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.

Real time quantitative phase microscopy based on single-shot transport of intensity equation (ssTIE) method

NASA Astrophysics Data System (ADS)

Yu, Wei; Tian, Xiaolin; He, Xiaoliang; Song, Xiaojun; Xue, Liang; Liu, Cheng; Wang, Shouyu

2016-08-01

Microscopy based on transport of intensity equation provides quantitative phase distributions which opens another perspective for cellular observations. However, it requires multi-focal image capturing while mechanical and electrical scanning limits its real time capacity in sample detections. Here, in order to break through this restriction, real time quantitative phase microscopy based on single-shot transport of the intensity equation method is proposed. A programmed phase mask is designed to realize simultaneous multi-focal image recording without any scanning; thus, phase distributions can be quantitatively retrieved in real time. It is believed the proposed method can be potentially applied in various biological and medical applications, especially for live cell imaging.

Structure-preserving interpolation of temporal and spatial image sequences using an optical flow-based method.

PubMed

Ehrhardt, J; Säring, D; Handels, H

2007-01-01

Modern tomographic imaging devices enable the acquisition of spatial and temporal image sequences. But, the spatial and temporal resolution of such devices is limited and therefore image interpolation techniques are needed to represent images at a desired level of discretization. This paper presents a method for structure-preserving interpolation between neighboring slices in temporal or spatial image sequences. In a first step, the spatiotemporal velocity field between image slices is determined using an optical flow-based registration method in order to establish spatial correspondence between adjacent slices. An iterative algorithm is applied using the spatial and temporal image derivatives and a spatiotemporal smoothing step. Afterwards, the calculated velocity field is used to generate an interpolated image at the desired time by averaging intensities between corresponding points. Three quantitative measures are defined to evaluate the performance of the interpolation method. The behavior and capability of the algorithm is demonstrated by synthetic images. A population of 17 temporal and spatial image sequences are utilized to compare the optical flow-based interpolation method to linear and shape-based interpolation. The quantitative results show that the optical flow-based method outperforms the linear and shape-based interpolation statistically significantly. The interpolation method presented is able to generate image sequences with appropriate spatial or temporal resolution needed for image comparison, analysis or visualization tasks. Quantitative and qualitative measures extracted from synthetic phantoms and medical image data show that the new method definitely has advantages over linear and shape-based interpolation.

Identification of ginseng root using quantitative X-ray microtomography.

PubMed

Ye, Linlin; Xue, Yanling; Wang, Yudan; Qi, Juncheng; Xiao, Tiqiao

2017-07-01

The use of X-ray phase-contrast microtomography for the investigation of Chinese medicinal materials is advantageous for its nondestructive, in situ , and three-dimensional quantitative imaging properties. The X-ray phase-contrast microtomography quantitative imaging method was used to investigate the microstructure of ginseng, and the phase-retrieval method is also employed to process the experimental data. Four different ginseng samples were collected and investigated; these were classified according to their species, production area, and sample growth pattern. The quantitative internal characteristic microstructures of ginseng were extracted successfully. The size and position distributions of the calcium oxalate cluster crystals (COCCs), important secondary metabolites that accumulate in ginseng, are revealed by the three-dimensional quantitative imaging method. The volume and amount of the COCCs in different species of the ginseng are obtained by a quantitative analysis of the three-dimensional microstructures, which shows obvious difference among the four species of ginseng. This study is the first to provide evidence of the distribution characteristics of COCCs to identify four types of ginseng, with regard to species authentication and age identification, by X-ray phase-contrast microtomography quantitative imaging. This method is also expected to reveal important relationships between COCCs and the occurrence of the effective medicinal components of ginseng.

Real-time quantitative fluorescence imaging using a single snapshot optical properties technique for neurosurgical guidance

NASA Astrophysics Data System (ADS)

Valdes, Pablo A.; Angelo, Joseph; Gioux, Sylvain

2015-03-01

Fluorescence imaging has shown promise as an adjunct to improve the extent of resection in neurosurgery and oncologic surgery. Nevertheless, current fluorescence imaging techniques do not account for the heterogeneous attenuation effects of tissue optical properties. In this work, we present a novel imaging system that performs real time quantitative fluorescence imaging using Single Snapshot Optical Properties (SSOP) imaging. We developed the technique and performed initial phantom studies to validate the quantitative capabilities of the system for intraoperative feasibility. Overall, this work introduces a novel real-time quantitative fluorescence imaging method capable of being used intraoperatively for neurosurgical guidance.

Some selected quantitative methods of thermal image analysis in Matlab.

PubMed

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantitative x-ray phase-contrast imaging using a single grating of comparable pitch to sample feature size.

PubMed

Morgan, Kaye S; Paganin, David M; Siu, Karen K W

2011-01-01

The ability to quantitatively retrieve transverse phase maps during imaging by using coherent x rays often requires a precise grating or analyzer-crystal-based setup. Imaging of live animals presents further challenges when these methods require multiple exposures for image reconstruction. We present a simple method of single-exposure, single-grating quantitative phase contrast for a regime in which the grating period is much greater than the effective pixel size. A grating is used to create a high-visibility reference pattern incident on the sample, which is distorted according to the complex refractive index and thickness of the sample. The resolution, along a line parallel to the grating, is not restricted by the grating spacing, and the detector resolution becomes the primary determinant of the spatial resolution. We present a method of analysis that maps the displacement of interrogation windows in order to retrieve a quantitative phase map. Application of this analysis to the imaging of known phantoms shows excellent correspondence.

Retinal status analysis method based on feature extraction and quantitative grading in OCT images.

PubMed

Fu, Dongmei; Tong, Hejun; Zheng, Shuang; Luo, Ling; Gao, Fulin; Minar, Jiri

2016-07-22

Optical coherence tomography (OCT) is widely used in ophthalmology for viewing the morphology of the retina, which is important for disease detection and assessing therapeutic effect. The diagnosis of retinal diseases is based primarily on the subjective analysis of OCT images by trained ophthalmologists. This paper describes an OCT images automatic analysis method for computer-aided disease diagnosis and it is a critical part of the eye fundus diagnosis. This study analyzed 300 OCT images acquired by Optovue Avanti RTVue XR (Optovue Corp., Fremont, CA). Firstly, the normal retinal reference model based on retinal boundaries was presented. Subsequently, two kinds of quantitative methods based on geometric features and morphological features were proposed. This paper put forward a retinal abnormal grading decision-making method which was used in actual analysis and evaluation of multiple OCT images. This paper showed detailed analysis process by four retinal OCT images with different abnormal degrees. The final grading results verified that the analysis method can distinguish abnormal severity and lesion regions. This paper presented the simulation of the 150 test images, where the results of analysis of retinal status showed that the sensitivity was 0.94 and specificity was 0.92.The proposed method can speed up diagnostic process and objectively evaluate the retinal status. This paper aims on studies of retinal status automatic analysis method based on feature extraction and quantitative grading in OCT images. The proposed method can obtain the parameters and the features that are associated with retinal morphology. Quantitative analysis and evaluation of these features are combined with reference model which can realize the target image abnormal judgment and provide a reference for disease diagnosis.

Normalized Temperature Contrast Processing in Infrared Flash Thermography

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2016-01-01

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

Objective evaluation of reconstruction methods for quantitative SPECT imaging in the absence of ground truth.

PubMed

Jha, Abhinav K; Song, Na; Caffo, Brian; Frey, Eric C

2015-04-13

Quantitative single-photon emission computed tomography (SPECT) imaging is emerging as an important tool in clinical studies and biomedical research. There is thus a need for optimization and evaluation of systems and algorithms that are being developed for quantitative SPECT imaging. An appropriate objective method to evaluate these systems is by comparing their performance in the end task that is required in quantitative SPECT imaging, such as estimating the mean activity concentration in a volume of interest (VOI) in a patient image. This objective evaluation can be performed if the true value of the estimated parameter is known, i.e. we have a gold standard. However, very rarely is this gold standard known in human studies. Thus, no-gold-standard techniques to optimize and evaluate systems and algorithms in the absence of gold standard are required. In this work, we developed a no-gold-standard technique to objectively evaluate reconstruction methods used in quantitative SPECT when the parameter to be estimated is the mean activity concentration in a VOI. We studied the performance of the technique with realistic simulated image data generated from an object database consisting of five phantom anatomies with all possible combinations of five sets of organ uptakes, where each anatomy consisted of eight different organ VOIs. Results indicate that the method provided accurate ranking of the reconstruction methods. We also demonstrated the application of consistency checks to test the no-gold-standard output.

A new method to evaluate image quality of CBCT images quantitatively without observers

PubMed Central

Shimizu, Mayumi; Okamura, Kazutoshi; Yoshida, Shoko; Weerawanich, Warangkana; Tokumori, Kenji; Jasa, Gainer R; Yoshiura, Kazunori

2017-01-01

Objectives: To develop an observer-free method for quantitatively evaluating the image quality of CBCT images by applying just-noticeable difference (JND). Methods: We used two test objects: (1) a Teflon (polytetrafluoroethylene) plate phantom attached to a dry human mandible; and (2) a block phantom consisting of a Teflon step phantom and an aluminium step phantom. These phantoms had holes with different depths. They were immersed in water and scanned with a CB MercuRay (Hitachi Medical Corporation, Tokyo, Japan) at tube voltages of 120 kV, 100 kV, 80 kV and 60 kV. Superimposed images of the phantoms with holes were used for evaluation. The number of detectable holes was used as an index of image quality. In detecting holes quantitatively, the threshold grey value (ΔG), which differentiated holes from the background, was calculated using a specific threshold (the JND), and we extracted the holes with grey values above ΔG. The indices obtained by this quantitative method (the extracted hole values) were compared with the observer evaluations (the observed hole values). In addition, the contrast-to-noise ratio (CNR) of the shallowest detectable holes and the deepest undetectable holes were measured to evaluate the contribution of CNR to detectability. Results: The results of this evaluation method corresponded almost exactly with the evaluations made by observers. The extracted hole values reflected the influence of different tube voltages. All extracted holes had an area with a CNR of ≥1.5. Conclusions: This quantitative method of evaluating CBCT image quality may be more useful and less time-consuming than evaluation by observation. PMID:28045343

Nonlocal means-based speckle filtering for ultrasound images

PubMed Central

Coupé, Pierrick; Hellier, Pierre; Kervrann, Charles; Barillot, Christian

2009-01-01

In image processing, restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques. In this paper, an adaptation of the Non Local (NL-) means filter is proposed for speckle reduction in ultrasound (US) images. Originally developed for additive white Gaussian noise, we propose to use a Bayesian framework to derive a NL-means filter adapted to a relevant ultrasound noise model. Quantitative results on synthetic data show the performances of the proposed method compared to well-established and state-of-the-art methods. Results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image. PMID:19482578

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

NASA Technical Reports Server (NTRS)

Koshti, Ajay M.

2016-01-01

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

Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software.

PubMed

Moon, Andres; Smith, Geoffrey H; Kong, Jun; Rogers, Thomas E; Ellis, Carla L; Farris, Alton B Brad

2018-02-01

Renal allograft rejection diagnosis depends on assessment of parameters such as interstitial inflammation; however, studies have shown interobserver variability regarding interstitial inflammation assessment. Since automated image analysis quantitation can be reproducible, we devised customized analysis methods for CD3+ T-cell staining density as a measure of rejection severity and compared them with established commercial methods along with visual assessment. Renal biopsy CD3 immunohistochemistry slides (n = 45), including renal allografts with various degrees of acute cellular rejection (ACR) were scanned for whole slide images (WSIs). Inflammation was quantitated in the WSIs using pathologist visual assessment, commercial algorithms (Aperio nuclear algorithm for CD3+ cells/mm 2 and Aperio positive pixel count algorithm), and customized open source algorithms developed in ImageJ with thresholding/positive pixel counting (custom CD3+%) and identification of pixels fulfilling "maxima" criteria for CD3 expression (custom CD3+ cells/mm 2 ). Based on visual inspections of "markup" images, CD3 quantitation algorithms produced adequate accuracy. Additionally, CD3 quantitation algorithms correlated between each other and also with visual assessment in a statistically significant manner (r = 0.44 to 0.94, p = 0.003 to < 0.0001). Methods for assessing inflammation suggested a progression through the tubulointerstitial ACR grades, with statistically different results in borderline versus other ACR types, in all but the custom methods. Assessment of CD3-stained slides using various open source image analysis algorithms presents salient correlations with established methods of CD3 quantitation. These analysis techniques are promising and highly customizable, providing a form of on-slide "flow cytometry" that can facilitate additional diagnostic accuracy in tissue-based assessments.

Sub-band denoising and spline curve fitting method for hemodynamic measurement in perfusion MRI

NASA Astrophysics Data System (ADS)

Lin, Hong-Dun; Huang, Hsiao-Ling; Hsu, Yuan-Yu; Chen, Chi-Chen; Chen, Ing-Yi; Wu, Liang-Chi; Liu, Ren-Shyan; Lin, Kang-Ping

2003-05-01

In clinical research, non-invasive MR perfusion imaging is capable of investigating brain perfusion phenomenon via various hemodynamic measurements, such as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean trasnit time (MTT). These hemodynamic parameters are useful in diagnosing brain disorders such as stroke, infarction and periinfarct ischemia by further semi-quantitative analysis. However, the accuracy of quantitative analysis is usually affected by poor signal-to-noise ratio image quality. In this paper, we propose a hemodynamic measurement method based upon sub-band denoising and spline curve fitting processes to improve image quality for better hemodynamic quantitative analysis results. Ten sets of perfusion MRI data and corresponding PET images were used to validate the performance. For quantitative comparison, we evaluate gray/white matter CBF ratio. As a result, the hemodynamic semi-quantitative analysis result of mean gray to white matter CBF ratio is 2.10 +/- 0.34. The evaluated ratio of brain tissues in perfusion MRI is comparable to PET technique is less than 1-% difference in average. Furthermore, the method features excellent noise reduction and boundary preserving in image processing, and short hemodynamic measurement time.

A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods

PubMed Central

Jha, Abhinav K; Caffo, Brian; Frey, Eric C

2016-01-01

The objective optimization and evaluation of nuclear-medicine quantitative imaging methods using patient data is highly desirable but often hindered by the lack of a gold standard. Previously, a regression-without-truth (RWT) approach has been proposed for evaluating quantitative imaging methods in the absence of a gold standard, but this approach implicitly assumes that bounds on the distribution of true values are known. Several quantitative imaging methods in nuclear-medicine imaging measure parameters where these bounds are not known, such as the activity concentration in an organ or the volume of a tumor. We extended upon the RWT approach to develop a no-gold-standard (NGS) technique for objectively evaluating such quantitative nuclear-medicine imaging methods with patient data in the absence of any ground truth. Using the parameters estimated with the NGS technique, a figure of merit, the noise-to-slope ratio (NSR), can be computed, which can rank the methods on the basis of precision. An issue with NGS evaluation techniques is the requirement of a large number of patient studies. To reduce this requirement, the proposed method explored the use of multiple quantitative measurements from the same patient, such as the activity concentration values from different organs in the same patient. The proposed technique was evaluated using rigorous numerical experiments and using data from realistic simulation studies. The numerical experiments demonstrated that the NSR was estimated accurately using the proposed NGS technique when the bounds on the distribution of true values were not precisely known, thus serving as a very reliable metric for ranking the methods on the basis of precision. In the realistic simulation study, the NGS technique was used to rank reconstruction methods for quantitative single-photon emission computed tomography (SPECT) based on their performance on the task of estimating the mean activity concentration within a known volume of interest. Results showed that the proposed technique provided accurate ranking of the reconstruction methods for 97.5% of the 50 noise realizations. Further, the technique was robust to the choice of evaluated reconstruction methods. The simulation study pointed to possible violations of the assumptions made in the NGS technique under clinical scenarios. However, numerical experiments indicated that the NGS technique was robust in ranking methods even when there was some degree of such violation. PMID:26982626

A no-gold-standard technique for objective assessment of quantitative nuclear-medicine imaging methods.

PubMed

Jha, Abhinav K; Caffo, Brian; Frey, Eric C

2016-04-07

The objective optimization and evaluation of nuclear-medicine quantitative imaging methods using patient data is highly desirable but often hindered by the lack of a gold standard. Previously, a regression-without-truth (RWT) approach has been proposed for evaluating quantitative imaging methods in the absence of a gold standard, but this approach implicitly assumes that bounds on the distribution of true values are known. Several quantitative imaging methods in nuclear-medicine imaging measure parameters where these bounds are not known, such as the activity concentration in an organ or the volume of a tumor. We extended upon the RWT approach to develop a no-gold-standard (NGS) technique for objectively evaluating such quantitative nuclear-medicine imaging methods with patient data in the absence of any ground truth. Using the parameters estimated with the NGS technique, a figure of merit, the noise-to-slope ratio (NSR), can be computed, which can rank the methods on the basis of precision. An issue with NGS evaluation techniques is the requirement of a large number of patient studies. To reduce this requirement, the proposed method explored the use of multiple quantitative measurements from the same patient, such as the activity concentration values from different organs in the same patient. The proposed technique was evaluated using rigorous numerical experiments and using data from realistic simulation studies. The numerical experiments demonstrated that the NSR was estimated accurately using the proposed NGS technique when the bounds on the distribution of true values were not precisely known, thus serving as a very reliable metric for ranking the methods on the basis of precision. In the realistic simulation study, the NGS technique was used to rank reconstruction methods for quantitative single-photon emission computed tomography (SPECT) based on their performance on the task of estimating the mean activity concentration within a known volume of interest. Results showed that the proposed technique provided accurate ranking of the reconstruction methods for 97.5% of the 50 noise realizations. Further, the technique was robust to the choice of evaluated reconstruction methods. The simulation study pointed to possible violations of the assumptions made in the NGS technique under clinical scenarios. However, numerical experiments indicated that the NGS technique was robust in ranking methods even when there was some degree of such violation.

Quantitative imaging assay for NF-κB nuclear translocation in primary human macrophages

PubMed Central

Noursadeghi, Mahdad; Tsang, Jhen; Haustein, Thomas; Miller, Robert F.; Chain, Benjamin M.; Katz, David R.

2008-01-01

Quantitative measurement of NF-κB nuclear translocation is an important research tool in cellular immunology. Established methodologies have a number of limitations, such as poor sensitivity, high cost or dependence on cell lines. Novel imaging methods to measure nuclear translocation of transcriptionally active components of NF-κB are being used but are also partly limited by the need for specialist imaging equipment or image analysis software. Herein we present a method for quantitative detection of NF-κB rel A nuclear translocation, using immunofluorescence microscopy and the public domain image analysis software ImageJ that can be easily adopted for cellular immunology research without the need for specialist image analysis expertise and at low cost. The method presented here is validated by demonstrating the time course and dose response of NF-κB nuclear translocation in primary human macrophages stimulated with LPS, and by comparison with a commercial NF-κB activation reporter cell line. PMID:18036607

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

PubMed Central

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

2012-01-01

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

Detection of blur artifacts in histopathological whole-slide images of endomyocardial biopsies.

PubMed

Hang Wu; Phan, John H; Bhatia, Ajay K; Cundiff, Caitlin A; Shehata, Bahig M; Wang, May D

2015-01-01

Histopathological whole-slide images (WSIs) have emerged as an objective and quantitative means for image-based disease diagnosis. However, WSIs may contain acquisition artifacts that affect downstream image feature extraction and quantitative disease diagnosis. We develop a method for detecting blur artifacts in WSIs using distributions of local blur metrics. As features, these distributions enable accurate classification of WSI regions as sharp or blurry. We evaluate our method using over 1000 portions of an endomyocardial biopsy (EMB) WSI. Results indicate that local blur metrics accurately detect blurry image regions.

Quantitative Analysis of Rat Dorsal Root Ganglion Neurons Cultured on Microelectrode Arrays Based on Fluorescence Microscopy Image Processing.

PubMed

Mari, João Fernando; Saito, José Hiroki; Neves, Amanda Ferreira; Lotufo, Celina Monteiro da Cruz; Destro-Filho, João-Batista; Nicoletti, Maria do Carmo

2015-12-01

Microelectrode Arrays (MEA) are devices for long term electrophysiological recording of extracellular spontaneous or evocated activities on in vitro neuron culture. This work proposes and develops a framework for quantitative and morphological analysis of neuron cultures on MEAs, by processing their corresponding images, acquired by fluorescence microscopy. The neurons are segmented from the fluorescence channel images using a combination of segmentation by thresholding, watershed transform, and object classification. The positioning of microelectrodes is obtained from the transmitted light channel images using the circular Hough transform. The proposed method was applied to images of dissociated culture of rat dorsal root ganglion (DRG) neuronal cells. The morphological and topological quantitative analysis carried out produced information regarding the state of culture, such as population count, neuron-to-neuron and neuron-to-microelectrode distances, soma morphologies, neuron sizes, neuron and microelectrode spatial distributions. Most of the analysis of microscopy images taken from neuronal cultures on MEA only consider simple qualitative analysis. Also, the proposed framework aims to standardize the image processing and to compute quantitative useful measures for integrated image-signal studies and further computational simulations. As results show, the implemented microelectrode identification method is robust and so are the implemented neuron segmentation and classification one (with a correct segmentation rate up to 84%). The quantitative information retrieved by the method is highly relevant to assist the integrated signal-image study of recorded electrophysiological signals as well as the physical aspects of the neuron culture on MEA. Although the experiments deal with DRG cell images, cortical and hippocampal cell images could also be processed with small adjustments in the image processing parameter estimation.

Principles of Quantitative MR Imaging with Illustrated Review of Applicable Modular Pulse Diagrams.

PubMed

Mills, Andrew F; Sakai, Osamu; Anderson, Stephan W; Jara, Hernan

2017-01-01

Continued improvements in diagnostic accuracy using magnetic resonance (MR) imaging will require development of methods for tissue analysis that complement traditional qualitative MR imaging studies. Quantitative MR imaging is based on measurement and interpretation of tissue-specific parameters independent of experimental design, compared with qualitative MR imaging, which relies on interpretation of tissue contrast that results from experimental pulse sequence parameters. Quantitative MR imaging represents a natural next step in the evolution of MR imaging practice, since quantitative MR imaging data can be acquired using currently available qualitative imaging pulse sequences without modifications to imaging equipment. The article presents a review of the basic physical concepts used in MR imaging and how quantitative MR imaging is distinct from qualitative MR imaging. Subsequently, the article reviews the hierarchical organization of major applicable pulse sequences used in this article, with the sequences organized into conventional, hybrid, and multispectral sequences capable of calculating the main tissue parameters of T1, T2, and proton density. While this new concept offers the potential for improved diagnostic accuracy and workflow, awareness of this extension to qualitative imaging is generally low. This article reviews the basic physical concepts in MR imaging, describes commonly measured tissue parameters in quantitative MR imaging, and presents the major available pulse sequences used for quantitative MR imaging, with a focus on the hierarchical organization of these sequences. © RSNA, 2017.

Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

NASA Astrophysics Data System (ADS)

Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

2015-08-01

A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as <0.66, 0.66-1.06, 1.06-1.62, and >1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

Image segmentation evaluation for very-large datasets

NASA Astrophysics Data System (ADS)

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

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

Vessel wall characterization using quantitative MRI: what's in a number?

PubMed

Coolen, Bram F; Calcagno, Claudia; van Ooij, Pim; Fayad, Zahi A; Strijkers, Gustav J; Nederveen, Aart J

2018-02-01

The past decade has witnessed the rapid development of new MRI technology for vessel wall imaging. Today, with advances in MRI hardware and pulse sequences, quantitative MRI of the vessel wall represents a real alternative to conventional qualitative imaging, which is hindered by significant intra- and inter-observer variability. Quantitative MRI can measure several important morphological and functional characteristics of the vessel wall. This review provides a detailed introduction to novel quantitative MRI methods for measuring vessel wall dimensions, plaque composition and permeability, endothelial shear stress and wall stiffness. Together, these methods show the versatility of non-invasive quantitative MRI for probing vascular disease at several stages. These quantitative MRI biomarkers can play an important role in the context of both treatment response monitoring and risk prediction. Given the rapid developments in scan acceleration techniques and novel image reconstruction, we foresee the possibility of integrating the acquisition of multiple quantitative vessel wall parameters within a single scan session.

Optical Ptychographic Microscope for Quantitative Bio-Mechanical Imaging

NASA Astrophysics Data System (ADS)

Anthony, Nicholas; Cadenazzi, Guido; Nugent, Keith; Abbey, Brian

The role that mechanical forces play in biological processes such as cell movement and death is becoming of significant interest to further develop our understanding of the inner workings of cells. The most common method used to obtain stress information is photoelasticity which maps a samples birefringence, or its direction dependent refractive indices, using polarized light. However this method only provides qualitative data and for stress information to be useful quantitative data is required. Ptychography is a method for quantitatively determining the phase of a samples complex transmission function. The technique relies upon the collection of multiple overlapping coherent diffraction patterns from laterally displaced points on the sample. The overlap of measurement points provides complementary information that significantly aids in the reconstruction of the complex wavefield exiting the sample and allows for quantitative imaging of weakly interacting specimens. Here we describe recent advances at La Trobe University Melbourne on achieving quantitative birefringence mapping using polarized light ptychography with applications in cell mechanics. Australian Synchrotron, ARC Centre of Excellence for Advanced Molecular Imaging.

An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

PubMed

Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

2016-07-01

Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions.

Informatics methods to enable sharing of quantitative imaging research data.

PubMed

Levy, Mia A; Freymann, John B; Kirby, Justin S; Fedorov, Andriy; Fennessy, Fiona M; Eschrich, Steven A; Berglund, Anders E; Fenstermacher, David A; Tan, Yongqiang; Guo, Xiaotao; Casavant, Thomas L; Brown, Bartley J; Braun, Terry A; Dekker, Andre; Roelofs, Erik; Mountz, James M; Boada, Fernando; Laymon, Charles; Oborski, Matt; Rubin, Daniel L

2012-11-01

The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers. Copyright © 2012 Elsevier Inc. All rights reserved.

Using the phase-space imager to analyze partially coherent imaging systems: bright-field, phase contrast, differential interference contrast, differential phase contrast, and spiral phase contrast

NASA Astrophysics Data System (ADS)

Mehta, Shalin B.; Sheppard, Colin J. R.

2010-05-01

Various methods that use large illumination aperture (i.e. partially coherent illumination) have been developed for making transparent (i.e. phase) specimens visible. These methods were developed to provide qualitative contrast rather than quantitative measurement-coherent illumination has been relied upon for quantitative phase analysis. Partially coherent illumination has some important advantages over coherent illumination and can be used for measurement of the specimen's phase distribution. However, quantitative analysis and image computation in partially coherent systems have not been explored fully due to the lack of a general, physically insightful and computationally efficient model of image formation. We have developed a phase-space model that satisfies these requirements. In this paper, we employ this model (called the phase-space imager) to elucidate five different partially coherent systems mentioned in the title. We compute images of an optical fiber under these systems and verify some of them with experimental images. These results and simulated images of a general phase profile are used to compare the contrast and the resolution of the imaging systems. We show that, for quantitative phase imaging of a thin specimen with matched illumination, differential phase contrast offers linear transfer of specimen information to the image. We also show that the edge enhancement properties of spiral phase contrast are compromised significantly as the coherence of illumination is reduced. The results demonstrate that the phase-space imager model provides a useful framework for analysis, calibration, and design of partially coherent imaging methods.

Simple and fast spectral domain algorithm for quantitative phase imaging of living cells with digital holographic microscopy

NASA Astrophysics Data System (ADS)

Min, Junwei; Yao, Baoli; Ketelhut, Steffi; Kemper, Björn

2017-02-01

The modular combination of optical microscopes with digital holographic microscopy (DHM) has been proven to be a powerful tool for quantitative live cell imaging. The introduction of condenser and different microscope objectives (MO) simplifies the usage of the technique and makes it easier to measure different kinds of specimens with different magnifications. However, the high flexibility of illumination and imaging also causes variable phase aberrations that need to be eliminated for high resolution quantitative phase imaging. The existent phase aberrations compensation methods either require add additional elements into the reference arm or need specimen free reference areas or separate reference holograms to build up suitable digital phase masks. These inherent requirements make them unpractical for usage with highly variable illumination and imaging systems and prevent on-line monitoring of living cells. In this paper, we present a simple numerical method for phase aberration compensation based on the analysis of holograms in spatial frequency domain with capabilities for on-line quantitative phase imaging. From a single shot off-axis hologram, the whole phase aberration can be eliminated automatically without numerical fitting or pre-knowledge of the setup. The capabilities and robustness for quantitative phase imaging of living cancer cells are demonstrated.

Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem.

PubMed

Gurcan, Metin N; Tomaszewski, John; Overton, James A; Doyle, Scott; Ruttenberg, Alan; Smith, Barry

2017-02-01

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology - QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts. Copyright © 2016 Elsevier Inc. All rights reserved.

Underwater image enhancement based on the dark channel prior and attenuation compensation

NASA Astrophysics Data System (ADS)

Guo, Qingwen; Xue, Lulu; Tang, Ruichun; Guo, Lingrui

2017-10-01

Aimed at the two problems of underwater imaging, fog effect and color cast, an Improved Segmentation Dark Channel Prior (ISDCP) defogging method is proposed to solve the fog effects caused by physical properties of water. Due to mass refraction of light in the process of underwater imaging, fog effects would lead to image blurring. And color cast is closely related to different degree of attenuation while light with different wavelengths is traveling in water. The proposed method here integrates the ISDCP and quantitative histogram stretching techniques into the image enhancement procedure. Firstly, the threshold value is set during the refinement process of the transmission maps to identify the original mismatching, and to conduct the differentiated defogging process further. Secondly, a method of judging the propagating distance of light is adopted to get the attenuation degree of energy during the propagation underwater. Finally, the image histogram is stretched quantitatively in Red-Green-Blue channel respectively according to the degree of attenuation in each color channel. The proposed method ISDCP can reduce the computational complexity and improve the efficiency in terms of defogging effect to meet the real-time requirements. Qualitative and quantitative comparison for several different underwater scenes reveals that the proposed method can significantly improve the visibility compared with previous methods.

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 for quantitative post-therapy monitoring of Y-90 activity distribution following hepatic radioembolization. PMID:27782730

A collimator optimization method for quantitative imaging: application to Y-90 bremsstrahlung SPECT.

PubMed

Rong, Xing; Frey, Eric C

2013-08-01

Post-therapy quantitative 90Y bremsstrahlung single photon emission computed tomography (SPECT) has shown great potential to provide reliable activity estimates, which are essential for dose verification. Typically 90Y imaging is performed with high- or medium-energy collimators. However, the energy spectrum of 90Y bremsstrahlung photons is substantially different than typical for these collimators. In addition, dosimetry requires quantitative images, and collimators are not typically optimized for such tasks. Optimizing a collimator for 90Y imaging is both novel and potentially important. Conventional optimization methods are not appropriate for 90Y bremsstrahlung photons, which have a continuous and broad energy distribution. In this work, the authors developed a parallel-hole collimator optimization method for quantitative tasks that is particularly applicable to radionuclides with complex emission energy spectra. The authors applied the proposed method to develop an optimal collimator for quantitative 90Y bremsstrahlung SPECT in the context of microsphere radioembolization. To account for the effects of the collimator on both the bias and the variance of the activity estimates, the authors used the root mean squared error (RMSE) of the volume of interest activity estimates as the figure of merit (FOM). In the FOM, the bias due to the null space of the image formation process was taken in account. The RMSE was weighted by the inverse mass to reflect the application to dosimetry; for a different application, more relevant weighting could easily be adopted. The authors proposed a parameterization for the collimator that facilitates the incorporation of the important factors (geometric sensitivity, geometric resolution, and septal penetration fraction) determining collimator performance, while keeping the number of free parameters describing the collimator small (i.e., two parameters). To make the optimization results for quantitative 90Y bremsstrahlung SPECT more general, the authors simulated multiple tumors of various sizes in the liver. The authors realistically simulated human anatomy using a digital phantom and the image formation process using a previously validated and computationally efficient method for modeling the image-degrading effects including object scatter, attenuation, and the full collimator-detector response (CDR). The scatter kernels and CDR function tables used in the modeling method were generated using a previously validated Monte Carlo simulation code. The hole length, hole diameter, and septal thickness of the obtained optimal collimator were 84, 3.5, and 1.4 mm, respectively. Compared to a commercial high-energy general-purpose collimator, the optimal collimator improved the resolution and FOM by 27% and 18%, respectively. The proposed collimator optimization method may be useful for improving quantitative SPECT imaging for radionuclides with complex energy spectra. The obtained optimal collimator provided a substantial improvement in quantitative performance for the microsphere radioembolization task considered.

Quantitative magnetic resonance micro-imaging methods for pharmaceutical research.

PubMed

Mantle, M D

2011-09-30

The use of magnetic resonance imaging (MRI) as a tool in pharmaceutical research is now well established and the current literature covers a multitude of different pharmaceutically relevant research areas. This review focuses on the use of quantitative magnetic resonance micro-imaging techniques and how they have been exploited to extract information that is of direct relevance to the pharmaceutical industry. The article is divided into two main areas. The first half outlines the theoretical aspects of magnetic resonance and deals with basic magnetic resonance theory, the effects of nuclear spin-lattice (T(1)), spin-spin (T(2)) relaxation and molecular diffusion upon image quantitation, and discusses the applications of rapid magnetic resonance imaging techniques. In addition to the theory, the review aims to provide some practical guidelines for the pharmaceutical researcher with an interest in MRI as to which MRI pulse sequences/protocols should be used and when. The second half of the article reviews the recent advances and developments that have appeared in the literature concerning the use of quantitative micro-imaging methods to pharmaceutically relevant research. Copyright © 2010 Elsevier B.V. All rights reserved.

Optofluidic time-stretch quantitative phase microscopy.

PubMed

Guo, Baoshan; Lei, Cheng; Wu, Yi; Kobayashi, Hirofumi; Ito, Takuro; Yalikun, Yaxiaer; Lee, Sangwook; Isozaki, Akihiro; Li, Ming; Jiang, Yiyue; Yasumoto, Atsushi; Di Carlo, Dino; Tanaka, Yo; Yatomi, Yutaka; Ozeki, Yasuyuki; Goda, Keisuke

2018-03-01

Innovations in optical microscopy have opened new windows onto scientific research, industrial quality control, and medical practice over the last few decades. One of such innovations is optofluidic time-stretch quantitative phase microscopy - an emerging method for high-throughput quantitative phase imaging that builds on the interference between temporally stretched signal and reference pulses by using dispersive properties of light in both spatial and temporal domains in an interferometric configuration on a microfluidic platform. It achieves the continuous acquisition of both intensity and phase images with a high throughput of more than 10,000 particles or cells per second by overcoming speed limitations that exist in conventional quantitative phase imaging methods. Applications enabled by such capabilities are versatile and include characterization of cancer cells and microalgal cultures. In this paper, we review the principles and applications of optofluidic time-stretch quantitative phase microscopy and discuss its future perspective. Copyright © 2017 Elsevier Inc. All rights reserved.

Image enhancement using MCNP5 code and MATLAB in neutron radiography.

PubMed

Tharwat, Montaser; Mohamed, Nader; Mongy, T

2014-07-01

This work presents a method that can be used to enhance the neutron radiography (NR) image for objects with high scattering materials like hydrogen, carbon and other light materials. This method used Monte Carlo code, MCNP5, to simulate the NR process and get the flux distribution for each pixel of the image and determines the scattered neutron distribution that caused image blur, and then uses MATLAB to subtract this scattered neutron distribution from the initial image to improve its quality. This work was performed before the commissioning of digital NR system in Jan. 2013. The MATLAB enhancement method is quite a good technique in the case of static based film neutron radiography, while in neutron imaging (NI) technique, image enhancement and quantitative measurement were efficient by using ImageJ software. The enhanced image quality and quantitative measurements were presented in this work. Copyright © 2014 Elsevier Ltd. All rights reserved.

Ptychography: use of quantitative phase information for high-contrast label free time-lapse imaging of living cells

NASA Astrophysics Data System (ADS)

Suman, Rakesh; O'Toole, Peter

2014-03-01

Here we report a novel label free, high contrast and quantitative method for imaging live cells. The technique reconstructs an image from overlapping diffraction patterns using a ptychographical algorithm. The algorithm utilises both amplitude and phase data from the sample to report on quantitative changes related to the refractive index (RI) and thickness of the specimen. We report the ability of this technique to generate high contrast images, to visualise neurite elongation in neuronal cells, and to provide measure of cell proliferation.

An iterative method for near-field Fresnel region polychromatic phase contrast imaging

NASA Astrophysics Data System (ADS)

Carroll, Aidan J.; van Riessen, Grant A.; Balaur, Eugeniu; Dolbnya, Igor P.; Tran, Giang N.; Peele, Andrew G.

2017-07-01

We present an iterative method for polychromatic phase contrast imaging that is suitable for broadband illumination and which allows for the quantitative determination of the thickness of an object given the refractive index of the sample material. Experimental and simulation results suggest the iterative method provides comparable image quality and quantitative object thickness determination when compared to the analytical polychromatic transport of intensity and contrast transfer function methods. The ability of the iterative method to work over a wider range of experimental conditions means the iterative method is a suitable candidate for use with polychromatic illumination and may deliver more utility for laboratory-based x-ray sources, which typically have a broad spectrum.

Dual respiratory and cardiac motion estimation in PET imaging: Methods design and quantitative evaluation.

PubMed

Feng, Tao; Wang, Jizhe; Tsui, Benjamin M W

2018-04-01

The goal of this study was to develop and evaluate four post-reconstruction respiratory and cardiac (R&C) motion vector field (MVF) estimation methods for cardiac 4D PET data. In Method 1, the dual R&C motions were estimated directly from the dual R&C gated images. In Method 2, respiratory motion (RM) and cardiac motion (CM) were separately estimated from the respiratory gated only and cardiac gated only images. The effects of RM on CM estimation were modeled in Method 3 by applying an image-based RM correction on the cardiac gated images before CM estimation, the effects of CM on RM estimation were neglected. Method 4 iteratively models the mutual effects of RM and CM during dual R&C motion estimations. Realistic simulation data were generated for quantitative evaluation of four methods. Almost noise-free PET projection data were generated from the 4D XCAT phantom with realistic R&C MVF using Monte Carlo simulation. Poisson noise was added to the scaled projection data to generate additional datasets of two more different noise levels. All the projection data were reconstructed using a 4D image reconstruction method to obtain dual R&C gated images. The four dual R&C MVF estimation methods were applied to the dual R&C gated images and the accuracy of motion estimation was quantitatively evaluated using the root mean square error (RMSE) of the estimated MVFs. Results show that among the four estimation methods, Methods 2 performed the worst for noise-free case while Method 1 performed the worst for noisy cases in terms of quantitative accuracy of the estimated MVF. Methods 4 and 3 showed comparable results and achieved RMSE lower by up to 35% than that in Method 1 for noisy cases. In conclusion, we have developed and evaluated 4 different post-reconstruction R&C MVF estimation methods for use in 4D PET imaging. Comparison of the performance of four methods on simulated data indicates separate R&C estimation with modeling of RM before CM estimation (Method 3) to be the best option for accurate estimation of dual R&C motion in clinical situation. © 2018 American Association of Physicists in Medicine.

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Technical Performance Assessment

PubMed Central

2017-01-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers (QIBs) to measure changes in these features. Critical to the performance of a QIB in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method and metrics used to assess a QIB for clinical use. It is therefore, difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America (RSNA) and the Quantitative Imaging Biomarker Alliance (QIBA) with technical, radiological and statistical experts developed a set of technical performance analysis methods, metrics and study designs that provide terminology, metrics and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of QIB performance studies so that results from multiple studies can be compared, contrasted or combined. PMID:24919831

Quantitative SIMS Imaging of Agar-Based Microbial Communities.

PubMed

Dunham, Sage J B; Ellis, Joseph F; Baig, Nameera F; Morales-Soto, Nydia; Cao, Tianyuan; Shrout, Joshua D; Bohn, Paul W; Sweedler, Jonathan V

2018-05-01

After several decades of widespread use for mapping elemental ions and small molecular fragments in surface science, secondary ion mass spectrometry (SIMS) has emerged as a powerful analytical tool for molecular imaging in biology. Biomolecular SIMS imaging has primarily been used as a qualitative technique; although the distribution of a single analyte can be accurately determined, it is difficult to map the absolute quantity of a compound or even to compare the relative abundance of one molecular species to that of another. We describe a method for quantitative SIMS imaging of small molecules in agar-based microbial communities. The microbes are cultivated on a thin film of agar, dried under nitrogen, and imaged directly with SIMS. By use of optical microscopy, we show that the area of the agar is reduced by 26 ± 2% (standard deviation) during dehydration, but the overall biofilm morphology and analyte distribution are largely retained. We detail a quantitative imaging methodology, in which the ion intensity of each analyte is (1) normalized to an external quadratic regression curve, (2) corrected for isomeric interference, and (3) filtered for sample-specific noise and lower and upper limits of quantitation. The end result is a two-dimensional surface density image for each analyte. The sample preparation and quantitation methods are validated by quantitatively imaging four alkyl-quinolone and alkyl-quinoline N-oxide signaling molecules (including Pseudomonas quinolone signal) in Pseudomonas aeruginosa colony biofilms. We show that the relative surface densities of the target biomolecules are substantially different from values inferred through direct intensity comparison and that the developed methodologies can be used to quantitatively compare as many ions as there are available standards.

Visualizing dispersive features in 2D image via minimum gradient method

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

He, Yu; Wang, Yan; Shen, Zhi -Xun

Here, we developed a minimum gradient based method to track ridge features in a 2D image plot, which is a typical data representation in many momentum resolved spectroscopy experiments. Through both analytic formulation and numerical simulation, we compare this new method with existing DC (distribution curve) based and higher order derivative based analyses. We find that the new method has good noise resilience and enhanced contrast especially for weak intensity features and meanwhile preserves the quantitative local maxima information from the raw image. An algorithm is proposed to extract 1D ridge dispersion from the 2D image plot, whose quantitative applicationmore » to angle-resolved photoemission spectroscopy measurements on high temperature superconductors is demonstrated.« less

Visualizing dispersive features in 2D image via minimum gradient method

DOE PAGES

He, Yu; Wang, Yan; Shen, Zhi -Xun

2017-07-24

Here, we developed a minimum gradient based method to track ridge features in a 2D image plot, which is a typical data representation in many momentum resolved spectroscopy experiments. Through both analytic formulation and numerical simulation, we compare this new method with existing DC (distribution curve) based and higher order derivative based analyses. We find that the new method has good noise resilience and enhanced contrast especially for weak intensity features and meanwhile preserves the quantitative local maxima information from the raw image. An algorithm is proposed to extract 1D ridge dispersion from the 2D image plot, whose quantitative applicationmore » to angle-resolved photoemission spectroscopy measurements on high temperature superconductors is demonstrated.« less

AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

PubMed

Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

2011-01-01

Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method frequently correspond to subregions of visible spots that may represent post-translational modifications or co-migrating proteins that cannot be visually resolved from adjacent, more abundant proteins on the gel image. Thus, it is possible that this image-based approach may actually improve the realized resolution of the gel, revealing differentially expressed proteins that would not have even been detected as spots by modern spot-based analyses.

Study on Mosaic and Uniform Color Method of Satellite Image Fusion in Large Srea

NASA Astrophysics Data System (ADS)

Liu, S.; Li, H.; Wang, X.; Guo, L.; Wang, R.

2018-04-01

Due to the improvement of satellite radiometric resolution and the color difference for multi-temporal satellite remote sensing images and the large amount of satellite image data, how to complete the mosaic and uniform color process of satellite images is always an important problem in image processing. First of all using the bundle uniform color method and least squares mosaic method of GXL and the dodging function, the uniform transition of color and brightness can be realized in large area and multi-temporal satellite images. Secondly, using Color Mapping software to color mosaic images of 16bit to mosaic images of 8bit based on uniform color method with low resolution reference images. At last, qualitative and quantitative analytical methods are used respectively to analyse and evaluate satellite image after mosaic and uniformity coloring. The test reflects the correlation of mosaic images before and after coloring is higher than 95 % and image information entropy increases, texture features are enhanced which have been proved by calculation of quantitative indexes such as correlation coefficient and information entropy. Satellite image mosaic and color processing in large area has been well implemented.

Accuracy and Precision of Radioactivity Quantification in Nuclear Medicine Images

PubMed Central

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

2012-01-01

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

Hepatitis Diagnosis Using Facial Color Image

NASA Astrophysics Data System (ADS)

Liu, Mingjia; Guo, Zhenhua

Facial color diagnosis is an important diagnostic method in traditional Chinese medicine (TCM). However, due to its qualitative, subjective and experi-ence-based nature, traditional facial color diagnosis has a very limited application in clinical medicine. To circumvent the subjective and qualitative problems of facial color diagnosis of Traditional Chinese Medicine, in this paper, we present a novel computer aided facial color diagnosis method (CAFCDM). The method has three parts: face Image Database, Image Preprocessing Module and Diagnosis Engine. Face Image Database is carried out on a group of 116 patients affected by 2 kinds of liver diseases and 29 healthy volunteers. The quantitative color feature is extracted from facial images by using popular digital image processing techni-ques. Then, KNN classifier is employed to model the relationship between the quantitative color feature and diseases. The results show that the method can properly identify three groups: healthy, severe hepatitis with jaundice and severe hepatitis without jaundice with accuracy higher than 73%.

Quantitative phase microscopy for cellular dynamics based on transport of intensity equation.

