can accrue from taking a multi-modal : approach to human factors rese...

A Noninvasive Imaging Modality for Cardiac Arrhythmias

PubMed Central

Burnes, John E.; Taccardi, Bruno; Rudy, Yoram

2007-01-01

Background The last decade witnessed an explosion of information regarding the genetic, molecular, and mechanistic basis of heart disease. Translating this information into clinical practice requires the development of novel functional imaging modalities for diagnosis, localization, and guided intervention. A noninvasive modality for imaging cardiac arrhythmias is not yet available. Present electrocardiographic methods cannot precisely localize a ventricular tachycardia (VT) or its key reentrant circuit components. Recently, we developed a noninvasive electrocardiographic imaging modality (ECGI) that can reconstruct epicardial electrophysiological information from body surface potentials. Here, we extend its application to image reentrant arrhythmias. Methods and Results Epicardial potentials were recorded during VT with a 490 electrode sock during an open chest procedure in 2 dogs with 4-day-old myocardial infarctions. Body surface potentials were generated from these epicardial potentials in a human torso model. Realistic geometry errors and measurement noise were added to the torso data, which were then used to noninvasively reconstruct epicardial isochrones, electrograms, and potentials with excellent accuracy. ECGI reconstructed the reentry pathway and its key components, including (1) the central common pathway, (2) the VT exit site, (3) lines of block, and (4) regions of slow and fast conduction. This allowed for detailed characterization of the reentrant circuit morphology. Conclusions ECGI can noninvasively image arrhythmic activation on the epicardium during VT to identify and localize key components of the arrhythmogenic pathway that can be effective targets for antiarrhythmic intervention. PMID:11044435

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.

Co-registration of multi-modality imaging allows for comprehensive analysis of tumor-induced bone disease

PubMed Central

Seeley, Erin H.; Wilson, Kevin J.; Yankeelov, Thomas E.; Johnson, Rachelle W.; Gore, John C.; Caprioli, Richard M.; Matrisian, Lynn M.; Sterling, Julie A.

2014-01-01

Bone metastases are a clinically significant problem that arises in approximately 70% of metastatic breast cancer patients. Once established in bone, tumor cells induce changes in the bone microenvironment that lead to bone destruction, pain, and significant morbidity. While much is known about the later stages of bone disease, less is known about the earlier stages or the changes in protein expression in the tumor micro-environment. Due to promising results of combining magnetic resonance imaging (MRI) and Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry (MALDI IMS) ion images in the brain, we developed methods for applying these modalities to models of tumor-induced bone disease in order to better understand the changes in protein expression that occur within the tumor-bone microenvironment. Specifically, we integrated three dimensional-volume reconstructions of spatially resolved MALDI IMS with high-resolution anatomical and diffusion weighted MRI data and histology in an intratibial model of breast tumor-induced bone disease. This approach enables us to analyze proteomic profiles from MALDI IMS data with corresponding in vivo imaging and ex vivo histology data. To the best of our knowledge, this is the first time these three modalities have been rigorously registered in the bone. The MALDI mass-to-charge ratio peaks indicate differential expression of calcyclin, ubiquitin, and other proteins within the tumor cells, while peaks corresponding to hemoglobin A and calgranulin A provided molecular information that aided in the identification of areas rich in red and white blood cells, respectively. This multimodality approach will allow us to comprehensively understand the bone-tumor microenvironment and thus may allow us to better develop and test approaches for inhibiting bone metastases. PMID:24487126

Cone Beam CT vs. Fan Beam CT: A Comparison of Image Quality and Dose Delivered Between Two Differing CT Imaging Modalities.

PubMed

Lechuga, Lawrence; Weidlich, Georg A

2016-09-12

A comparison of image quality and dose delivered between two differing computed tomography (CT) imaging modalities-fan beam and cone beam-was performed. A literature review of quantitative analyses for various image quality aspects such as uniformity, signal-to-noise ratio, artifact presence, spatial resolution, modulation transfer function (MTF), and low contrast resolution was generated. With these aspects quantified, cone beam computed tomography (CBCT) shows a superior spatial resolution to that of fan beam, while fan beam shows a greater ability to produce clear and anatomically correct images with better soft tissue differentiation. The results indicate that fan beam CT produces superior images to that of on-board imaging (OBI) cone beam CT systems, while providing a considerably less dose to the patient.

Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma.

PubMed

Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

2015-02-28

To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P<0.001) and objective tumor response (P=0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P=0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P<0.001). Multivariate analysis identified tumor stage (P<0.001) and tumor type (P=0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P<0.001), surgical treatment (P=0.009), and multi-modal treatment (P=0.002) were identified as independent post-treatment prognostic factors. TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC.

Outcome of transarterial chemoembolization-based multi-modal treatment in patients with unresectable hepatocellular carcinoma

PubMed Central

Song, Do Seon; Nam, Soon Woo; Bae, Si Hyun; Kim, Jin Dong; Jang, Jeong Won; Song, Myeong Jun; Lee, Sung Won; Kim, Hee Yeon; Lee, Young Joon; Chun, Ho Jong; You, Young Kyoung; Choi, Jong Young; Yoon, Seung Kew

2015-01-01

AIM: To investigate the efficacy and safety of transarterial chemoembolization (TACE)-based multimodal treatment in patients with large hepatocellular carcinoma (HCC). METHODS: A total of 146 consecutive patients were included in the analysis, and their medical records and radiological data were reviewed retrospectively. RESULTS: In total, 119 patients received TACE-based multi-modal treatments, and the remaining 27 received conservative management. Overall survival (P < 0.001) and objective tumor response (P = 0.003) were significantly better in the treatment group than in the conservative group. After subgroup analysis, survival benefits were observed not only in the multi-modal treatment group compared with the TACE-only group (P = 0.002) but also in the surgical treatment group compared with the loco-regional treatment-only group (P < 0.001). Multivariate analysis identified tumor stage (P < 0.001) and tumor type (P = 0.009) as two independent pre-treatment factors for survival. After adjusting for significant pre-treatment prognostic factors, objective response (P < 0.001), surgical treatment (P = 0.009), and multi-modal treatment (P = 0.002) were identified as independent post-treatment prognostic factors. CONCLUSION: TACE-based multi-modal treatments were safe and more beneficial than conservative management. Salvage surgery after successful downstaging resulted in long-term survival in patients with large, unresectable HCC. PMID:25741147

Integrated quantitative phase and birefringence microscopy for imaging malaria-infected red blood cells.

PubMed

Li, Chengshuai; Chen, Shichao; Klemba, Michael; Zhu, Yizheng

2016-09-01

A dual-modality birefringence/phase imaging system is presented. The system features a crystal retarder that provides polarization mixing and generates two interferometric carrier waves in a single signal spectrum. The retardation and orientation of sample birefringence can then be measured simultaneously based on spectral multiplexing interferometry. Further, with the addition of a Nomarski prism, the same setup can be used for quantitative differential interference contrast (DIC) imaging. Sample phase can then be obtained with two-dimensional integration. In addition, birefringence-induced phase error can be corrected using the birefringence data. This dual-modality approach is analyzed theoretically with Jones calculus and validated experimentally with malaria-infected red blood cells. The system generates not only corrected DIC and phase images, but a birefringence map that highlights the distribution of hemozoin crystals.

Integrated quantitative phase and birefringence microscopy for imaging malaria-infected red blood cells

NASA Astrophysics Data System (ADS)

Li, Chengshuai; Chen, Shichao; Klemba, Michael; Zhu, Yizheng

2016-09-01

A dual-modality birefringence/phase imaging system is presented. The system features a crystal retarder that provides polarization mixing and generates two interferometric carrier waves in a single signal spectrum. The retardation and orientation of sample birefringence can then be measured simultaneously based on spectral multiplexing interferometry. Further, with the addition of a Nomarski prism, the same setup can be used for quantitative differential interference contrast (DIC) imaging. Sample phase can then be obtained with two-dimensional integration. In addition, birefringence-induced phase error can be corrected using the birefringence data. This dual-modality approach is analyzed theoretically with Jones calculus and validated experimentally with malaria-infected red blood cells. The system generates not only corrected DIC and phase images, but a birefringence map that highlights the distribution of hemozoin crystals.

Compton scatter imaging: A promising modality for image guidance in lung stereotactic body radiation therapy

PubMed Central

Redler, Gage; Jones, Kevin C.; Templeton, Alistair; Bernard, Damian; Turian, Julius; Chu, James C. H.

2018-01-01

Purpose Lung stereotactic body radiation therapy (SBRT) requires delivering large radiation doses with millimeter accuracy, making image guidance essential. An approach to forming images of patient anatomy from Compton-scattered photons during lung SBRT is presented. Methods To investigate the potential of scatter imaging, a pinhole collimator and flat-panel detector are used for spatial localization and detection of photons scattered during external beam therapy using lung SBRT treatment conditions (6 MV FFF beam). MCNP Monte Carlo software is used to develop a model to simulate scatter images. This model is validated by comparing experimental and simulated phantom images. Patient scatter images are then simulated from 4DCT data. Results Experimental lung tumor phantom images have sufficient contrast-to-noise to visualize the tumor with as few as 10 MU (0.5 s temporal resolution). The relative signal intensity from objects of different composition as well as lung tumor contrast for simulated phantom images agree quantitatively with experimental images, thus validating the Monte Carlo model. Scatter images are shown to display high contrast between different materials (lung, water, bone). Simulated patient images show superior (~double) tumor contrast compared to MV transmission images. Conclusions Compton scatter imaging is a promising modality for directly imaging patient anatomy during treatment without additional radiation, and it has the potential to complement existing technologies and aid tumor tracking and lung SBRT image guidance. PMID:29360151

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

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.

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.

Quantitative Hyperspectral Reflectance Imaging

PubMed Central

Klein, Marvin E.; Aalderink, Bernard J.; Padoan, Roberto; de Bruin, Gerrit; Steemers, Ted A.G.

2008-01-01

Hyperspectral imaging is a non-destructive optical analysis technique that can for instance be used to obtain information from cultural heritage objects unavailable with conventional colour or multi-spectral photography. This technique can be used to distinguish and recognize materials, to enhance the visibility of faint or obscured features, to detect signs of degradation and study the effect of environmental conditions on the object. We describe the basic concept, working principles, construction and performance of a laboratory instrument specifically developed for the analysis of historical documents. The instrument measures calibrated spectral reflectance images at 70 wavelengths ranging from 365 to 1100 nm (near-ultraviolet, visible and near-infrared). By using a wavelength tunable narrow-bandwidth light-source, the light energy used to illuminate the measured object is minimal, so that any light-induced degradation can be excluded. Basic analysis of the hyperspectral data includes a qualitative comparison of the spectral images and the extraction of quantitative data such as mean spectral reflectance curves and statistical information from user-defined regions-of-interest. More sophisticated mathematical feature extraction and classification techniques can be used to map areas on the document, where different types of ink had been applied or where one ink shows various degrees of degradation. The developed quantitative hyperspectral imager is currently in use by the Nationaal Archief (National Archives of The Netherlands) to study degradation effects of artificial samples and original documents, exposed in their permanent exhibition area or stored in their deposit rooms. PMID:27873831

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...

Quantitative Assessment of Retinopathy Using Multi-parameter Image Analysis

PubMed Central

Ghanian, Zahra; Staniszewski, Kevin; Jamali, Nasim; Sepehr, Reyhaneh; Wang, Shoujian; Sorenson, Christine M.; Sheibani, Nader; Ranji, Mahsa

2016-01-01

A multi-parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. This method was applied to wholemount retinal trypsin digest images of diabetic Akita/+, and bcl-2 knocked out mice models. Five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well as quantifying the disease progression. Our approach was validated through simulations of retinal images. Results showed fewer number of cells (P = 5.1205e-05), greater population ratios of endothelial cells to pericytes (PCs) (P = 5.1772e-04; an indicator of PC loss), higher fractal dimension (P = 8.2202e-05), smaller vessel coverage (P = 1.4214e-05), and greater number of acellular capillaries (P = 7.0414e-04) for diabetic retina as compared to normal retina. Quantification using the present method would be helpful in evaluating physiological and pathological retinopathy in a high-throughput and reproducible manner. PMID:27186534

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...

Flaw investigation in a multi-layered, multi-material composite: Using air-coupled ultrasonic resonance imaging

NASA Astrophysics Data System (ADS)

Livings, R. A.; Dayal, V.; Barnard, D. J.; Hsu, D. K.

2012-05-01

Ceramic tiles are the main ingredient of a multi-material, multi-layered composite being considered for the modernization of tank armors. The high stiffness, low attenuation, and precise dimensions of these uniform tiles make them remarkable resonators when driven to vibrate. Defects in the tile, during manufacture or after usage, are expected to change the resonance frequencies and resonance images of the tile. The comparison of the resonance frequencies and resonance images of a pristine tile/lay-up to a defective tile/lay-up will thus be a quantitative damage metric. By examining the vibrational behavior of these tiles and the composite lay-up with Finite Element Modeling and analytical plate vibration equations, the development of a new Nondestructive Evaluation technique is possible. This study examines the development of the Air-Coupled Ultrasonic Resonance Imaging technique as applied to a hexagonal ceramic tile and a multi-material, multi-layered composite.

The image evaluation of iterative motion correction reconstruction algorithm PROPELLER T2-weighted imaging compared with MultiVane T2-weighted imaging

NASA Astrophysics Data System (ADS)

Lee, Suk-Jun; Yu, Seung-Man

2017-08-01

The purpose of this study was to evaluate the usefulness and clinical applications of MultiVaneXD which was applying iterative motion correction reconstruction algorithm T2-weighted images compared with MultiVane images taken with a 3T MRI. A total of 20 patients with suspected pathologies of the liver and pancreatic-biliary system based on clinical and laboratory findings underwent upper abdominal MRI, acquired using the MultiVane and MultiVaneXD techniques. Two reviewers analyzed the MultiVane and MultiVaneXD T2-weighted images qualitatively and quantitatively. Each reviewer evaluated vessel conspicuity by observing motion artifacts and the sharpness of the portal vein, hepatic vein, and upper organs. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated by one reviewer for quantitative analysis. The interclass correlation coefficient was evaluated to measure inter-observer reliability. There were significant differences between MultiVane and MultiVaneXD in motion artifact evaluation. Furthermore, MultiVane was given a better score than MultiVaneXD in abdominal organ sharpness and vessel conspicuity, but the difference was insignificant. The reliability coefficient values were over 0.8 in every evaluation. MultiVaneXD (2.12) showed a higher value than did MultiVane (1.98), but the difference was insignificant ( p = 0.135). MultiVaneXD is a motion correction method that is more advanced than MultiVane, and it produced an increased SNR, resulting in a greater ability to detect focal abdominal lesions.

Biomarkers and Surrogate Endpoints in Uveitis: The Impact of Quantitative Imaging.

PubMed

Denniston, Alastair K; Keane, Pearse A; Srivastava, Sunil K

2017-05-01

Uveitis is a major cause of sight loss across the world. The reliable assessment of intraocular inflammation in uveitis ('disease activity') is essential in order to score disease severity and response to treatment. In this review, we describe how 'quantitative imaging', the approach of using automated analysis and measurement algorithms across both standard and emerging imaging modalities, can develop objective instrument-based measures of disease activity. This is a narrative review based on searches of the current world literature using terms related to quantitative imaging techniques in uveitis, supplemented by clinical trial registry data, and expert knowledge of surrogate endpoints and outcome measures in ophthalmology. Current measures of disease activity are largely based on subjective clinical estimation, and are relatively insensitive, with poor discrimination and reliability. The development of quantitative imaging in uveitis is most established in the use of optical coherence tomographic (OCT) measurement of central macular thickness (CMT) to measure severity of macular edema (ME). The transformative effect of CMT in clinical assessment of patients with ME provides a paradigm for the development and impact of other forms of quantitative imaging. Quantitative imaging approaches are now being developed and validated for other key inflammatory parameters such as anterior chamber cells, vitreous haze, retinovascular leakage, and chorioretinal infiltrates. As new forms of quantitative imaging in uveitis are proposed, the uveitis community will need to evaluate these tools against the current subjective clinical estimates and reach a new consensus for how disease activity in uveitis should be measured. The development, validation, and adoption of sensitive and discriminatory measures of disease activity is an unmet need that has the potential to transform both drug development and routine clinical care for the patient with uveitis.

Compton scatter imaging: A promising modality for image guidance in lung stereotactic body radiation therapy.

PubMed

Redler, Gage; Jones, Kevin C; Templeton, Alistair; Bernard, Damian; Turian, Julius; Chu, James C H

2018-03-01

Lung stereotactic body radiation therapy (SBRT) requires delivering large radiation doses with millimeter accuracy, making image guidance essential. An approach to forming images of patient anatomy from Compton-scattered photons during lung SBRT is presented. To investigate the potential of scatter imaging, a pinhole collimator and flat-panel detector are used for spatial localization and detection of photons scattered during external beam therapy using lung SBRT treatment conditions (6 MV FFF beam). MCNP Monte Carlo software is used to develop a model to simulate scatter images. This model is validated by comparing experimental and simulated phantom images. Patient scatter images are then simulated from 4DCT data. Experimental lung tumor phantom images have sufficient contrast-to-noise to visualize the tumor with as few as 10 MU (0.5 s temporal resolution). The relative signal intensity from objects of different composition as well as lung tumor contrast for simulated phantom images agree quantitatively with experimental images, thus validating the Monte Carlo model. Scatter images are shown to display high contrast between different materials (lung, water, bone). Simulated patient images show superior (~double) tumor contrast compared to MV transmission images. Compton scatter imaging is a promising modality for directly imaging patient anatomy during treatment without additional radiation, and it has the potential to complement existing technologies and aid tumor tracking and lung SBRT image guidance. © 2018 American Association of Physicists in Medicine.

Evaluation of the Spies TM modalities image quality.

PubMed

Emiliani, Esteban; Talso, Michele; Baghdadi, Mohammed; Barreiro, Aaron; Orosa, Andrea; Serviàn, Pol; Gavrilov, Pavel; Proietti, Silvia; Traxer, Olivier

2017-01-01

The Spies™ system (Karl-Storz®) was introduced into digital ureteroscopy to improve endoscopic vision. To date, there is no data to either indicate which of the Spies modalities is better for improving diagnosis and treatment procedures, nor to compare the modalities in terms of image quality. The aim of this study was to evaluate and compare the image quality of five Spies™ modalities (SM) to the standard white light in an in-vitro model. Two standardized grids and 3 stones of different composition were recorded in white light and the 5SM (Clara, Chroma, Clara+Chroma), Spectra A and B) using 4 standardized aqueous scenarios. Twelve templates were done in order to simultaneously compare the same objective in the different modalities. Six urologists, five medical students, five urology residents, and five persons not involved with urology evaluated each video on a scale of 1 (very bad) to 5 (very good). Comparing white light to SM, subjects scored better the quality of Clara and Clara+Chroma than white light (p=0.0139 and p<0.05) and scored worse Spectra A and B (p=0.0005 and p=0.0023). When comparing Clara to the other SM, it was ranked equivalent to Clara+Chroma (p=0.67) and obtained a higher rank than Chroma, Spectra A and B (p<0.05, p=0.0001 and p=0.0001). In the multivariate analysis mean scores were higher among urologists. In all analyzed scenarios, the subjects ranked Clara and Clara+Chroma as the modalities with better image quality compared to white light. Copyright® by the International Brazilian Journal of Urology.

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

Unsupervised Segmentation of Head Tissues from Multi-modal MR Images for EEG Source Localization.