PubMed

Li, Ying; Di, Jianglei; Ma, Chaojie; Zhang, Jiwei; Zhong, Jinzhan; Wang, Kaiqiang; Xi, Teli; Zhao, Jianlin

2018-01-08

We demonstrate a simple method for quantitative phase imaging of tiny transparent objects such as living cells based on the transport of intensity equation. The experiments are performed using an inverted bright field microscope upgraded with a flipping imaging module, which enables to simultaneously create two laterally separated images with unequal defocus distances. This add-on module does not include any lenses or gratings and is cost-effective and easy-to-alignment. The validity of this method is confirmed by the measurement of microlens array and human osteoblastic cells in culture, indicating its potential in the applications of dynamically measuring living cells and other transparent specimens in a quantitative, non-invasive and label-free manner.

Accuracy of a remote quantitative image analysis in the whole slide images.

PubMed

Słodkowska, Janina; Markiewicz, Tomasz; Grala, Bartłomiej; Kozłowski, Wojciech; Papierz, Wielisław; Pleskacz, Katarzyna; Murawski, Piotr

2011-03-30

The rationale for choosing a remote quantitative method supporting a diagnostic decision requires some empirical studies and knowledge on scenarios including valid telepathology standards. The tumours of the central nervous system [CNS] are graded on the base of the morphological features and the Ki-67 labelling Index [Ki-67 LI]. Various methods have been applied for Ki-67 LI estimation. Recently we have introduced the Computerized Analysis of Medical Images [CAMI] software for an automated Ki-67 LI counting in the digital images. Aims of our study was to explore the accuracy and reliability of a remote assessment of Ki-67 LI with CAMI software applied to the whole slide images [WSI]. The WSI representing CNS tumours: 18 meningiomas and 10 oligodendrogliomas were stored on the server of the Warsaw University of Technology. The digital copies of entire glass slides were created automatically by the Aperio ScanScope CS with objective 20x or 40x. Aperio's Image Scope software provided functionality for a remote viewing of WSI. The Ki-67 LI assessment was carried on within 2 out of 20 selected fields of view (objective 40x) representing the highest labelling areas in each WSI. The Ki-67 LI counting was performed by 3 various methods: 1) the manual reading in the light microscope - LM, 2) the automated counting with CAMI software on the digital images - DI , and 3) the remote quantitation on the WSIs - as WSI method. The quality of WSIs and technical efficiency of the on-line system were analysed. The comparative statistical analysis was performed for the results obtained by 3 methods of Ki-67 LI counting. The preliminary analysis showed that in 18% of WSI the results of Ki-67 LI differed from those obtained in other 2 methods of counting when the quality of the glass slides was below the standard range. The results of our investigations indicate that the remote automated Ki-67 LI analysis performed with the CAMI algorithm on the whole slide images of meningiomas and oligodendrogliomas could be successfully used as an alternative method to the manual reading as well as to the digital images quantitation with CAMI software. According to our observation a need of a remote supervision/consultation and training for the effective use of remote quantitative analysis of WSI is necessary.

Quantitative Phase Imaging in a Volume Holographic Microscope

NASA Astrophysics Data System (ADS)

Waller, Laura; Luo, Yuan; Barbastathis, George

2010-04-01

We demonstrate a method for quantitative phase imaging in a Volume Holographic Microscope (VHM) from a single exposure, describe the properties of the system and show experimental results. The VHM system uses a multiplexed volume hologram (VH) to laterally separate images from different focal planes. This 3D intensity information is then used to solve the transport of intensity (TIE) equation and recover phase quantitatively. We discuss the modifications to the technique that were made in order to give accurate results.

The quantitative control and matching of an optical false color composite imaging system

NASA Astrophysics Data System (ADS)

Zhou, Chengxian; Dai, Zixin; Pan, Xizhe; Li, Yinxi

1993-10-01

Design of an imaging system for optical false color composite (OFCC) capable of high-precision density-exposure time control and color balance is presented. The system provides high quality FCC image data that can be analyzed using a quantitative calculation method. The quality requirement to each part of the image generation system is defined, and the distribution of satellite remote sensing image information is analyzed. The proposed technology makes it possible to present the remote sensing image data more effectively and accurately.

Use of local noise power spectrum and wavelet analysis in quantitative image quality assurance for EPIDs

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

Lee, Soyoung

Purpose: To investigate the use of local noise power spectrum (NPS) to characterize image noise and wavelet analysis to isolate defective pixels and inter-subpanel flat-fielding artifacts for quantitative quality assurance (QA) of electronic portal imaging devices (EPIDs). Methods: A total of 93 image sets including custom-made bar-pattern images and open exposure images were collected from four iViewGT a-Si EPID systems over three years. Global quantitative metrics such as modulation transform function (MTF), NPS, and detective quantum efficiency (DQE) were computed for each image set. Local NPS was also calculated for individual subpanels by sampling region of interests within each subpanelmore » of the EPID. The 1D NPS, obtained by radially averaging the 2D NPS, was fitted to a power-law function. The r-square value of the linear regression analysis was used as a singular metric to characterize the noise properties of individual subpanels of the EPID. The sensitivity of the local NPS was first compared with the global quantitative metrics using historical image sets. It was then compared with two commonly used commercial QA systems with images collected after applying two different EPID calibration methods (single-level gain and multilevel gain). To detect isolated defective pixels and inter-subpanel flat-fielding artifacts, Haar wavelet transform was applied on the images. Results: Global quantitative metrics including MTF, NPS, and DQE showed little change over the period of data collection. On the contrary, a strong correlation between the local NPS (r-square values) and the variation of the EPID noise condition was observed. The local NPS analysis indicated image quality improvement with the r-square values increased from 0.80 ± 0.03 (before calibration) to 0.85 ± 0.03 (after single-level gain calibration) and to 0.96 ± 0.03 (after multilevel gain calibration), while the commercial QA systems failed to distinguish the image quality improvement between the two calibration methods. With wavelet analysis, defective pixels and inter-subpanel flat-fielding artifacts were clearly identified as spikes after thresholding the inversely transformed images. Conclusions: The proposed local NPS (r-square values) showed superior sensitivity to the noise level variations of individual subpanels compared with global quantitative metrics such as MTF, NPS, and DQE. Wavelet analysis was effective in detecting isolated defective pixels and inter-subpanel flat-fielding artifacts. The proposed methods are promising for the early detection of imaging artifacts of EPIDs.« less

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Automatic 3D segmentation of multiphoton images: a key step for the quantification of human skin.

PubMed

Decencière, Etienne; Tancrède-Bohin, Emmanuelle; Dokládal, Petr; Koudoro, Serge; Pena, Ana-Maria; Baldeweck, Thérèse

2013-05-01

Multiphoton microscopy has emerged in the past decade as a useful noninvasive imaging technique for in vivo human skin characterization. However, it has not been used until now in evaluation clinical trials, mainly because of the lack of specific image processing tools that would allow the investigator to extract pertinent quantitative three-dimensional (3D) information from the different skin components. We propose a 3D automatic segmentation method of multiphoton images which is a key step for epidermis and dermis quantification. This method, based on the morphological watershed and graph cuts algorithms, takes into account the real shape of the skin surface and of the dermal-epidermal junction, and allows separating in 3D the epidermis and the superficial dermis. The automatic segmentation method and the associated quantitative measurements have been developed and validated on a clinical database designed for aging characterization. The segmentation achieves its goals for epidermis-dermis separation and allows quantitative measurements inside the different skin compartments with sufficient relevance. This study shows that multiphoton microscopy associated with specific image processing tools provides access to new quantitative measurements on the various skin components. The proposed 3D automatic segmentation method will contribute to build a powerful tool for characterizing human skin condition. To our knowledge, this is the first 3D approach to the segmentation and quantification of these original images. © 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

Quantitative Imaging of Single Unstained Magnetotactic Bacteria by Coherent X-ray Diffraction Microscopy.

PubMed

Fan, Jiadong; Sun, Zhibin; Zhang, Jian; Huang, Qingjie; Yao, Shengkun; Zong, Yunbing; Kohmura, Yoshiki; Ishikawa, Tetsuya; Liu, Hong; Jiang, Huaidong

2015-06-16

Novel coherent diffraction microscopy provides a powerful lensless imaging method to obtain a better understanding of the microorganism at the nanoscale. Here we demonstrated quantitative imaging of intact unstained magnetotactic bacteria using coherent X-ray diffraction microscopy combined with an iterative phase retrieval algorithm. Although the signal-to-noise ratio of the X-ray diffraction pattern from single magnetotactic bacterium is weak due to low-scattering ability of biomaterials, an 18.6 nm half-period resolution of reconstructed image was achieved by using a hybrid input-output phase retrieval algorithm. On the basis of the quantitative reconstructed images, the morphology and some intracellular structures, such as nucleoid, polyβ-hydroxybutyrate granules, and magnetosomes, were identified, which were also confirmed by scanning electron microscopy and energy dispersive spectroscopy. With the benefit from the quantifiability of coherent diffraction imaging, for the first time to our knowledge, an average density of magnetotactic bacteria was calculated to be ∼1.19 g/cm(3). This technique has a wide range of applications, especially in quantitative imaging of low-scattering biomaterials and multicomponent materials at nanoscale resolution. Combined with the cryogenic technique or X-ray free electron lasers, the method could image cells in a hydrated condition, which helps to maintain their natural structure.

Automated image analysis for quantification of reactive oxygen species in plant leaves.

PubMed

Sekulska-Nalewajko, Joanna; Gocławski, Jarosław; Chojak-Koźniewska, Joanna; Kuźniak, Elżbieta

2016-10-15

The paper presents an image processing method for the quantitative assessment of ROS accumulation areas in leaves stained with DAB or NBT for H 2 O 2 and O 2 - detection, respectively. Three types of images determined by the combination of staining method and background color are considered. The method is based on the principle of supervised machine learning with manually labeled image patterns used for training. The method's algorithm is developed as a JavaScript macro in the public domain Fiji (ImageJ) environment. It allows to select the stained regions of ROS-mediated histochemical reactions, subsequently fractionated according to the weak, medium and intense staining intensity and thus ROS accumulation. It also evaluates total leaf blade area. The precision of ROS accumulation area detection is validated by the Dice Similarity Coefficient in the case of manual patterns. The proposed framework reduces the computation complexity, once prepared, requires less image processing expertise than the competitive methods and represents a routine quantitative imaging assay for a general histochemical image classification. Copyright © 2016 Elsevier Inc. All rights reserved.

The influence of biological and technical factors on quantitative analysis of amyloid PET: Points to consider and recommendations for controlling variability in longitudinal data.

PubMed

Schmidt, Mark E; Chiao, Ping; Klein, Gregory; Matthews, Dawn; Thurfjell, Lennart; Cole, Patricia E; Margolin, Richard; Landau, Susan; Foster, Norman L; Mason, N Scott; De Santi, Susan; Suhy, Joyce; Koeppe, Robert A; Jagust, William

2015-09-01

In vivo imaging of amyloid burden with positron emission tomography (PET) provides a means for studying the pathophysiology of Alzheimer's and related diseases. Measurement of subtle changes in amyloid burden requires quantitative analysis of image data. Reliable quantitative analysis of amyloid PET scans acquired at multiple sites and over time requires rigorous standardization of acquisition protocols, subject management, tracer administration, image quality control, and image processing and analysis methods. We review critical points in the acquisition and analysis of amyloid PET, identify ways in which technical factors can contribute to measurement variability, and suggest methods for mitigating these sources of noise. Improved quantitative accuracy could reduce the sample size necessary to detect intervention effects when amyloid PET is used as a treatment end point and allow more reliable interpretation of change in amyloid burden and its relationship to clinical course. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching

PubMed Central

Chen, Cheng; Wang, Wei; Ozolek, John A.; Rohde, Gustavo K.

2013-01-01

We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be segmented. Segmentation of subsequent, unlabeled, images is then performed by finding the model instance that best matches (in the normalized cross correlation sense) local neighborhood in the input image. We demonstrate the application of our method to segmenting nuclei from a variety of imaging modalities, and quantitatively compare our results to several other methods. Quantitative results using both simulated and real image data show that, while certain methods may work well for certain imaging modalities, our software is able to obtain high accuracy across several imaging modalities studied. Results also demonstrate that, relative to several existing methods, the template-based method we propose presents increased robustness in the sense of better handling variations in illumination, variations in texture from different imaging modalities, providing more smooth and accurate segmentation borders, as well as handling better cluttered nuclei. PMID:23568787

Automatic registration of ICG images using mutual information and perfusion analysis

NASA Astrophysics Data System (ADS)

Kim, Namkug; Seo, Jong-Mo; Lee, June-goo; Kim, Jong Hyo; Park, Kwangsuk; Yu, Hyeong-Gon; Yu, Young Suk; Chung, Hum

2005-04-01

Introduction: Indocyanin green fundus angiographic images (ICGA) of the eyes is useful method in detecting and characterizing the choroidal neovascularization (CNV), which is the major cause of the blindness over 65 years of age. To investigate the quantitative analysis of the blood flow on ICGA, systematic approach for automatic registration of using mutual information and a quantitative analysis was developed. Methods: Intermittent sequential images of indocyanin green angiography were acquired by Heidelberg retinal angiography that uses the laser scanning system for the image acquisition. Misalignment of the each image generated by the minute eye movement of the patients was corrected by the mutual information method because the distribution of the contrast media on image is changing throughout the time sequences. Several region of interest (ROI) were selected by a physician and the intensities of the selected region were plotted according to the time sequences. Results: The registration of ICGA time sequential images is required not only translate transform but also rotational transform. Signal intensities showed variation based on gamma-variate function depending on ROIs and capillary vessels show more variance of signal intensity than major vessels. CNV showed intermediate variance of signal intensity and prolonged transit time. Conclusion: The resulting registered images can be used not only for quantitative analysis, but also for perfusion analysis. Various investigative approached on CNV using this method will be helpful in the characterization of the lesion and follow-up.

Quantitative Ultrasound for Measuring Obstructive Severity in Children with Hydronephrosis.

PubMed

Cerrolaza, Juan J; Peters, Craig A; Martin, Aaron D; Myers, Emmarie; Safdar, Nabile; Linguraru, Marius George

2016-04-01

We define sonographic biomarkers for hydronephrotic renal units that can predict the necessity of diuretic nuclear renography. We selected a cohort of 50 consecutive patients with hydronephrosis of varying severity in whom 2-dimensional sonography and diuretic mercaptoacetyltriglycine renography had been performed. A total of 131 morphological parameters were computed using quantitative image analysis algorithms. Machine learning techniques were then applied to identify ultrasound based safety thresholds that agreed with the t½ for washout. A best fit model was then derived for each threshold level of t½ that would be clinically relevant at 20, 30 and 40 minutes. Receiver operating characteristic curve analysis was performed. Sensitivity, specificity and area under the receiver operating characteristic curve were determined. Improvement obtained by the quantitative imaging method compared to the Society for Fetal Urology grading system and the hydronephrosis index was statistically verified. For the 3 thresholds considered and at 100% sensitivity the specificities of the quantitative imaging method were 94%, 70% and 74%, respectively. Corresponding area under the receiver operating characteristic curve values were 0.98, 0.94 and 0.94, respectively. Improvement obtained by the quantitative imaging method over the Society for Fetal Urology grade and hydronephrosis index was statistically significant (p <0.05 in all cases). Quantitative imaging analysis of renal sonograms in children with hydronephrosis can identify thresholds of clinically significant washout times with 100% sensitivity to decrease the number of diuretic renograms in up to 62% of children. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

A method for normalizing pathology images to improve feature extraction for quantitative pathology.

PubMed

Tam, Allison; Barker, Jocelyn; Rubin, Daniel

2016-01-01

With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology images by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. ICHE may be a useful preprocessing step a digital pathology image processing pipeline.

Quantitative phase imaging method based on an analytical nonparaxial partially coherent phase optical transfer function.

PubMed

Bao, Yijun; Gaylord, Thomas K

2016-11-01

Multifilter phase imaging with partially coherent light (MFPI-PC) is a promising new quantitative phase imaging method. However, the existing MFPI-PC method is based on the paraxial approximation. In the present work, an analytical nonparaxial partially coherent phase optical transfer function is derived. This enables the MFPI-PC to be extended to the realistic nonparaxial case. Simulations over a wide range of test phase objects as well as experimental measurements on a microlens array verify higher levels of imaging accuracy compared to the paraxial method. Unlike the paraxial version, the nonparaxial MFPI-PC with obliquity factor correction exhibits no systematic error. In addition, due to its analytical expression, the increase in computation time compared to the paraxial version is negligible.

Single-exposure quantitative phase imaging in color-coded LED microscopy.

PubMed

Lee, Wonchan; Jung, Daeseong; Ryu, Suho; Joo, Chulmin

2017-04-03

We demonstrate single-shot quantitative phase imaging (QPI) in a platform of color-coded LED microscopy (cLEDscope). The light source in a conventional microscope is replaced by a circular LED pattern that is trisected into subregions with equal area, assigned to red, green, and blue colors. Image acquisition with a color image sensor and subsequent computation based on weak object transfer functions allow for the QPI of a transparent specimen. We also provide a correction method for color-leakage, which may be encountered in implementing our method with consumer-grade LEDs and image sensors. Most commercially available LEDs and image sensors do not provide spectrally isolated emissions and pixel responses, generating significant error in phase estimation in our method. We describe the correction scheme for this color-leakage issue, and demonstrate improved phase measurement accuracy. The computational model and single-exposure QPI capability of our method are presented by showing images of calibrated phase samples and cellular specimens.

Quantitative magnetic resonance imaging in traumatic brain injury.

PubMed

Bigler, E D

2001-04-01

Quantitative neuroimaging has now become a well-established method for analyzing magnetic resonance imaging in traumatic brain injury (TBI). A general review of studies that have examined quantitative changes following TBI is presented. The consensus of quantitative neuroimaging studies is that most brain structures demonstrate changes in volume or surface area after injury. The patterns of atrophy are consistent with the generalized nature of brain injury and diffuse axonal injury. Various clinical caveats are provided including how quantitative neuroimaging findings can be used clinically and in predicting rehabilitation outcome. The future of quantitative neuroimaging also is discussed.

A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.

PubMed

Saito, Akira; Numata, Yasushi; Hamada, Takuya; Horisawa, Tomoyoshi; Cosatto, Eric; Graf, Hans-Peter; Kuroda, Masahiko; Yamamoto, Yoichiro

2016-01-01

Recent developments in molecular pathology and genetic/epigenetic analysis of cancer tissue have resulted in a marked increase in objective and measurable data. In comparison, the traditional morphological analysis approach to pathology diagnosis, which can connect these molecular data and clinical diagnosis, is still mostly subjective. Even though the advent and popularization of digital pathology has provided a boost to computer-aided diagnosis, some important pathological concepts still remain largely non-quantitative and their associated data measurements depend on the pathologist's sense and experience. Such features include pleomorphism and heterogeneity. In this paper, we propose a method for the objective measurement of pleomorphism and heterogeneity, using the cell-level co-occurrence matrix. Our method is based on the widely used Gray-level co-occurrence matrix (GLCM), where relations between neighboring pixel intensity levels are captured into a co-occurrence matrix, followed by the application of analysis functions such as Haralick features. In the pathological tissue image, through image processing techniques, each nucleus can be measured and each nucleus has its own measureable features like nucleus size, roundness, contour length, intra-nucleus texture data (GLCM is one of the methods). In GLCM each nucleus in the tissue image corresponds to one pixel. In this approach the most important point is how to define the neighborhood of each nucleus. We define three types of neighborhoods of a nucleus, then create the co-occurrence matrix and apply Haralick feature functions. In each image pleomorphism and heterogeneity are then determined quantitatively. For our method, one pixel corresponds to one nucleus feature, and we therefore named our method Cell Feature Level Co-occurrence Matrix (CFLCM). We tested this method for several nucleus features. CFLCM is showed as a useful quantitative method for pleomorphism and heterogeneity on histopathological image analysis.

Hematocrit Measurement with R2* and Quantitative Susceptibility Mapping in Postmortem Brain.

PubMed

Walsh, A J; Sun, H; Emery, D J; Wilman, A H

2018-05-24

Noninvasive venous oxygenation quantification with MR imaging will improve the neurophysiologic investigation and the understanding of the pathophysiology in neurologic diseases. Available MR imaging methods are limited by sensitivity to flow and often require assumptions of the hematocrit level. In situ postmortem imaging enables evaluation of methods in a fully deoxygenated environment without flow artifacts, allowing direct calculation of hematocrit. This study compares 2 venous oxygenation quantification methods in in situ postmortem subjects. Transverse relaxation (R2*) mapping and quantitative susceptibility mapping were performed on a whole-body 4.7T MR imaging system. Intravenous measurements in major draining intracranial veins were compared between the 2 methods in 3 postmortem subjects. The quantitative susceptibility mapping technique was also applied in 10 healthy control subjects and compared with reference venous oxygenation values. In 2 early postmortem subjects, R2* mapping and quantitative susceptibility mapping measurements within intracranial veins had a significant and strong correlation ( R 2 = 0.805, P = .004 and R 2 = 0.836, P = .02). Higher R2* and susceptibility values were consistently demonstrated within gravitationally dependent venous segments during the early postmortem period. Hematocrit ranged from 0.102 to 0.580 in postmortem subjects, with R2* and susceptibility as large as 291 seconds -1 and 1.75 ppm, respectively. Measurements of R2* and quantitative susceptibility mapping within large intracranial draining veins have a high correlation in early postmortem subjects. This study supports the use of quantitative susceptibility mapping for evaluation of in vivo venous oxygenation and postmortem hematocrit concentrations. © 2018 by American Journal of Neuroradiology.

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-90 activity distribution following hepatic radioembolization.

A method for operative quantitative interpretation of multispectral images of biological tissues

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Kugeiko, M. M.

2013-10-01

A method for operative retrieval of spatial distributions of biophysical parameters of a biological tissue by using a multispectral image of it has been developed. The method is based on multiple regressions between linearly independent components of the diffuse reflection spectrum of the tissue and unknown parameters. Possibilities of the method are illustrated by an example of determining biophysical parameters of the skin (concentrations of melanin, hemoglobin and bilirubin, blood oxygenation, and scattering coefficient of the tissue). Examples of quantitative interpretation of the experimental data are presented.

Comparative assessment of fluorescent transgene methods for quantitative imaging in human cells.

PubMed

Mahen, Robert; Koch, Birgit; Wachsmuth, Malte; Politi, Antonio Z; Perez-Gonzalez, Alexis; Mergenthaler, Julia; Cai, Yin; Ellenberg, Jan

2014-11-05

Fluorescence tagging of proteins is a widely used tool to study protein function and dynamics in live cells. However, the extent to which different mammalian transgene methods faithfully report on the properties of endogenous proteins has not been studied comparatively. Here we use quantitative live-cell imaging and single-molecule spectroscopy to analyze how different transgene systems affect imaging of the functional properties of the mitotic kinase Aurora B. We show that the transgene method fundamentally influences level and variability of expression and can severely compromise the ability to report on endogenous binding and localization parameters, providing a guide for quantitative imaging studies in mammalian cells. © 2014 Mahen et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

A new hue capturing technique for the quantitative interpretation of liquid crystal images used in convective heat transfer studies

NASA Technical Reports Server (NTRS)

Camci, C.; Kim, K.; Hippensteele, S. A.

1992-01-01

A new image processing based color capturing technique for the quantitative interpretation of liquid crystal images used in convective heat transfer studies is presented. This method is highly applicable to the surfaces exposed to convective heating in gas turbine engines. It is shown that, in the single-crystal mode, many of the colors appearing on the heat transfer surface correlate strongly with the local temperature. A very accurate quantitative approach using an experimentally determined linear hue vs temperature relation is found to be possible. The new hue-capturing process is discussed in terms of the strength of the light source illuminating the heat transfer surface, the effect of the orientation of the illuminating source with respect to the surface, crystal layer uniformity, and the repeatability of the process. The present method is more advantageous than the multiple filter method because of its ability to generate many isotherms simultaneously from a single-crystal image at a high resolution in a very time-efficient manner.

Three-dimensional quantitative flow diagnostics

NASA Technical Reports Server (NTRS)

Miles, Richard B.; Nosenchuck, Daniel M.

1989-01-01

The principles, capabilities, and practical implementation of advanced measurement techniques for the quantitative characterization of three-dimensional flows are reviewed. Consideration is given to particle, Rayleigh, and Raman scattering; fluorescence; flow marking by H2 bubbles, photochromism, photodissociation, and vibrationally excited molecules; light-sheet volume imaging; and stereo imaging. Also discussed are stereo schlieren methods, holographic particle imaging, optical tomography, acoustic and magnetic-resonance imaging, and the display of space-filling data. Extensive diagrams, graphs, photographs, sample images, and tables of numerical data are provided.

3D Actin Network Centerline Extraction with Multiple Active Contours

PubMed Central

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2013-01-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and actin cables. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we propose a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D Total Internal Reflection Fluorescence Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy. Quantitative evaluation of the method using synthetic images shows that for images with SNR above 5.0, the average vertex error measured by the distance between our result and ground truth is 1 voxel, and the average Hausdorff distance is below 10 voxels. PMID:24316442

Dynamic phase differences based on quantitative phase imaging for the objective evaluation of cell behavior.

PubMed

Krizova, Aneta; Collakova, Jana; Dostal, Zbynek; Kvasnica, Lukas; Uhlirova, Hana; Zikmund, Tomas; Vesely, Pavel; Chmelik, Radim

2015-01-01

Quantitative phase imaging (QPI) brought innovation to noninvasive observation of live cell dynamics seen as cell behavior. Unlike the Zernike phase contrast or differential interference contrast, QPI provides quantitative information about cell dry mass distribution. We used such data for objective evaluation of live cell behavioral dynamics by the advanced method of dynamic phase differences (DPDs). The DPDs method is considered a rational instrument offered by QPI. By subtracting the antecedent from the subsequent image in a time-lapse series, only the changes in mass distribution in the cell are detected. The result is either visualized as a two dimensional color-coded projection of these two states of the cell or as a time dependence of changes quantified in picograms. Then in a series of time-lapse recordings, the chain of cell mass distribution changes that would otherwise escape attention is revealed. Consequently, new salient features of live cell behavior should emerge. Construction of the DPDs method and results exhibiting the approach are presented. Advantage of the DPDs application is demonstrated on cells exposed to an osmotic challenge. For time-lapse acquisition of quantitative phase images, the recently developed coherence-controlled holographic microscope was employed.

Dynamic phase differences based on quantitative phase imaging for the objective evaluation of cell behavior

NASA Astrophysics Data System (ADS)

Krizova, Aneta; Collakova, Jana; Dostal, Zbynek; Kvasnica, Lukas; Uhlirova, Hana; Zikmund, Tomas; Vesely, Pavel; Chmelik, Radim

2015-11-01

Quantitative phase imaging (QPI) brought innovation to noninvasive observation of live cell dynamics seen as cell behavior. Unlike the Zernike phase contrast or differential interference contrast, QPI provides quantitative information about cell dry mass distribution. We used such data for objective evaluation of live cell behavioral dynamics by the advanced method of dynamic phase differences (DPDs). The DPDs method is considered a rational instrument offered by QPI. By subtracting the antecedent from the subsequent image in a time-lapse series, only the changes in mass distribution in the cell are detected. The result is either visualized as a two-dimensional color-coded projection of these two states of the cell or as a time dependence of changes quantified in picograms. Then in a series of time-lapse recordings, the chain of cell mass distribution changes that would otherwise escape attention is revealed. Consequently, new salient features of live cell behavior should emerge. Construction of the DPDs method and results exhibiting the approach are presented. Advantage of the DPDs application is demonstrated on cells exposed to an osmotic challenge. For time-lapse acquisition of quantitative phase images, the recently developed coherence-controlled holographic microscope was employed.

Image enhancement in positron emission mammography

NASA Astrophysics Data System (ADS)

Slavine, Nikolai V.; Seiler, Stephen; McColl, Roderick W.; Lenkinski, Robert E.

2017-02-01

Purpose: To evaluate an efficient iterative deconvolution method (RSEMD) for improving the quantitative accuracy of previously reconstructed breast images by commercial positron emission mammography (PEM) scanner. Materials and Methods: The RSEMD method was tested on breast phantom data and clinical PEM imaging data. Data acquisition was performed on a commercial Naviscan Flex Solo II PEM camera. This method was applied to patient breast images previously reconstructed with Naviscan software (MLEM) to determine improvements in resolution, signal to noise ratio (SNR) and contrast to noise ratio (CNR.) Results: In all of the patients' breast studies the post-processed images proved to have higher resolution and lower noise as compared with images reconstructed by conventional methods. In general, the values of SNR reached a plateau at around 6 iterations with an improvement factor of about 2 for post-processed Flex Solo II PEM images. Improvements in image resolution after the application of RSEMD have also been demonstrated. Conclusions: A rapidly converging, iterative deconvolution algorithm with a novel resolution subsets-based approach RSEMD that operates on patient DICOM images has been used for quantitative improvement in breast imaging. The RSEMD method can be applied to clinical PEM images to improve image quality to diagnostically acceptable levels and will be crucial in order to facilitate diagnosis of tumor progression at the earliest stages. The RSEMD method can be considered as an extended Richardson-Lucy algorithm with multiple resolution levels (resolution subsets).

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

Approaches to quantitating the results of differentially dyed cottons

USDA-ARS?s Scientific Manuscript database

The differential dyeing (DD) method has served as a subjective method for visually determining immature cotton fibers. In an attempt to quantitate the results of the differential dyeing method, and thus offer an efficient means of elucidating cotton maturity without visual discretion, image analysi...

Quantitative comparison of bright field and annular bright field imaging modes for characterization of oxygen octahedral tilts

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

Kim, Young-Min; Pennycook, Stephen J.; Borisevich, Albina Y.

Octahedral tilt behavior is increasingly recognized as an important contributing factor to the physical behavior of perovskite oxide materials and especially their interfaces, necessitating the development of high-resolution methods of tilt mapping. There are currently two major approaches for quantitative imaging of tilts in scanning transmission electron microscopy (STEM), bright field (BF) and annular bright field (ABF). In this study, we show that BF STEM can be reliably used for measurements of oxygen octahedral tilts. While optimal conditions for BF imaging are more restricted with respect to sample thickness and defocus, we find that BF imaging with an aberration-corrected microscopemore » with the accelerating voltage of 300 kV gives us the most accurate quantitative measurement of the oxygen column positions. Using the tilted perovskite structure of BiFeO 3 (BFO) as our test sample, we simulate BF and ABF images in a wide range of conditions, identifying the optimal imaging conditions for each mode. Finally, we show that unlike ABF imaging, BF imaging remains directly quantitatively interpretable for a wide range of the specimen mistilt, suggesting that it should be preferable to the ABF STEM imaging for quantitative structure determination.« less

Quantitative comparison of bright field and annular bright field imaging modes for characterization of oxygen octahedral tilts

DOE PAGES

Kim, Young-Min; Pennycook, Stephen J.; Borisevich, Albina Y.

2017-04-29

Octahedral tilt behavior is increasingly recognized as an important contributing factor to the physical behavior of perovskite oxide materials and especially their interfaces, necessitating the development of high-resolution methods of tilt mapping. There are currently two major approaches for quantitative imaging of tilts in scanning transmission electron microscopy (STEM), bright field (BF) and annular bright field (ABF). In this study, we show that BF STEM can be reliably used for measurements of oxygen octahedral tilts. While optimal conditions for BF imaging are more restricted with respect to sample thickness and defocus, we find that BF imaging with an aberration-corrected microscopemore » with the accelerating voltage of 300 kV gives us the most accurate quantitative measurement of the oxygen column positions. Using the tilted perovskite structure of BiFeO 3 (BFO) as our test sample, we simulate BF and ABF images in a wide range of conditions, identifying the optimal imaging conditions for each mode. Finally, we show that unlike ABF imaging, BF imaging remains directly quantitatively interpretable for a wide range of the specimen mistilt, suggesting that it should be preferable to the ABF STEM imaging for quantitative structure determination.« less

Mechanistic and quantitative insight into cell surface targeted molecular imaging agent design.

PubMed

Zhang, Liang; Bhatnagar, Sumit; Deschenes, Emily; Thurber, Greg M

2016-05-05

Molecular imaging agent design involves simultaneously optimizing multiple probe properties. While several desired characteristics are straightforward, including high affinity and low non-specific background signal, in practice there are quantitative trade-offs between these properties. These include plasma clearance, where fast clearance lowers background signal but can reduce target uptake, and binding, where high affinity compounds sometimes suffer from lower stability or increased non-specific interactions. Further complicating probe development, many of the optimal parameters vary depending on both target tissue and imaging agent properties, making empirical approaches or previous experience difficult to translate. Here, we focus on low molecular weight compounds targeting extracellular receptors, which have some of the highest contrast values for imaging agents. We use a mechanistic approach to provide a quantitative framework for weighing trade-offs between molecules. Our results show that specific target uptake is well-described by quantitative simulations for a variety of targeting agents, whereas non-specific background signal is more difficult to predict. Two in vitro experimental methods for estimating background signal in vivo are compared - non-specific cellular uptake and plasma protein binding. Together, these data provide a quantitative method to guide probe design and focus animal work for more cost-effective and time-efficient development of molecular imaging agents.

Ultra-fast quantitative imaging using ptychographic iterative engine based digital micro-mirror device

NASA Astrophysics Data System (ADS)

Sun, Aihui; Tian, Xiaolin; Kong, Yan; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-01-01

As a lensfree imaging technique, ptychographic iterative engine (PIE) method can provide both quantitative sample amplitude and phase distributions avoiding aberration. However, it requires field of view (FoV) scanning often relying on mechanical translation, which not only slows down measuring speed, but also introduces mechanical errors decreasing both resolution and accuracy in retrieved information. In order to achieve high-accurate quantitative imaging with fast speed, digital micromirror device (DMD) is adopted in PIE for large FoV scanning controlled by on/off state coding by DMD. Measurements were implemented using biological samples as well as USAF resolution target, proving high resolution in quantitative imaging using the proposed system. Considering its fast and accurate imaging capability, it is believed the DMD based PIE technique provides a potential solution for medical observation and measurements.

Attenuation correction with region growing method used in the positron emission mammography imaging system

NASA Astrophysics Data System (ADS)

Gu, Xiao-Yue; Li, Lin; Yin, Peng-Fei; Yun, Ming-Kai; Chai, Pei; Huang, Xian-Chao; Sun, Xiao-Li; Wei, Long

2015-10-01

The Positron Emission Mammography imaging system (PEMi) provides a novel nuclear diagnosis method dedicated for breast imaging. With a better resolution than whole body PET, PEMi can detect millimeter-sized breast tumors. To address the requirement of semi-quantitative analysis with a radiotracer concentration map of the breast, a new attenuation correction method based on a three-dimensional seeded region growing image segmentation (3DSRG-AC) method has been developed. The method gives a 3D connected region as the segmentation result instead of image slices. The continuity property of the segmentation result makes this new method free of activity variation of breast tissues. The threshold value chosen is the key process for the segmentation method. The first valley in the grey level histogram of the reconstruction image is set as the lower threshold, which works well in clinical application. Results show that attenuation correction for PEMi improves the image quality and the quantitative accuracy of radioactivity distribution determination. Attenuation correction also improves the probability of detecting small and early breast tumors. Supported by Knowledge Innovation Project of The Chinese Academy of Sciences (KJCX2-EW-N06)

Quantitative imaging of glutathione in live cells using a reversible reaction-based ratiometric fluorescent probe

USDA-ARS?s Scientific Manuscript database

Glutathione (GSH) plays an important role in maintaining redox homeostasis inside cells. Currently, there are no methods available to quantitatively assess the GSH concentration in live cells. Live cell fluorescence imaging revolutionized the understanding of cell biology and has become an indispens...

Using normalization 3D model for automatic clinical brain quantative analysis and evaluation

NASA Astrophysics Data System (ADS)

Lin, Hong-Dun; Yao, Wei-Jen; Hwang, Wen-Ju; Chung, Being-Tau; Lin, Kang-Ping

2003-05-01

Functional medical imaging, such as PET or SPECT, is capable of revealing physiological functions of the brain, and has been broadly used in diagnosing brain disorders by clinically quantitative analysis for many years. In routine procedures, physicians manually select desired ROIs from structural MR images and then obtain physiological information from correspondent functional PET or SPECT images. The accuracy of quantitative analysis thus relies on that of the subjectively selected ROIs. Therefore, standardizing the analysis procedure is fundamental and important in improving the analysis outcome. In this paper, we propose and evaluate a normalization procedure with a standard 3D-brain model to achieve precise quantitative analysis. In the normalization process, the mutual information registration technique was applied for realigning functional medical images to standard structural medical images. Then, the standard 3D-brain model that shows well-defined brain regions was used, replacing the manual ROIs in the objective clinical analysis. To validate the performance, twenty cases of I-123 IBZM SPECT images were used in practical clinical evaluation. The results show that the quantitative analysis outcomes obtained from this automated method are in agreement with the clinical diagnosis evaluation score with less than 3% error in average. To sum up, the method takes advantage of obtaining precise VOIs, information automatically by well-defined standard 3-D brain model, sparing manually drawn ROIs slice by slice from structural medical images in traditional procedure. That is, the method not only can provide precise analysis results, but also improve the process rate for mass medical images in clinical.

Quantitative assessment of image motion blur in diffraction images of moving biological cells

NASA Astrophysics Data System (ADS)

Wang, He; Jin, Changrong; Feng, Yuanming; Qi, Dandan; Sa, Yu; Hu, Xin-Hua

2016-02-01

Motion blur (MB) presents a significant challenge for obtaining high-contrast image data from biological cells with a polarization diffraction imaging flow cytometry (p-DIFC) method. A new p-DIFC experimental system has been developed to evaluate the MB and its effect on image analysis using a time-delay-integration (TDI) CCD camera. Diffraction images of MCF-7 and K562 cells have been acquired with different speed-mismatch ratios and compared to characterize MB quantitatively. Frequency analysis of the diffraction images shows that the degree of MB can be quantified by bandwidth variations of the diffraction images along the motion direction. The analytical results were confirmed by the p-DIFC image data acquired at different speed-mismatch ratios and used to validate a method of numerical simulation of MB on blur-free diffraction images, which provides a useful tool to examine the blurring effect on diffraction images acquired from the same cell. These results provide insights on the dependence of diffraction image on MB and allow significant improvement on rapid biological cell assay with the p-DIFC method.

WE-FG-207B-12: Quantitative Evaluation of a Spectral CT Scanner in a Phantom Study: Results of Spectral Reconstructions

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

Duan, X; Arbique, G; Guild, J

Purpose: To evaluate the quantitative image quality of spectral reconstructions of phantom data from a spectral CT scanner. Methods: The spectral CT scanner (IQon Spectral CT, Philips Healthcare) is equipped with a dual-layer detector and generates conventional 80-140 kVp images and variety of spectral reconstructions, e.g., virtual monochromatic (VM) images, virtual non-contrast (VNC) images, iodine maps, and effective atomic number (Z) images. A cylindrical solid water phantom (Gammex 472, 33 cm diameter and 5 cm thick) with iodine (2.0-20.0 mg I/ml) and calcium (50-600 mg/ml) rod inserts was scanned at 120 kVp and 27 mGy CTDIvol. Spectral reconstructions were evaluatedmore » by comparing image measurements with theoretical values calculated from nominal rod compositions provided by the phantom manufacturer. The theoretical VNC was calculated using water and iodine basis material decomposition, and the theoretical Z was calculated using two common methods, the chemical formula method (Z1) and the dual-energy ratio method (Z2). Results: Beam-hardening-like artifacts between high-attenuation calcium rods (≥300 mg/ml, >800 HU) influenced quantitative measurements, so the quantitative analysis was only performed on iodine rods using the images from the scan with all the calcium rods removed. The CT numbers of the iodine rods in the VM images (50∼150 keV) were close to theoretical values with average difference of 2.4±6.9 HU. Compared with theoretical values, the average difference for iodine concentration, VNC CT number and effective Z of iodine rods were −0.10±0.38 mg/ml, −0.1±8.2 HU, 0.25±0.06 (Z1) and −0.23±0.07 (Z2). Conclusion: The results indicate that the spectral CT scanner generates quantitatively accurate spectral reconstructions at clinically relevant iodine concentrations. Beam-hardening-like artifacts still exist when high-attenuation objects are present and their impact on patient images needs further investigation. YY is an employee of Philips Healthcare.« less

Three-dimensional Hessian matrix-based quantitative vascular imaging of rat iris with optical-resolution photoacoustic microscopy in vivo

NASA Astrophysics Data System (ADS)

Zhao, Huangxuan; Wang, Guangsong; Lin, Riqiang; Gong, Xiaojing; Song, Liang; Li, Tan; Wang, Wenjia; Zhang, Kunya; Qian, Xiuqing; Zhang, Haixia; Li, Lin; Liu, Zhicheng; Liu, Chengbo

2018-04-01

For the diagnosis and evaluation of ophthalmic diseases, imaging and quantitative characterization of vasculature in the iris are very important. The recently developed photoacoustic imaging, which is ultrasensitive in imaging endogenous hemoglobin molecules, provides a highly efficient label-free method for imaging blood vasculature in the iris. However, the development of advanced vascular quantification algorithms is still needed to enable accurate characterization of the underlying vasculature. We have developed a vascular information quantification algorithm by adopting a three-dimensional (3-D) Hessian matrix and applied for processing iris vasculature images obtained with a custom-built optical-resolution photoacoustic imaging system (OR-PAM). For the first time, we demonstrate in vivo 3-D vascular structures of a rat iris with a the label-free imaging method and also accurately extract quantitative vascular information, such as vessel diameter, vascular density, and vascular tortuosity. Our results indicate that the developed algorithm is capable of quantifying the vasculature in the 3-D photoacoustic images of the iris in-vivo, thus enhancing the diagnostic capability of the OR-PAM system for vascular-related ophthalmic diseases in vivo.

[The application of stereology in radiology imaging and cell biology fields].

PubMed

Hu, Na; Wang, Yan; Feng, Yuanming; Lin, Wang

2012-08-01

Stereology is an interdisciplinary method for 3D morphological study developed from mathematics and morphology. It is widely used in medical image analysis and cell biology studies. Because of its unbiased, simple, fast, reliable and non-invasive characteristics, stereology has been widely used in biomedical areas for quantitative analysis and statistics, such as histology, pathology and medical imaging. Because the stereological parameters show distinct differences in different pathology, many scholars use stereological methods to do quantitative analysis in their studies in recent years, for example, in the areas of the condition of cancer cells, tumor grade, disease development and the patient's prognosis, etc. This paper describes the stereological concept and estimation methods, also illustrates the applications of stereology in the fields of CT images, MRI images and cell biology, and finally reflects the universality, the superiority and reliability of stereology.

Quantitation of spatially-localized proteins in tissue samples using MALDI-MRM imaging.

PubMed

Clemis, Elizabeth J; Smith, Derek S; Camenzind, Alexander G; Danell, Ryan M; Parker, Carol E; Borchers, Christoph H

2012-04-17

MALDI imaging allows the creation of a "molecular image" of a tissue slice. This image is reconstructed from the ion abundances in spectra obtained while rastering the laser over the tissue. These images can then be correlated with tissue histology to detect potential biomarkers of, for example, aberrant cell types. MALDI, however, is known to have problems with ion suppression, making it difficult to correlate measured ion abundance with concentration. It would be advantageous to have a method which could provide more accurate protein concentration measurements, particularly for screening applications or for precise comparisons between samples. In this paper, we report the development of a novel MALDI imaging method for the localization and accurate quantitation of proteins in tissues. This method involves optimization of in situ tryptic digestion, followed by reproducible and uniform deposition of an isotopically labeled standard peptide from a target protein onto the tissue, using an aerosol-generating device. Data is acquired by MALDI multiple reaction monitoring (MRM) mass spectrometry (MS), and accurate peptide quantitation is determined from the ratio of MRM transitions for the endogenous unlabeled proteolytic peptides to the corresponding transitions from the applied isotopically labeled standard peptides. In a parallel experiment, the quantity of the labeled peptide applied to the tissue was determined using a standard curve generated from MALDI time-of-flight (TOF) MS data. This external calibration curve was then used to determine the quantity of endogenous peptide in a given area. All standard curves generate by this method had coefficients of determination greater than 0.97. These proof-of-concept experiments using MALDI MRM-based imaging show the feasibility for the precise and accurate quantitation of tissue protein concentrations over 2 orders of magnitude, while maintaining the spatial localization information for the proteins.

Digitized hand-wrist radiographs: comparison of subjective and software-derived image quality at various compression ratios.

PubMed

McCord, Layne K; Scarfe, William C; Naylor, Rachel H; Scheetz, James P; Silveira, Anibal; Gillespie, Kevin R

2007-05-01

The objectives of this study were to compare the effect of JPEG 2000 compression of hand-wrist radiographs on observer image quality qualitative assessment and to compare with a software-derived quantitative image quality index. Fifteen hand-wrist radiographs were digitized and saved as TIFF and JPEG 2000 images at 4 levels of compression (20:1, 40:1, 60:1, and 80:1). The images, including rereads, were viewed by 13 orthodontic residents who determined the image quality rating on a scale of 1 to 5. A quantitative analysis was also performed by using a readily available software based on the human visual system (Image Quality Measure Computer Program, version 6.2, Mitre, Bedford, Mass). ANOVA was used to determine the optimal compression level (P < or =.05). When we compared subjective indexes, JPEG compression greater than 60:1 significantly reduced image quality. When we used quantitative indexes, the JPEG 2000 images had lower quality at all compression ratios compared with the original TIFF images. There was excellent correlation (R2 >0.92) between qualitative and quantitative indexes. Image Quality Measure indexes are more sensitive than subjective image quality assessments in quantifying image degradation with compression. There is potential for this software-based quantitative method in determining the optimal compression ratio for any image without the use of subjective raters.