PubMed

Mahmood, Qaiser; Chodorowski, Artur; Mehnert, Andrew; Gellermann, Johanna; Persson, Mikael

2015-08-01

In this paper, we present and evaluate an automatic unsupervised segmentation method, hierarchical segmentation approach (HSA)-Bayesian-based adaptive mean shift (BAMS), for use in the construction of a patient-specific head conductivity model for electroencephalography (EEG) source localization. It is based on a HSA and BAMS for segmenting the tissues from multi-modal magnetic resonance (MR) head images. The evaluation of the proposed method was done both directly in terms of segmentation accuracy and indirectly in terms of source localization accuracy. The direct evaluation was performed relative to a commonly used reference method brain extraction tool (BET)-FMRIB's automated segmentation tool (FAST) and four variants of the HSA using both synthetic data and real data from ten subjects. The synthetic data includes multiple realizations of four different noise levels and several realizations of typical noise with a 20% bias field level. The Dice index and Hausdorff distance were used to measure the segmentation accuracy. The indirect evaluation was performed relative to the reference method BET-FAST using synthetic two-dimensional (2D) multimodal magnetic resonance (MR) data with 3% noise and synthetic EEG (generated for a prescribed source). The source localization accuracy was determined in terms of localization error and relative error of potential. The experimental results demonstrate the efficacy of HSA-BAMS, its robustness to noise and the bias field, and that it provides better segmentation accuracy than the reference method and variants of the HSA. They also show that it leads to a more accurate localization accuracy than the commonly used reference method and suggest that it has potential as a surrogate for expert manual segmentation for the EEG source localization problem.

A tri-modality image fusion method for target delineation of brain tumors in radiotherapy.

PubMed

Guo, Lu; Shen, Shuming; Harris, Eleanor; Wang, Zheng; Jiang, Wei; Guo, Yu; Feng, Yuanming

2014-01-01

To develop a tri-modality image fusion method for better target delineation in image-guided radiotherapy for patients with brain tumors. A new method of tri-modality image fusion was developed, which can fuse and display all image sets in one panel and one operation. And a feasibility study in gross tumor volume (GTV) delineation using data from three patients with brain tumors was conducted, which included images of simulation CT, MRI, and 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) examinations before radiotherapy. Tri-modality image fusion was implemented after image registrations of CT+PET and CT+MRI, and the transparency weight of each modality could be adjusted and set by users. Three radiation oncologists delineated GTVs for all patients using dual-modality (MRI/CT) and tri-modality (MRI/CT/PET) image fusion respectively. Inter-observer variation was assessed by the coefficient of variation (COV), the average distance between surface and centroid (ADSC), and the local standard deviation (SDlocal). Analysis of COV was also performed to evaluate intra-observer volume variation. The inter-observer variation analysis showed that, the mean COV was 0.14(± 0.09) and 0.07(± 0.01) for dual-modality and tri-modality respectively; the standard deviation of ADSC was significantly reduced (p<0.05) with tri-modality; SDlocal averaged over median GTV surface was reduced in patient 2 (from 0.57 cm to 0.39 cm) and patient 3 (from 0.42 cm to 0.36 cm) with the new method. The intra-observer volume variation was also significantly reduced (p = 0.00) with the tri-modality method as compared with using the dual-modality method. With the new tri-modality image fusion method smaller inter- and intra-observer variation in GTV definition for the brain tumors can be achieved, which improves the consistency and accuracy for target delineation in individualized radiotherapy.

Full-field modal analysis during base motion excitation using high-speed 3D digital image correlation

NASA Astrophysics Data System (ADS)

Molina-Viedma, Ángel J.; López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2017-10-01

In recent years, many efforts have been made to exploit full-field measurement optical techniques for modal identification. Three-dimensional digital image correlation using high-speed cameras has been extensively employed for this purpose. Modal identification algorithms are applied to process the frequency response functions (FRF), which relate the displacement response of the structure to the excitation force. However, one of the most common tests for modal analysis involves the base motion excitation of a structural element instead of force excitation. In this case, the relationship between response and excitation is typically based on displacements, which are known as transmissibility functions. In this study, a methodology for experimental modal analysis using high-speed 3D digital image correlation and base motion excitation tests is proposed. In particular, a cantilever beam was excited from its base with a random signal, using a clamped edge join. Full-field transmissibility functions were obtained through the beam and converted into FRF for proper identification, considering a single degree-of-freedom theoretical conversion. Subsequently, modal identification was performed using a circle-fit approach. The proposed methodology facilitates the management of the typically large amounts of data points involved in the DIC measurement during modal identification. Moreover, it was possible to determine the natural frequencies, damping ratios and full-field mode shapes without requiring any additional tests. Finally, the results were experimentally validated by comparing them with those obtained by employing traditional accelerometers, analytical models and finite element method analyses. The comparison was performed by using the quantitative indicator modal assurance criterion. The results showed a high level of correspondence, consolidating the proposed experimental methodology.

A calibrated iterative reconstruction for quantitative photoacoustic tomography using multi-angle light-sheet illuminations

NASA Astrophysics Data System (ADS)

Wang, Yihan; Lu, Tong; Zhang, Songhe; Song, Shaoze; Wang, Bingyuan; Li, Jiao; Zhao, Huijuan; Gao, Feng

2018-02-01

Quantitative photoacoustic tomography (q-PAT) is a nontrivial technique can be used to reconstruct the absorption image with a high spatial resolution. Several attempts have been investigated by setting point sources or fixed-angle illuminations. However, in practical applications, these schemes normally suffer from low signal-to-noise ratio (SNR) or poor quantification especially for large-size domains, due to the limitation of the ANSI-safety incidence and incompleteness in the data acquisition. We herein present a q-PAT implementation that uses multi-angle light-sheet illuminations and a calibrated iterative multi-angle reconstruction. The approach can acquire more complete information on the intrinsic absorption and SNR-boosted photoacoustic signals at selected planes from the multi-angle wide-field excitations of light-sheet. Therefore, the sliced absorption maps over whole body can be recovered in a measurementflexible, noise-robust and computation-economic way. The proposed approach is validated by the phantom experiment, exhibiting promising performances in image fidelity and quantitative accuracy.

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

A gantry-based tri-modality system for bioluminescence tomography

PubMed Central

Yan, Han; Lin, Yuting; Barber, William C.; Unlu, Mehmet Burcin; Gulsen, Gultekin

2012-01-01

A gantry-based tri-modality system that combines bioluminescence (BLT), diffuse optical (DOT), and x-ray computed tomography (XCT) into the same setting is presented here. The purpose of this system is to perform bioluminescence tomography using a multi-modality imaging approach. As parts of this hybrid system, XCT and DOT provide anatomical information and background optical property maps. This structural and functional a priori information is used to guide and restrain bioluminescence reconstruction algorithm and ultimately improve the BLT results. The performance of the combined system is evaluated using multi-modality phantoms. In particular, a cylindrical heterogeneous multi-modality phantom that contains regions with higher optical absorption and x-ray attenuation is constructed. We showed that a 1.5 mm diameter bioluminescence inclusion can be localized accurately with the functional a priori information while its source strength can be recovered more accurately using both structural and the functional a priori information. PMID:22559540

Multi-exponential analysis of magnitude MR images using a quantitative multispectral edge-preserving filter.

PubMed

Bonny, Jean Marie; Boespflug-Tanguly, Odile; Zanca, Michel; Renou, Jean Pierre

2003-03-01

A solution for discrete multi-exponential analysis of T(2) relaxation decay curves obtained in current multi-echo imaging protocol conditions is described. We propose a preprocessing step to improve the signal-to-noise ratio and thus lower the signal-to-noise ratio threshold from which a high percentage of true multi-exponential detection is detected. It consists of a multispectral nonlinear edge-preserving filter that takes into account the signal-dependent Rician distribution of noise affecting magnitude MR images. Discrete multi-exponential decomposition, which requires no a priori knowledge, is performed by a non-linear least-squares procedure initialized with estimates obtained from a total least-squares linear prediction algorithm. This approach was validated and optimized experimentally on simulated data sets of normal human brains.

TU-AB-202-11: Tumor Segmentation by Fusion of Multi-Tracer PET Images Using Copula Based Statistical Methods

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

Lapuyade-Lahorgue, J; Ruan, S; Li, H

Purpose: Multi-tracer PET imaging is getting more attention in radiotherapy by providing additional tumor volume information such as glucose and oxygenation. However, automatic PET-based tumor segmentation is still a very challenging problem. We propose a statistical fusion approach to joint segment the sub-area of tumors from the two tracers FDG and FMISO PET images. Methods: Non-standardized Gamma distributions are convenient to model intensity distributions in PET. As a serious correlation exists in multi-tracer PET images, we proposed a new fusion method based on copula which is capable to represent dependency between different tracers. The Hidden Markov Field (HMF) model ismore » used to represent spatial relationship between PET image voxels and statistical dynamics of intensities for each modality. Real PET images of five patients with FDG and FMISO are used to evaluate quantitatively and qualitatively our method. A comparison between individual and multi-tracer segmentations was conducted to show advantages of the proposed fusion method. Results: The segmentation results show that fusion with Gaussian copula can receive high Dice coefficient of 0.84 compared to that of 0.54 and 0.3 of monomodal segmentation results based on individual segmentation of FDG and FMISO PET images. In addition, high correlation coefficients (0.75 to 0.91) for the Gaussian copula for all five testing patients indicates the dependency between tumor regions in the multi-tracer PET images. Conclusion: This study shows that using multi-tracer PET imaging can efficiently improve the segmentation of tumor region where hypoxia and glucidic consumption are present at the same time. Introduction of copulas for modeling the dependency between two tracers can simultaneously take into account information from both tracers and deal with two pathological phenomena. Future work will be to consider other families of copula such as spherical and archimedian copulas, and to eliminate partial

Students' Multi-Modal Re-Presentations of Scientific Knowledge and Creativity

ERIC Educational Resources Information Center

Koren, Yitzhak; Klavir, Rama; Gorodetsky, Malka

2005-01-01

The paper brings the results of a project that passed on to students the opportunity for re-presenting their acquired knowledge via the construction of multi-modal "learning resources". These "learning resources" substituted for lectures and books and became the official learning sources in the classroom. The rational for the…

A Multi-Modal Active Learning Experience for Teaching Social Categorization

ERIC Educational Resources Information Center

Schwarzmueller, April

2011-01-01

This article details a multi-modal active learning experience to help students understand elements of social categorization. Each student in a group dynamics course observed two groups in conflict and identified examples of in-group bias, double-standard thinking, out-group homogeneity bias, law of small numbers, group attribution error, ultimate…

Rhesus macaques recognize unique multi-modal face-voice relations of familiar individuals and not of unfamiliar ones

PubMed Central

Habbershon, Holly M.; Ahmed, Sarah Z.; Cohen, Yale E.

2013-01-01

Communication signals in non-human primates are inherently multi-modal. However, for laboratory-housed monkeys, there is relatively little evidence in support of the use of multi-modal communication signals in individual recognition. Here, we used a preferential-looking paradigm to test whether laboratory-housed rhesus could “spontaneously” (i.e., in the absence of operant training) use multi-modal communication stimuli to discriminate between known conspecifics. The multi-modal stimulus was a silent movie of two monkeys vocalizing and an audio file of the vocalization from one of the monkeys in the movie. We found that the gaze patterns of those monkeys that knew the individuals in the movie were reliably biased toward the individual that did not produce the vocalization. In contrast, there was not a systematic gaze pattern for those monkeys that did not know the individuals in the movie. These data are consistent with the hypothesis that laboratory-housed rhesus can recognize and distinguish between conspecifics based on auditory and visual communication signals. PMID:23774779

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

Laser Polarized 129Xe Magnetic Resonance Imaging and Spectroscopy Studies: Development of a New Modality of Functional Imaging

NASA Astrophysics Data System (ADS)

Rosen, M.; Coulter, K. P.; Chupp, T. E.; Swanson, S. D.; Agranoff, B. W.

1996-05-01

One of the most exciting prospects for the application of laser polarized noble gas magnetic resonance imaging and spectroscopy of ^129Xe is the quantitative measurement of cerebral blood flow changes in response to various stimuli. Development of this new modality of functional imaging requires tracking the transport of inspirated laser polarized ^129Xe from the lungs to the blood and to the brain. We describe a series of experiments with rats that include producing noble gas magnetic resonance images and study of the uptake and transport of polarized ^129Xe in the blood and to the head. We have observed spectral components of the ^129Xe at about -200 ppm relative to the free gas and confirmed their transport to the head. The time dependence of this component in the head has been studied. Current efforts are to spatially localize the polarized ^129Xe and image the magnetization in the steady state.

Multi-Wavelength Photomagnetic Imaging for Oral Cancer

NASA Astrophysics Data System (ADS)

Marks, Michael

In this study, a multi-wavelength Photomagnetic Imaging (PMI) system is developed and evaluated with experimental studies.. PMI measures temperature increases in samples illuminated by near-infrared light sources using magnetic resonance thermometry. A multiphysics solver combining light and heat transfer models the spatiotemporal distribution of the temperature change. The PMI system develop in this work uses three lasers of varying wavelength (785 nm, 808 nm, 860 nm) to heat the sample. By using multiple wavelengths, we enable the PMI system to quantify the relative concentrations of optical contrast in turbid media and monitor their distribution, at a higher resolution than conventional diffuse optical imaging. The data collected from agarose phantoms with multiple embedded contrast agents designed to simulate the optical properties of oxy- and deoxy-hemoglobin is presented. The reconstructed images demonstrate that multi-wavelength PMI can resolve this complex inclusion structure with high resolution and recover the concentration of each contrast agent with high quantitative accuracy. The modified multi-wavelength PMI system operates under the maximum skin exposure limits defined by the American National Standards Institute, to enable future clinical applications.

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…

A quantitative study to design an experimental setup for photoacoustic imaging.

PubMed

Marion, Adrien; Boutet, Jérôme; Debourdeau, Mathieu; Dinten, Jean-Marc; Vray, Didier

2011-01-01

During the last decade, a new modality called photoacoustic imaging has emerged. The increasing interest for this new modality is due to the fact that it combines advantages of ultrasound and optical imaging, i.e. the high contrast due to optical absorption and the low acoustic attenuation in biological tissues. It is thus possible to study vascularization because blood has high optical absorption coefficient. Papers in the literature often focus on applications and rarely discuss quantitative parameters. The goal of this paper is to provide quantitative elements to design an acquisition setup. By defining the targeted resolution and penetration depth, it is then possible to evaluate which kind of excitation and reception systems have to be used. First, we recall theoretical background related to photoacoustic effect before to describe the experiments based on a nanosecond laser at 1064 nm and 2.25-5 MHz transducers. Second, we present results about the relation linking fluence laser to signal amplitude and axial and lateral resolutions of our acquisition setup. We verify the linear relation between fluence and amplitude before to estimate axial resolution at 550 μm for a 2.25 MHz ultrasonic transducer. Concerning lateral resolution, we show that a reconstruction technique based on curvilinear acquisition of 30 lines improves it by a factor of 3 compared to a lateral displacement. Future works will include improvement of lateral resolution using probes, like in ultrasound imaging, instead of single-element transducers.

Quantitative diffusion MRI using reduced field-of-view and multi-shot acquisition techniques: Validation in phantoms and prostate imaging.

PubMed

Zhang, Yuxin; Holmes, James; Rabanillo, Iñaki; Guidon, Arnaud; Wells, Shane; Hernando, Diego

2018-09-01

To evaluate the reproducibility of quantitative diffusion measurements obtained with reduced Field of View (rFOV) and Multi-shot EPI (msEPI) acquisitions, using single-shot EPI (ssEPI) as a reference. Diffusion phantom experiments, and prostate diffusion-weighted imaging in healthy volunteers and patients with known or suspected prostate cancer were performed across the three different sequences. Quantitative diffusion measurements of apparent diffusion coefficient, and diffusion kurtosis parameters (healthy volunteers), were obtained and compared across diffusion sequences (rFOV, msEPI, and ssEPI). Other possible confounding factors like b-value combinations and acquisition parameters were also investigated. Both msEPI and rFOV have shown reproducible quantitative diffusion measurements relative to ssEPI; no significant difference in ADC was observed across pulse sequences in the standard diffusion phantom (p = 0.156), healthy volunteers (p ≥ 0.12) or patients (p ≥ 0.26). The ADC values within the non-cancerous central gland and peripheral zone of patients were 1.29 ± 0.17 × 10 -3  mm 2 /s and 1.74 ± 0.23 × 10 -3  mm 2 /s respectively. However, differences in quantitative diffusion parameters were observed across different number of averages for rFOV, and across b-value groups and diffusion models for all the three sequences. Both rFOV and msEPI have the potential to provide high image quality with reproducible quantitative diffusion measurements in prostate diffusion MRI. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Radiological Evaluation of Ambiguous Genitalia with Various Imaging Modalities

NASA Astrophysics Data System (ADS)

Ravi, N.; Bindushree, Kadakola

2012-07-01

Disorders of sex development (DSDs) are congenital conditions in which the development of chromosomal, gonadal, or anatomic sex is atypical. These can be classified broadly into four categories on the basis of gonadal histologic features: female pseudohermaphroditism (46,XX with two ovaries); male pseudohermaphroditism (46,XY with two testes); true hermaphroditism (ovotesticular DSD) (both ovarian and testicular tissues); and gonadal dysgenesis, either mixed (a testis and a streak gonad) or pure (bilateral streak gonads). Imaging plays an important role in demonstrating the anatomy and associated anomalies. Ultrasonography is the primary modality for demonstrating internal organs and magnetic resonance imaging is used as an adjunct modality to assess for internal gonads and genitalia. Early and appropriate gender assignment is necessary for healthy physical and psychologic development of children with ambiguous genitalia. Gender assignment can be facilitated with a team approach that involves a pediatric endocrinologist, geneticist, urologist, psychiatrist, social worker, neonatologist, nurse, and radiologist, allowing timely diagnosis and proper management. We describe case series on ambiguous genitalia presented to our department who were evaluated with multiple imaging modalities.

Construction of specific magnetic resonance imaging/optical dual-modality molecular probe used for imaging angiogenesis of gastric cancer.

PubMed

Yan, Xuejie; Song, Xiaoyan; Wang, Zhenbo

2017-05-01

The purpose of the study was to construct specific magnetic resonance imaging (MRI)/optical dual-modality molecular probe. Tumor-bearing animal models were established. MRI/optical dual-modality molecular probe was construed by coupling polyethylene glycol (PEG)-modified nano-Fe 3 O 4 with specific targeted cyclopeptide GX1 and near-infrared fluorescent dyes Cy5.5. MRI/optical imaging effects of the probe were observed and the feasibility of in vivo double-modality imaging was discussed. It was found that, the double-modality probe was of high stability; tumor signal of the experimental group tended to be weak after injection of the probe, but rose to a level which was close to the previous level after 18 h (p > 0.05). We successively completed the construction of an ideal MRI/optical dual-modality molecular probe. MRI/optical dual-modality molecular probe which can selectively gather in gastric cancer is expected to be a novel probe used for diagnosing gastric cancer in the early stage.

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.

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.

A meta-classifier for detecting prostate cancer by quantitative integration of in vivo magnetic resonance spectroscopy and magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Tiwari, Pallavi; Rosen, Mark; Madabhushi, Anant

2008-03-01

Recently, in vivo Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) have emerged as promising new modalities to aid in prostate cancer (CaP) detection. MRI provides anatomic and structural information of the prostate while MRS provides functional data pertaining to biochemical concentrations of metabolites such as creatine, choline and citrate. We have previously presented a hierarchical clustering scheme for CaP detection on in vivo prostate MRS and have recently developed a computer-aided method for CaP detection on in vivo prostate MRI. In this paper we present a novel scheme to develop a meta-classifier to detect CaP in vivo via quantitative integration of multimodal prostate MRS and MRI by use of non-linear dimensionality reduction (NLDR) methods including spectral clustering and locally linear embedding (LLE). Quantitative integration of multimodal image data (MRI and PET) involves the concatenation of image intensities following image registration. However multimodal data integration is non-trivial when the individual modalities include spectral and image intensity data. We propose a data combination solution wherein we project the feature spaces (image intensities and spectral data) associated with each of the modalities into a lower dimensional embedding space via NLDR. NLDR methods preserve the relationships between the objects in the original high dimensional space when projecting them into the reduced low dimensional space. Since the original spectral and image intensity data are divorced from their original physical meaning in the reduced dimensional space, data at the same spatial location can be integrated by concatenating the respective embedding vectors. Unsupervised consensus clustering is then used to partition objects into different classes in the combined MRS and MRI embedding space. Quantitative results of our multimodal computer-aided diagnosis scheme on 16 sets of patient data obtained from the ACRIN trial, for which

Imaging of congenital heart disease in adults: choice of modalities.

PubMed

Orwat, Stefan; Diller, Gerhard-Paul; Baumgartner, Helmut

2014-01-01

Major advances in noninvasive imaging of adult congenital heart disease have been accomplished. These tools play now a key role in comprehensive diagnostic work-up, decision for intervention, evaluation for the suitability of specific therapeutic options, monitoring of interventions and regular follow-up. Besides echocardiography, magnetic resonance (CMR) and computed tomography (CT) have gained particular importance. The choice of imaging modality has thus become a critical issue. This review summarizes strengths and limitations of the different imaging modalities and how they may be used in a complementary fashion. Echocardiography obviously remains the workhorse of imaging routinely used in all patients. However, in complex disease and after surgery echocardiography alone frequently remains insufficient. CMR is particularly useful in this setting and allows reproducible and accurate quantification of ventricular function and comprehensive assessment of cardiac anatomy, aorta, pulmonary arteries and venous return including complex flow measurements. CT is preferred when CMR is contraindicated, when superior spatial resolution is required or when "metallic" artefacts limit CMR imaging. In conclusion, the use of currently available imaging modalities in adult congenital heart disease needs to be complementary. Echocardiography remains the basis tool, CMR and CT should be added considering specific open questions and the ability to answer them, availability and economic issues.

FAIR exempting separate T (1) measurement (FAIREST): a novel technique for online quantitative perfusion imaging and multi-contrast fMRI.

PubMed

Lai, S; Wang, J; Jahng, G H

2001-01-01

A new pulse sequence, dubbed FAIR exempting separate T(1) measurement (FAIREST) in which a slice-selective saturation recovery acquisition is added in addition to the standard FAIR (flow-sensitive alternating inversion recovery) scheme, was developed for quantitative perfusion imaging and multi-contrast fMRI. The technique allows for clean separation between and thus simultaneous assessment of BOLD and perfusion effects, whereas quantitative cerebral blood flow (CBF) and tissue T(1) values are monitored online. Online CBF maps were obtained using the FAIREST technique and the measured CBF values were consistent with the off-line CBF maps obtained from using the FAIR technique in combination with a separate sequence for T(1) measurement. Finger tapping activation studies were carried out to demonstrate the applicability of the FAIREST technique in a typical fMRI setting for multi-contrast fMRI. The relative CBF and BOLD changes induced by finger-tapping were 75.1 +/- 18.3 and 1.8 +/- 0.4%, respectively, and the relative oxygen consumption rate change was 2.5 +/- 7.7%. The results from correlation of the T(1) maps with the activation images on a pixel-by-pixel basis show that the mean T(1) value of the CBF activation pixels is close to the T(1) of gray matter while the mean T(1) value of the BOLD activation pixels is close to the T(1) range of blood and cerebrospinal fluid. Copyright 2001 John Wiley & Sons, Ltd.

SU-D-210-03: Limited-View Multi-Source Quantitative Photoacoustic Tomography

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

Feng, J; Gao, H

2015-06-15

Purpose: This work is to investigate a novel limited-view multi-source acquisition scheme for the direct and simultaneous reconstruction of optical coefficients in quantitative photoacoustic tomography (QPAT), which has potentially improved signal-to-noise ratio and reduced data acquisition time. Methods: Conventional QPAT is often considered in two steps: first to reconstruct the initial acoustic pressure from the full-view ultrasonic data after each optical illumination, and then to quantitatively reconstruct optical coefficients (e.g., absorption and scattering coefficients) from the initial acoustic pressure, using multi-source or multi-wavelength scheme.Based on a novel limited-view multi-source scheme here, We have to consider the direct reconstruction of opticalmore » coefficients from the ultrasonic data, since the initial acoustic pressure can no longer be reconstructed as an intermediate variable due to the incomplete acoustic data in the proposed limited-view scheme. In this work, based on a coupled photo-acoustic forward model combining diffusion approximation and wave equation, we develop a limited-memory Quasi-Newton method (LBFGS) for image reconstruction that utilizes the adjoint forward problem for fast computation of gradients. Furthermore, the tensor framelet sparsity is utilized to improve the image reconstruction which is solved by Alternative Direction Method of Multipliers (ADMM). Results: The simulation was performed on a modified Shepp-Logan phantom to validate the feasibility of the proposed limited-view scheme and its corresponding image reconstruction algorithms. Conclusion: A limited-view multi-source QPAT scheme is proposed, i.e., the partial-view acoustic data acquisition accompanying each optical illumination, and then the simultaneous rotations of both optical sources and ultrasonic detectors for next optical illumination. Moreover, LBFGS and ADMM algorithms are developed for the direct reconstruction of optical coefficients from

Multi-modal myocontrol: Testing combined force- and electromyography.

PubMed

Nowak, Markus; Eiband, Thomas; Castellini, Claudio

2017-07-01

Myocontrol, that is control of prostheses using bodily signals, has proved in the decades to be a surprisingly hard problem for the scientific community of assistive and rehabilitation robotics. In particular, traditional surface electromyography (sEMG) seems to be no longer enough to guarantee dexterity (i.e., control over several degrees of freedom) and, most importantly, reliability. Multi-modal myocontrol is concerned with the idea of using novel signal gathering techniques as a replacement of, or alongside, sEMG, to provide high-density and diverse signals to improve dexterity and make the control more reliable. In this paper we present an offline and online assessment of multi-modal sEMG and force myography (FMG) targeted at hand and wrist myocontrol. A total number of twenty sEMG and FMG sensors were used simultaneously, in several combined configurations, to predict opening/closing of the hand and activation of two degrees of freedom of the wrist of ten intact subjects. The analysis was targeted at determining the optimal sensor combination and control parameters; the experimental results indicate that sEMG sensors alone perform worst, yielding a nRMSE of 9.1%, while mixing FMG and sEMG or using FMG only reduces the nRMSE to 5.2-6.6%. To validate these results, we engaged the subject with median performance in an online goal-reaching task. Analysis of this further experiment reveals that the online behaviour is similar to the offline one.

Towards quantitative magnetic particle imaging: A comparison with magnetic particle spectroscopy

NASA Astrophysics Data System (ADS)

Paysen, Hendrik; Wells, James; Kosch, Olaf; Steinhoff, Uwe; Trahms, Lutz; Schaeffter, Tobias; Wiekhorst, Frank

2018-05-01

Magnetic Particle Imaging (MPI) is a quantitative imaging modality with promising features for several biomedical applications. Here, we study quantitatively the raw data obtained during MPI measurements. We present a method for the calibration of the MPI scanner output using measurements from a magnetic particle spectrometer (MPS) to yield data in units of magnetic moments. The calibration technique is validated in a simplified MPI mode with a 1D excitation field. Using the calibrated results from MPS and MPI, we determine and compare the detection limits for each system. The detection limits were found to be 5.10-12 Am2 for MPS and 3.6.10-10 Am2 for MPI. Finally, the quantitative information contained in a standard MPI measurement with a 3D excitation is analyzed and compared to the previous results, showing a decrease in signal amplitudes of the odd harmonics related to the case of 1D excitation. We propose physical explanations for all acquired results; and discuss the possible benefits for the improvement of MPI technology.

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.

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.

[Study of Cervical Exfoliated Cell's DNA Quantitative Analysis Based on Multi-Spectral Imaging Technology].

PubMed

Wu, Zheng; Zeng, Li-bo; Wu, Qiong-shui

2016-02-01

The conventional cervical cancer screening methods mainly include TBS (the bethesda system) classification method and cellular DNA quantitative analysis, however, by using multiple staining method in one cell slide, which is staining the cytoplasm with Papanicolaou reagent and the nucleus with Feulgen reagent, the study of achieving both two methods in the cervical cancer screening at the same time is still blank. Because the difficulty of this multiple staining method is that the absorbance of the non-DNA material may interfere with the absorbance of DNA, so that this paper has set up a multi-spectral imaging system, and established an absorbance unmixing model by using multiple linear regression method based on absorbance's linear superposition character, and successfully stripped out the absorbance of DNA to run the DNA quantitative analysis, and achieved the perfect combination of those two kinds of conventional screening method. Through a series of experiment we have proved that between the absorbance of DNA which is calculated by the absorbance unmixxing model and the absorbance of DNA which is measured there is no significant difference in statistics when the test level is 1%, also the result of actual application has shown that there is no intersection between the confidence interval of the DNA index of the tetraploid cells which are screened by using this paper's analysis method when the confidence level is 99% and the DNA index's judging interval of cancer cells, so that the accuracy and feasibility of the quantitative DNA analysis with multiple staining method expounded by this paper have been verified, therefore this analytical method has a broad application prospect and considerable market potential in early diagnosis of cervical cancer and other cancers.

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

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.

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.

Carbon-11 radiolabeling of iron-oxide nanoparticles for dual-modality PET/MR imaging

NASA Astrophysics Data System (ADS)

Sharma, Ramesh; Xu, Youwen; Kim, Sung Won; Schueller, Michael J.; Alexoff, David; Smith, S. David; Wang, Wei; Schlyer, David

2013-07-01

Dual-modality imaging, using Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) simultaneously, is a powerful tool to gain valuable information correlating structure with function in biomedicine. The advantage of this dual approach is that the strengths of one modality can balance the weaknesses of the other. However, success of this technique requires developing imaging probes suitable for both. Here, we report on the development of a nanoparticle labeling procedure via covalent bonding with carbon-11 PET isotope. Carbon-11 in the form of [11C]methyl iodide was used as a methylation agent to react with carboxylic acid (-COOH) and amine (-NH2) functional groups of ligands bound to the nanoparticles (NPs). The surface coating ligands present on superparamagnetic iron-oxide nanoparticles (SPIO NPs) were radiolabeled to achieve dual-modality PET/MR imaging capabilities. The proof-of-concept dual-modality PET/MR imaging using the radiolabeled SPIO NPs was demonstrated in an in vivo experiment.Dual-modality imaging, using Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) simultaneously, is a powerful tool to gain valuable information correlating structure with function in biomedicine. The advantage of this dual approach is that the strengths of one modality can balance the weaknesses of the other. However, success of this technique requires developing imaging probes suitable for both. Here, we report on the development of a nanoparticle labeling procedure via covalent bonding with carbon-11 PET isotope. Carbon-11 in the form of [11C]methyl iodide was used as a methylation agent to react with carboxylic acid (-COOH) and amine (-NH2) functional groups of ligands bound to the nanoparticles (NPs). The surface coating ligands present on superparamagnetic iron-oxide nanoparticles (SPIO NPs) were radiolabeled to achieve dual-modality PET/MR imaging capabilities. The proof-of-concept dual-modality PET/MR imaging using the radiolabeled

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.

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 imaging as cancer biomarker

NASA Astrophysics Data System (ADS)

Mankoff, David A.

2015-03-01

The ability to assay tumor biologic features and the impact of drugs on tumor biology is fundamental to drug development. Advances in our ability to measure genomics, gene expression, protein expression, and cellular biology have led to a host of new targets for anticancer drug therapy. In translating new drugs into clinical trials and clinical practice, these same assays serve to identify patients most likely to benefit from specific anticancer treatments. As cancer therapy becomes more individualized and targeted, there is an increasing need to characterize tumors and identify therapeutic targets to select therapy most likely to be successful in treating the individual patient's cancer. Thus far assays to identify cancer therapeutic targets or anticancer drug pharmacodynamics have been based upon in vitro assay of tissue or blood samples. Advances in molecular imaging, particularly PET, have led to the ability to perform quantitative non-invasive molecular assays. Imaging has traditionally relied on structural and anatomic features to detect cancer and determine its extent. More recently, imaging has expanded to include the ability to image regional biochemistry and molecular biology, often termed molecular imaging. Molecular imaging can be considered an in vivo assay technique, capable of measuring regional tumor biology without perturbing it. This makes molecular imaging a unique tool for cancer drug development, complementary to traditional assay methods, and a potentially powerful method for guiding targeted therapy in clinical trials and clinical practice. The ability to quantify, in absolute measures, regional in vivo biologic parameters strongly supports the use of molecular imaging as a tool to guide therapy. This review summarizes current and future applications of quantitative molecular imaging as a biomarker for cancer therapy, including the use of imaging to (1) identify patients whose tumors express a specific therapeutic target; (2) determine

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

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.

Graduate Student Perceptions of Multi-Modal Tablet Use in Academic Environments

ERIC Educational Resources Information Center

Bryant, Ezzard C., Jr.

2016-01-01

The purpose of this study was to explore graduate student perceptions of use and the ease of use of multi-modal tablets to access electronic course materials, and the perceived differences based on students' gender, age, college of enrollment, and previous experience. This study used the Unified Theory of Acceptance and Use of Technology to…

Identification of multi-modal plasma responses to applied magnetic perturbations using the plasma reluctance

DOE PAGES

Logan, Nikolas C.; Paz-Soldan, Carlos; Park, Jong-Kyu; ...

2016-05-03

Using the plasma reluctance, the Ideal Perturbed Equilibrium Code is able to efficiently identify the structure of multi-modal magnetic plasma response measurements and the corresponding impact on plasma performance in the DIII-D tokamak. Recent experiments demonstrated that multiple kink modes of comparable amplitudes can be driven by applied nonaxisymmetric fields with toroidal mode number n = 2. This multi-modal response is in good agreement with ideal magnetohydrodynamic models, but detailed decompositions presented here show that the mode structures are not fully described by either the least stable modes or the resonant plasma response. This paper identifies the measured response fieldsmore » as the first eigenmodes of the plasma reluctance, enabling clear diagnosis of the plasma modes and their impact on performance from external sensors. The reluctance shows, for example, how very stable modes compose a significant portion of the multi-modal plasma response field and that these stable modes drive significant resonant current. Finally, this work is an overview of the first experimental applications using the reluctance to interpret the measured response and relate it to multifaceted physics, aimed towards providing the foundation of understanding needed to optimize nonaxisymmetric fields for independent control of stability and transport.« less

Assessment of global longitudinal strain using standardized myocardial deformation imaging: a modality independent software approach.

PubMed

Riffel, Johannes H; Keller, Marius G P; Aurich, Matthias; Sander, Yannick; Andre, Florian; Giusca, Sorin; Aus dem Siepen, Fabian; Seitz, Sebastian; Galuschky, Christian; Korosoglou, Grigorios; Mereles, Derliz; Katus, Hugo A; Buss, Sebastian J

2015-07-01

Myocardial deformation measurement is superior to left ventricular ejection fraction in identifying early changes in myocardial contractility and prediction of cardiovascular outcome. The lack of standardization hinders its clinical implementation. The aim of the study is to investigate a novel standardized deformation imaging approach based on the feature tracking algorithm for the assessment of global longitudinal (GLS) and global circumferential strain (GCS) in echocardiography and cardiac magnetic resonance imaging (CMR). 70 subjects undergoing CMR were consecutively investigated with echocardiography within a median time of 30 min. GLS and GCS were analyzed with a post-processing software incorporating the same standardized algorithm for both modalities. Global strain was defined as the relative shortening of the whole endocardial contour length and calculated according to the strain formula. Mean GLS values were -16.2 ± 5.3 and -17.3 ± 5.3 % for echocardiography and CMR, respectively. GLS did not differ significantly between the two imaging modalities, which showed strong correlation (r = 0.86), a small bias (-1.1 %) and narrow 95 % limits of agreement (LOA ± 5.4 %). Mean GCS values were -17.9 ± 6.3 and -24.4 ± 7.8 % for echocardiography and CMR, respectively. GCS was significantly underestimated by echocardiography (p < 0.001). A weaker correlation (r = 0.73), a higher bias (-6.5 %) and wider LOA (± 10.5 %) were observed for GCS. GLS showed a strong correlation (r = 0.92) when image quality was good, while correlation dropped to r = 0.82 with poor acoustic windows in echocardiography. GCS assessment revealed only a strong correlation (r = 0.87) when echocardiographic image quality was good. No significant differences for GLS between two different echocardiographic vendors could be detected. Quantitative assessment of GLS using a standardized software algorithm allows the direct comparison of values acquired irrespective of the imaging modality. GLS may

Accuracy of Diagnostic Imaging Modalities for Classifying Pediatric Eyes as Papilledema Versus Pseudopapilledema.

PubMed

Chang, Melinda Y; Velez, Federico G; Demer, Joseph L; Bonelli, Laura; Quiros, Peter A; Arnold, Anthony C; Sadun, Alfredo A; Pineles, Stacy L

2017-12-01

To identify the most accurate diagnostic imaging modality for classifying pediatric eyes as papilledema (PE) or pseudopapilledema (PPE). Prospective observational study. Nineteen children between the ages of 5 and 18 years were recruited. Five children (10 eyes) with PE, 11 children (19 eyes) with PPE owing to suspected buried optic disc drusen (ODD), and 3 children (6 eyes) with PPE owing to superficial ODD were included. All subjects underwent imaging with B-scan ultrasonography, fundus photography, autofluorescence, fluorescein angiography (FA), optical coherence tomography (OCT) of the retinal nerve fiber layer (RNFL), and volumetric OCT scans through the optic nerve head with standard spectral-domain (SD OCT) and enhanced depth imaging (EDI OCT) settings. Images were read by 3 masked neuro-ophthalmologists, and the final image interpretation was based on 2 of 3 reads. Image interpretations were compared with clinical diagnosis to calculate accuracy and misinterpretation rates of each imaging modality. Accuracy of each imaging technique for classifying eyes as PE or PPE, and misinterpretation rates of each imaging modality for PE and PPE. Fluorescein angiography had the highest accuracy (97%, 34 of 35 eyes, 95% confidence interval 92%-100%) for classifying an eye as PE or PPE. FA of eyes with PE showed leakage of the optic nerve, whereas eyes with suspected buried ODD demonstrated no hyperfluorescence, and eyes with superficial ODD showed nodular staining. Other modalities had substantial likelihood (30%-70%) of misinterpretation of PE as PPE. The best imaging technique for correctly classifying pediatric eyes as PPE or PE is FA. Other imaging modalities, if used in isolation, are more likely to lead to misinterpretation of PE as PPE, which could potentially result in failure to identify a life-threatening disorder causing elevated intracranial pressure and papilledema. Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights

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.

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.

MO-B-BRC-00: Prostate HDR Treatment Planning - Considering Different Imaging Modalities

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

NONE

2016-06-15

Brachytherapy has proven to be an effective treatment option for prostate cancer. Initially, prostate brachytherapy was delivered through permanently implanted low dose rate (LDR) radioactive sources; however, high dose rate (HDR) temporary brachytherapy for prostate cancer is gaining popularity. Needle insertion during prostate brachytherapy is most commonly performed under ultrasound (U/S) guidance; however, treatment planning may be performed utilizing several imaging modalities either in an intra- or post-operative setting. During intra-operative prostate HDR, the needles are imaged during implantation, and planning may be performed in real time. At present, the most common imaging modality utilized for intra-operative prostate HDR ismore » U/S. Alternatively, in the post-operative setting, following needle implantation, patients may be simulated with computed tomography (CT) or magnetic resonance imaging (MRI). Each imaging modality and workflow provides its share of benefits and limitations. Prostate HDR has been adopted in a number of cancer centers across the nation. In this educational session, we will explore the role of U/S, CT, and MRI in HDR prostate brachytherapy. Example workflows and operational details will be shared, and we will discuss how to establish a prostate HDR program in a clinical setting. Learning Objectives: Review prostate HDR techniques based on the imaging modality Discuss the challenges and pitfalls introduced by the three imagebased options for prostate HDR brachytherapy Review the QA process and learn about the development of clinical workflows for these imaging options at different institutions.« less

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

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.

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 ...

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.

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

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.

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

Rapid Multi-Tracer PET Tumor Imaging With F-FDG and Secondary Shorter-Lived Tracers.