Diagnostic accuracy of stress perfusion CMR in comparison with quantitative coronary angiography: fully quantitative, semiquantitative, and qualitative assessment.

PubMed

Mordini, Federico E; Haddad, Tariq; Hsu, Li-Yueh; Kellman, Peter; Lowrey, Tracy B; Aletras, Anthony H; Bandettini, W Patricia; Arai, Andrew E

2014-01-01

This study's primary objective was to determine the sensitivity, specificity, and accuracy of fully quantitative stress perfusion cardiac magnetic resonance (CMR) versus a reference standard of quantitative coronary angiography. We hypothesized that fully quantitative analysis of stress perfusion CMR would have high diagnostic accuracy for identifying significant coronary artery stenosis and exceed the accuracy of semiquantitative measures of perfusion and qualitative interpretation. Relatively few studies apply fully quantitative CMR perfusion measures to patients with coronary disease and comparisons to semiquantitative and qualitative methods are limited. Dual bolus dipyridamole stress perfusion CMR exams were performed in 67 patients with clinical indications for assessment of myocardial ischemia. Stress perfusion images alone were analyzed with a fully quantitative perfusion (QP) method and 3 semiquantitative methods including contrast enhancement ratio, upslope index, and upslope integral. Comprehensive exams (cine imaging, stress/rest perfusion, late gadolinium enhancement) were analyzed qualitatively with 2 methods including the Duke algorithm and standard clinical interpretation. A 70% or greater stenosis by quantitative coronary angiography was considered abnormal. The optimum diagnostic threshold for QP determined by receiver-operating characteristic curve occurred when endocardial flow decreased to <50% of mean epicardial flow, which yielded a sensitivity of 87% and specificity of 93%. The area under the curve for QP was 92%, which was superior to semiquantitative methods: contrast enhancement ratio: 78%; upslope index: 82%; and upslope integral: 75% (p = 0.011, p = 0.019, p = 0.004 vs. QP, respectively). Area under the curve for QP was also superior to qualitative methods: Duke algorithm: 70%; and clinical interpretation: 78% (p < 0.001 and p < 0.001 vs. QP, respectively). Fully quantitative stress perfusion CMR has high diagnostic accuracy for detecting obstructive coronary artery disease. QP outperforms semiquantitative measures of perfusion and qualitative methods that incorporate a combination of cine, perfusion, and late gadolinium enhancement imaging. These findings suggest a potential clinical role for quantitative stress perfusion CMR. Copyright © 2014 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Visual Search with Image Modification in Age-Related Macular Degeneration

PubMed Central

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

2012-01-01

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

Real-time label-free quantitative fluorescence microscopy-based detection of ATP using a tunable fluorescent nano-aptasensor platform

NASA Astrophysics Data System (ADS)

Shrivastava, Sajal; Sohn, Il-Yung; Son, Young-Min; Lee, Won-Il; Lee, Nae-Eung

2015-11-01

Although real-time label-free fluorescent aptasensors based on nanomaterials are increasingly recognized as a useful strategy for the detection of target biomolecules with high fidelity, the lack of an imaging-based quantitative measurement platform limits their implementation with biological samples. Here we introduce an ensemble strategy for a real-time label-free fluorescent graphene (Gr) aptasensor platform. This platform employs aptamer length-dependent tunability, thus enabling the reagentless quantitative detection of biomolecules through computational processing coupled with real-time fluorescence imaging data. We demonstrate that this strategy effectively delivers dose-dependent quantitative readouts of adenosine triphosphate (ATP) concentration on chemical vapor deposited (CVD) Gr and reduced graphene oxide (rGO) surfaces, thereby providing cytotoxicity assessment. Compared with conventional fluorescence spectrometry methods, our highly efficient, universally applicable, and rational approach will facilitate broader implementation of imaging-based biosensing platforms for the quantitative evaluation of a range of target molecules.Although real-time label-free fluorescent aptasensors based on nanomaterials are increasingly recognized as a useful strategy for the detection of target biomolecules with high fidelity, the lack of an imaging-based quantitative measurement platform limits their implementation with biological samples. Here we introduce an ensemble strategy for a real-time label-free fluorescent graphene (Gr) aptasensor platform. This platform employs aptamer length-dependent tunability, thus enabling the reagentless quantitative detection of biomolecules through computational processing coupled with real-time fluorescence imaging data. We demonstrate that this strategy effectively delivers dose-dependent quantitative readouts of adenosine triphosphate (ATP) concentration on chemical vapor deposited (CVD) Gr and reduced graphene oxide (rGO) surfaces, thereby providing cytotoxicity assessment. Compared with conventional fluorescence spectrometry methods, our highly efficient, universally applicable, and rational approach will facilitate broader implementation of imaging-based biosensing platforms for the quantitative evaluation of a range of target molecules. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr05839b

Diagnosis of breast cancer biopsies using quantitative phase imaging

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Kandel, Mikhail E.; Han, Kevin; Luo, Zelun; Macias, Virgilia; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

2015-03-01

The standard practice in the histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope. The pathologist looks at certain morphological features, visible under the stain, to diagnose whether a tumor is benign or malignant. This determination is made based on qualitative inspection making it subject to investigator bias. Furthermore, since this method requires a microscopic examination by the pathologist it suffers from low throughput. A quantitative, label-free and high throughput method for detection of these morphological features from images of tissue biopsies is, hence, highly desirable as it would assist the pathologist in making a quicker and more accurate diagnosis of cancers. We present here preliminary results showing the potential of using quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated optical path length maps of unstained breast tissue biopsies using Spatial Light Interference Microscopy (SLIM). As a first step towards diagnosis based on quantitative phase imaging, we carried out a qualitative evaluation of the imaging resolution and contrast of our label-free phase images. These images were shown to two pathologists who marked the tumors present in tissue as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on H&E stained tissue images and the number of agreements were counted. In our experiment, the agreement between SLIM and H&E based diagnosis was measured to be 88%. Our preliminary results demonstrate the potential and promise of SLIM for a push in the future towards quantitative, label-free and high throughput diagnosis.

Quantitative Oxygenation Venography from MRI Phase

PubMed Central

Fan, Audrey P.; Bilgic, Berkin; Gagnon, Louis; Witzel, Thomas; Bhat, Himanshu; Rosen, Bruce R.; Adalsteinsson, Elfar

2014-01-01

Purpose To demonstrate acquisition and processing methods for quantitative oxygenation venograms that map in vivo oxygen saturation (SvO2) along cerebral venous vasculature. Methods Regularized quantitative susceptibility mapping (QSM) is used to reconstruct susceptibility values and estimate SvO2 in veins. QSM with ℓ1 and ℓ2 regularization are compared in numerical simulations of vessel structures with known magnetic susceptibility. Dual-echo, flow-compensated phase images are collected in three healthy volunteers to create QSM images. Bright veins in the susceptibility maps are vectorized and used to form a three-dimensional vascular mesh, or venogram, along which to display SvO2 values from QSM. Results Quantitative oxygenation venograms that map SvO2 along brain vessels of arbitrary orientation and geometry are shown in vivo. SvO2 values in major cerebral veins lie within the normal physiological range reported by 15O positron emission tomography. SvO2 from QSM is consistent with previous MR susceptometry methods for vessel segments oriented parallel to the main magnetic field. In vessel simulations, ℓ1 regularization results in less than 10% SvO2 absolute error across all vessel tilt orientations and provides more accurate SvO2 estimation than ℓ2 regularization. Conclusion The proposed analysis of susceptibility images enables reliable mapping of quantitative SvO2 along venograms and may facilitate clinical use of venous oxygenation imaging. PMID:24006229

Development and evaluation of a model-based downscatter compensation method for quantitative I-131 SPECT

PubMed Central

Song, Na; Du, Yong; He, Bin; Frey, Eric C.

2011-01-01

Purpose: The radionuclide 131I has found widespread use in targeted radionuclide therapy (TRT), partly due to the fact that it emits photons that can be imaged to perform treatment planning or posttherapy dose verification as well as beta rays that are suitable for therapy. In both the treatment planning and dose verification applications, it is necessary to estimate the activity distribution in organs or tumors at several time points. In vivo estimates of the 131I activity distribution at each time point can be obtained from quantitative single-photon emission computed tomography (QSPECT) images and organ activity estimates can be obtained either from QSPECT images or quantification of planar projection data. However, in addition to the photon used for imaging, 131I decay results in emission of a number of other higher-energy photons with significant abundances. These higher-energy photons can scatter in the body, collimator, or detector and be counted in the 364 keV photopeak energy window, resulting in reduced image contrast and degraded quantitative accuracy; these photons are referred to as downscatter. The goal of this study was to develop and evaluate a model-based downscatter compensation method specifically designed for the compensation of high-energy photons emitted by 131I and detected in the imaging energy window. Methods: In the evaluation study, we used a Monte Carlo simulation (MCS) code that had previously been validated for other radionuclides. Thus, in preparation for the evaluation study, we first validated the code for 131I imaging simulation by comparison with experimental data. Next, we assessed the accuracy of the downscatter model by comparing downscatter estimates with MCS results. Finally, we combined the downscatter model with iterative reconstruction-based compensation for attenuation (A) and scatter (S) and the full (D) collimator-detector response of the 364 keV photons to form a comprehensive compensation method. We evaluated this combined method in terms of quantitative accuracy using the realistic 3D NCAT phantom and an activity distribution obtained from patient studies. We compared the accuracy of organ activity estimates in images reconstructed with and without addition of downscatter compensation from projections with and without downscatter contamination. Results: We observed that the proposed method provided substantial improvements in accuracy compared to no downscatter compensation and had accuracies comparable to reconstructions from projections without downscatter contamination. Conclusions: The results demonstrate that the proposed model-based downscatter compensation method is effective and may have a role in quantitative 131I imaging. PMID:21815394

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

Bogunovic, Hrvoje; Pozo, Jose Maria; Villa-Uriol, Maria Cruz

Purpose: To evaluate the suitability of an improved version of an automatic segmentation method based on geodesic active regions (GAR) for segmenting cerebral vasculature with aneurysms from 3D x-ray reconstruction angiography (3DRA) and time of flight magnetic resonance angiography (TOF-MRA) images available in the clinical routine. Methods: Three aspects of the GAR method have been improved: execution time, robustness to variability in imaging protocols, and robustness to variability in image spatial resolutions. The improved GAR was retrospectively evaluated on images from patients containing intracranial aneurysms in the area of the Circle of Willis and imaged with two modalities: 3DRA andmore » TOF-MRA. Images were obtained from two clinical centers, each using different imaging equipment. Evaluation included qualitative and quantitative analyses of the segmentation results on 20 images from 10 patients. The gold standard was built from 660 cross-sections (33 per image) of vessels and aneurysms, manually measured by interventional neuroradiologists. GAR has also been compared to an interactive segmentation method: isointensity surface extraction (ISE). In addition, since patients had been imaged with the two modalities, we performed an intermodality agreement analysis with respect to both the manual measurements and each of the two segmentation methods. Results: Both GAR and ISE differed from the gold standard within acceptable limits compared to the imaging resolution. GAR (ISE) had an average accuracy of 0.20 (0.24) mm for 3DRA and 0.27 (0.30) mm for TOF-MRA, and had a repeatability of 0.05 (0.20) mm. Compared to ISE, GAR had a lower qualitative error in the vessel region and a lower quantitative error in the aneurysm region. The repeatability of GAR was superior to manual measurements and ISE. The intermodality agreement was similar between GAR and the manual measurements. Conclusions: The improved GAR method outperformed ISE qualitatively as well as quantitatively and is suitable for segmenting 3DRA and TOF-MRA images from clinical routine.« less

Estimating weak ratiometric signals in imaging data. II. Meta-analysis with multiple, dual-channel datasets.

PubMed

Sornborger, Andrew; Broder, Josef; Majumder, Anirban; Srinivasamoorthy, Ganesh; Porter, Erika; Reagin, Sean S; Keith, Charles; Lauderdale, James D

2008-09-01

Ratiometric fluorescent indicators are used for making quantitative measurements of a variety of physiological variables. Their utility is often limited by noise. This is the second in a series of papers describing statistical methods for denoising ratiometric data with the aim of obtaining improved quantitative estimates of variables of interest. Here, we outline a statistical optimization method that is designed for the analysis of ratiometric imaging data in which multiple measurements have been taken of systems responding to the same stimulation protocol. This method takes advantage of correlated information across multiple datasets for objectively detecting and estimating ratiometric signals. We demonstrate our method by showing results of its application on multiple, ratiometric calcium imaging experiments.

Quantitative Analysis Tools and Digital Phantoms for Deformable Image Registration Quality Assurance.

PubMed

Kim, Haksoo; Park, Samuel B; Monroe, James I; Traughber, Bryan J; Zheng, Yiran; Lo, Simon S; Yao, Min; Mansur, David; Ellis, Rodney; Machtay, Mitchell; Sohn, Jason W

2015-08-01

This article proposes quantitative analysis tools and digital phantoms to quantify intrinsic errors of deformable image registration (DIR) systems and establish quality assurance (QA) procedures for clinical use of DIR systems utilizing local and global error analysis methods with clinically realistic digital image phantoms. Landmark-based image registration verifications are suitable only for images with significant feature points. To address this shortfall, we adapted a deformation vector field (DVF) comparison approach with new analysis techniques to quantify the results. Digital image phantoms are derived from data sets of actual patient images (a reference image set, R, a test image set, T). Image sets from the same patient taken at different times are registered with deformable methods producing a reference DVFref. Applying DVFref to the original reference image deforms T into a new image R'. The data set, R', T, and DVFref, is from a realistic truth set and therefore can be used to analyze any DIR system and expose intrinsic errors by comparing DVFref and DVFtest. For quantitative error analysis, calculating and delineating differences between DVFs, 2 methods were used, (1) a local error analysis tool that displays deformation error magnitudes with color mapping on each image slice and (2) a global error analysis tool that calculates a deformation error histogram, which describes a cumulative probability function of errors for each anatomical structure. Three digital image phantoms were generated from three patients with a head and neck, a lung and a liver cancer. The DIR QA was evaluated using the case with head and neck. © The Author(s) 2014.

Metrology Standards for Quantitative Imaging Biomarkers

PubMed Central

Obuchowski, Nancy A.; Kessler, Larry G.; Raunig, David L.; Gatsonis, Constantine; Huang, Erich P.; Kondratovich, Marina; McShane, Lisa M.; Reeves, Anthony P.; Barboriak, Daniel P.; Guimaraes, Alexander R.; Wahl, Richard L.

2015-01-01

Although investigators in the imaging community have been active in developing and evaluating quantitative imaging biomarkers (QIBs), the development and implementation of QIBs have been hampered by the inconsistent or incorrect use of terminology or methods for technical performance and statistical concepts. Technical performance is an assessment of how a test performs in reference objects or subjects under controlled conditions. In this article, some of the relevant statistical concepts are reviewed, methods that can be used for evaluating and comparing QIBs are described, and some of the technical performance issues related to imaging biomarkers are discussed. More consistent and correct use of terminology and study design principles will improve clinical research, advance regulatory science, and foster better care for patients who undergo imaging studies. © RSNA, 2015 PMID:26267831

Temporal Lobe Epilepsy: Quantitative MR Volumetry in Detection of Hippocampal Atrophy

PubMed Central

Farid, Nikdokht; Girard, Holly M.; Kemmotsu, Nobuko; Smith, Michael E.; Magda, Sebastian W.; Lim, Wei Y.; Lee, Roland R.

2012-01-01

Purpose: To determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE). Materials and Methods: This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated by using U.S. Food and Drug Administration–cleared software for automated quantitative MR imaging analysis (NeuroQuant). Results of quantitative MR imaging were compared with visual detection of atrophy, and, when available, with histologic specimens. Receiver operating characteristic analyses were performed to determine the optimal sensitivity and specificity of quantitative MR imaging for detecting HA and asymmetry. A linear classifier with cross validation was used to estimate the ability of quantitative MR imaging to help lateralize the seizure focus. Results: Quantitative MR imaging–derived hippocampal asymmetries discriminated patients with TLE from control subjects with high sensitivity (86.7%–89.5%) and specificity (92.2%–94.1%). When a linear classifier was used to discriminate left versus right TLE, hippocampal asymmetry achieved 94% classification accuracy. Volumetric asymmetries of other subcortical structures did not improve classification. Compared with invasive video electroencephalographic recordings, lateralization accuracy was 88% with quantitative MR imaging and 85% with visual inspection of volumetric MR imaging studies but only 76% with visual inspection of clinical MR imaging studies. Conclusion: Quantitative MR imaging can depict the presence and laterality of HA in TLE with accuracy rates that may exceed those achieved with visual inspection of clinical MR imaging studies. Thus, quantitative MR imaging may enhance standard visual analysis, providing a useful and viable means for translating volumetric analysis into clinical practice. © RSNA, 2012 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12112638/-/DC1 PMID:22723496

Three-dimensional label-free imaging and quantification of lipid droplets in live hepatocytes

NASA Astrophysics Data System (ADS)

Kim, Kyoohyun; Lee, Seoeun; Yoon, Jonghee; Heo, Jihan; Choi, Chulhee; Park, Yongkeun

2016-11-01

Lipid droplets (LDs) are subcellular organelles with important roles in lipid storage and metabolism and involved in various diseases including cancer, obesity, and diabetes. Conventional methods, however, have limited ability to provide quantitative information on individual LDs and have limited capability for three-dimensional (3-D) imaging of LDs in live cells especially for fast acquisition of 3-D dynamics. Here, we present an optical method based on 3-D quantitative phase imaging to measure the 3-D structural distribution and biochemical parameters (concentration and dry mass) of individual LDs in live cells without using exogenous labelling agents. The biochemical change of LDs under oleic acid treatment was quantitatively investigated, and 4-D tracking of the fast dynamics of LDs revealed the intracellular transport of LDs in live cells.

A method for three-dimensional quantitative observation of the microstructure of biological samples

NASA Astrophysics Data System (ADS)

Wang, Pengfei; Chen, Dieyan; Ma, Wanyun; Wu, Hongxin; Ji, Liang; Sun, Jialin; Lv, Danyu; Zhang, Lu; Li, Ying; Tian, Ning; Zheng, Jinggao; Zhao, Fengying

2009-07-01

Contemporary biology has developed into the era of cell biology and molecular biology, and people try to study the mechanism of all kinds of biological phenomena at the microcosmic level now. Accurate description of the microstructure of biological samples is exigent need from many biomedical experiments. This paper introduces a method for 3-dimensional quantitative observation on the microstructure of vital biological samples based on two photon laser scanning microscopy (TPLSM). TPLSM is a novel kind of fluorescence microscopy, which has excellence in its low optical damage, high resolution, deep penetration depth and suitability for 3-dimensional (3D) imaging. Fluorescent stained samples were observed by TPLSM, and afterward the original shapes of them were obtained through 3D image reconstruction. The spatial distribution of all objects in samples as well as their volumes could be derived by image segmentation and mathematic calculation. Thus the 3-dimensionally and quantitatively depicted microstructure of the samples was finally derived. We applied this method to quantitative analysis of the spatial distribution of chromosomes in meiotic mouse oocytes at metaphase, and wonderful results came out last.

A Computer-Aided Analysis Method of SPECT Brain Images for Quantitative Treatment Monitoring: Performance Evaluations and Clinical Applications.

PubMed

Zheng, Xiujuan; Wei, Wentao; Huang, Qiu; Song, Shaoli; Wan, Jieqing; Huang, Gang

2017-01-01

The objective and quantitative analysis of longitudinal single photon emission computed tomography (SPECT) images are significant for the treatment monitoring of brain disorders. Therefore, a computer aided analysis (CAA) method is introduced to extract a change-rate map (CRM) as a parametric image for quantifying the changes of regional cerebral blood flow (rCBF) in longitudinal SPECT brain images. The performances of the CAA-CRM approach in treatment monitoring are evaluated by the computer simulations and clinical applications. The results of computer simulations show that the derived CRMs have high similarities with their ground truths when the lesion size is larger than system spatial resolution and the change rate is higher than 20%. In clinical applications, the CAA-CRM approach is used to assess the treatment of 50 patients with brain ischemia. The results demonstrate that CAA-CRM approach has a 93.4% accuracy of recovered region's localization. Moreover, the quantitative indexes of recovered regions derived from CRM are all significantly different among the groups and highly correlated with the experienced clinical diagnosis. In conclusion, the proposed CAA-CRM approach provides a convenient solution to generate a parametric image and derive the quantitative indexes from the longitudinal SPECT brain images for treatment monitoring.

Statistical issues in the comparison of quantitative imaging biomarker algorithms using pulmonary nodule volume as an example.

PubMed

Obuchowski, Nancy A; Barnhart, Huiman X; Buckler, Andrew J; Pennello, Gene; Wang, Xiao-Feng; Kalpathy-Cramer, Jayashree; Kim, Hyun J Grace; Reeves, Anthony P

2015-02-01

Quantitative imaging biomarkers are being used increasingly in medicine to diagnose and monitor patients' disease. The computer algorithms that measure quantitative imaging biomarkers have different technical performance characteristics. In this paper we illustrate the appropriate statistical methods for assessing and comparing the bias, precision, and agreement of computer algorithms. We use data from three studies of pulmonary nodules. The first study is a small phantom study used to illustrate metrics for assessing repeatability. The second study is a large phantom study allowing assessment of four algorithms' bias and reproducibility for measuring tumor volume and the change in tumor volume. The third study is a small clinical study of patients whose tumors were measured on two occasions. This study allows a direct assessment of six algorithms' performance for measuring tumor change. With these three examples we compare and contrast study designs and performance metrics, and we illustrate the advantages and limitations of various common statistical methods for quantitative imaging biomarker studies. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Visualisation and quantitative analysis of the rodent malaria liver stage by real time imaging.

PubMed

Ploemen, Ivo H J; Prudêncio, Miguel; Douradinha, Bruno G; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J F; Hermsen, Cornelus C; Sauerwein, Robert W; Baptista, Fernanda G; Mota, Maria M; Waters, Andrew P; Que, Ivo; Lowik, Clemens W G M; Khan, Shahid M; Janse, Chris J; Franke-Fayard, Blandine M D

2009-11-18

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luc(con), expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1-5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium.

Visualisation and Quantitative Analysis of the Rodent Malaria Liver Stage by Real Time Imaging

PubMed Central

Douradinha, Bruno G.; Ramesar, Jai; Fonager, Jannik; van Gemert, Geert-Jan; Luty, Adrian J. F.; Hermsen, Cornelus C.; Sauerwein, Robert W.; Baptista, Fernanda G.; Mota, Maria M.; Waters, Andrew P.; Que, Ivo; Lowik, Clemens W. G. M.; Khan, Shahid M.; Janse, Chris J.; Franke-Fayard, Blandine M. D.

2009-01-01

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luccon, expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1–5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium. PMID:19924309

Non-interferometric quantitative phase imaging of yeast cells

NASA Astrophysics Data System (ADS)

Poola, Praveen K.; Pandiyan, Vimal Prabhu; John, Renu

2015-12-01

Real-time imaging of live cells is quite difficult without the addition of external contrast agents. Various methods for quantitative phase imaging of living cells have been proposed like digital holographic microscopy and diffraction phase microscopy. In this paper, we report theoretical and experimental results of quantitative phase imaging of live yeast cells with nanometric precision using transport of intensity equations (TIE). We demonstrate nanometric depth sensitivity in imaging live yeast cells using this technique. This technique being noninterferometric, does not need any coherent light sources and images can be captured through a regular bright-field microscope. This real-time imaging technique would deliver the depth or 3-D volume information of cells and is highly promising in real-time digital pathology applications, screening of pathogens and staging of diseases like malaria as it does not need any preprocessing of samples.

A Quantitative Three-Dimensional Image Analysis Tool for Maximal Acquisition of Spatial Heterogeneity Data.

PubMed

Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios

2017-02-01

Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.

MR Imaging-based Semi-quantitative Methods for Knee Osteoarthritis

PubMed Central

JARRAYA, Mohamed; HAYASHI, Daichi; ROEMER, Frank Wolfgang; GUERMAZI, Ali

2016-01-01

Magnetic resonance imaging (MRI)-based semi-quantitative (SQ) methods applied to knee osteoarthritis (OA) have been introduced during the last decade and have fundamentally changed our understanding of knee OA pathology since then. Several epidemiological studies and clinical trials have used MRI-based SQ methods to evaluate different outcome measures. Interest in MRI-based SQ scoring system has led to continuous update and refinement. This article reviews the different SQ approaches for MRI-based whole organ assessment of knee OA and also discuss practical aspects of whole joint assessment. PMID:26632537

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

A method for normalizing pathology images to improve feature extraction for quantitative pathology

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

Tam, Allison; Barker, Jocelyn; Rubin, Daniel

Purpose: With the advent of digital slide scanning technologies and the potential proliferation of large repositories of digital pathology images, many research studies can leverage these data for biomedical discovery and to develop clinical applications. However, quantitative analysis of digital pathology images is impeded by batch effects generated by varied staining protocols and staining conditions of pathological slides. Methods: To overcome this problem, this paper proposes a novel, fully automated stain normalization method to reduce batch effects and thus aid research in digital pathology applications. Their method, intensity centering and histogram equalization (ICHE), normalizes a diverse set of pathology imagesmore » by first scaling the centroids of the intensity histograms to a common point and then applying a modified version of contrast-limited adaptive histogram equalization. Normalization was performed on two datasets of digitized hematoxylin and eosin (H&E) slides of different tissue slices from the same lung tumor, and one immunohistochemistry dataset of digitized slides created by restaining one of the H&E datasets. Results: The ICHE method was evaluated based on image intensity values, quantitative features, and the effect on downstream applications, such as a computer aided diagnosis. For comparison, three methods from the literature were reimplemented and evaluated using the same criteria. The authors found that ICHE not only improved performance compared with un-normalized images, but in most cases showed improvement compared with previous methods for correcting batch effects in the literature. Conclusions: ICHE may be a useful preprocessing step a digital pathology image processing pipeline.« less

Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures.

PubMed

Larue, Ruben T H M; Defraene, Gilles; De Ruysscher, Dirk; Lambin, Philippe; van Elmpt, Wouter

2017-02-01

Quantitative analysis of tumour characteristics based on medical imaging is an emerging field of research. In recent years, quantitative imaging features derived from CT, positron emission tomography and MR scans were shown to be of added value in the prediction of outcome parameters in oncology, in what is called the radiomics field. However, results might be difficult to compare owing to a lack of standardized methodologies to conduct quantitative image analyses. In this review, we aim to present an overview of the current challenges, technical routines and protocols that are involved in quantitative imaging studies. The first issue that should be overcome is the dependency of several features on the scan acquisition and image reconstruction parameters. Adopting consistent methods in the subsequent target segmentation step is evenly crucial. To further establish robust quantitative image analyses, standardization or at least calibration of imaging features based on different feature extraction settings is required, especially for texture- and filter-based features. Several open-source and commercial software packages to perform feature extraction are currently available, all with slightly different functionalities, which makes benchmarking quite challenging. The number of imaging features calculated is typically larger than the number of patients studied, which emphasizes the importance of proper feature selection and prediction model-building routines to prevent overfitting. Even though many of these challenges still need to be addressed before quantitative imaging can be brought into daily clinical practice, radiomics is expected to be a critical component for the integration of image-derived information to personalize treatment in the future.

A New Method to Comprehensively Diagnose Shock Waves in the Solar Atmosphere Based on Simultaneous Spectroscopic and Imaging Observations

NASA Astrophysics Data System (ADS)

Ruan, Wenzhi; Yan, Limei; He, Jiansen; Zhang, Lei; Wang, Linghua; Wei, Yong

2018-06-01

Shock waves are believed to play an important role in plasma heating. The shock-like temporal jumps in radiation intensity and Doppler shift have been identified in the solar atmosphere. However, a quantitative diagnosis of the shocks in the solar atmosphere is still lacking, seriously hindering the understanding of shock dissipative heating of the solar atmosphere. Here, we propose a new method to realize the goal of the shock quantitative diagnosis, based on Rankine–Hugoniot equations and taking the advantages of simultaneous imaging and spectroscopic observations from, e.g., IRIS (Interface Region Imaging Spectrograph). Because of this method, the key parameters of shock candidates can be derived, such as the bulk velocity and temperature of the plasma in the upstream and downstream, the propagation speed and direction. The method is applied to the shock candidates observed by IRIS, and the overall characteristics of the shocks are revealed quantitatively for the first time. This method is also tested with the help of forward modeling, i.e., virtual observations of simulated shocks. The parameters obtained from the method are consistent with the parameters of the shock formed in the model and are independent of the viewing direction. Therefore, the method we proposed here is applicable to the quantitative and comprehensive diagnosis of the observed shocks in the solar atmosphere.

Analytical robustness of quantitative NIR chemical imaging for Islamic paper characterization

NASA Astrophysics Data System (ADS)

Mahgoub, Hend; Gilchrist, John R.; Fearn, Thomas; Strlič, Matija

2017-07-01

Recently, spectral imaging techniques such as Multispectral (MSI) and Hyperspectral Imaging (HSI) have gained importance in the field of heritage conservation. This paper explores the analytical robustness of quantitative chemical imaging for Islamic paper characterization by focusing on the effect of different measurement and processing parameters, i.e. acquisition conditions and calibration on the accuracy of the collected spectral data. This will provide a better understanding of the technique that can provide a measure of change in collections through imaging. For the quantitative model, special calibration target was devised using 105 samples from a well-characterized reference Islamic paper collection. Two material properties were of interest: starch sizing and cellulose degree of polymerization (DP). Multivariate data analysis methods were used to develop discrimination and regression models which were used as an evaluation methodology for the metrology of quantitative NIR chemical imaging. Spectral data were collected using a pushbroom HSI scanner (Gilden Photonics Ltd) in the 1000-2500 nm range with a spectral resolution of 6.3 nm using a mirror scanning setup and halogen illumination. Data were acquired at different measurement conditions and acquisition parameters. Preliminary results showed the potential of the evaluation methodology to show that measurement parameters such as the use of different lenses and different scanning backgrounds may not have a great influence on the quantitative results. Moreover, the evaluation methodology allowed for the selection of the best pre-treatment method to be applied to the data.

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

PubMed

Apostolou, N; Papazoglou, Th; Koutsouris, D

2006-01-01

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

Quantitative Determination of Photosynthetic Pigments in Green Beans Using Thin-Layer Chromatography and a Flatbed Scanner as Densitometer

ERIC Educational Resources Information Center

Valverde, Juan; This, Herve; Vignolle, Marc

2007-01-01

A simple method for the quantitative determination of photosynthetic pigments extracted from green beans using thin-layer chromatography is proposed. Various extraction methods are compared, and it is shown how a simple flatbed scanner and free software for image processing can give a quantitative determination of pigments. (Contains 5 figures.)

Quantitative phase imaging of biological cells and tissues using singleshot white light interference microscopy and phase subtraction method for extended range of measurement

NASA Astrophysics Data System (ADS)

Mehta, Dalip Singh; Sharma, Anuradha; Dubey, Vishesh; Singh, Veena; Ahmad, Azeem

2016-03-01

We present a single-shot white light interference microscopy for the quantitative phase imaging (QPI) of biological cells and tissues. A common path white light interference microscope is developed and colorful white light interferogram is recorded by three-chip color CCD camera. The recorded white light interferogram is decomposed into the red, green and blue color wavelength component interferograms and processed it to find out the RI for different color wavelengths. The decomposed interferograms are analyzed using local model fitting (LMF)" algorithm developed for reconstructing the phase map from single interferogram. LMF is slightly off-axis interferometric QPI method which is a single-shot method that employs only a single image, so it is fast and accurate. The present method is very useful for dynamic process where path-length changes at millisecond level. From the single interferogram a wavelength-dependent quantitative phase imaging of human red blood cells (RBCs) are reconstructed and refractive index is determined. The LMF algorithm is simple to implement and is efficient in computation. The results are compared with the conventional phase shifting interferometry and Hilbert transform techniques.

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

PubMed Central

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

2013-01-01

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

Comparative study of quantitative phase imaging techniques for refractometry of optical fibers

NASA Astrophysics Data System (ADS)

de Dorlodot, Bertrand; Bélanger, Erik; Bérubé, Jean-Philippe; Vallée, Réal; Marquet, Pierre

2018-02-01

The refractive index difference profile of optical fibers is the key design parameter because it determines, among other properties, the insertion losses and propagating modes. Therefore, an accurate refractive index profiling method is of paramount importance to their development and optimization. Quantitative phase imaging (QPI) is one of the available tools to retrieve structural characteristics of optical fibers, including the refractive index difference profile. Having the advantage of being non-destructive, several different QPI methods have been developed over the last decades. Here, we present a comparative study of three different available QPI techniques, namely the transport-of-intensity equation, quadriwave lateral shearing interferometry and digital holographic microscopy. To assess the accuracy and precision of those QPI techniques, quantitative phase images of the core of a well-characterized optical fiber have been retrieved for each of them and a robust image processing procedure has been applied in order to retrieve their refractive index difference profiles. As a result, even if the raw images for all the three QPI methods were suffering from different shortcomings, our robust automated image-processing pipeline successfully corrected these. After this treatment, all three QPI techniques yielded accurate, reliable and mutually consistent refractive index difference profiles in agreement with the accuracy and precision of the refracted near-field benchmark measurement.

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods

PubMed Central

Wells, Darren M.; French, Andrew P.; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein; Bennett, Malcolm J.; Pridmore, Tony P.

2012-01-01

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana. PMID:22527394

Recovering the dynamics of root growth and development using novel image acquisition and analysis methods.

PubMed

Wells, Darren M; French, Andrew P; Naeem, Asad; Ishaq, Omer; Traini, Richard; Hijazi, Hussein I; Hijazi, Hussein; Bennett, Malcolm J; Pridmore, Tony P

2012-06-05

Roots are highly responsive to environmental signals encountered in the rhizosphere, such as nutrients, mechanical resistance and gravity. As a result, root growth and development is very plastic. If this complex and vital process is to be understood, methods and tools are required to capture the dynamics of root responses. Tools are needed which are high-throughput, supporting large-scale experimental work, and provide accurate, high-resolution, quantitative data. We describe and demonstrate the efficacy of the high-throughput and high-resolution root imaging systems recently developed within the Centre for Plant Integrative Biology (CPIB). This toolset includes (i) robotic imaging hardware to generate time-lapse datasets from standard cameras under infrared illumination and (ii) automated image analysis methods and software to extract quantitative information about root growth and development both from these images and via high-resolution light microscopy. These methods are demonstrated using data gathered during an experimental study of the gravitropic response of Arabidopsis thaliana.

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 to remove blurred signal from an image. 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. Copyright © 1998 Elsevier Inc. All rights reserved.

Diffraction enhance x-ray imaging for quantitative phase contrast studies

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

Agrawal, A. K.; Singh, B., E-mail: balwants@rrcat.gov.in; Kashyap, Y. S.

2016-05-23

Conventional X-ray imaging based on absorption contrast permits limited visibility of feature having small density and thickness variations. For imaging of weakly absorbing material or materials possessing similar densities, a novel phase contrast imaging techniques called diffraction enhanced imaging has been designed and developed at imaging beamline Indus-2 RRCAT Indore. The technique provides improved visibility of the interfaces and show high contrast in the image forsmall density or thickness gradients in the bulk. This paper presents basic principle, instrumentation and analysis methods for this technique. Initial results of quantitative phase retrieval carried out on various samples have also been presented.

CALIPSO: an interactive image analysis software package for desktop PACS workstations

NASA Astrophysics Data System (ADS)

Ratib, Osman M.; Huang, H. K.

1990-07-01

The purpose of this project is to develop a low cost workstation for quantitative analysis of multimodality images using a Macintosh II personal computer. In the current configuration the Macintosh operates as a stand alone workstation where images are imported either from a central PACS server through a standard Ethernet network or recorded through video digitizer board. The CALIPSO software developed contains a large variety ofbasic image display and manipulation tools. We focused our effort however on the design and implementation ofquantitative analysis methods that can be applied to images from different imaging modalities. Analysis modules currently implemented include geometric and densitometric volumes and ejection fraction calculation from radionuclide and cine-angiograms Fourier analysis ofcardiac wall motion vascular stenosis measurement color coded parametric display of regional flow distribution from dynamic coronary angiograms automatic analysis ofmyocardial distribution ofradiolabelled tracers from tomoscintigraphic images. Several of these analysis tools were selected because they use similar color coded andparametric display methods to communicate quantitative data extracted from the images. 1. Rationale and objectives of the project Developments of Picture Archiving and Communication Systems (PACS) in clinical environment allow physicians and radiologists to assess radiographic images directly through imaging workstations (''). This convenient access to the images is often limited by the number of workstations available due in part to their high cost. There is also an increasing need for quantitative analysis ofthe images. During thepast decade

Probing myocardium biomechanics using quantitative optical coherence elastography

NASA Astrophysics Data System (ADS)

Wang, Shang; Lopez, Andrew L.; Morikawa, Yuka; Tao, Ge; Li, Jiasong; Larina, Irina V.; Martin, James F.; Larin, Kirill V.

2015-03-01

We present a quantitative optical coherence elastographic method for noncontact assessment of the myocardium elasticity. The method is based on shear wave imaging optical coherence tomography (SWI-OCT), where a focused air-puff system is used to induce localized tissue deformation through a low-pressure short-duration air stream and a phase-sensitive OCT system is utilized to monitor the propagation of the induced tissue displacement with nanoscale sensitivity. The 1-D scanning of M-mode OCT imaging and the application of optical phase retrieval and mapping techniques enable the reconstruction and visualization of 2-D depth-resolved shear wave propagation in tissue with ultra-high frame rate. The feasibility of this method in quantitative elasticity measurement is demonstrated on tissue-mimicking phantoms with the estimated Young's modulus compared with uniaxial compression tests. We also performed pilot experiments on ex vivo mouse cardiac muscle tissues with normal and genetically altered cardiomyocytes. Our results indicate this noncontact quantitative optical coherence elastographic method can be a useful tool for the cardiac muscle research and studies.

Quantitative single-molecule imaging by confocal laser scanning microscopy.

PubMed

Vukojevic, Vladana; Heidkamp, Marcus; Ming, Yu; Johansson, Björn; Terenius, Lars; Rigler, Rudolf

2008-11-25

A new approach to quantitative single-molecule imaging by confocal laser scanning microscopy (CLSM) is presented. It relies on fluorescence intensity distribution to analyze the molecular occurrence statistics captured by digital imaging and enables direct determination of the number of fluorescent molecules and their diffusion rates without resorting to temporal or spatial autocorrelation analyses. Digital images of fluorescent molecules were recorded by using fast scanning and avalanche photodiode detectors. In this way the signal-to-background ratio was significantly improved, enabling direct quantitative imaging by CLSM. The potential of the proposed approach is demonstrated by using standard solutions of fluorescent dyes, fluorescently labeled DNA molecules, quantum dots, and the Enhanced Green Fluorescent Protein in solution and in live cells. The method was verified by using fluorescence correlation spectroscopy. The relevance for biological applications, in particular, for live cell imaging, is discussed.

The Use of Mouse Models of Breast Cancer and Quantitative Image Analysis to Evaluate Hormone Receptor Antigenicity after Microwave-assisted Formalin Fixation

PubMed Central

Engelberg, Jesse A.; Giberson, Richard T.; Young, Lawrence J.T.; Hubbard, Neil E.

2014-01-01

Microwave methods of fixation can dramatically shorten fixation times while preserving tissue structure; however, it remains unclear if adequate tissue antigenicity is preserved. To assess and validate antigenicity, robust quantitative methods and animal disease models are needed. We used two mouse mammary models of human breast cancer to evaluate microwave-assisted and standard 24-hr formalin fixation. The mouse models expressed four antigens prognostic for breast cancer outcome: estrogen receptor, progesterone receptor, Ki67, and human epidermal growth factor receptor 2. Using pathologist evaluation and novel methods of quantitative image analysis, we measured and compared the quality of antigen preservation, percentage of positive cells, and line plots of cell intensity. Visual evaluations by pathologists established that the amounts and patterns of staining were similar in tissues fixed by the different methods. The results of the quantitative image analysis provided a fine-grained evaluation, demonstrating that tissue antigenicity is preserved in tissues fixed using microwave methods. Evaluation of the results demonstrated that a 1-hr, 150-W fixation is better than a 45-min, 150-W fixation followed by a 15-min, 650-W fixation. The results demonstrated that microwave-assisted formalin fixation can standardize fixation times to 1 hr and produce immunohistochemistry that is in every way commensurate with longer conventional fixation methods. PMID:24682322

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

PubMed

Bigler, Erin D

2015-09-01

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

A novel iris transillumination grading scale allowing flexible assessment with quantitative image analysis and visual matching.

PubMed

Wang, Chen; Brancusi, Flavia; Valivullah, Zaheer M; Anderson, Michael G; Cunningham, Denise; Hedberg-Buenz, Adam; Power, Bradley; Simeonov, Dimitre; Gahl, William A; Zein, Wadih M; Adams, David R; Brooks, Brian

2018-01-01

To develop a sensitive scale of iris transillumination suitable for clinical and research use, with the capability of either quantitative analysis or visual matching of images. Iris transillumination photographic images were used from 70 study subjects with ocular or oculocutaneous albinism. Subjects represented a broad range of ocular pigmentation. A subset of images was subjected to image analysis and ranking by both expert and nonexpert reviewers. Quantitative ordering of images was compared with ordering by visual inspection. Images were binned to establish an 8-point scale. Ranking consistency was evaluated using the Kendall rank correlation coefficient (Kendall's tau). Visual ranking results were assessed using Kendall's coefficient of concordance (Kendall's W) analysis. There was a high degree of correlation among the image analysis, expert-based and non-expert-based image rankings. Pairwise comparisons of the quantitative ranking with each reviewer generated an average Kendall's tau of 0.83 ± 0.04 (SD). Inter-rater correlation was also high with Kendall's W of 0.96, 0.95, and 0.95 for nonexpert, expert, and all reviewers, respectively. The current standard for assessing iris transillumination is expert assessment of clinical exam findings. We adapted an image-analysis technique to generate quantitative transillumination values. Quantitative ranking was shown to be highly similar to a ranking produced by both expert and nonexpert reviewers. This finding suggests that the image characteristics used to quantify iris transillumination do not require expert interpretation. Inter-rater rankings were also highly similar, suggesting that varied methods of transillumination ranking are robust in terms of producing reproducible results.

Dual function microscope for quantitative DIC and birefringence imaging

NASA Astrophysics Data System (ADS)

Li, Chengshuai; Zhu, Yizheng

2016-03-01

A spectral multiplexing interferometry (SXI) method is presented for integrated birefringence and phase gradient measurement on label-free biological specimens. With SXI, the retardation and orientation of sample birefringence are simultaneously encoded onto two separate spectral carrier waves, generated by a crystal retarder oriented at a specific angle. Thus sufficient information for birefringence determination can be obtained from a single interference spectrum, eliminating the need for multiple acquisitions with mechanical rotation or electrical modulation. In addition, with the insertion of a Nomarski prism, the setup can then acquire quantitative differential interference contrast images. Red blood cells infected by malaria parasites are imaged for birefringence retardation as well as phase gradient. The results demonstrate that the SXI approach can achieve both quantitative phase imaging and birefringence imaging with a single, high-sensitivity system.

PCA-based groupwise image registration for quantitative MRI.

PubMed

Huizinga, W; Poot, D H J; Guyader, J-M; Klaassen, R; Coolen, B F; van Kranenburg, M; van Geuns, R J M; Uitterdijk, A; Polfliet, M; Vandemeulebroucke, J; Leemans, A; Niessen, W J; Klein, S

2016-04-01

Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or at multiple time points after injection of a contrast agent) and by fitting a qMRI signal model to the image intensities. Image registration is often necessary to compensate for misalignments due to subject motion and/or geometric distortions caused by the acquisition. However, large differences in image appearance make accurate image registration challenging. In this work, we propose a groupwise image registration method for compensating misalignment in qMRI. The groupwise formulation of the method eliminates the requirement of choosing a reference image, thus avoiding a registration bias. The method minimizes a cost function that is based on principal component analysis (PCA), exploiting the fact that intensity changes in qMRI can be described by a low-dimensional signal model, but not requiring knowledge on the specific acquisition model. The method was evaluated on 4D CT data of the lungs, and both real and synthetic images of five different qMRI applications: T1 mapping in a porcine heart, combined T1 and T2 mapping in carotid arteries, ADC mapping in the abdomen, diffusion tensor mapping in the brain, and dynamic contrast-enhanced mapping in the abdomen. Each application is based on a different acquisition model. The method is compared to a mutual information-based pairwise registration method and four other state-of-the-art groupwise registration methods. Registration accuracy is evaluated in terms of the precision of the estimated qMRI parameters, overlap of segmented structures, distance between corresponding landmarks, and smoothness of the deformation. In all qMRI applications the proposed method performed better than or equally well as competing methods, while avoiding the need to choose a reference image. It is also shown that the results of the conventional pairwise approach do depend on the choice of this reference image. We therefore conclude that our groupwise registration method with a similarity measure based on PCA is the preferred technique for compensating misalignments in qMRI. Copyright © 2015 Elsevier B.V. All rights reserved.