PubMed

Black, Noel F; McJames, Scott; Kadrmas, Dan J

2009-10-01

Rapid multi-tracer PET, where two to three PET tracers are rapidly scanned with staggered injections, can recover certain imaging measures for each tracer based on differences in tracer kinetics and decay. We previously showed that single-tracer imaging measures can be recovered to a certain extent from rapid dual-tracer (62)Cu - PTSM (blood flow) + (62)Cu - ATSM (hypoxia) tumor imaging. In this work, the feasibility of rapidly imaging (18)F-FDG plus one or two of these shorter-lived secondary tracers was evaluated in the same tumor model. Dynamic PET imaging was performed in four dogs with pre-existing tumors, and the raw scan data was combined to emulate 60 minute long dual- and triple-tracer scans, using the single-tracer scans as gold standards. The multi-tracer data were processed for static (SUV) and kinetic (K(1), K(net)) endpoints for each tracer, followed by linear regression analysis of multi-tracer versus single-tracer results. Static and quantitative dynamic imaging measures of FDG were both accurately recovered from the multi-tracer scans, closely matching the single-tracer FDG standards (R > 0.99). Quantitative blood flow information, as measured by PTSM K(1) and SUV, was also accurately recovered from the multi-tracer scans (R = 0.97). Recovery of ATSM kinetic parameters proved more difficult, though the ATSM SUV was reasonably well recovered (R = 0.92). We conclude that certain additional information from one to two shorter-lived PET tracers may be measured in a rapid multi-tracer scan alongside FDG without compromising the assessment of glucose metabolism. Such additional and complementary information has the potential to improve tumor characterization in vivo, warranting further investigation of rapid multi-tracer techniques.

Laser Illumination Modality of Photoacoustic Imaging Technique for Prostate Cancer

NASA Astrophysics Data System (ADS)

Peng, Dong-qing; Peng, Yuan-yuan; Guo, Jian; Li, Hui

2016-02-01

Photoacoustic imaging (PAI) has recently emerged as a promising imaging technique for prostate cancer. But there was still a lot of challenge in the PAI for prostate cancer detection, such as laser illumination modality. Knowledge of absorbed light distribution in prostate tissue was essential since the distribution characteristic of absorbed light energy would influence the imaging depth and range of PAI. In order to make a comparison of different laser illumination modality of photoacoustic imaging technique for prostate cancer, optical model of human prostate was established and combined with Monte Carlo simulation method to calculate the light absorption distribution in the prostate tissue. Characteristic of light absorption distribution of transurethral and trans-rectal illumination case, and of tumor at different location was compared with each other.The relevant conclusions would be significant for optimizing the light illumination in a PAI system for prostate cancer detection.

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

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.

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

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.

Dual-modality brain PET-CT image segmentation based on adaptive use of functional and anatomical information.

PubMed

Xia, Yong; Eberl, Stefan; Wen, Lingfeng; Fulham, Michael; Feng, David Dagan

2012-01-01

Dual medical imaging modalities, such as PET-CT, are now a routine component of clinical practice. Medical image segmentation methods, however, have generally only been applied to single modality images. In this paper, we propose the dual-modality image segmentation model to segment brain PET-CT images into gray matter, white matter and cerebrospinal fluid. This model converts PET-CT image segmentation into an optimization process controlled simultaneously by PET and CT voxel values and spatial constraints. It is innovative in the creation and application of the modality discriminatory power (MDP) coefficient as a weighting scheme to adaptively combine the functional (PET) and anatomical (CT) information on a voxel-by-voxel basis. Our approach relies upon allowing the modality with higher discriminatory power to play a more important role in the segmentation process. We compared the proposed approach to three other image segmentation strategies, including PET-only based segmentation, combination of the results of independent PET image segmentation and CT image segmentation, and simultaneous segmentation of joint PET and CT images without an adaptive weighting scheme. Our results in 21 clinical studies showed that our approach provides the most accurate and reliable segmentation for brain PET-CT images. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

Gold nanoclusters as contrast agents for fluorescent and X-ray dual-modality imaging.

PubMed

Zhang, Aili; Tu, Yu; Qin, Songbing; Li, Yan; Zhou, Juying; Chen, Na; Lu, Qiang; Zhang, Bingbo

2012-04-15

Multimodal imaging technique is an alternative approach to improve sensitivity of early cancer diagnosis. In this study, highly fluorescent and strong X-ray absorption coefficient gold nanoclusters (Au NCs) are synthesized as dual-modality imaging contrast agents (CAs) for fluorescent and X-ray dual-modality imaging. The experimental results show that the as-prepared Au NCs are well constructed with ultrasmall sizes, reliable fluorescent emission, high computed tomography (CT) value and fine biocompatibility. In vivo imaging results indicate that the obtained Au NCs are capable of fluorescent and X-ray enhanced imaging. Copyright © 2012 Elsevier Inc. All rights reserved.

General solution for quantitative dark-field contrast imaging with grating interferometers

NASA Astrophysics Data System (ADS)

Strobl, M.

2014-11-01

Grating interferometer based imaging with X-rays and neutrons has proven to hold huge potential for applications in key research fields conveying biology and medicine as well as engineering and magnetism, respectively. The thereby amenable dark-field imaging modality implied the promise to access structural information beyond reach of direct spatial resolution. However, only here a yet missing approach is reported that finally allows exploiting this outstanding potential for non-destructive materials characterizations. It enables to obtain quantitative structural small angle scattering information combined with up to 3-dimensional spatial image resolution even at lab based x-ray or at neutron sources. The implied two orders of magnitude efficiency gain as compared to currently available techniques in this regime paves the way for unprecedented structural investigations of complex sample systems of interest for material science in a vast range of fields.

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.

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.

Isotropic differential phase contrast microscopy for quantitative phase bio-imaging.

PubMed

Chen, Hsi-Hsun; Lin, Yu-Zi; Luo, Yuan

2018-05-16

Quantitative phase imaging (QPI) has been investigated to retrieve optical phase information of an object and applied to biological microscopy and related medical studies. In recent examples, differential phase contrast (DPC) microscopy can recover phase image of thin sample under multi-axis intensity measurements in wide-field scheme. Unlike conventional DPC, based on theoretical approach under partially coherent condition, we propose a new method to achieve isotropic differential phase contrast (iDPC) with high accuracy and stability for phase recovery in simple and high-speed fashion. The iDPC is simply implemented with a partially coherent microscopy and a programmable thin-film transistor (TFT) shield to digitally modulate structured illumination patterns for QPI. In this article, simulation results show consistency of our theoretical approach for iDPC under partial coherence. In addition, we further demonstrate experiments of quantitative phase images of a standard micro-lens array, as well as label-free live human cell samples. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Assessing agreement between preclinical magnetic resonance imaging and histology: An evaluation of their image qualities and quantitative results

PubMed Central

Elschner, Cindy; Korn, Paula; Hauptstock, Maria; Schulz, Matthias C.; Range, Ursula; Jünger, Diana; Scheler, Ulrich

2017-01-01

One consequence of demographic change is the increasing demand for biocompatible materials for use in implants and prostheses. This is accompanied by a growing number of experimental animals because the interactions between new biomaterials and its host tissue have to be investigated. To evaluate novel materials and engineered tissues the use of non-destructive imaging modalities have been identified as a strategic priority. This provides the opportunity for studying interactions repeatedly with individual animals, along with the advantages of reduced biological variability and decreased number of laboratory animals. However, histological techniques are still the golden standard in preclinical biomaterial research. The present article demonstrates a detailed method comparison between histology and magnetic resonance imaging. This includes the presentation of their image qualities as well as the detailed statistical analysis for assessing agreement between quantitative measures. Exemplarily, the bony ingrowth of tissue engineered bone substitutes for treatment of a cleft-like maxillary bone defect has been evaluated. By using a graphical concordance analysis the mean difference between MRI results and histomorphometrical measures has been examined. The analysis revealed a slightly but significant bias in the case of the bone volume (biasHisto−MRI:Bone volume=2.40 %, p<0.005) and a clearly significant deviation for the remaining defect width (biasHisto−MRI:Defect width=−6.73 %, p≪0.005). But the study although showed a considerable effect of the analyzed section position to the quantitative result. It could be proven, that the bias of the data sets was less originated due to the imaging modalities, but mainly on the evaluation of different slice positions. The article demonstrated that method comparisons not always need the use of an independent animal study, additionally. PMID:28666026

LapTrain: multi-modality training curriculum for laparoscopic cholecystectomy-results of a randomized controlled trial.

PubMed

Kowalewski, K F; Garrow, C R; Proctor, T; Preukschas, A A; Friedrich, M; Müller, P C; Kenngott, H G; Fischer, L; Müller-Stich, B P; Nickel, F

2018-02-12

Multiple training modalities for laparoscopy have different advantages, but little research has been conducted on the benefit of a training program that includes multiple different training methods compared to one method only. This study aimed to evaluate benefits of a combined multi-modality training program for surgical residents. Laparoscopic cholecystectomy (LC) was performed on a porcine liver as the pre-test. Randomization was stratified for experience to the multi-modality Training group (12 h of training on Virtual Reality (VR) and box trainer) or Control group (no training). The post-test consisted of a VR LC and porcine LC. Performance was rated with the Global Operative Assessment of Laparoscopic Skills (GOALS) score by blinded experts. Training (n = 33) and Control (n = 31) were similar in the pre-test (GOALS: 13.7 ± 3.4 vs. 14.7 ± 2.6; p = 0.198; operation time 57.0 ± 18.1 vs. 63.4 ± 17.5 min; p = 0.191). In the post-test porcine LC, Training had improved GOALS scores (+ 2.84 ± 2.85 points, p < 0.001), while Control did not (+ 0.55 ± 2.34 points, p = 0.154). Operation time in the post-test was shorter for Training vs. Control (40.0 ± 17.0 vs. 55.0 ± 22.2 min; p = 0.012). Junior residents improved GOALS scores to the level of senior residents (pre-test: 13.7 ± 2.7 vs. 18.3 ± 2.9; p = 0.010; post-test: 15.5 ± 3.4 vs. 18.8 ± 3.8; p = 0.120) but senior residents remained faster (50.1 ± 20.6 vs. 25.0 ± 1.9 min; p < 0.001). No differences were found between groups on the post-test VR trainer. Structured multi-modality training is beneficial for novices to improve basics and overcome the initial learning curve in laparoscopy as well as to decrease operation time for LCs in different stages of experience. Future studies should evaluate multi-modality training in comparison with single modalities. German Clinical Trials Register DRKS00011040.

The Art of Multi-Image.

ERIC Educational Resources Information Center

Gordon, Roger L., Ed.

This guide to multi-image program production for practitioners describes the process from the beginning stages through final presentation, examines historical perspectives, theory, and research in multi-image, and provides examples of successful utilization. Ten chapters focus on the following topics: (1) definition of multi-image field and…

A multi-focus image fusion method via region mosaicking on Laplacian pyramids

PubMed Central

Kou, Liang; Zhang, Liguo; Sun, Jianguo; Han, Qilong; Jin, Zilong

2018-01-01

In this paper, a method named Region Mosaicking on Laplacian Pyramids (RMLP) is proposed to fuse multi-focus images that is captured by microscope. First, the Sum-Modified-Laplacian is applied to measure the focus of multi-focus images. Then the density-based region growing algorithm is utilized to segment the focused region mask of each image. Finally, the mask is decomposed into a mask pyramid to supervise region mosaicking on a Laplacian pyramid. The region level pyramid keeps more original information than the pixel level. The experiment results show that RMLP has best performance in quantitative comparison with other methods. In addition, RMLP is insensitive to noise and can reduces the color distortion of the fused images on two datasets. PMID:29771912

Multi-temporal and multi-source remote sensing image classification by nonlinear relative normalization

NASA Astrophysics Data System (ADS)

Tuia, Devis; Marcos, Diego; Camps-Valls, Gustau

2016-10-01

Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one must be able to cope with datasets that are not co-registered, acquired under different illumination and atmospheric conditions, by different sensors, and with scarce ground references. Traditionally, methods based on histogram matching have been used. However, they fail when densities have very different shapes or when there is no corresponding band to be matched between the images. An alternative builds upon manifold alignment. Manifold alignment performs a multidimensional relative normalization of the data prior to product generation that can cope with data of different dimensionality (e.g. different number of bands) and possibly unpaired examples. Aligning data distributions is an appealing strategy, since it allows to provide data spaces that are more similar to each other, regardless of the subsequent use of the transformed data. In this paper, we study a methodology that aligns data from different domains in a nonlinear way through kernelization. We introduce the Kernel Manifold Alignment (KEMA) method, which provides a flexible and discriminative projection map, exploits only a few labeled samples (or semantic ties) in each domain, and reduces to solving a generalized eigenvalue problem. We successfully test KEMA in multi-temporal and multi-source very high resolution classification tasks, as well as on the task of making a model invariant to shadowing for hyperspectral imaging.

Monte Carlo simulations of medical imaging modalities

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

Estes, G.P.

Because continuous-energy Monte Carlo radiation transport calculations can be nearly exact simulations of physical reality (within data limitations, geometric approximations, transport algorithms, etc.), it follows that one should be able to closely approximate the results of many experiments from first-principles computations. This line of reasoning has led to various MCNP studies that involve simulations of medical imaging modalities and other visualization methods such as radiography, Anger camera, computerized tomography (CT) scans, and SABRINA particle track visualization. It is the intent of this paper to summarize some of these imaging simulations in the hope of stimulating further work, especially as computermore » power increases. Improved interpretation and prediction of medical images should ultimately lead to enhanced medical treatments. It is also reasonable to assume that such computations could be used to design new or more effective imaging instruments.« less

Fusion of multi-tracer PET images for dose painting.

PubMed

Lelandais, Benoît; Ruan, Su; Denœux, Thierry; Vera, Pierre; Gardin, Isabelle

2014-10-01

PET imaging with FluoroDesoxyGlucose (FDG) tracer is clinically used for the definition of Biological Target Volumes (BTVs) for radiotherapy. Recently, new tracers, such as FLuoroThymidine (FLT) or FluoroMisonidazol (FMiso), have been proposed. They provide complementary information for the definition of BTVs. Our work is to fuse multi-tracer PET images to obtain a good BTV definition and to help the radiation oncologist in dose painting. Due to the noise and the partial volume effect leading, respectively, to the presence of uncertainty and imprecision in PET images, the segmentation and the fusion of PET images is difficult. In this paper, a framework based on Belief Function Theory (BFT) is proposed for the segmentation of BTV from multi-tracer PET images. The first step is based on an extension of the Evidential C-Means (ECM) algorithm, taking advantage of neighboring voxels for dealing with uncertainty and imprecision in each mono-tracer PET image. Then, imprecision and uncertainty are, respectively, reduced using prior knowledge related to defects in the acquisition system and neighborhood information. Finally, a multi-tracer PET image fusion is performed. The results are represented by a set of parametric maps that provide important information for dose painting. The performances are evaluated on PET phantoms and patient data with lung cancer. Quantitative results show good performance of our method compared with other methods. Copyright © 2014 Elsevier B.V. All rights reserved.

Rapid Multi-Tracer PET Tumor Imaging With 18F-FDG and Secondary Shorter-Lived Tracers

PubMed Central

Black, Noel F.; McJames, Scott; Kadrmas, Dan J.

2009-01-01

Rapid multi-tracer PET, where two to three PET tracers are rapidly scanned with staggered injections, can recover certain imaging measures for each tracer based on differences in tracer kinetics and decay. We previously showed that single-tracer imaging measures can be recovered to a certain extent from rapid dual-tracer 62Cu – PTSM (blood flow) + 62Cu — ATSM (hypoxia) tumor imaging. In this work, the feasibility of rapidly imaging 18F-FDG plus one or two of these shorter-lived secondary tracers was evaluated in the same tumor model. Dynamic PET imaging was performed in four dogs with pre-existing tumors, and the raw scan data was combined to emulate 60 minute long dual- and triple-tracer scans, using the single-tracer scans as gold standards. The multi-tracer data were processed for static (SUV) and kinetic (K1, Knet) endpoints for each tracer, followed by linear regression analysis of multi-tracer versus single-tracer results. Static and quantitative dynamic imaging measures of FDG were both accurately recovered from the multi-tracer scans, closely matching the single-tracer FDG standards (R > 0.99). Quantitative blood flow information, as measured by PTSM K1 and SUV, was also accurately recovered from the multi-tracer scans (R = 0.97). Recovery of ATSM kinetic parameters proved more difficult, though the ATSM SUV was reasonably well recovered (R = 0.92). We conclude that certain additional information from one to two shorter-lived PET tracers may be measured in a rapid multi-tracer scan alongside FDG without compromising the assessment of glucose metabolism. Such additional and complementary information has the potential to improve tumor characterization in vivo, warranting further investigation of rapid multi-tracer techniques. PMID:20046800

A Multi-modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling.

PubMed

Asif, Umar; Bennamoun, Mohammed; Sohel, Ferdous

2017-08-30

While deep convolutional neural networks have shown a remarkable success in image classification, the problems of inter-class similarities, intra-class variances, the effective combination of multimodal data, and the spatial variability in images of objects remain to be major challenges. To address these problems, this paper proposes a novel framework to learn a discriminative and spatially invariant classification model for object and indoor scene recognition using multimodal RGB-D imagery. This is achieved through three postulates: 1) spatial invariance - this is achieved by combining a spatial transformer network with a deep convolutional neural network to learn features which are invariant to spatial translations, rotations, and scale changes, 2) high discriminative capability - this is achieved by introducing Fisher encoding within the CNN architecture to learn features which have small inter-class similarities and large intra-class compactness, and 3) multimodal hierarchical fusion - this is achieved through the regularization of semantic segmentation to a multi-modal CNN architecture, where class probabilities are estimated at different hierarchical levels (i.e., imageand pixel-levels), and fused into a Conditional Random Field (CRF)- based inference hypothesis, the optimization of which produces consistent class labels in RGB-D images. Extensive experimental evaluations on RGB-D object and scene datasets, and live video streams (acquired from Kinect) show that our framework produces superior object and scene classification results compared to the state-of-the-art methods.

Magnetic Polarization Measurements of the Multi-modal Plasma Response to 3D fields in the EAST Tokamak

DOE PAGES

Logan, Nikolas; Cui, L.; Wang, Hui -Hui; ...

2018-04-30

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n=2 fields in the same plasma for which the n=1 responses are well synchronized.more » Neither the maximum radial nor the maximum poloidal field response to n=2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n=1 and n=2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.« less

Magnetic Polarization Measurements of the Multi-modal Plasma Response to 3D fields in the EAST Tokamak

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

Logan, Nikolas; Cui, L.; Wang, Hui -Hui

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n=2 fields in the same plasma for which the n=1 responses are well synchronized.more » Neither the maximum radial nor the maximum poloidal field response to n=2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n=1 and n=2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.« less

Versatile quantitative phase imaging system applied to high-speed, low noise and multimodal imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Federici, Antoine; Aknoun, Sherazade; Savatier, Julien; Wattellier, Benoit F.

2017-02-01

Quadriwave lateral shearing interferometry (QWLSI) is a well-established quantitative phase imaging (QPI) technique based on the analysis of interference patterns of four diffraction orders by an optical grating set in front of an array detector [1]. As a QPI modality, this is a non-invasive imaging technique which allow to measure the optical path difference (OPD) of semi-transparent samples. We present a system enabling QWLSI with high-performance sCMOS cameras [2] and apply it to perform high-speed imaging, low noise as well as multimodal imaging. This modified QWLSI system contains a versatile optomechanical device which images the optical grating near the detector plane. Such a device is coupled with any kind of camera by varying its magnification. In this paper, we study the use of a sCMOS Zyla5.5 camera from Andor along with our modified QWLSI system. We will present high-speed live cell imaging, up to 200Hz frame rate, in order to follow intracellular fast motions while measuring the quantitative phase information. The structural and density information extracted from the OPD signal is complementary to the specific and localized fluorescence signal [2]. In addition, QPI detects cells even when the fluorophore is not expressed. This is very useful to follow a protein expression with time. The 10 µm spatial pixel resolution of our modified QWLSI associated to the high sensitivity of the Zyla5.5 enabling to perform high quality fluorescence imaging, we have carried out multimodal imaging revealing fine structures cells, like actin filaments, merged with the morphological information of the phase. References [1]. P. Bon, G. Maucort, B. Wattellier, and S. Monneret, "Quadriwave lateral shearing interferometry for quantitative phase microscopy of living cells," Opt. Express, vol. 17, pp. 13080-13094, 2009. [2] P. Bon, S. Lécart, E. Fort and S. Lévêque-Fort, "Fast label-free cytoskeletal network imaging in living mammalian cells," Biophysical journal, 106

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.

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...

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

Multi-modal data fusion using source separation: Two effective models based on ICA and IVA and their properties

PubMed Central

Adali, Tülay; Levin-Schwartz, Yuri; Calhoun, Vince D.

2015-01-01

Fusion of information from multiple sets of data in order to extract a set of features that are most useful and relevant for the given task is inherent to many problems we deal with today. Since, usually, very little is known about the actual interaction among the datasets, it is highly desirable to minimize the underlying assumptions. This has been the main reason for the growing importance of data-driven methods, and in particular of independent component analysis (ICA) as it provides useful decompositions with a simple generative model and using only the assumption of statistical independence. A recent extension of ICA, independent vector analysis (IVA) generalizes ICA to multiple datasets by exploiting the statistical dependence across the datasets, and hence, as we discuss in this paper, provides an attractive solution to fusion of data from multiple datasets along with ICA. In this paper, we focus on two multivariate solutions for multi-modal data fusion that let multiple modalities fully interact for the estimation of underlying features that jointly report on all modalities. One solution is the Joint ICA model that has found wide application in medical imaging, and the second one is the the Transposed IVA model introduced here as a generalization of an approach based on multi-set canonical correlation analysis. In the discussion, we emphasize the role of diversity in the decompositions achieved by these two models, present their properties and implementation details to enable the user make informed decisions on the selection of a model along with its associated parameters. Discussions are supported by simulation results to help highlight the main issues in the implementation of these methods. PMID:26525830

Nonlinear dynamics of magnetically coupled beams for multi-modal vibration energy harvesting

NASA Astrophysics Data System (ADS)

Abed, I.; Kacem, N.; Bouhaddi, N.; Bouazizi, M. L.

2016-04-01

We investigate the nonlinear dynamics of magnetically coupled beams for multi-modal vibration energy harvesting. A multi-physics model for the proposed device is developed taking into account geometric and magnetic nonlinearities. The coupled nonlinear equations of motion are solved using the Galerkin discretization coupled with the harmonic balance method and the asymptotic numerical method. Several numerical simulations have been performed showing that the expected performances of the proposed vibration energy harvester are significantly promising with up to 130 % in term of bandwidth and up to 60 μWcm-3g-2 in term of normalized harvested power.

Cell Motility Dynamics: A Novel Segmentation Algorithm to Quantify Multi-Cellular Bright Field Microscopy Images

PubMed Central

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single

Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.

PubMed

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single

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.

Quantitative breast tissue characterization using grating-based x-ray phase-contrast imaging

NASA Astrophysics Data System (ADS)

Willner, M.; Herzen, J.; Grandl, S.; Auweter, S.; Mayr, D.; Hipp, A.; Chabior, M.; Sarapata, A.; Achterhold, K.; Zanette, I.; Weitkamp, T.; Sztrókay, A.; Hellerhoff, K.; Reiser, M.; Pfeiffer, F.

2014-04-01

X-ray phase-contrast imaging has received growing interest in recent years due to its high capability in visualizing soft tissue. Breast imaging became the focus of particular attention as it is considered the most promising candidate for a first clinical application of this contrast modality. In this study, we investigate quantitative breast tissue characterization using grating-based phase-contrast computed tomography (CT) at conventional polychromatic x-ray sources. Different breast specimens have been scanned at a laboratory phase-contrast imaging setup and were correlated to histopathology. Ascertained tumor types include phylloides tumor, fibroadenoma and infiltrating lobular carcinoma. Identified tissue types comprising adipose, fibroglandular and tumor tissue have been analyzed in terms of phase-contrast Hounsfield units and are compared to high-quality, high-resolution data obtained with monochromatic synchrotron radiation, as well as calculated values based on tabulated tissue properties. The results give a good impression of the method’s prospects and limitations for potential tumor detection and the associated demands on such a phase-contrast breast CT system. Furthermore, the evaluated quantitative tissue values serve as a reference for simulations and the design of dedicated phantoms for phase-contrast mammography.

A big-data model for multi-modal public transportation with application to macroscopic control and optimisation

NASA Astrophysics Data System (ADS)

Faizrahnemoon, Mahsa; Schlote, Arieh; Maggi, Lorenzo; Crisostomi, Emanuele; Shorten, Robert

2015-11-01

This paper describes a Markov-chain-based approach to modelling multi-modal transportation networks. An advantage of the model is the ability to accommodate complex dynamics and handle huge amounts of data. The transition matrix of the Markov chain is built and the model is validated using the data extracted from a traffic simulator. A realistic test-case using multi-modal data from the city of London is given to further support the ability of the proposed methodology to handle big quantities of data. Then, we use the Markov chain as a control tool to improve the overall efficiency of a transportation network, and some practical examples are described to illustrate the potentials of the approach.

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

NASA Astrophysics Data System (ADS)

Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

2012-02-01

Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

Rapid fabrication of carbon quantum dots as multifunctional nanovehicles for dual-modal targeted imaging and chemotherapy.

PubMed

Chiu, Sheng-Hui; Gedda, Gangaraju; Girma, Wubshet Mekonnen; Chen, Jem-Kun; Ling, Yong-Chien; Ghule, Anil V; Ou, Keng-Liang; Chang, Jia-Yaw

2016-12-01

Herein, we synthesized an S, N, and Gd tri-element doped magnetofluorescent carbon quantum dots (GdNS@CQDs) within 10min by using a one-pot microwave method. Our results showed that these magnetofluorescent GdNS@CQDs have excellent fluorescent and magnetic properties. Moreover, GdNS@CQDs exhibited high stability at physiological conditions and ionic strength. These magnetofluorescent GdNS@CQDs were conjugated with a folic acid, denoted as FA-GdNS@CQDs, for targeting dual modal fluorescence/magnetic resonance (MR) imaging. The in vitro and in vivo studies confirmed the high biocompatibility and low toxicity of FA-GdNS@CQDs. FA-GdNS@CQDs enhanced the MR response as compared to that for commercial Gd-DTPA. The targeting capabilities of FA-GdNS@CQDs were confirmed in HeLa and HepG2 cells using in vitro fluorescence and MR dual modality imaging. Additionally, an anticancer drug, doxorubicin, was incorporated into the FA-GdNS@CQDs forming FA-GdNS@CQDs-DOX, which enables targeted drug delivery. Importantly, the prepared FA-GdNS@CQDs-DOX showed a high quantity of doxorubicin loading capacity (about 80%) and pH-sensitive drug release. The uptake into cancer cells and the intracellular location of the FA-GdNS@CQDs were observed by confocal laser scanning microscopy. We also successfully demonstrated in vivo fluorescence bio imaging of the FA-GdNS@CQDs, using zebrafish as an animal model. In this manuscript, we reported a facial, rapid, and environmental friendly method to fabricate hetero atoms including gadolinium, nitrogen, and sulfur doped multi-functional magnetofluorescent carbon quantum dots (GdNS@CQDs) nanocomposite. These multifunctional GdNS@CQDs were conjugated with a folic acid for targeting dual modal fluorescence/magnetic resonance imaging. Additionally, an anticancer drug, doxorubicin, was incorporated into the nanocomposite forming FA-GdNS@CQDs-DOX, which enables targeted drug delivery. We have developed GdNS@CQDs with integrated functions for simultaneous in

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.

Multi-Modal Use of a Socially Directed Call in Bonobos

PubMed Central

Genty, Emilie; Clay, Zanna; Hobaiter, Catherine; Zuberbühler, Klaus

2014-01-01

‘Contest hoots’ are acoustically complex vocalisations produced by adult and subadult male bonobos (Pan paniscus). These calls are often directed at specific individuals and regularly combined with gestures and other body signals. The aim of our study was to describe the multi-modal use of this call type and to clarify its communicative and social function. To this end, we observed two large groups of bonobos, which generated a sample of 585 communicative interactions initiated by 10 different males. We found that contest hooting, with or without other associated signals, was produced to challenge and provoke a social reaction in the targeted individual, usually agonistic chase. Interestingly, ‘contest hoots’ were sometimes also used during friendly play. In both contexts, males were highly selective in whom they targeted by preferentially choosing individuals of equal or higher social rank, suggesting that the calls functioned to assert social status. Multi-modal sequences were not more successful in eliciting reactions than contest hoots given alone, but we found a significant difference in the choice of associated gestures between playful and agonistic contexts. During friendly play, contest hoots were significantly more often combined with soft than rough gestures compared to agonistic challenges, while the calls' acoustic structure remained the same. We conclude that contest hoots indicate the signaller's intention to interact socially with important group members, while the gestures provide additional cues concerning the nature of the desired interaction. PMID:24454745

Magnetic polarization measurements of the multi-modal plasma response to 3D fields in the EAST tokamak

NASA Astrophysics Data System (ADS)

Logan, N. C.; Cui, L.; Wang, H.; Sun, Y.; Gu, S.; Li, G.; Nazikian, R.; Paz-Soldan, C.

2018-07-01

A multi-modal plasma response to applied non-axisymmetric fields has been found in EAST tokamak plasmas. Here, multi-modal means the radial and poloidal structure of an individually driven toroidal harmonic is not fixed. The signature of such a multi-modal response is the magnetic polarization (ratio of radial and poloidal components) of the plasma response field measured on the low field side device mid-plane. A difference in the 3D coil phasing (the relative phase of two coil arrays) dependencies between the two responses is observed in response to n  =  2 fields in the same plasma for which the n  =  1 responses are well synchronized. Neither the maximum radial nor the maximum poloidal field response to n  =  2 fields agrees with the best applied phasing for mitigating edge localized modes, suggesting that the edge plasma response is not a dominant component of either polarization. GPEC modeling reproduces the discrepant phasing dependences of the experimental measurements, and confirms the edge resonances are maximized by the coil phasing that mitigates ELMs in the experiments. The model confirms the measured plasma response is not dominated by resonant current drive from the external field. Instead, non-resonant contributions play a large role in the diagnostic signal for both toroidal harmonics n  =  1 and n  =  2. The analysis in this paper demonstrates the ability of 3D modeling to connect external magnetic sensor measurements to the internal plasma physics and accurately predict optimal applied 3D field configurations in multi-modal plasmas.

Building an EEG-fMRI Multi-Modal Brain Graph: A Concurrent EEG-fMRI Study

PubMed Central

Yu, Qingbao; Wu, Lei; Bridwell, David A.; Erhardt, Erik B.; Du, Yuhui; He, Hao; Chen, Jiayu; Liu, Peng; Sui, Jing; Pearlson, Godfrey; Calhoun, Vince D.

2016-01-01

The topological architecture of brain connectivity has been well-characterized by graph theory based analysis. However, previous studies have primarily built brain graphs based on a single modality of brain imaging data. Here we develop a framework to construct multi-modal brain graphs using concurrent EEG-fMRI data which are simultaneously collected during eyes open (EO) and eyes closed (EC) resting states. FMRI data are decomposed into independent components with associated time courses by group independent component analysis (ICA). EEG time series are segmented, and then spectral power time courses are computed and averaged within 5 frequency bands (delta; theta; alpha; beta; low gamma). EEG-fMRI brain graphs, with EEG electrodes and fMRI brain components serving as nodes, are built by computing correlations within and between fMRI ICA time courses and EEG spectral power time courses. Dynamic EEG-fMRI graphs are built using a sliding window method, versus static ones treating the entire time course as stationary. In global level, static graph measures and properties of dynamic graph measures are different across frequency bands and are mainly showing higher values in eyes closed than eyes open. Nodal level graph measures of a few brain components are also showing higher values during eyes closed in specific frequency bands. Overall, these findings incorporate fMRI spatial localization and EEG frequency information which could not be obtained by examining only one modality. This work provides a new approach to examine EEG-fMRI associations within a graph theoretic framework with potential application to many topics. PMID:27733821

(In)Flexibility of Constituency in Japanese in Multi-Modal Categorial Grammar with Structured Phonology

ERIC Educational Resources Information Center

Kubota, Yusuke

2010-01-01

This dissertation proposes a theory of categorial grammar called Multi-Modal Categorial Grammar with Structured Phonology. The central feature that distinguishes this theory from the majority of contemporary syntactic theories is that it decouples (without completely segregating) two aspects of syntax--hierarchical organization (reflecting…

Multi-focus image fusion with the all convolutional neural network

NASA Astrophysics Data System (ADS)

Du, Chao-ben; Gao, She-sheng

2018-01-01

A decision map contains complete and clear information about the image to be fused, which is crucial to various image fusion issues, especially multi-focus image fusion. However, in order to get a satisfactory image fusion effect, getting a decision map is very necessary and usually difficult to finish. In this letter, we address this problem with convolutional neural network (CNN), aiming to get a state-of-the-art decision map. The main idea is that the max-pooling of CNN is replaced by a convolution layer, the residuals are propagated backwards by gradient descent, and the training parameters of the individual layers of the CNN are updated layer by layer. Based on this, we propose a new all CNN (ACNN)-based multi-focus image fusion method in spatial domain. We demonstrate that the decision map obtained from the ACNN is reliable and can lead to high-quality fusion results. Experimental results clearly validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.

A multimodal image sensor system for identifying water stress in grapevines

NASA Astrophysics Data System (ADS)

Zhao, Yong; Zhang, Qin; Li, Minzan; Shao, Yongni; Zhou, Jianfeng; Sun, Hong

2012-11-01

Water stress is one of the most common limitations of fruit growth. Water is the most limiting resource for crop growth. In grapevines, as well as in other fruit crops, fruit quality benefits from a certain level of water deficit which facilitates to balance vegetative and reproductive growth and the flow of carbohydrates to reproductive structures. A multi-modal sensor system was designed to measure the reflectance signature of grape plant surfaces and identify different water stress levels in this paper. The multi-modal sensor system was equipped with one 3CCD camera (three channels in R, G, and IR). The multi-modal sensor can capture and analyze grape canopy from its reflectance features, and identify the different water stress levels. This research aims at solving the aforementioned problems. The core technology of this multi-modal sensor system could further be used as a decision support system that combines multi-modal sensory data to improve plant stress detection and identify the causes of stress. The images were taken by multi-modal sensor which could output images in spectral bands of near-infrared, green and red channel. Based on the analysis of the acquired images, color features based on color space and reflectance features based on image process method were calculated. The results showed that these parameters had the potential as water stress indicators. More experiments and analysis are needed to validate the conclusion.

Diagnosis and Characterization of Patellofemoral Instability: Review of Available Imaging Modalities.

PubMed

Haj-Mirzaian, Arya; Thawait, Gaurav K; Tanaka, Miho J; Demehri, Shadpour

2017-06-01

Patellofemoral instability (PI) is defined as single or multiple episodes of patellar dislocation. Imaging modalities are useful for characterization of patellar malalignment, maltracking, underlying morphologic abnormalities, and stabilizing soft-tissue injuries. Using these findings, orthopedic surgeons can decide when to operate, determine the best operation, and measure degree of correction postoperatively in PI patients. Also, these methods assist with PI diagnosis in some suspicious cases. Magnetic resonance imaging is the preferred method especially in the setting of acute dislocations. Multidetector computed tomography allows a more accurate assessment for malalignment such as patellar tilt and lateral subluxation and secondary osteoarthritis. Dynamic magnetic resonance imaging and 4-dimensional computed tomography have been introduced for better kinematic assessment of the patellofemoral maltracking during extension-flexion motions. In this review article, we will discuss the currently available evidence regarding both the conventional and the novel imaging modalities that can be used for diagnosis and characterization of PI.

The effectiveness of multi modal representation text books to improve student's scientific literacy of senior high school students

NASA Astrophysics Data System (ADS)

Zakiya, Hanifah; Sinaga, Parlindungan; Hamidah, Ida

2017-05-01

The results of field studies showed the ability of science literacy of students was still low. One root of the problem lies in the books used in learning is not oriented toward science literacy component. This study focused on the effectiveness of the use of textbook-oriented provisioning capability science literacy by using multi modal representation. The text books development method used Design Representational Approach Learning to Write (DRALW). Textbook design which was applied to the topic of "Kinetic Theory of Gases" is implemented in XI grade students of high school learning. Effectiveness is determined by consideration of the effect and the normalized percentage gain value, while the hypothesis was tested using Independent T-test. The results showed that the textbooks which were developed using multi-mode representation science can improve the literacy skills of students. Based on the size of the effect size textbooks developed with representation multi modal was found effective in improving students' science literacy skills. The improvement was occurred in all the competence and knowledge of scientific literacy. The hypothesis testing showed that there was a significant difference on the ability of science literacy between class that uses textbooks with multi modal representation and the class that uses the regular textbook used in schools.

Detecting ordered small molecule drug aggregates in live macrophages: a multi-parameter microscope image data acquisition and analysis strategy

PubMed Central

Rzeczycki, Phillip; Yoon, Gi Sang; Keswani, Rahul K.; Sud, Sudha; Stringer, Kathleen A.; Rosania, Gus R.

2017-01-01

Following prolonged administration, certain orally bioavailable but poorly soluble small molecule drugs are prone to precipitate out and form crystal-like drug inclusions (CLDIs) within the cells of living organisms. In this research, we present a quantitative multi-parameter imaging platform for measuring the fluorescence and polarization diattenuation signals of cells harboring intracellular CLDIs. To validate the imaging system, the FDA-approved drug clofazimine (CFZ) was used as a model compound. Our results demonstrated that a quantitative multi-parameter microscopy image analysis platform can be used to study drug sequestering macrophages, and to detect the formation of ordered molecular aggregates formed by poorly soluble small molecule drugs in animals. PMID:28270989

Detecting ordered small molecule drug aggregates in live macrophages: a multi-parameter microscope image data acquisition and analysis strategy.

PubMed

Rzeczycki, Phillip; Yoon, Gi Sang; Keswani, Rahul K; Sud, Sudha; Stringer, Kathleen A; Rosania, Gus R

2017-02-01

Following prolonged administration, certain orally bioavailable but poorly soluble small molecule drugs are prone to precipitate out and form crystal-like drug inclusions (CLDIs) within the cells of living organisms. In this research, we present a quantitative multi-parameter imaging platform for measuring the fluorescence and polarization diattenuation signals of cells harboring intracellular CLDIs. To validate the imaging system, the FDA-approved drug clofazimine (CFZ) was used as a model compound. Our results demonstrated that a quantitative multi-parameter microscopy image analysis platform can be used to study drug sequestering macrophages, and to detect the formation of ordered molecular aggregates formed by poorly soluble small molecule drugs in animals.

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

X-ray Phase Contrast Allows Three Dimensional, Quantitative Imaging of Hydrogel Implants

DOE PAGES

Appel, Alyssa A.; Larson, Jeffrey C.; Jiang, Bin; ...

2015-10-20

Three dimensional imaging techniques are needed for the evaluation and assessment of biomaterials used for tissue engineering and drug delivery applications. Hydrogels are a particularly popular class of materials for medical applications but are difficult to image in tissue using most available imaging modalities. Imaging techniques based on X-ray Phase Contrast (XPC) have shown promise for tissue engineering applications due to their ability to provide image contrast based on multiple X-ray properties. In this manuscript we describe results using XPC to image a model hydrogel and soft tissue structure. Porous fibrin loaded poly(ethylene glycol) hydrogels were synthesized and implanted inmore » a rodent subcutaneous model. Samples were explanted and imaged with an analyzer-based XPC technique and processed and stained for histology for comparison. Both hydrogel and soft tissues structures could be identified in XPC images. Structure in skeletal muscle adjacent could be visualized and invading fibrovascular tissue could be quantified. In quantitative results, there were no differences between XPC and the gold-standard histological measurements. These results provide evidence of the significant potential of techniques based on XPC for 3D imaging of hydrogel structure and local tissue response.« less

Object discrimination using optimized multi-frequency auditory cross-modal haptic feedback.