An improved level set method for brain MR images segmentation and bias correction.

PubMed

Chen, Yunjie; Zhang, Jianwei; Macione, Jim

2009-10-01

Intensity inhomogeneities cause considerable difficulty in the quantitative analysis of magnetic resonance (MR) images. Thus, bias field estimation is a necessary step before quantitative analysis of MR data can be undertaken. This paper presents a variational level set approach to bias correction and segmentation for images with intensity inhomogeneities. Our method is based on an observation that intensities in a relatively small local region are separable, despite of the inseparability of the intensities in the whole image caused by the overall intensity inhomogeneity. We first define a localized K-means-type clustering objective function for image intensities in a neighborhood around each point. The cluster centers in this objective function have a multiplicative factor that estimates the bias within the neighborhood. The objective function is then integrated over the entire domain to define the data term into the level set framework. Our method is able to capture bias of quite general profiles. Moreover, it is robust to initialization, and thereby allows fully automated applications. The proposed method has been used for images of various modalities with promising results.

Near-infrared fluorescence image quality test methods for standardized performance evaluation

NASA Astrophysics Data System (ADS)

Kanniyappan, Udayakumar; Wang, Bohan; Yang, Charles; Ghassemi, Pejhman; Wang, Quanzeng; Chen, Yu; Pfefer, Joshua

2017-03-01

Near-infrared fluorescence (NIRF) imaging has gained much attention as a clinical method for enhancing visualization of cancers, perfusion and biological structures in surgical applications where a fluorescent dye is monitored by an imaging system. In order to address the emerging need for standardization of this innovative technology, it is necessary to develop and validate test methods suitable for objective, quantitative assessment of device performance. Towards this goal, we develop target-based test methods and investigate best practices for key NIRF imaging system performance characteristics including spatial resolution, depth of field and sensitivity. Characterization of fluorescence properties was performed by generating excitation-emission matrix properties of indocyanine green and quantum dots in biological solutions and matrix materials. A turbid, fluorophore-doped target was used, along with a resolution target for assessing image sharpness. Multi-well plates filled with either liquid or solid targets were generated to explore best practices for evaluating detection sensitivity. Overall, our results demonstrate the utility of objective, quantitative, target-based testing approaches as well as the need to consider a wide range of factors in establishing standardized approaches for NIRF imaging system performance.

A method for energy window optimization for quantitative tasks that includes the effects of model-mismatch on bias: application to Y-90 bremsstrahlung SPECT imaging.

PubMed

Rong, Xing; Du, Yong; Frey, Eric C

2012-06-21

Quantitative Yttrium-90 ((90)Y) bremsstrahlung single photon emission computed tomography (SPECT) imaging has shown great potential to provide reliable estimates of (90)Y activity distribution for targeted radionuclide therapy dosimetry applications. One factor that potentially affects the reliability of the activity estimates is the choice of the acquisition energy window. In contrast to imaging conventional gamma photon emitters where the acquisition energy windows are usually placed around photopeaks, there has been great variation in the choice of the acquisition energy window for (90)Y imaging due to the continuous and broad energy distribution of the bremsstrahlung photons. In quantitative imaging of conventional gamma photon emitters, previous methods for optimizing the acquisition energy window assumed unbiased estimators and used the variance in the estimates as a figure of merit (FOM). However, for situations, such as (90)Y imaging, where there are errors in the modeling of the image formation process used in the reconstruction there will be bias in the activity estimates. In (90)Y bremsstrahlung imaging this will be especially important due to the high levels of scatter, multiple scatter, and collimator septal penetration and scatter. Thus variance will not be a complete measure of reliability of the estimates and thus is not a complete FOM. To address this, we first aimed to develop a new method to optimize the energy window that accounts for both the bias due to model-mismatch and the variance of the activity estimates. We applied this method to optimize the acquisition energy window for quantitative (90)Y bremsstrahlung SPECT imaging in microsphere brachytherapy. Since absorbed dose is defined as the absorbed energy from the radiation per unit mass of tissues in this new method we proposed a mass-weighted root mean squared error of the volume of interest (VOI) activity estimates as the FOM. To calculate this FOM, two analytical expressions were derived for calculating the bias due to model-mismatch and the variance of the VOI activity estimates, respectively. To obtain the optimal acquisition energy window for general situations of interest in clinical (90)Y microsphere imaging, we generated phantoms with multiple tumors of various sizes and various tumor-to-normal activity concentration ratios using a digital phantom that realistically simulates human anatomy, simulated (90)Y microsphere imaging with a clinical SPECT system and typical imaging parameters using a previously validated Monte Carlo simulation code, and used a previously proposed method for modeling the image degrading effects in quantitative SPECT reconstruction. The obtained optimal acquisition energy window was 100-160 keV. The values of the proposed FOM were much larger than the FOM taking into account only the variance of the activity estimates, thus demonstrating in our experiment that the bias of the activity estimates due to model-mismatch was a more important factor than the variance in terms of limiting the reliability of activity estimates.

A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis

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

Larimer, Curtis J.; Winder, Eric M.; Jeters, Robert T.

Here, the accumulation of bacteria in surface attached biofilms, or biofouling, can be detrimental to human health, dental hygiene, and many industrial processes. A critical need in identifying and preventing the deleterious effects of biofilms is the ability to observe and quantify their development. Analytical methods capable of assessing early stage fouling are cumbersome or lab-confined, subjective, and qualitative. Herein, a novel photographic method is described that uses biomolecular staining and image analysis to enhance contrast of early stage biofouling. A robust algorithm was developed to objectively and quantitatively measure surface accumulation of Pseudomonas putida from photographs and results weremore » compared to independent measurements of cell density. Results from image analysis quantified biofilm growth intensity accurately and with approximately the same precision of the more laborious cell counting method. This simple method for early stage biofilm detection enables quantifiable measurement of surface fouling and is flexible enough to be applied from the laboratory to the field. Broad spectrum staining highlights fouling biomass, photography quickly captures a large area of interest, and image analysis rapidly quantifies fouling in the image.« less

A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis

DOE PAGES

Larimer, Curtis J.; Winder, Eric M.; Jeters, Robert T.; ...

2015-12-07

Here, the accumulation of bacteria in surface attached biofilms, or biofouling, can be detrimental to human health, dental hygiene, and many industrial processes. A critical need in identifying and preventing the deleterious effects of biofilms is the ability to observe and quantify their development. Analytical methods capable of assessing early stage fouling are cumbersome or lab-confined, subjective, and qualitative. Herein, a novel photographic method is described that uses biomolecular staining and image analysis to enhance contrast of early stage biofouling. A robust algorithm was developed to objectively and quantitatively measure surface accumulation of Pseudomonas putida from photographs and results weremore » compared to independent measurements of cell density. Results from image analysis quantified biofilm growth intensity accurately and with approximately the same precision of the more laborious cell counting method. This simple method for early stage biofilm detection enables quantifiable measurement of surface fouling and is flexible enough to be applied from the laboratory to the field. Broad spectrum staining highlights fouling biomass, photography quickly captures a large area of interest, and image analysis rapidly quantifies fouling in the image.« less

Highly sensitive transient absorption imaging of graphene and graphene oxide in living cells and circulating blood.

PubMed

Li, Junjie; Zhang, Weixia; Chung, Ting-Fung; Slipchenko, Mikhail N; Chen, Yong P; Cheng, Ji-Xin; Yang, Chen

2015-07-23

We report a transient absorption (TA) imaging method for fast visualization and quantitative layer analysis of graphene and GO. Forward and backward imaging of graphene on various substrates under ambient condition was imaged with a speed of 2 μs per pixel. The TA intensity linearly increased with the layer number of graphene. Real-time TA imaging of GO in vitro with capability of quantitative analysis of intracellular concentration and ex vivo in circulating blood were demonstrated. These results suggest that TA microscopy is a valid tool for the study of graphene based materials.

Imaging Cerebral Microhemorrhages in Military Service Members with Chronic Traumatic Brain Injury

PubMed Central

Liu, Wei; Soderlund, Karl; Senseney, Justin S.; Joy, David; Yeh, Ping-Hong; Ollinger, John; Sham, Elyssa B.; Liu, Tian; Wang, Yi; Oakes, Terrence R.; Riedy, Gerard

2017-01-01

Purpose To detect cerebral microhemorrhages in military service members with chronic traumatic brain injury by using susceptibility-weighted magnetic resonance (MR) imaging. The longitudinal evolution of microhemorrhages was monitored in a subset of patients by using quantitative susceptibility mapping. Materials and Methods The study was approved by the Walter Reed National Military Medical Center institutional review board and is compliant with HIPAA guidelines. All participants underwent two-dimensional conventional gradient-recalled-echo MR imaging and three-dimensional flow-compensated multi-echo gradient-recalled-echo MR imaging (processed to generate susceptibility-weighted images and quantitative susceptibility maps), and a subset of patients underwent follow-up imaging. Microhemorrhages were identified by two radiologists independently. Comparisons of microhemorrhage number, size, and magnetic susceptibility derived from quantitative susceptibility maps between baseline and follow-up imaging examinations were performed by using the paired t test. Results Among the 603 patients, cerebral microhemorrhages were identified in 43 patients, with six excluded for further analysis owing to artifacts. Seventy-seven percent (451 of 585) of the microhemorrhages on susceptibility-weighted images had a more conspicuous appearance than on gradient-recalled-echo images. Thirteen of the 37 patients underwent follow-up imaging examinations. In these patients, a smaller number of microhemorrhages were identified at follow-up imaging compared with baseline on quantitative susceptibility maps (mean ± standard deviation, 9.8 microhemorrhages ± 12.8 vs 13.7 microhemorrhages ± 16.6; P = .019). Quantitative susceptibility mapping–derived quantitative measures of microhemorrhages also decreased over time: −0.85 mm3 per day ± 1.59 for total volume (P = .039) and −0.10 parts per billion per day ± 0.14 for mean magnetic susceptibility (P = .016). Conclusion The number of microhemorrhages and quantitative susceptibility mapping–derived quantitative measures of microhemorrhages all decreased over time, suggesting that hemosiderin products undergo continued, subtle evolution in the chronic stage. PMID:26371749

A preliminary study of DTI Fingerprinting on stroke analysis.

PubMed

Ma, Heather T; Ye, Chenfei; Wu, Jun; Yang, Pengfei; Chen, Xuhui; Yang, Zhengyi; Ma, Jingbo

2014-01-01

DTI (Diffusion Tensor Imaging) is a well-known MRI (Magnetic Resonance Imaging) technique which provides useful structural information about human brain. However, the quantitative measurement to physiological variation of subtypes of ischemic stroke is not available. An automatically quantitative method for DTI analysis will enhance the DTI application in clinics. In this study, we proposed a DTI Fingerprinting technology to quantitatively analyze white matter tissue, which was applied in stroke classification. The TBSS (Tract Based Spatial Statistics) method was employed to generate mask automatically. To evaluate the clustering performance of the automatic method, lesion ROI (Region of Interest) is manually drawn on the DWI images as a reference. The results from the DTI Fingerprinting were compared with those obtained from the reference ROIs. It indicates that the DTI Fingerprinting could identify different states of ischemic stroke and has promising potential to provide a more comprehensive measure of the DTI data. Further development should be carried out to improve DTI Fingerprinting technology in clinics.

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

NASA Astrophysics Data System (ADS)

Zhu, Xiaokun; Jia, Yonghong

2005-10-01

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

Use of quantitative SPECT/CT reconstruction in 99mTc-sestamibi imaging of patients with renal masses.

PubMed

Jones, Krystyna M; Solnes, Lilja B; Rowe, Steven P; Gorin, Michael A; Sheikhbahaei, Sara; Fung, George; Frey, Eric C; Allaf, Mohamad E; Du, Yong; Javadi, Mehrbod S

2018-02-01

Technetium-99m ( 99m Tc)-sestamibi single-photon emission computed tomography/computed tomography (SPECT/CT) has previously been shown to allow for the accurate differentiation of benign renal oncocytomas and hybrid oncocytic/chromophobe tumors (HOCTs) apart from other malignant renal tumor histologies, with oncocytomas/HOCTs showing high uptake and renal cell carcinoma (RCC) showing low uptake based on uptake ratios from non-quantitative single-photon emission computed tomography (SPECT) reconstructions. However, in this study, several tumors fell close to the uptake ratio cutoff, likely due to limitations in conventional SPECT/CT reconstruction methods. We hypothesized that application of quantitative SPECT/CT (QSPECT) reconstruction methods developed by our group would provide more robust separation of hot and cold lesions, serving as an imaging framework on which quantitative biomarkers can be validated for evaluation of renal masses with 99m Tc-sestamibi. Single-photon emission computed tomography data were reconstructed using the clinical Flash 3D reconstruction and QSPECT methods. Two blinded readers then characterized each tumor as hot or cold. Semi-quantitative uptake ratios were calculated by dividing lesion activity by background renal activity for both Flash 3D and QSPECT reconstructions. The difference between median (mean) hot and cold tumor uptake ratios measured 0.655 (0.73) with the QSPECT method and 0.624 (0.67) with the conventional method, resulting in increased separation between hot and cold tumors. Sub-analysis of 7 lesions near the separation point showed a higher absolute difference (0.16) between QPSECT and Flash 3D mean uptake ratios compared to the remaining lesions. Our finding of improved separation between uptake ratios of hot and cold lesions using QSPECT reconstruction lays the foundation for additional quantitative SPECT techniques such as SPECT-UV in the setting of renal 99m Tc-sestamibi and other SPECT/CT exams. With robust quantitative image reconstruction and biomarker analysis, there may be an expanded role for SPECT/CT imaging in renal masses and other pathologic conditions.

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Computer Algorithm Comparisons

PubMed Central

2014-01-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. PMID:24919829

Towards standardized assessment of endoscope optical performance: geometric distortion

NASA Astrophysics Data System (ADS)

Wang, Quanzeng; Desai, Viraj N.; Ngo, Ying Z.; Cheng, Wei-Chung; Pfefer, Joshua

2013-12-01

Technological advances in endoscopes, such as capsule, ultrathin and disposable devices, promise significant improvements in safety, clinical effectiveness and patient acceptance. Unfortunately, the industry lacks test methods for preclinical evaluation of key optical performance characteristics (OPCs) of endoscopic devices that are quantitative, objective and well-validated. As a result, it is difficult for researchers and developers to compare image quality and evaluate equivalence to, or improvement upon, prior technologies. While endoscope OPCs include resolution, field of view, and depth of field, among others, our focus in this paper is geometric image distortion. We reviewed specific test methods for distortion and then developed an objective, quantitative test method based on well-defined experimental and data processing steps to evaluate radial distortion in the full field of view of an endoscopic imaging system. Our measurements and analyses showed that a second-degree polynomial equation could well describe the radial distortion curve of a traditional endoscope. The distortion evaluation method was effective for correcting the image and can be used to explain other widely accepted evaluation methods such as picture height distortion. Development of consensus standards based on promising test methods for image quality assessment, such as the method studied here, will facilitate clinical implementation of innovative endoscopic devices.

Quantitative analysis of drug distribution by ambient mass spectrometry imaging method with signal extinction normalization strategy and inkjet-printing technology.

PubMed

Luo, Zhigang; He, Jingjing; He, Jiuming; Huang, Lan; Song, Xiaowei; Li, Xin; Abliz, Zeper

2018-03-01

Quantitative mass spectrometry imaging (MSI) is a robust approach that provides both quantitative and spatial information for drug candidates' research. However, because of complicated signal suppression and interference, acquiring accurate quantitative information from MSI data remains a challenge, especially for whole-body tissue sample. Ambient MSI techniques using spray-based ionization appear to be ideal for pharmaceutical quantitative MSI analysis. However, it is more challenging, as it involves almost no sample preparation and is more susceptible to ion suppression/enhancement. Herein, based on our developed air flow-assisted desorption electrospray ionization (AFADESI)-MSI technology, an ambient quantitative MSI method was introduced by integrating inkjet-printing technology with normalization of the signal extinction coefficient (SEC) using the target compound itself. The method utilized a single calibration curve to quantify multiple tissue types. Basic blue 7 and an antitumor drug candidate (S-(+)-deoxytylophorinidine, CAT) were chosen to initially validate the feasibility and reliability of the quantitative MSI method. Rat tissue sections (heart, kidney, and brain) administered with CAT was then analyzed. The quantitative MSI analysis results were cross-validated by LC-MS/MS analysis data of the same tissues. The consistency suggests that the approach is able to fast obtain the quantitative MSI data without introducing interference into the in-situ environment of the tissue sample, and is potential to provide a high-throughput, economical and reliable approach for drug discovery and development. Copyright © 2017 Elsevier B.V. All rights reserved.

Attenuation correction for brain PET imaging using deep neural network based on dixon and ZTE MR images.

PubMed

Gong, Kuang; Yang, Jaewon; Kim, Kyungsang; El Fakhri, Georges; Seo, Youngho; Li, Quanzheng

2018-05-23

Positron Emission Tomography (PET) is a functional imaging modality widely used in neuroscience studies. To obtain meaningful quantitative results from PET images, attenuation correction is necessary during image reconstruction. For PET/MR hybrid systems, PET attenuation is challenging as Magnetic Resonance (MR) images do not reflect attenuation coefficients directly. To address this issue, we present deep neural network methods to derive the continuous attenuation coefficients for brain PET imaging from MR images. With only Dixon MR images as the network input, the existing U-net structure was adopted and analysis using forty patient data sets shows it is superior than other Dixon based methods. When both Dixon and zero echo time (ZTE) images are available, we have proposed a modified U-net structure, named GroupU-net, to efficiently make use of both Dixon and ZTE information through group convolution modules when the network goes deeper. Quantitative analysis based on fourteen real patient data sets demonstrates that both network approaches can perform better than the standard methods, and the proposed network structure can further reduce the PET quantification error compared to the U-net structure. © 2018 Institute of Physics and Engineering in Medicine.

Quantitative 17O imaging towards oxygen consumption study in tumor bearing mice at 7 T.

PubMed

Narazaki, Michiko; Kanazawa, Yoko; Koike, Sachiko; Ando, Koichi; Ikehira, Hiroo

2013-06-01

(17)O magnetic resonance imaging (MRI) using a conventional pulse sequence was explored as a method of quantitative imaging towards regional oxygen consumption rate measurement for tumor evaluation in mice. At 7 T, fast imaging with steady state (FISP) was the best among gradient echo, fast spin echo and FISP for the purpose. The distribution of natural abundance H2(17)O in mice was visualized under spatial resolution of 2.5 × 2.5mm(2) by FISP in 10 min. The signal intensity by FISP showed a linear relationship with (17)O quantity both in phantom and mice. Following the injection of 5% (17)O enriched saline, (17)O re-distribution was monitored in temporal resolution down to 5 sec with an image quality sufficient to distinguish each organ. The image of labeled water produced from inhaled (17)O2 gas was also obtained. The present method provides quantitative (17)O images under sufficient temporal and spatial resolution for the evaluation of oxygen consumption rate in each organ. Experiments using various model compounds of R-OH type clarified that the signal contribution of body constituents other than water in the present in vivo(17)O FISP image was negligible. Copyright © 2013 Elsevier Inc. All rights reserved.

Quantitative optical scanning tests of complex microcircuits

NASA Technical Reports Server (NTRS)

Erickson, J. J.

1980-01-01

An approach for the development of the optical scanner as a screening inspection instrument for microcircuits involves comparing the quantitative differences in photoresponse images and then correlating them with electrical parameter differences in test devices. The existing optical scanner was modified so that the photoresponse data could be recorded and subsequently digitized. A method was devised for applying digital image processing techniques to the digitized photoresponse data in order to quantitatively compare the data. Electrical tests were performed and photoresponse images were recorded before and following life test intervals on two groups of test devices. Correlations were made between differences or changes in the electrical parameters of the test devices.

Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM

PubMed Central

Giger, Maryellen L.; Chan, Heang-Ping; Boone, John

2008-01-01

The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists’ goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities that are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists—as opposed to a completely automatic computer interpretation—focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous—from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects—collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more—from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis. PMID:19175137

Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM

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

Giger, Maryellen L.; Chan, Heang-Ping; Boone, John

2008-12-15

The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists' goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities thatmore » are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists--as opposed to a completely automatic computer interpretation--focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous--from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects--collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more--from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis.« less

Leaf epidermis images for robust identification of plants

PubMed Central

da Silva, Núbia Rosa; Oliveira, Marcos William da Silva; Filho, Humberto Antunes de Almeida; Pinheiro, Luiz Felipe Souza; Rossatto, Davi Rodrigo; Kolb, Rosana Marta; Bruno, Odemir Martinez

2016-01-01

This paper proposes a methodology for plant analysis and identification based on extracting texture features from microscopic images of leaf epidermis. All the experiments were carried out using 32 plant species with 309 epidermal samples captured by an optical microscope coupled to a digital camera. The results of the computational methods using texture features were compared to the conventional approach, where quantitative measurements of stomatal traits (density, length and width) were manually obtained. Epidermis image classification using texture has achieved a success rate of over 96%, while success rate was around 60% for quantitative measurements taken manually. Furthermore, we verified the robustness of our method accounting for natural phenotypic plasticity of stomata, analysing samples from the same species grown in different environments. Texture methods were robust even when considering phenotypic plasticity of stomatal traits with a decrease of 20% in the success rate, as quantitative measurements proved to be fully sensitive with a decrease of 77%. Results from the comparison between the computational approach and the conventional quantitative measurements lead us to discover how computational systems are advantageous and promising in terms of solving problems related to Botany, such as species identification. PMID:27217018

The effects of AVIRIS atmospheric calibration methodology on identification and quantitative mapping of surface mineralogy, Drum Mountains, Utah

NASA Technical Reports Server (NTRS)

Kruse, Fred A.; Dwyer, John L.

1993-01-01

The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) measures reflected light in 224 contiguous spectra bands in the 0.4 to 2.45 micron region of the electromagnetic spectrum. Numerous studies have used these data for mineralogic identification and mapping based on the presence of diagnostic spectral features. Quantitative mapping requires conversion of the AVIRIS data to physical units (usually reflectance) so that analysis results can be compared and validated with field and laboratory measurements. This study evaluated two different AVIRIS calibration techniques to ground reflectance: an empirically-based method and an atmospheric model based method to determine their effects on quantitative scientific analyses. Expert system analysis and linear spectral unmixing were applied to both calibrated data sets to determine the effect of the calibration on the mineral identification and quantitative mapping results. Comparison of the image-map results and image reflectance spectra indicate that the model-based calibrated data can be used with automated mapping techniques to produce accurate maps showing the spatial distribution and abundance of surface mineralogy. This has positive implications for future operational mapping using AVIRIS or similar imaging spectrometer data sets without requiring a priori knowledge.