PubMed

Gibson, Alison; Artemiadis, Panagiotis

2014-01-01

As the field of brain-machine interfaces and neuro-prosthetics continues to grow, there is a high need for sensor and actuation mechanisms that can provide haptic feedback to the user. Current technologies employ expensive, invasive and often inefficient force feedback methods, resulting in an unrealistic solution for individuals who rely on these devices. This paper responds through the development, integration and analysis of a novel feedback architecture where haptic information during the neural control of a prosthetic hand is perceived through multi-frequency auditory signals. Through representing force magnitude with volume and force location with frequency, the feedback architecture can translate the haptic experiences of a robotic end effector into the alternative sensory modality of sound. Previous research with the proposed cross-modal feedback method confirmed its learnability, so the current work aimed to investigate which frequency map (i.e. frequency-specific locations on the hand) is optimal in helping users distinguish between hand-held objects and tasks associated with them. After short use with the cross-modal feedback during the electromyographic (EMG) control of a prosthetic hand, testing results show that users are able to use audial feedback alone to discriminate between everyday objects. While users showed adaptation to three different frequency maps, the simplest map containing only two frequencies was found to be the most useful in discriminating between objects. This outcome provides support for the feasibility and practicality of the cross-modal feedback method during the neural control of prosthetics.

Automated unsupervised multi-parametric classification of adipose tissue depots in skeletal muscle

PubMed Central

Valentinitsch, Alexander; Karampinos, Dimitrios C.; Alizai, Hamza; Subburaj, Karupppasamy; Kumar, Deepak; Link, Thomas M.; Majumdar, Sharmila

2012-01-01

Purpose To introduce and validate an automated unsupervised multi-parametric method for segmentation of the subcutaneous fat and muscle regions in order to determine subcutaneous adipose tissue (SAT) and intermuscular adipose tissue (IMAT) areas based on data from a quantitative chemical shift-based water-fat separation approach. Materials and Methods Unsupervised standard k-means clustering was employed to define sets of similar features (k = 2) within the whole multi-modal image after the water-fat separation. The automated image processing chain was composed of three primary stages including tissue, muscle and bone region segmentation. The algorithm was applied on calf and thigh datasets to compute SAT and IMAT areas and was compared to a manual segmentation. Results The IMAT area using the automatic segmentation had excellent agreement with the IMAT area using the manual segmentation for all the cases in the thigh (R2: 0.96) and for cases with up to moderate IMAT area in the calf (R2: 0.92). The group with the highest grade of muscle fat infiltration in the calf had the highest error in the inner SAT contour calculation. Conclusion The proposed multi-parametric segmentation approach combined with quantitative water-fat imaging provides an accurate and reliable method for an automated calculation of the SAT and IMAT areas reducing considerably the total post-processing time. PMID:23097409

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

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.

Intraoperative utilization of advanced imaging modalities in a complex kidney stone case: a pilot case study.

PubMed

Christiansen, Andrew R; Shorti, Rami M; Smith, Cory D; Prows, William C; Bishoff, Jay T

2018-05-01

Despite the increasing use of advanced 3D imaging techniques and 3D printing, these techniques have not yet been comprehensively compared in a surgical setting. The purpose of this study is to explore the effectiveness of five different advanced imaging modalities during a complex renal surgical procedure. A patient with a horseshoe kidney and multiple large, symptomatic stones that had failed Extracorporeal Shock Wave Lithotripsy (ESWL) and ureteroscopy treatment was used for this evaluation. CT data were used to generate five different imaging modalities, including a 3D printed model, three different volume rendered models, and a geometric CAD model. A survey was used to evaluate the quality and breadth of the imaging modalities during four different phases of the laparoscopic procedure. In the case of a complex kidney procedure, the CAD model, 3D print, volume render on an autostereoscopic 3D display, interactive and basic volume render models demonstrated added insight and complemented the surgical procedure. CAD manual segmentation allowed tissue layers and/or kidney stones to be made colorful and semi-transparent, allowing easier navigation through abnormal vasculature. The 3D print allowed for simultaneous visualization of renal pelvis and surrounding vasculature. Our preliminary exploration indicates that various advanced imaging modalities, when properly utilized and supported during surgery, can be useful in complementing the CT data and laparoscopic display. This study suggests that various imaging modalities, such as ones utilized in this case, can be beneficial intraoperatively depending on the surgical step involved and may be more helpful than 3D printed models. We also present factors to consider when evaluating advanced imaging modalities during complex surgery.

Methodology for quantitative rapid multi-tracer PET tumor characterizations.

PubMed

Kadrmas, Dan J; Hoffman, John M

2013-10-04

Positron emission tomography (PET) can image a wide variety of functional and physiological parameters in vivo using different radiotracers. As more is learned about the molecular basis for disease and treatment, the potential value of molecular imaging for characterizing and monitoring disease status has increased. Characterizing multiple aspects of tumor physiology by imaging multiple PET tracers in a single patient provides additional complementary information, and there is a significant body of literature supporting the potential value of multi-tracer PET imaging in oncology. However, imaging multiple PET tracers in a single patient presents a number of challenges. A number of techniques are under development for rapidly imaging multiple PET tracers in a single scan, where signal-recovery processing algorithms are employed to recover various imaging endpoints for each tracer. Dynamic imaging is generally used with tracer injections staggered in time, and kinetic constraints are utilized to estimate each tracers' contribution to the multi-tracer imaging signal. This article summarizes past and ongoing work in multi-tracer PET tumor imaging, and then organizes and describes the main algorithmic approaches for achieving multi-tracer PET signal-recovery. While significant advances have been made, the complexity of the approach necessitates protocol design, optimization, and testing for each particular tracer combination and application. Rapid multi-tracer PET techniques have great potential for both research and clinical cancer imaging applications, and continued research in this area is warranted.

Methodology for Quantitative Rapid Multi-Tracer PET Tumor Characterizations

PubMed Central

Kadrmas, Dan J.; Hoffman, John M.

2013-01-01

Positron emission tomography (PET) can image a wide variety of functional and physiological parameters in vivo using different radiotracers. As more is learned about the molecular basis for disease and treatment, the potential value of molecular imaging for characterizing and monitoring disease status has increased. Characterizing multiple aspects of tumor physiology by imaging multiple PET tracers in a single patient provides additional complementary information, and there is a significant body of literature supporting the potential value of multi-tracer PET imaging in oncology. However, imaging multiple PET tracers in a single patient presents a number of challenges. A number of techniques are under development for rapidly imaging multiple PET tracers in a single scan, where signal-recovery processing algorithms are employed to recover various imaging endpoints for each tracer. Dynamic imaging is generally used with tracer injections staggered in time, and kinetic constraints are utilized to estimate each tracers' contribution to the multi-tracer imaging signal. This article summarizes past and ongoing work in multi-tracer PET tumor imaging, and then organizes and describes the main algorithmic approaches for achieving multi-tracer PET signal-recovery. While significant advances have been made, the complexity of the approach necessitates protocol design, optimization, and testing for each particular tracer combination and application. Rapid multi-tracer PET techniques have great potential for both research and clinical cancer imaging applications, and continued research in this area is warranted. PMID:24312149

Obstacle traversal and self-righting of bio-inspired robots reveal the physics of multi-modal locomotion

NASA Astrophysics Data System (ADS)

Li, Chen; Fearing, Ronald; Full, Robert

Most animals move in nature in a variety of locomotor modes. For example, to traverse obstacles like dense vegetation, cockroaches can climb over, push across, reorient their bodies to maneuver through slits, or even transition among these modes forming diverse locomotor pathways; if flipped over, they can also self-right using wings or legs to generate body pitch or roll. By contrast, most locomotion studies have focused on a single mode such as running, walking, or jumping, and robots are still far from capable of life-like, robust, multi-modal locomotion in the real world. Here, we present two recent studies using bio-inspired robots, together with new locomotion energy landscapes derived from locomotor-environment interaction physics, to begin to understand the physics of multi-modal locomotion. (1) Our experiment of a cockroach-inspired legged robot traversing grass-like beam obstacles reveals that, with a terradynamically ``streamlined'' rounded body like that of the insect, robot traversal becomes more probable by accessing locomotor pathways that overcome lower potential energy barriers. (2) Our experiment of a cockroach-inspired self-righting robot further suggests that body vibrations are crucial for exploring locomotion energy landscapes and reaching lower barrier pathways. Finally, we posit that our new framework of locomotion energy landscapes holds promise to better understand and predict multi-modal biological and robotic movement.

Percolated microstructures for multi-modal transport enhancement in porous active materials

DOEpatents

McKay, Ian Salmon; Yang, Sungwoo; Wang, Evelyn N.; Kim, Hyunho

2018-03-13

A method of forming a composite material for use in multi-modal transport includes providing three-dimensional graphene having hollow channels, enabling a polymer to wick into the hollow channels of the three-dimensional graphene, curing the polymer to form a cured three-dimensional graphene, adding an active material to the cured three-dimensional graphene to form a composite material, and removing the polymer from within the hollow channels. A composite material formed according to the method is also provided.

Imaging modalities for the non-invasive diagnosis of endometriosis.

PubMed

Nisenblat, Vicki; Bossuyt, Patrick M M; Farquhar, Cindy; Johnson, Neil; Hull, M Louise

2016-02-26

participants; sensitivity 0.95 (95% CI 0.90, 1.00), specificity 0.91 (95% CI 0.86, 0.97)) met the criteria for a replacement and SnNout triage test and approached the criteria for a SpPin test. For DIE, TVUS (nine studies, 12 data sets, 934 participants; sensitivity 0.79 (95% CI 0.69, 0.89) and specificity 0.94 (95% CI 0.88, 1.00)) approached the criteria for a SpPin triage test, and MRI (six studies, seven data sets, 266 participants; sensitivity 0.94 (95% CI 0.90, 0.97), specificity 0.77 (95% CI 0.44, 1.00)) approached the criteria for a replacement and SnNout triage test. Other imaging tests assessed in small individual studies could not be statistically evaluated.TVUS met the criteria for a SpPin triage test in mapping DIE to uterosacral ligaments, rectovaginal septum, vaginal wall, pouch of Douglas (POD) and rectosigmoid. MRI met the criteria for a SpPin triage test for POD and vaginal and rectosigmoid endometriosis. Transrectal ultrasonography (TRUS) might qualify as a SpPin triage test for rectosigmoid involvement but could not be adequately assessed for other anatomical sites because heterogeneous data were scant. Multi-detector computerised tomography enema (MDCT-e) displayed the highest diagnostic performance for rectosigmoid and other bowel endometriosis and met the criteria for both SpPin and SnNout triage tests, but studies were too few to provide meaningful results.Diagnostic accuracies were higher for TVUS with bowel preparation (TVUS-BP) and rectal water contrast (RWC-TVS) and for 3.0TMRI than for conventional methods, although the paucity of studies precluded statistical evaluation. None of the evaluated imaging modalities were able to detect overall pelvic endometriosis with enough accuracy that they would be suggested to replace surgery. Specifically for endometrioma, TVUS qualified as a SpPin triage test. MRI displayed sufficient accuracy to suggest utility as a replacement test, but the data were too scant to permit meaningful conclusions. TVUS could be

An adaptive block-based fusion method with LUE-SSIM for multi-focus images

NASA Astrophysics Data System (ADS)

Zheng, Jianing; Guo, Yongcai; Huang, Yukun

2016-09-01

Because of the lenses' limited depth of field, digital cameras are incapable of acquiring an all-in-focus image of objects at varying distances in a scene. Multi-focus image fusion technique can effectively solve this problem. Aiming at the block-based multi-focus image fusion methods, the problem that blocking-artifacts often occurs. An Adaptive block-based fusion method based on lifting undistorted-edge structural similarity (LUE-SSIM) is put forward. In this method, image quality metrics LUE-SSIM is firstly proposed, which utilizes the characteristics of human visual system (HVS) and structural similarity (SSIM) to make the metrics consistent with the human visual perception. Particle swarm optimization(PSO) algorithm which selects LUE-SSIM as the object function is used for optimizing the block size to construct the fused image. Experimental results on LIVE image database shows that LUE-SSIM outperform SSIM on Gaussian defocus blur images quality assessment. Besides, multi-focus image fusion experiment is carried out to verify our proposed image fusion method in terms of visual and quantitative evaluation. The results show that the proposed method performs better than some other block-based methods, especially in reducing the blocking-artifact of the fused image. And our method can effectively preserve the undistorted-edge details in focus region of the source images.

MEDCIS: Multi-Modality Epilepsy Data Capture and Integration System

PubMed Central

Zhang, Guo-Qiang; Cui, Licong; Lhatoo, Samden; Schuele, Stephan U.; Sahoo, Satya S.

2014-01-01

Sudden Unexpected Death in Epilepsy (SUDEP) is the leading mode of epilepsy-related death and is most common in patients with intractable, frequent, and continuing seizures. A statistically significant cohort of patients for SUDEP study requires meticulous, prospective follow up of a large population that is at an elevated risk, best represented by the Epilepsy Monitoring Unit (EMU) patient population. Multiple EMUs need to collaborate, share data for building a larger cohort of potential SUDEP patient using a state-of-the-art informatics infrastructure. To address the challenges of data integration and data access from multiple EMUs, we developed the Multi-Modality Epilepsy Data Capture and Integration System (MEDCIS) that combines retrospective clinical free text processing using NLP, prospective structured data capture using an ontology-driven interface, interfaces for cohort search and signal visualization, all in a single integrated environment. A dedicated Epilepsy and Seizure Ontology (EpSO) has been used to streamline the user interfaces, enhance its usability, and enable mappings across distributed databases so that federated queries can be executed. MEDCIS contained 936 patient data sets from the EMUs of University Hospitals Case Medical Center (UH CMC) in Cleveland and Northwestern Memorial Hospital (NMH) in Chicago. Patients from UH CMC and NMH were stored in different databases and then federated through MEDCIS using EpSO and our mapping module. More than 77GB of multi-modal signal data were processed using the Cloudwave pipeline and made available for rendering through the web-interface. About 74% of the 40 open clinical questions of interest were answerable accurately using the EpSO-driven VISual AGregagator and Explorer (VISAGE) interface. Questions not directly answerable were either due to their inherent computational complexity, the unavailability of primary information, or the scope of concept that has been formulated in the existing Ep

MineScan: non-image data monitoring and mining from imaging modalities

NASA Astrophysics Data System (ADS)

Zaidi, Shayan M.; Huff, Dov; Bhalodia, Pankit; Mongkolwat, Pattanasak; Channin, David S.

2003-05-01

This project is intended to capture and interactively display non-image information routinely generated by imaging modalities. This information relates to the device's performance of the individual procedures and is not necessarily available in other information streams such as DICOM headers. While originally intended for use in servicing the modalities, this information can also be presented to radiologists and administrators within the department for both micro- and macro-management purposes. This data can help hospital administrators and radiologists manage available resources and discover clues to indicate what modifications in hospital operations might significantly improve its ability to provide efficient patient care. Data is collected from a departmental CT scanner. The data consists of a running record of exams followed by a list of processing records logged over a 24-hour period. MineScan extracts information from these records and stores it into a database. A statistical program is run once a day to collect relevant metrics. MineScan can be accessed via a Web browser or through an advanced prototype PACS workstation. This information, if provided in real-time, can be used to manage operations in a busy department. Even when provided historically, the data can be used to assess current activity, analyze trends and plan future operations.

Multi-Modalities Sensor Science

DTIC Science & Technology

2015-02-28

enhanced multi-mode sensor science. bio -sensing, cross-discipling, multi-physics, nano-technology sailing He +46-8790 8465 1 Final Report for SOARD Project...spectroscopy, nano-technology, biophotonics and multi-physics modeling to produce adaptable bio -nanostructure enhanced multi-mode sensor science. 1...adaptable bio -nanostructure enhanced multi-mode sensor science. The accomplishments includes 1) A General Method for Designing a Radome to Enhance

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.

A multi-modal approach to assessing recovery in youth athletes following concussion.

PubMed

Reed, Nick; Murphy, James; Dick, Talia; Mah, Katie; Paniccia, Melissa; Verweel, Lee; Dobney, Danielle; Keightley, Michelle

2014-09-25

Concussion is one of the most commonly reported injuries amongst children and youth involved in sport participation. Following a concussion, youth can experience a range of short and long term neurobehavioral symptoms (somatic, cognitive and emotional/behavioral) that can have a significant impact on one's participation in daily activities and pursuits of interest (e.g., school, sports, work, family/social life, etc.). Despite this, there remains a paucity in clinically driven research aimed specifically at exploring concussion within the youth sport population, and more specifically, multi-modal approaches to measuring recovery. This article provides an overview of a novel and multi-modal approach to measuring recovery amongst youth athletes following concussion. The presented approach involves the use of both pre-injury/baseline testing and post-injury/follow-up testing to assess performance across a wide variety of domains (post-concussion symptoms, cognition, balance, strength, agility/motor skills and resting state heart rate variability). The goal of this research is to gain a more objective and accurate understanding of recovery following concussion in youth athletes (ages 10-18 years). Findings from this research can help to inform the development and use of improved approaches to concussion management and rehabilitation specific to the youth sport community.

Interactive natural language acquisition in a multi-modal recurrent neural architecture

NASA Astrophysics Data System (ADS)

Heinrich, Stefan; Wermter, Stefan

2018-01-01

For the complex human brain that enables us to communicate in natural language, we gathered good understandings of principles underlying language acquisition and processing, knowledge about sociocultural conditions, and insights into activity patterns in the brain. However, we were not yet able to understand the behavioural and mechanistic characteristics for natural language and how mechanisms in the brain allow to acquire and process language. In bridging the insights from behavioural psychology and neuroscience, the goal of this paper is to contribute a computational understanding of appropriate characteristics that favour language acquisition. Accordingly, we provide concepts and refinements in cognitive modelling regarding principles and mechanisms in the brain and propose a neurocognitively plausible model for embodied language acquisition from real-world interaction of a humanoid robot with its environment. In particular, the architecture consists of a continuous time recurrent neural network, where parts have different leakage characteristics and thus operate on multiple timescales for every modality and the association of the higher level nodes of all modalities into cell assemblies. The model is capable of learning language production grounded in both, temporal dynamic somatosensation and vision, and features hierarchical concept abstraction, concept decomposition, multi-modal integration, and self-organisation of latent representations.

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.

Multishaker modal testing

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.

1983-01-01

Procedures for improving the modal modeling of structures using test data and to determine appropriate analytical models based on substructure experimental data were explored. Two related research topics were considered in modal modeling: using several independently acquired columns of frequency response data, and modal modeling using simultaneous multi-point excitation. In component mode synthesis modeling, the emphasis is on determining the best way to employ complex modes and residuals.

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.

Summary of Quantitative Interpretation of Image Far Ultraviolet Auroral Data

NASA Technical Reports Server (NTRS)

Frey, H. U.; Immel, T. J.; Mende, S. B.; Gerard, J.-C.; Hubert, B.; Habraken, S.; Span, J.; Gladstone, G. R.; Bisikalo, D. V.; Shematovich, V. I.;

Activatable albumin-photosensitizer nanoassemblies for triple-modal imaging and thermal-modulated photodynamic therapy of cancer.

PubMed

Hu, Dehong; Sheng, Zonghai; Gao, Guanhui; Siu, Fungming; Liu, Chengbo; Wan, Qian; Gong, Ping; Zheng, Hairong; Ma, Yifan; Cai, Lintao

2016-07-01

Photodynamic therapy (PDT) is a noninvasive and effective approach for cancer treatment. The main bottlenecks of clinical PDT are poor selectivity of photosensitizer and inadequate oxygen supply resulting in serious side effects and low therapeutic efficiency. Herein, a thermal-modulated reactive oxygen species (ROS) strategy using activatable human serum albumin-chlorin e6 nanoassemblies (HSA-Ce6 NAs) for promoting PDT against cancer is developed. Through intermolecular disulfide bond crosslinking and hydrophobic interaction, Ce6 photosensitizer is effectively loaded into the HSA NAs, and the obtained HSA-Ce6 NAs exhibit excellent reduction response, as well as enhanced tumor accumulation and retention. By the precision control of the overall body temperature instead of local tumor temperature increasing from 37 °C to 43 °C, the photosensitization reaction rate of HSA-Ce6 NAs increases 20%, and the oxygen saturation of tumor tissue raise 52%, significantly enhancing the generation of ROS for promoting PDT. Meanwhile, the intrinsic fluorescence and photoacoustic properties, and the chelating characteristic of porphyrin ring can endow the HSA-Ce6 NAs with fluorescence, photoacoustic and magnetic resonance triple-modal imaging functions. Upon irradiation of low-energy near-infrared laser, the tumors are completely suppressed without tumor recurrence and therapy-induced side effects. The robust thermal-modulated ROS strategy combined with albumin-based activatable nanophotosensitizer is highly potential for multi-modal imaging-guided PDT and clinical translation. Copyright © 2016 Elsevier Ltd. All rights reserved.

A novel image-based quantitative method for the characterization of NETosis

PubMed Central

Zhao, Wenpu; Fogg, Darin K.; Kaplan, Mariana J.

2015-01-01

NETosis is a newly recognized mechanism of programmed neutrophil death. It is characterized by a stepwise progression of chromatin decondensation, membrane rupture, and release of bactericidal DNA-based structures called neutrophil extracellular traps (NETs). Conventional ‘suicidal’ NETosis has been described in pathogenic models of systemic autoimmune disorders. Recent in vivo studies suggest that a process of ‘vital’ NETosis also exists, in which chromatin is condensed and membrane integrity is preserved. Techniques to assess ‘suicidal’ or ‘vital’ NET formation in a specific, quantitative, rapid and semiautomated way have been lacking, hindering the characterization of this process. Here we have developed a new method to simultaneously assess both ‘suicidal’ and ‘vital’ NETosis, using high-speed multi-spectral imaging coupled to morphometric image analysis, to quantify spontaneous NET formation observed ex-vivo or stimulus-induced NET formation triggered in vitro. Use of imaging flow cytometry allows automated, quantitative and rapid analysis of subcellular morphology and texture, and introduces the potential for further investigation using NETosis as a biomarker in pre-clinical and clinical studies. PMID:26003624

Automatic registration of multi-modal microscopy images for integrative analysis of prostate tissue sections.

PubMed

Lippolis, Giuseppe; Edsjö, Anders; Helczynski, Leszek; Bjartell, Anders; Overgaard, Niels Chr

2013-09-05

Prostate cancer is one of the leading causes of cancer related deaths. For diagnosis, predicting the outcome of the disease, and for assessing potential new biomarkers, pathologists and researchers routinely analyze histological samples. Morphological and molecular information may be integrated by aligning microscopic histological images in a multiplex fashion. This process is usually time-consuming and results in intra- and inter-user variability. The aim of this study is to investigate the feasibility of using modern image analysis methods for automated alignment of microscopic images from differently stained adjacent paraffin sections from prostatic tissue specimens. Tissue samples, obtained from biopsy or radical prostatectomy, were sectioned and stained with either hematoxylin & eosin (H&E), immunohistochemistry for p63 and AMACR or Time Resolved Fluorescence (TRF) for androgen receptor (AR). Image pairs were aligned allowing for translation, rotation and scaling. The registration was performed automatically by first detecting landmarks in both images, using the scale invariant image transform (SIFT), followed by the well-known RANSAC protocol for finding point correspondences and finally aligned by Procrustes fit. The Registration results were evaluated using both visual and quantitative criteria as defined in the text. Three experiments were carried out. First, images of consecutive tissue sections stained with H&E and p63/AMACR were successfully aligned in 85 of 88 cases (96.6%). The failures occurred in 3 out of 13 cores with highly aggressive cancer (Gleason score ≥ 8). Second, TRF and H&E image pairs were aligned correctly in 103 out of 106 cases (97%).The third experiment considered the alignment of image pairs with the same staining (H&E) coming from a stack of 4 sections. The success rate for alignment dropped from 93.8% in adjacent sections to 22% for sections furthest away. The proposed method is both reliable and fast and therefore well suited

Optical and photoacoustic dual-modality imaging guided synergistic photodynamic/photothermal therapies

NASA Astrophysics Data System (ADS)

Yan, Xuefeng; Hu, Hao; Lin, Jing; Jin, Albert J.; Niu, Gang; Zhang, Shaoliang; Huang, Peng; Shen, Baozhong; Chen, Xiaoyuan

2015-01-01

Phototherapies such as photodynamic therapy (PDT) and photothermal therapy (PTT), due to their specific spatiotemporal selectivity and minimal invasiveness, have been widely investigated as alternative treatments of malignant diseases. Graphene and its derivatives not only have been used as carriers to deliver photosensitizers for PDT, but also as photothermal conversion agents (PTCAs) for PTT. Herein, we strategically designed and produced a novel photo-theranostic platform based on sinoporphyrin sodium (DVDMS) photosensitizer-loaded PEGylated graphene oxide (GO-PEG-DVDMS) for enhanced fluorescence/photoacoustic (PA) dual-modal imaging and combined PDT and PTT. The GO-PEG carrier drastically improves the fluorescence of loaded DVDMS via intramolecular charge transfer. Concurrently, DVDMS significantly enhances the near-infrared (NIR) absorption of GO for improved PA imaging and PTT. The cancer theranostic capability of the as-prepared GO-PEG-DVDMS was carefully investigated both in vitro and in vivo. This novel theranostics is well suited for fluorescence/PA dual-modal imaging and synergistic PDT/PTT.

Micro/nano-computed tomography technology for quantitative dynamic, multi-scale imaging of morphogenesis.

PubMed

Gregg, Chelsea L; Recknagel, Andrew K; Butcher, Jonathan T

2015-01-01

Tissue morphogenesis and embryonic development are dynamic events challenging to quantify, especially considering the intricate events that happen simultaneously in different locations and time. Micro- and more recently nano-computed tomography (micro/nanoCT) has been used for the past 15 years to characterize large 3D fields of tortuous geometries at high spatial resolution. We and others have advanced micro/nanoCT imaging strategies for quantifying tissue- and organ-level fate changes throughout morphogenesis. Exogenous soft tissue contrast media enables visualization of vascular lumens and tissues via extravasation. Furthermore, the emergence of antigen-specific tissue contrast enables direct quantitative visualization of protein and mRNA expression. Micro-CT X-ray doses appear to be non-embryotoxic, enabling longitudinal imaging studies in live embryos. In this chapter we present established soft tissue contrast protocols for obtaining high-quality micro/nanoCT images and the image processing techniques useful for quantifying anatomical and physiological information from the data sets.

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

Influence of region-of-interest designs on quantitative measurement of multimodal imaging of MR non-enhancing gliomas.

PubMed

Takano, Koji; Kinoshita, Manabu; Arita, Hideyuki; Okita, Yoshiko; Chiba, Yasuyoshi; Kagawa, Naoki; Watanabe, Yoshiyuki; Shimosegawa, Eku; Hatazawa, Jun; Hashimoto, Naoya; Fujimoto, Yasunori; Kishima, Haruhiko

2018-05-01

A number of studies have revealed the usefulness of multimodal imaging in gliomas. Although the results have been heavily affected by the method used for region of interest (ROI) design, the most discriminatory method for setting the ROI remains unclear. The aim of the present study was to determine the most suitable ROI design for 18 F-fluorodeoxyglucose (FDG) and 11 C-methionine (MET) positron emission tomography (PET), apparent diffusion coefficient (ADC), and fractional anisotropy (FA) obtained by diffusion tensor imaging (DTI) from the viewpoint of grades of non-enhancing gliomas. A total of 31 consecutive patients with newly diagnosed, histologically confirmed magnetic resonance (MR) non-enhancing gliomas who underwent FDG-PET, MET-PET and DTI were retrospectively investigated. Quantitative measurements were performed using four different ROIs; hotspot/tumor center and whole tumor, constructed in either two-dimensional (2D) or three-dimensional (3D). Histopathological grading of the tumor was considered as empirical truth and the quantitative measurements obtained from each ROI was correlated with the grade of the tumor. The most discriminating ROI for non-enhancing glioma grading was different according to the different imaging modalities. 2D-hotspot/center ROI was most discriminating for FDG-PET (P=0.087), ADC map (P=0.0083), and FA map (P=0.25), whereas 3D-whole tumor ROI was best for MET-PET (P=0.0050). In the majority of scenarios, 2D-ROIs performed better than 3D-ROIs. Results from the image analysis using FDG-PET, MET-PET, ADC and FA may be affected by ROI design and the most discriminating ROI for non-enhancing glioma grading was different according to the imaging modality.

Toward Quantitative Small Animal Pinhole SPECT: Assessment of Quantitation Accuracy Prior to Image Compensations

PubMed Central

Chen, Chia-Lin; Wang, Yuchuan; Lee, Jason J. S.; Tsui, Benjamin M. W.

2011-01-01

Purpose We assessed the quantitation accuracy of small animal pinhole single photon emission computed tomography (SPECT) under the current preclinical settings, where image compensations are not routinely applied. Procedures The effects of several common image-degrading factors and imaging parameters on quantitation accuracy were evaluated using Monte-Carlo simulation methods. Typical preclinical imaging configurations were modeled, and quantitative analyses were performed based on image reconstructions without compensating for attenuation, scatter, and limited system resolution. Results Using mouse-sized phantom studies as examples, attenuation effects alone degraded quantitation accuracy by up to −18% (Tc-99m or In-111) or −41% (I-125). The inclusion of scatter effects changed the above numbers to −12% (Tc-99m or In-111) and −21% (I-125), respectively, indicating the significance of scatter in quantitative I-125 imaging. Region-of-interest (ROI) definitions have greater impacts on regional quantitation accuracy for small sphere sources as compared to attenuation and scatter effects. For the same ROI, SPECT acquisitions using pinhole apertures of different sizes could significantly affect the outcome, whereas the use of different radii-of-rotation yielded negligible differences in quantitation accuracy for the imaging configurations simulated. Conclusions We have systematically quantified the influence of several factors affecting the quantitation accuracy of small animal pinhole SPECT. In order to consistently achieve accurate quantitation within 5% of the truth, comprehensive image compensation methods are needed. PMID:19048346

Facile preparation of multifunctional uniform magnetic microspheres for T1-T2 dual modal magnetic resonance and optical imaging.

PubMed

Zhang, Li; Liang, Shuang; Liu, Ruiqing; Yuan, Tianmeng; Zhang, Shulai; Xu, Zushun; Xu, Haibo

2016-08-01

Molecular imaging is of significant importance for early detection and diagnosis of cancer. Herein, a novel core-shell magnetic microsphere for dual modal magnetic resonance imaging (MRI) and optical imaging was produced by one-pot emulsifier-free emulsion polymerization, which could provide high resolution rate of histologic structure information and realize high sensitive detection at the same time. The synthesized magnetic microspheres composed of cores containing oleic acid (OA) and sodium undecylenate (NaUA) modified Fe3O4 nanoparticles and styrene (St), Glycidyl methacrylate (GMA), and polymerizable lanthanide complexes (Gd(AA)3Phen and Eu(AA)3Phen) polymerized on the surface for outer shells. Fluorescence spectra show characteristic emission peaks from Eu(3+) at 590nm and 615nm and vivid red fluorescence luminescence can be observed by 2-photon confocal scanning laser microscopy (CLSM). In vitro cytotoxicity tests based on the MTT assay demonstrate good cytocompatibility, the composites have longitudinal relaxivity value (r1) of 8.39mM(-1)s(-1) and also have transverse relaxivity value (r2) of 71.18mM(-1)s(-1) at clinical 3.0 T MR scanner. In vitro and in vivo MRI studies exhibit high signal enhancement on both T1- and T2-weighted MR images. These fascinating multifunctional properties suggest that the polymer microspheres have large clinical potential as multi-modal MRI/optical probes. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

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...

Switchable multi-wavelength fiber laser based on modal interference

NASA Astrophysics Data System (ADS)

Ma, Lin; Jiang, Sun; Qi, Yan-Hui; Kang, Ze-Xin; Jian, Shui-Sheng

2015-08-01

A comb fiber filter based on modal interference is proposed and demonstrated in this paper. Here two cascaded up-tapers are used to excite the cladding mode, and a core-offset jointing point is used to act as an interference component. Experimental results show that this kind of structure possesses a comb filter property in a range of the C-band. The measured extinction ratio is better than 12 dB with an insertion loss of about 11 dB. A switchable multi-wavelength erbium-doped fiber laser based on this novel comb filter is demonstrated. By adjusting the polarization controller, the output laser can be switched among single-, dual-, and three-wavelengths with a side mode suppression ratio of better than 45 dB.

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

PubMed

Zhan, Mei; Crane, Matthew M; Entchev, Eugeni V; Caballero, Antonio; Fernandes de Abreu, Diana Andrea; Ch'ng, QueeLim; Lu, Hang

2015-04-01

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision

A phase I feasibility study of multi-modality imaging assessing rapid expansion of marrow fat and decreased bone mineral density in cancer patients

PubMed Central

Hui, Susanta K; Arentsen, Luke; Sueblinvong, Thanasak; Brown, Keenan; Bolan, Pat; Ghebre, Rahel G; Downs, Levi; Shanley, Ryan; Hansen, Karen E.; Minenko, Anne G.; Takhashi, Yutaka; Yagi, Masashi; Zhang, Yan; Geller, Melissa; Reynolds, Margaret; Lee, Chung K; Blaes, Anne H.; Allen, Sharon; Zobel, Bruno Beomonte; Le, Chap; Froelich, Jerry; Rosen, Clifford; Yee, Douglas

2014-01-01

Purpose Cancer survivors are at an increased risk for fractures, but lack of effective and economical biomarkers limits quantitative assessments of marrow fat (MF), bone mineral density (BMD) and their relation in response to cytotoxic cancer treatment. We report dual energy CT (DECT) imaging, commonly used for cancer diagnosis, treatment and surveillance, as a novel biomarker of MF and BMD. Methods We validated DECT in pre-clinical and Phase I clinical trials and verified with water-fat MRI (WF-MRI), quantitative CT (QCT) and dual-energy X-ray absorptiometry (DXA). Basis material composition framework was validated using water and small-chain alcohols simulating different components of bone marrow. Histologic validation was achieved by measuring percent adipocyte in cadaver vertebrae and compared with DECT and WF-MRI. For a Phase I trial, sixteen patients with gynecologic malignancies (treated with oophorectomy, radiotherapy or chemotherapy) underwent DECT, QCT, WF-MRI and DXA before and 12 months after treatment. BMD and MF percent and distribution were quantified in lumbar vertebrae and the right femoral neck. Results Measured precision (3 mg/cm3) was sufficient to distinguish test solutions. Adiposity in cadaver bone histology was highly correlated with MF measured using DECT and WF-MRI (r = 0.80 and 0.77, respectively). In the clinical trial, DECT showed high overall correlation (r = 0.77, 95% CI: 0.69, 0.83) with WF-MRI. MF increased significantly after treatment (p<0.002). Chemotherapy and radiation caused greater increases in MF than oophorectomy (p<0.032). L4 BMD decreased 14% by DECT, 20% by QCT, but only by 5% by DXA (p<0.002 for all). At baseline, we observed a statistically significant inverse association between MF and BMD which was dramatically attenuated after treatment. Conclusion Our study demonstrated that DECT, similar to WF-MRI, can accurately measure marrow adiposity. Both imaging modalities show rapid increase in MF following cancer treatment

A phase I feasibility study of multi-modality imaging assessing rapid expansion of marrow fat and decreased bone mineral density in cancer patients.

PubMed

Hui, Susanta K; Arentsen, Luke; Sueblinvong, Thanasak; Brown, Keenan; Bolan, Pat; Ghebre, Rahel G; Downs, Levi; Shanley, Ryan; Hansen, Karen E; Minenko, Anne G; Takhashi, Yutaka; Yagi, Masashi; Zhang, Yan; Geller, Melissa; Reynolds, Margaret; Lee, Chung K; Blaes, Anne H; Allen, Sharon; Zobel, Bruno Beomonte; Le, Chap; Froelich, Jerry; Rosen, Clifford; Yee, Douglas

2015-04-01

Cancer survivors are at an increased risk for fractures, but lack of effective and economical biomarkers limits quantitative assessments of marrow fat (MF), bone mineral density (BMD) and their relation in response to cytotoxic cancer treatment. We report dual energy CT (DECT) imaging, commonly used for cancer diagnosis, treatment and surveillance, as a novel biomarker of MF and BMD. We validated DECT in pre-clinical and phase I clinical trials and verified with water-fat MRI (WF-MRI), quantitative CT (QCT) and dual-energy X-ray absorptiometry (DXA). Basis material composition framework was validated using water and small-chain alcohols simulating different components of bone marrow. Histologic validation was achieved by measuring percent adipocyte in the cadaver vertebrae and compared with DECT and WF-MRI. For a phase I trial, sixteen patients with gynecologic malignancies (treated with oophorectomy, radiotherapy or chemotherapy) underwent DECT, QCT, WF-MRI and DXA before and 12months after treatment. BMD and MF percent and distribution were quantified in the lumbar vertebrae and the right femoral neck. Measured precision (3mg/cm(3)) was sufficient to distinguish test solutions. Adiposity in cadaver bone histology was highly correlated with MF measured using DECT and WF-MRI (r=0.80 and 0.77, respectively). In the clinical trial, DECT showed high overall correlation (r=0.77, 95% CI: 0.69, 0.83) with WF-MRI. MF increased significantly after treatment (p<0.002). Chemotherapy and radiation caused greater increases in MF than oophorectomy (p<0.032). L4 BMD decreased 14% by DECT, 20% by QCT, but only 5% by DXA (p<0.002 for all). At baseline, we observed a statistically significant inverse association between MF and BMD which was dramatically attenuated after treatment. Our study demonstrated that DECT, similar to WF-MRI, can accurately measure marrow adiposity. Both imaging modalities show rapid increase in MF following cancer treatment. Our results suggest that MF and

Quantitation of stress echocardiography by tissue Doppler and strain rate imaging: a dream come true?

PubMed

Galderisi, Maurizio; Mele, Donato; Marino, Paolo Nicola

2005-01-01

Tissue Doppler (TD) is an ultrasound tool providing a quantitative agreement of left ventricular regional myocardial function in different modalities. Spectral pulsed wave (PW) TD, performed online during the examination, measures instantaneous myocardial velocities. By means of color TD, velocity images are digitally stored for subsequent off-line analysis and mean myocardial velocities are measured. An implementation of color TD includes strain rate imaging (SRI), based on post-processing conversion of regional velocities in local myocardial deformation rate (strain rate) and percent deformation (strain). These three modalities have been applied to stress echocardiography for quantitative evaluation of regional left ventricular function and detection of ischemia and viability. They present advantages and limitations. PWTD does not permit the simultaneous assessment of multiple walls and therefore is not compatible with clinical stress echocardiography while it could be used in a laboratory setting. Color TD provides a spatial map of velocity throughout the myocardium but its results are strongly affected by the frame rate. Both color TD and PWTD are also influenced by overall cardiac motion and tethering from adjacent segments and require reference velocity values for interpretation of regional left ventricular function. High frame rate (i.e. > 150 ms) post-processing-derived SRI can potentially overcome these limitations, since measurements of myocardial deformation have not any significant apex-to-base gradient. Preliminary studies have shown encouraging results about the ability of SRI to detect ischemia and viability, in terms of both strain rate changes and/or evidence of post-systolic thickening. SRI is, however, Doppler-dependent and time-consuming. Further technical refinements are needed to improve its application and introduce new ultrasound modalities to overcome the limitations of the Doppler-derived deformation analysis.

Towards precision medicine: from quantitative imaging to radiomics

PubMed Central

Acharya, U. Rajendra; Hagiwara, Yuki; Sudarshan, Vidya K.; Chan, Wai Yee; Ng, Kwan Hoong

2018-01-01

Radiology (imaging) and imaging-guided interventions, which provide multi-parametric morphologic and functional information, are playing an increasingly significant role in precision medicine. Radiologists are trained to understand the imaging phenotypes, transcribe those observations (phenotypes) to correlate with underlying diseases and to characterize the images. However, in order to understand and characterize the molecular phenotype (to obtain genomic information) of solid heterogeneous tumours, the advanced sequencing of those tissues using biopsy is required. Thus, radiologists image the tissues from various views and angles in order to have the complete image phenotypes, thereby acquiring a huge amount of data. Deriving meaningful details from all these radiological data becomes challenging and raises the big data issues. Therefore, interest in the application of radiomics has been growing in recent years as it has the potential to provide significant interpretive and predictive information for decision support. Radiomics is a combination of conventional computer-aided diagnosis, deep learning methods, and human skills, and thus can be used for quantitative characterization of tumour phenotypes. This paper discusses the overview of radiomics workflow, the results of various radiomics-based studies conducted using various radiological images such as computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET), the challenges we are facing, and the potential contribution of radiomics towards precision medicine. PMID:29308604

Dual-Modality PET/Ultrasound imaging of the Prostate

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

Huber, Jennifer S.; Moses, William W.; Pouliot, Jean

2005-11-11

Functional imaging with positron emission tomography (PET)will detect malignant tumors in the prostate and/or prostate bed, as well as possibly help determine tumor ''aggressiveness''. However, the relative uptake in a prostate tumor can be so great that few other anatomical landmarks are visible in a PET image. Ultrasound imaging with a transrectal probe provides anatomical detail in the prostate region that can be co-registered with the sensitive functional information from the PET imaging. Imaging the prostate with both PET and transrectal ultrasound (TRUS) will help determine the location of any cancer within the prostate region. This dual-modality imaging should helpmore » provide better detection and treatment of prostate cancer. LBNL has built a high performance positron emission tomograph optimized to image the prostate.Compared to a standard whole-body PET camera, our prostate-optimized PET camera has the same sensitivity and resolution, less backgrounds and lower cost. We plan to develop the hardware and software tools needed for a validated dual PET/TRUS prostate imaging system. We also plan to develop dual prostate imaging with PET and external transabdominal ultrasound, in case the TRUS system is too uncomfortable for some patients. We present the design and intended clinical uses for these dual imaging systems.« less

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.

Quantitative fluorescence microscopy and image deconvolution.

PubMed

Swedlow, Jason R

2013-01-01

Quantitative imaging and image deconvolution have become standard techniques for the modern cell biologist because they can form the basis of an increasing number of assays for molecular function in a cellular context. There are two major types of deconvolution approaches--deblurring and restoration algorithms. Deblurring algorithms remove blur but treat a series of optical sections as individual two-dimensional entities and therefore sometimes mishandle blurred light. Restoration algorithms determine an object that, when convolved with the point-spread function of the microscope, could produce the image data. The advantages and disadvantages of these methods are discussed in this chapter. Image deconvolution in fluorescence microscopy has usually been applied to high-resolution imaging to improve contrast and thus detect small, dim objects that might otherwise be obscured. Their proper use demands some consideration of the imaging hardware, the acquisition process, fundamental aspects of photon detection, and image processing. This can prove daunting for some cell biologists, but the power of these techniques has been proven many times in the works cited in the chapter and elsewhere. Their usage is now well defined, so they can be incorporated into the capabilities of most laboratories. A major application of fluorescence microscopy is the quantitative measurement of the localization, dynamics, and interactions of cellular factors. The introduction of green fluorescent protein and its spectral variants has led to a significant increase in the use of fluorescence microscopy as a quantitative assay system. For quantitative imaging assays, it is critical to consider the nature of the image-acquisition system and to validate its response to known standards. Any image-processing algorithms used before quantitative analysis should preserve the relative signal levels in different parts of the image. A very common image-processing algorithm, image deconvolution, is used

Quantitative phase imaging of arthropods

PubMed Central

Sridharan, Shamira; Katz, Aron; Soto-Adames, Felipe; Popescu, Gabriel

2015-01-01

Abstract. Classification of arthropods is performed by characterization of fine features such as setae and cuticles. An unstained whole arthropod specimen mounted on a slide can be preserved for many decades, but is difficult to study since current methods require sample manipulation or tedious image processing. Spatial light interference microscopy (SLIM) is a quantitative phase imaging (QPI) technique that is an add-on module to a commercial phase contrast microscope. We use SLIM to image a whole organism springtail Ceratophysella denticulata mounted on a slide. This is the first time, to our knowledge, that an entire organism has been imaged using QPI. We also demonstrate the ability of SLIM to image fine structures in addition to providing quantitative data that cannot be obtained by traditional bright field microscopy. PMID:26334858

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.

Design of magnetic and fluorescent nanoparticles for in vivo MR and NIRF cancer imaging

NASA Astrophysics Data System (ADS)

Key, Jaehong

One big challenge for cancer treatment is that it has many errors in detection of cancers in the early stages before metastasis occurs. Using a current imaging modality, the detection of small tumors having potential metastasis is still very difficult. Thus, the development of multi-component nanoparticles (NPs) for dual modality cancer imaging is invaluable. The multi-component NPs can be an alternative to overcome the limitations from an imaging modality. For example, the multi-component NPs can visualize small tumors in both magnetic resonance imaging (MRI) and near infrared fluorescence (NIRF) imaging, which can help find the location of the tumors deep inside the body using MRI and subsequently guide surgeons to delineate the margin of tumors using highly sensitive NIRF imaging during a surgical operation. In this dissertation, we demonstrated the potential of the MRI and NIRF dual-modality NPs for skin and bladder cancer imaging. The multi-component NPs consisted of glycol chitosan, superparamagnetic iron oxide, NIRF dye, and cancer targeting peptides. We characterized the NPs and evaluated them with tumor bearing mice as well as various cancer cells. The findings of this research will contribute to the development of cancer diagnostic imaging and it can also be extensively applied to drug delivery system and fluorescence-guided surgical removal of cancer.

Quantitative optical imaging and sensing by joint design of point spread functions and estimation algorithms

NASA Astrophysics Data System (ADS)

Quirin, Sean Albert

The joint application of tailored optical Point Spread Functions (PSF) and estimation methods is an important tool for designing quantitative imaging and sensing solutions. By enhancing the information transfer encoded by the optical waves into an image, matched post-processing algorithms are able to complete tasks with improved performance relative to conventional designs. In this thesis, new engineered PSF solutions with image processing algorithms are introduced and demonstrated for quantitative imaging using information-efficient signal processing tools and/or optical-efficient experimental implementations. The use of a 3D engineered PSF, the Double-Helix (DH-PSF), is applied as one solution for three-dimensional, super-resolution fluorescence microscopy. The DH-PSF is a tailored PSF which was engineered to have enhanced information transfer for the task of localizing point sources in three dimensions. Both an information- and optical-efficient implementation of the DH-PSF microscope are demonstrated here for the first time. This microscope is applied to image single-molecules and micro-tubules located within a biological sample. A joint imaging/axial-ranging modality is demonstrated for application to quantifying sources of extended transverse and axial extent. The proposed implementation has improved optical-efficiency relative to prior designs due to the use of serialized cycling through select engineered PSFs. This system is demonstrated for passive-ranging, extended Depth-of-Field imaging and digital refocusing of random objects under broadband illumination. Although the serialized engineered PSF solution is an improvement over prior designs for the joint imaging/passive-ranging modality, it requires the use of multiple PSFs---a potentially significant constraint. Therefore an alternative design is proposed, the Single-Helix PSF, where only one engineered PSF is necessary and the chromatic behavior of objects under broadband illumination provides the

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...

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.

Siloxane nanoprobes for labeling and dual modality imaging of neural stem cells

PubMed Central

Addington, Caroline P.; Cusick, Alex; Shankar, Rohini Vidya; Agarwal, Shubhangi; Stabenfeldt, Sarah E.; Kodibagkar, Vikram D.

2015-01-01

Cell therapy represents a promising therapeutic for a myriad of medical conditions, including cancer, traumatic brain injury, and cardiovascular disease among others. A thorough understanding of the efficacy and cellular dynamics of these therapies necessitates the ability to non-invasively track cells in vivo. Magnetic resonance imaging (MRI) provides a platform to track cells as a non-invasive modality with superior resolution and soft tissue contrast. We recently reported a new nanoprobe platform for cell labeling and imaging using fluorophore doped siloxane core nanoemulsions as dual modality (1H MRI/Fluorescence), dual-functional (oximetry/detection) nanoprobes. Here, we successfully demonstrate the labeling, dual-modality imaging, and oximetry of neural progenitor/stem cells (NPSCs) in vitro using this platform. Labeling at a concentration of 10 μl/104 cells with a 40%v/v polydimethylsiloxane core nanoemulsion, doped with rhodamine, had minimal effect on viability, no effect on migration, proliferation and differentiation of NPSCs and allowed for unambiguous visualization of labeled NPSCs by 1H MR and fluorescence and local pO2 reporting by labeled NPSCs. This new approach for cell labeling with a positive contrast 1H MR probe has the potential to improve mechanistic knowledge of current therapies, and guide the design of future cell therapies due to its clinical translatability. PMID:26597417

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

Imaging with hypertelescopes: a simple modal approach

NASA Astrophysics Data System (ADS)

Aime, C.

2008-05-01

Aims: We give a simple analysis of imaging with hypertelescopes, a technique proposed by Labeyrie to produce snapshot images using arrays of telescopes. The approach is modal: we describe the transformations induced by the densification onto a sinusoidal decomposition of the focal image instead of the usual point spread function approach. Methods: We first express the image formed at the focus of a diluted array of apertures as the product R_0(α) X_F(α) of the diffraction pattern of the elementary apertures R_0(α) by the object-dependent interference term X_F(α) between all apertures. The interference term, which can be written in the form of a Fourier Series for an extremely diluted array, produces replications of the object, which makes observing the image difficult. We express the focal image after the densification using the approach of Tallon and Tallon-Bosc. Results: The result is very simple for an extremely diluted array. We show that the focal image in a periscopic densification of the array can be written as R_0(α) X_F(α/γ), where γ is the factor of densification. There is a dilatation of the interference term while the diffraction term is unchanged. After de-zooming, the image can be written as γ2 X_F(α)R_0(γ α), an expression which clearly indicates that the final image corresponds to the center of the Fizeau image intensified by γ2. The imaging limitations of hypertelescopes are therefore those of the original configuration. The effect of the suppression of image replications is illustrated in a numerical simulation for a fully redundant configuration and a non-redundant one.

A review of imaging modalities in pulmonary hypertension

PubMed Central

Ascha, Mona; Renapurkar, Rahul D.; Tonelli, Adriano R.

2017-01-01

Pulmonary hypertension (PH) is defined as resting mean pulmonary artery pressure ≥25 mmHg measured by right heart catheterization. PH is a progressive, life-threatening disease with a variety of etiologies. Swift and accurate diagnosis of PH and appropriate classification in etiologic group will allow for earlier treatment and improved outcomes. A number of imaging tools are utilized in the evaluation of PH, such as chest X-ray, computed tomography (CT), ventilation/perfusion (V/Q) scan, and cardiac magnetic resonance imaging. Newer imaging tools such as dual-energy CT and single-photon emission computed tomography/computed tomography V/Q scanning have also emerged; however, their place in the diagnostic evaluation of PH remains to be determined. In general, each imaging technique provides incremental information, with varying degrees of sensitivity and specificity, which helps suspect the presence and identify the etiology of PH. The present study aims to provide a comprehensive review of the utility, advantages, and shortcomings of the imaging modalities that may be used to evaluate patients with PH. PMID:28469715

Quantitative, Noninvasive Imaging of DNA Damage in Vivo of Prostate Cancer Therapy by Transurethral Photoacoustic (TUPA) Imaging

DTIC Science & Technology

2015-12-01

Xiang, L Xing, “ X - Ray Fluorescence CT as a Novel Imaging Modality for Improved Radiation Therapy Target Delineation”, Presented at 56th Annual Meeting... Imaging and Sensing, 1: 18-22 (2014).  Moiz Ahmad, Magdalena Bazalova, Liangzhong Xiang, and Lei Xing, Order of magnitude sensitivity increase in x - ray ...Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The goals of this training grant is to develop the foundations for a new medical imaging modality, now

Retinex Preprocessing for Improved Multi-Spectral Image Classification

NASA Technical Reports Server (NTRS)

Thompson, B.; Rahman, Z.; Park, S.

2000-01-01

The goal of multi-image classification is to identify and label "similar regions" within a scene. The ability to correctly classify a remotely sensed multi-image of a scene is affected by the ability of the classification process to adequately compensate for the effects of atmospheric variations and sensor anomalies. Better classification may be obtained if the multi-image is preprocessed before classification, so as to reduce the adverse effects of image formation. In this paper, we discuss the overall impact on multi-spectral image classification when the retinex image enhancement algorithm is used to preprocess multi-spectral images. The retinex is a multi-purpose image enhancement algorithm that performs dynamic range compression, reduces the dependence on lighting conditions, and generally enhances apparent spatial resolution. The retinex has been successfully applied to the enhancement of many different types of grayscale and color images. We show in this paper that retinex preprocessing improves the spatial structure of multi-spectral images and thus provides better within-class variations than would otherwise be obtained without the preprocessing. For a series of multi-spectral images obtained with diffuse and direct lighting, we show that without retinex preprocessing the class spectral signatures vary substantially with the lighting conditions. Whereas multi-dimensional clustering without preprocessing produced one-class homogeneous regions, the classification on the preprocessed images produced multi-class non-homogeneous regions. This lack of homogeneity is explained by the interaction between different agronomic treatments applied to the regions: the preprocessed images are closer to ground truth. The principle advantage that the retinex offers is that for different lighting conditions classifications derived from the retinex preprocessed images look remarkably "similar", and thus more consistent, whereas classifications derived from the original

Miniature all-optical probe for photoacoustic and ultrasound dual-modality imaging

NASA Astrophysics Data System (ADS)

Li, Guangyao; Guo, Zhendong; Chen, Sung-Liang

2018-02-01

Photoacoustic (PA) imaging forms an image based on optical absorption contrasts with ultrasound (US) resolution. In contrast, US imaging is based on acoustic backscattering to provide structural information. In this study, we develop a miniature all-optical probe for high-resolution PA-US dual-modality imaging over a large imaging depth range. The probe employs three individual optical fibers (F1-F3) to achieve optical generation and detection of acoustic waves for both PA and US modalities. To offer wide-angle laser illumination, fiber F1 with a large numerical aperture (NA) is used for PA excitation. On the other hand, wide-angle US waves are generated by laser illumination on an optically absorbing composite film which is coated on the end face of fiber F2. Both the excited PA and backscattered US waves are detected by a Fabry-Pérot cavity on the tip of fiber F3 for wide-angle acoustic detection. The wide angular features of the three optical fibers make large-NA synthetic aperture focusing technique possible and thus high-resolution PA and US imaging. The probe diameter is less than 2 mm. Over a depth range of 4 mm, lateral resolutions of PA and US imaging are 104-154 μm and 64-112 μm, respectively, and axial resolutions of PA and US imaging are 72-117 μm and 31-67 μm, respectively. To show the imaging capability of the probe, phantom imaging with both PA and US contrasts is demonstrated. The results show that the probe has potential for endoscopic and intravascular imaging applications that require PA and US contrast with high resolution.

Motion immune diffusion imaging using augmented MUSE (AMUSE) for high-resolution multi-shot EPI

PubMed Central

Guhaniyogi, Shayan; Chu, Mei-Lan; Chang, Hing-Chiu; Song, Allen W.; Chen, Nan-kuei

2015-01-01

Purpose To develop new techniques for reducing the effects of microscopic and macroscopic patient motion in diffusion imaging acquired with high-resolution multi-shot EPI. Theory The previously reported Multiplexed Sensitivity Encoding (MUSE) algorithm is extended to account for macroscopic pixel misregistrations as well as motion-induced phase errors in a technique called Augmented MUSE (AMUSE). Furthermore, to obtain more accurate quantitative DTI measures in the presence of subject motion, we also account for the altered diffusion encoding among shots arising from macroscopic motion. Methods MUSE and AMUSE were evaluated on simulated and in vivo motion-corrupted multi-shot diffusion data. Evaluations were made both on the resulting imaging quality and estimated diffusion tensor metrics. Results AMUSE was found to reduce image blurring resulting from macroscopic subject motion compared to MUSE, but yielded inaccurate tensor estimations when neglecting the altered diffusion encoding. Including the altered diffusion encoding in AMUSE produced better estimations of diffusion tensors. Conclusion The use of AMUSE allows for improved image quality and diffusion tensor accuracy in the presence of macroscopic subject motion during multi-shot diffusion imaging. These techniques should facilitate future high-resolution diffusion imaging. PMID:25762216

Multi-Band Miniaturized Patch Antennas for a Compact, Shielded Microwave Breast Imaging Array.

PubMed

Aguilar, Suzette M; Al-Joumayly, Mudar A; Burfeindt, Matthew J; Behdad, Nader; Hagness, Susan C

2013-12-18

We present a comprehensive study of a class of multi-band miniaturized patch antennas designed for use in a 3D enclosed sensor array for microwave breast imaging. Miniaturization and multi-band operation are achieved by loading the antenna with non-radiating slots at strategic locations along the patch. This results in symmetric radiation patterns and similar radiation characteristics at all frequencies of operation. Prototypes were fabricated and tested in a biocompatible immersion medium. Excellent agreement was obtained between simulations and measurements. The trade-off between miniaturization and radiation efficiency within this class of patch antennas is explored via a numerical analysis of the effects of the location and number of slots, as well as the thickness and permittivity of the dielectric substrate, on the resonant frequencies and gain. Additionally, we compare 3D quantitative microwave breast imaging performance achieved with two different enclosed arrays of slot-loaded miniaturized patch antennas. Simulated array measurements were obtained for a 3D anatomically realistic numerical breast phantom. The reconstructed breast images generated from miniaturized patch array data suggest that, for the realistic noise power levels assumed in this study, the variations in gain observed across this class of multi-band patch antennas do not significantly impact the overall image quality. We conclude that these miniaturized antennas are promising candidates as compact array elements for shielded, multi-frequency microwave breast imaging systems.

SU-E-I-53: Variation in Measurements of Breast Skin Thickness Obtained Using Different Imaging Modalities

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

Nguyen, U; Kumaraswamy, N; Markey, M

Purpose: To investigate variation in measurements of breast skin thickness obtained using different imaging modalities, including mammography, computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI). Methods: Breast skin thicknesses as measured by mammography, CT, ultrasound, and MRI were compared. Mammographic measurements of skin thickness were obtained from published studies that utilized standard positioning (upright) and compression. CT measurements of skin thickness were obtained from a published study of a prototype breast CT scanner in which the women were in the prone position and the breast was uncompressed. Dermatological ultrasound exams of the breast skin were conducted at our institution,more » with the subjects in the upright position and the breast uncompressed. Breast skin thickness was calculated from breast MRI exams at our institution, with the patient in the prone position and the breast uncompressed. Results: T tests for independent samples demonstrated significant differences in the mean breast skin thickness as measured by different imaging modalities. Repeated measures ANOVA revealed significant differences in breast skin thickness across different quadrants of the breast for some modalities. Conclusion: The measurement of breast skin thickness is significantly different across different imaging modalities. Differences in the amount of compression and differences in patient positioning are possible reasons why measurements of breast skin thickness vary by modality.« less

Quantitative, spectrally-resolved intraoperative fluorescence imaging

PubMed Central

Valdés, Pablo A.; Leblond, Frederic; Jacobs, Valerie L.; Wilson, Brian C.; Paulsen, Keith D.; Roberts, David W.

2012-01-01

Intraoperative visual fluorescence imaging (vFI) has emerged as a promising aid to surgical guidance, but does not fully exploit the potential of the fluorescent agents that are currently available. Here, we introduce a quantitative fluorescence imaging (qFI) approach that converts spectrally-resolved data into images of absolute fluorophore concentration pixel-by-pixel across the surgical field of view (FOV). The resulting estimates are linear, accurate, and precise relative to true values, and spectral decomposition of multiple fluorophores is also achieved. Experiments with protoporphyrin IX in a glioma rodent model demonstrate in vivo quantitative and spectrally-resolved fluorescence imaging of infiltrating tumor margins for the first time. Moreover, we present images from human surgery which detect residual tumor not evident with state-of-the-art vFI. The wide-field qFI technique has broad implications for intraoperative surgical guidance because it provides near real-time quantitative assessment of multiple fluorescent biomarkers across the operative field. PMID:23152935