Bayesian parameter estimation in spectral quantitative photoacoustic tomography

NASA Astrophysics Data System (ADS)

Pulkkinen, Aki; Cox, Ben T.; Arridge, Simon R.; Kaipio, Jari P.; Tarvainen, Tanja

2016-03-01

Photoacoustic tomography (PAT) is an imaging technique combining strong contrast of optical imaging to high spatial resolution of ultrasound imaging. These strengths are achieved via photoacoustic effect, where a spatial absorption of light pulse is converted into a measurable propagating ultrasound wave. The method is seen as a potential tool for small animal imaging, pre-clinical investigations, study of blood vessels and vasculature, as well as for cancer imaging. The goal in PAT is to form an image of the absorbed optical energy density field via acoustic inverse problem approaches from the measured ultrasound data. Quantitative PAT (QPAT) proceeds from these images and forms quantitative estimates of the optical properties of the target. This optical inverse problem of QPAT is illposed. To alleviate the issue, spectral QPAT (SQPAT) utilizes PAT data formed at multiple optical wavelengths simultaneously with optical parameter models of tissue to form quantitative estimates of the parameters of interest. In this work, the inverse problem of SQPAT is investigated. Light propagation is modelled using the diffusion equation. Optical absorption is described with chromophore concentration weighted sum of known chromophore absorption spectra. Scattering is described by Mie scattering theory with an exponential power law. In the inverse problem, the spatially varying unknown parameters of interest are the chromophore concentrations, the Mie scattering parameters (power law factor and the exponent), and Gruneisen parameter. The inverse problem is approached with a Bayesian method. It is numerically demonstrated, that estimation of all parameters of interest is possible with the approach.

Comparison of longitudinal excursion of a nerve-phantom model using quantitative ultrasound imaging and motion analysis system methods: A convergent validity study.

PubMed

Paquette, Philippe; El Khamlichi, Youssef; Lamontagne, Martin; Higgins, Johanne; Gagnon, Dany H

2017-08-01

Quantitative ultrasound imaging is gaining popularity in research and clinical settings to measure the neuromechanical properties of the peripheral nerves such as their capability to glide in response to body segment movement. Increasing evidence suggests that impaired median nerve longitudinal excursion is associated with carpal tunnel syndrome. To date, psychometric properties of longitudinal nerve excursion measurements using quantitative ultrasound imaging have not been extensively investigated. This study investigates the convergent validity of the longitudinal nerve excursion by comparing measures obtained using quantitative ultrasound imaging with those determined with a motion analysis system. A 38-cm long rigid nerve-phantom model was used to assess the longitudinal excursion in a laboratory environment. The nerve-phantom model, immersed in a 20-cm deep container filled with a gelatin-based solution, was moved 20 times using a linear forward and backward motion. Three light-emitting diodes were used to record nerve-phantom excursion with a motion analysis system, while a 5-cm linear transducer allowed simultaneous recording via ultrasound imaging. Both measurement techniques yielded excellent association ( r  = 0.99) and agreement (mean absolute difference between methods = 0.85 mm; mean relative difference between methods = 7.48 %). Small discrepancies were largely found when larger excursions (i.e. > 10 mm) were performed, revealing slight underestimation of the excursion by the ultrasound imaging analysis software. Quantitative ultrasound imaging is an accurate method to assess the longitudinal excursion of an in vitro nerve-phantom model and appears relevant for future research protocols investigating the neuromechanical properties of the peripheral nerves.

Effects of calibration methods on quantitative material decomposition in photon-counting spectral computed tomography using a maximum a posteriori estimator.

PubMed

Curtis, Tyler E; Roeder, Ryan K

2017-10-01

Advances in photon-counting detectors have enabled quantitative material decomposition using multi-energy or spectral computed tomography (CT). Supervised methods for material decomposition utilize an estimated attenuation for each material of interest at each photon energy level, which must be calibrated based upon calculated or measured values for known compositions. Measurements using a calibration phantom can advantageously account for system-specific noise, but the effect of calibration methods on the material basis matrix and subsequent quantitative material decomposition has not been experimentally investigated. Therefore, the objective of this study was to investigate the influence of the range and number of contrast agent concentrations within a modular calibration phantom on the accuracy of quantitative material decomposition in the image domain. Gadolinium was chosen as a model contrast agent in imaging phantoms, which also contained bone tissue and water as negative controls. The maximum gadolinium concentration (30, 60, and 90 mM) and total number of concentrations (2, 4, and 7) were independently varied to systematically investigate effects of the material basis matrix and scaling factor calibration on the quantitative (root mean squared error, RMSE) and spatial (sensitivity and specificity) accuracy of material decomposition. Images of calibration and sample phantoms were acquired using a commercially available photon-counting spectral micro-CT system with five energy bins selected to normalize photon counts and leverage the contrast agent k-edge. Material decomposition of gadolinium, calcium, and water was performed for each calibration method using a maximum a posteriori estimator. Both the quantitative and spatial accuracy of material decomposition were most improved by using an increased maximum gadolinium concentration (range) in the basis matrix calibration; the effects of using a greater number of concentrations were relatively small in magnitude by comparison. The material basis matrix calibration was more sensitive to changes in the calibration methods than the scaling factor calibration. The material basis matrix calibration significantly influenced both the quantitative and spatial accuracy of material decomposition, while the scaling factor calibration influenced quantitative but not spatial accuracy. Importantly, the median RMSE of material decomposition was as low as ~1.5 mM (~0.24 mg/mL gadolinium), which was similar in magnitude to that measured by optical spectroscopy on the same samples. The accuracy of quantitative material decomposition in photon-counting spectral CT was significantly influenced by calibration methods which must therefore be carefully considered for the intended diagnostic imaging application. © 2017 American Association of Physicists in Medicine.

Differential diagnosis of breast cancer using quantitative, label-free and molecular vibrational imaging

PubMed Central

Yang, Yaliang; Li, Fuhai; Gao, Liang; Wang, Zhiyong; Thrall, Michael J.; Shen, Steven S.; Wong, Kelvin K.; Wong, Stephen T. C.

2011-01-01

We present a label-free, chemically-selective, quantitative imaging strategy to identify breast cancer and differentiate its subtypes using coherent anti-Stokes Raman scattering (CARS) microscopy. Human normal breast tissue, benign proliferative, as well as in situ and invasive carcinomas, were imaged ex vivo. Simply by visualizing cellular and tissue features appearing on CARS images, cancerous lesions can be readily separated from normal tissue and benign proliferative lesion. To further distinguish cancer subtypes, quantitative disease-related features, describing the geometry and distribution of cancer cell nuclei, were extracted and applied to a computerized classification system. The results show that in situ carcinoma was successfully distinguished from invasive carcinoma, while invasive ductal carcinoma (IDC) and invasive lobular carcinoma were also distinguished from each other. Furthermore, 80% of intermediate-grade IDC and 85% of high-grade IDC were correctly distinguished from each other. The proposed quantitative CARS imaging method has the potential to enable rapid diagnosis of breast cancer. PMID:21833355

Photothermal technique in cell microscopy studies

NASA Astrophysics Data System (ADS)

Lapotko, Dmitry; Chebot'ko, Igor; Kutchinsky, Georgy; Cherenkevitch, Sergey

1995-01-01

Photothermal (PT) method is applied for a cell imaging and quantitative studies. The techniques for cell monitoring, imaging and cell viability test are developed. The method and experimental set up for optical and PT-image acquisition and analysis is described. Dual- pulsed laser set up combined with phase contrast illumination of a sample provides visualization of temperature field or absorption structure of a sample with spatial resolution 0.5 micrometers . The experimental optics, hardware and software are designed using the modular principle, so the whole set up can be adjusted for various experiments: PT-response monitoring or photothermal spectroscopy studies. Sensitivity of PT-method provides the imaging of the structural elements of live (non-stained) white blood cells. The results of experiments with normal and subnormal blood cells (red blood cells, lymphocytes, neutrophyles and lymphoblasts) are reported. Obtained PT-images are different from optical analogs and deliver additional information about cell structure. The quantitative analysis of images was used for cell population comparative diagnostic. The viability test for red blood cell differentiation is described. During the study of neutrophyles in norma and sarcoidosis disease the differences in PT-images of cells were found.

Dependence of quantitative accuracy of CT perfusion imaging on system parameters

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Guang-Hong

2017-03-01

Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.

A Complete Color Normalization Approach to Histopathology Images Using Color Cues Computed From Saturation-Weighted Statistics.

PubMed

Li, Xingyu; Plataniotis, Konstantinos N

2015-07-01

In digital histopathology, tasks of segmentation and disease diagnosis are achieved by quantitative analysis of image content. However, color variation in image samples makes it challenging to produce reliable results. This paper introduces a complete normalization scheme to address the problem of color variation in histopathology images jointly caused by inconsistent biopsy staining and nonstandard imaging condition. Method : Different from existing normalization methods that either address partial cause of color variation or lump them together, our method identifies causes of color variation based on a microscopic imaging model and addresses inconsistency in biopsy imaging and staining by an illuminant normalization module and a spectral normalization module, respectively. In evaluation, we use two public datasets that are representative of histopathology images commonly received in clinics to examine the proposed method from the aspects of robustness to system settings, performance consistency against achromatic pixels, and normalization effectiveness in terms of histological information preservation. As the saturation-weighted statistics proposed in this study generates stable and reliable color cues for stain normalization, our scheme is robust to system parameters and insensitive to image content and achromatic colors. Extensive experimentation suggests that our approach outperforms state-of-the-art normalization methods as the proposed method is the only approach that succeeds to preserve histological information after normalization. The proposed color normalization solution would be useful to mitigate effects of color variation in pathology images on subsequent quantitative analysis.

Photogrammetry Applied to Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

PubMed

Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

Semi-automated identification of cones in the human retina using circle Hough transform

PubMed Central

Bukowska, Danuta M.; Chew, Avenell L.; Huynh, Emily; Kashani, Irwin; Wan, Sue Ling; Wan, Pak Ming; Chen, Fred K

2015-01-01

A large number of human retinal diseases are characterized by a progressive loss of cones, the photoreceptors critical for visual acuity and color perception. Adaptive Optics (AO) imaging presents a potential method to study these cells in vivo. However, AO imaging in ophthalmology is a relatively new phenomenon and quantitative analysis of these images remains difficult and tedious using manual methods. This paper illustrates a novel semi-automated quantitative technique enabling registration of AO images to macular landmarks, cone counting and its radius quantification at specified distances from the foveal center. The new cone counting approach employs the circle Hough transform (cHT) and is compared to automated counting methods, as well as arbitrated manual cone identification. We explore the impact of varying the circle detection parameter on the validity of cHT cone counting and discuss the potential role of using this algorithm in detecting both cones and rods separately. PMID:26713186

Theory and preliminary experimental verification of quantitative edge illumination x-ray phase contrast tomography.

PubMed

Hagen, C K; Diemoz, P C; Endrizzi, M; Rigon, L; Dreossi, D; Arfelli, F; Lopez, F C M; Longo, R; Olivo, A

2014-04-07

X-ray phase contrast imaging (XPCi) methods are sensitive to phase in addition to attenuation effects and, therefore, can achieve improved image contrast for weakly attenuating materials, such as often encountered in biomedical applications. Several XPCi methods exist, most of which have already been implemented in computed tomographic (CT) modality, thus allowing volumetric imaging. The Edge Illumination (EI) XPCi method had, until now, not been implemented as a CT modality. This article provides indications that quantitative 3D maps of an object's phase and attenuation can be reconstructed from EI XPCi measurements. Moreover, a theory for the reconstruction of combined phase and attenuation maps is presented. Both reconstruction strategies find applications in tissue characterisation and the identification of faint, weakly attenuating details. Experimental results for wires of known materials and for a biological object validate the theory and confirm the superiority of the phase over conventional, attenuation-based image contrast.

Semi-automated discrimination of retinal pigmented epithelial cells in two-photon fluorescence images of mouse retinas.

PubMed

Alexander, Nathan S; Palczewska, Grazyna; Palczewski, Krzysztof

2015-08-01

Automated image segmentation is a critical step toward achieving a quantitative evaluation of disease states with imaging techniques. Two-photon fluorescence microscopy (TPM) has been employed to visualize the retinal pigmented epithelium (RPE) and provide images indicating the health of the retina. However, segmentation of RPE cells within TPM images is difficult due to small differences in fluorescence intensity between cell borders and cell bodies. Here we present a semi-automated method for segmenting RPE cells that relies upon multiple weak features that differentiate cell borders from the remaining image. These features were scored by a search optimization procedure that built up the cell border in segments around a nucleus of interest. With six images used as a test, our method correctly identified cell borders for 69% of nuclei on average. Performance was strongly dependent upon increasing retinosome content in the RPE. TPM image analysis has the potential of providing improved early quantitative assessments of diseases affecting the RPE.

3D Filament Network Segmentation with Multiple Active Contours

NASA Astrophysics Data System (ADS)

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2014-03-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

New semi-quantitative 123I-MIBG estimation method compared with scoring system in follow-up of advanced neuroblastoma: utility of total MIBG retention ratio versus scoring method.

PubMed

Sano, Yuko; Okuyama, Chio; Iehara, Tomoko; Matsushima, Shigenori; Yamada, Kei; Hosoi, Hajime; Nishimura, Tsunehiko

2012-07-01

The purpose of this study is to evaluate a new semi-quantitative estimation method using (123)I-MIBG retention ratio to assess response to chemotherapy for advanced neuroblastoma. Thirteen children with advanced neuroblastoma (International Neuroblastoma Risk Group Staging System: stage M) were examined for a total of 51 studies with (123)I-MIBG scintigraphy (before and during chemotherapy). We proposed a new semi-quantitative method using MIBG retention ratio (count obtained with delayed image/count obtained with early image with decay correction) to estimate MIBG accumulation. We analyzed total (123)I-MIBG retention ratio (TMRR: total body count obtained with delayed image/total body count obtained with early image with decay correction) and compared with a scoring method in terms of correlation with tumor markers. TMRR showed significantly higher correlations with urinary catecholamine metabolites before chemotherapy (VMA: r(2) = 0.45, P < 0.05, HVA: r(2) = 0.627, P < 0.01) than MIBG score (VMA: r(2) = 0.19, P = 0.082, HVA: r(2) = 0.25, P = 0.137). There were relatively good correlations between serial change of TMRR and those of urinary catecholamine metabolites (VMA: r(2) = 0.274, P < 0.001, HVA: r(2) = 0.448, P < 0.0001) compared with serial change of MIBG score and those of tumor markers (VMA: r(2) = 0.01, P = 0.537, HVA: 0.084, P = 0.697) during chemotherapy for advanced neuroblastoma. TMRR could be a useful semi-quantitative method for estimating early response to chemotherapy of advanced neuroblastoma because of its high correlation with urine catecholamine metabolites.

Quantitative Detection of Cracks in Steel Using Eddy Current Pulsed Thermography.

PubMed

Shi, Zhanqun; Xu, Xiaoyu; Ma, Jiaojiao; Zhen, Dong; Zhang, Hao

2018-04-02

Small cracks are common defects in steel and often lead to catastrophic accidents in industrial applications. Various nondestructive testing methods have been investigated for crack detection; however, most current methods focus on qualitative crack identification and image processing. In this study, eddy current pulsed thermography (ECPT) was applied for quantitative crack detection based on derivative analysis of temperature variation. The effects of the incentive parameters on the temperature variation were analyzed in the simulation study. The crack profile and position are identified in the thermal image based on the Canny edge detection algorithm. Then, one or more trajectories are determined through the crack profile in order to determine the crack boundary through its temperature distribution. The slope curve along the trajectory is obtained. Finally, quantitative analysis of the crack sizes was performed by analyzing the features of the slope curves. The experimental verification showed that the crack sizes could be quantitatively detected with errors of less than 1%. Therefore, the proposed ECPT method was demonstrated to be a feasible and effective nondestructive approach for quantitative crack detection.

Real-time label-free quantitative fluorescence microscopy-based detection of ATP using a tunable fluorescent nano-aptasensor platform.

PubMed

Shrivastava, Sajal; Sohn, Il-Yung; Son, Young-Min; Lee, Won-Il; Lee, Nae-Eung

2015-12-14

Although real-time label-free fluorescent aptasensors based on nanomaterials are increasingly recognized as a useful strategy for the detection of target biomolecules with high fidelity, the lack of an imaging-based quantitative measurement platform limits their implementation with biological samples. Here we introduce an ensemble strategy for a real-time label-free fluorescent graphene (Gr) aptasensor platform. This platform employs aptamer length-dependent tunability, thus enabling the reagentless quantitative detection of biomolecules through computational processing coupled with real-time fluorescence imaging data. We demonstrate that this strategy effectively delivers dose-dependent quantitative readouts of adenosine triphosphate (ATP) concentration on chemical vapor deposited (CVD) Gr and reduced graphene oxide (rGO) surfaces, thereby providing cytotoxicity assessment. Compared with conventional fluorescence spectrometry methods, our highly efficient, universally applicable, and rational approach will facilitate broader implementation of imaging-based biosensing platforms for the quantitative evaluation of a range of target molecules.

Development of a quantitative assessment method of pigmentary skin disease using ultraviolet optical imaging.

PubMed

Lee, Onseok; Park, Sunup; Kim, Jaeyoung; Oh, Chilhwan

2017-11-01

The visual scoring method has been used as a subjective evaluation of pigmentary skin disorders. Severity of pigmentary skin disease, especially melasma, is evaluated using a visual scoring method, the MASI (melasma area severity index). This study differentiates between epidermal and dermal pigmented disease. The study was undertaken to determine methods to quantitatively measure the severity of pigmentary skin disorders under ultraviolet illumination. The optical imaging system consists of illumination (white LED, UV-A lamp) and image acquisition (DSLR camera, air cooling CMOS CCD camera). Each camera is equipped with a polarizing filter to remove glare. To analyze images of visible and UV light, images are divided into frontal, cheek, and chin regions of melasma patients. Each image must undergo image processing. To reduce the curvature error in facial contours, a gradient mask is used. The new method of segmentation of front and lateral facial images is more objective for face-area-measurement than the MASI score. Image analysis of darkness and homogeneity is adequate to quantify the conventional MASI score. Under visible light, active lesion margins appear in both epidermal and dermal melanin, whereas melanin is found in the epidermis under UV light. This study objectively analyzes severity of melasma and attempts to develop new methods of image analysis with ultraviolet optical imaging equipment. Based on the results of this study, our optical imaging system could be used as a valuable tool to assess the severity of pigmentary skin disease. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Accurate Construction of Photoactivated Localization Microscopy (PALM) Images for Quantitative Measurements

PubMed Central

Coltharp, Carla; Kessler, Rene P.; Xiao, Jie

2012-01-01

Localization-based superresolution microscopy techniques such as Photoactivated Localization Microscopy (PALM) and Stochastic Optical Reconstruction Microscopy (STORM) have allowed investigations of cellular structures with unprecedented optical resolutions. One major obstacle to interpreting superresolution images, however, is the overcounting of molecule numbers caused by fluorophore photoblinking. Using both experimental and simulated images, we determined the effects of photoblinking on the accurate reconstruction of superresolution images and on quantitative measurements of structural dimension and molecule density made from those images. We found that structural dimension and relative density measurements can be made reliably from images that contain photoblinking-related overcounting, but accurate absolute density measurements, and consequently faithful representations of molecule counts and positions in cellular structures, require the application of a clustering algorithm to group localizations that originate from the same molecule. We analyzed how applying a simple algorithm with different clustering thresholds (tThresh and dThresh) affects the accuracy of reconstructed images, and developed an easy method to select optimal thresholds. We also identified an empirical criterion to evaluate whether an imaging condition is appropriate for accurate superresolution image reconstruction with the clustering algorithm. Both the threshold selection method and imaging condition criterion are easy to implement within existing PALM clustering algorithms and experimental conditions. The main advantage of our method is that it generates a superresolution image and molecule position list that faithfully represents molecule counts and positions within a cellular structure, rather than only summarizing structural properties into ensemble parameters. This feature makes it particularly useful for cellular structures of heterogeneous densities and irregular geometries, and allows a variety of quantitative measurements tailored to specific needs of different biological systems. PMID:23251611

Research on respiratory motion correction method based on liver contrast-enhanced ultrasound images of single mode

NASA Astrophysics Data System (ADS)

Zhang, Ji; Li, Tao; Zheng, Shiqiang; Li, Yiyong

2015-03-01

To reduce the effects of respiratory motion in the quantitative analysis based on liver contrast-enhanced ultrasound (CEUS) image sequencesof single mode. The image gating method and the iterative registration method using model image were adopted to register liver contrast-enhanced ultrasound image sequences of single mode. The feasibility of the proposed respiratory motion correction method was explored preliminarily using 10 hepatocellular carcinomas CEUS cases. The positions of the lesions in the time series of 2D ultrasound images after correction were visually evaluated. Before and after correction, the quality of the weighted sum of transit time (WSTT) parametric images were also compared, in terms of the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) of time-intensity curve (TIC) fitting derived from CEUS sequences were measured. After the correction, the positions of the lesions in the time series of 2D ultrasound images were almost invariant. In contrast, the lesions in the uncorrected images all shifted noticeably. The quality of the WSTT parametric maps derived from liver CEUS image sequences were improved more greatly. Moreover, the mDVs of TIC fitting derived from CEUS sequences after the correction decreased by an average of 48.48+/-42.15. The proposed correction method could improve the accuracy of quantitative analysis based on liver CEUS image sequences of single mode, which would help in enhancing the differential diagnosis efficiency of liver tumors.

Phase calibration target for quantitative phase imaging with ptychography.

PubMed

Godden, T M; Muñiz-Piniella, A; Claverley, J D; Yacoot, A; Humphry, M J

2016-04-04

Quantitative phase imaging (QPI) utilizes refractive index and thickness variations that lead to optical phase shifts. This gives contrast to images of transparent objects. In quantitative biology, phase images are used to accurately segment cells and calculate properties such as dry mass, volume and proliferation rate. The fidelity of the measured phase shifts is of critical importance in this field. However to date, there has been no standardized method for characterizing the performance of phase imaging systems. Consequently, there is an increasing need for protocols to test the performance of phase imaging systems using well-defined phase calibration and resolution targets. In this work, we present a candidate for a standardized phase resolution target, and measurement protocol for the determination of the transfer of spatial frequencies, and sensitivity of a phase imaging system. The target has been carefully designed to contain well-defined depth variations over a broadband range of spatial frequencies. In order to demonstrate the utility of the target, we measure quantitative phase images on a ptychographic microscope, and compare the measured optical phase shifts with Atomic Force Microscopy (AFM) topography maps and surface profile measurements from coherence scanning interferometry. The results show that ptychography has fully quantitative nanometer sensitivity in optical path differences over a broadband range of spatial frequencies for feature sizes ranging from micrometers to hundreds of micrometers.

Wave field restoration using three-dimensional Fourier filtering method.

PubMed

Kawasaki, T; Takai, Y; Ikuta, T; Shimizu, R

2001-11-01

A wave field restoration method in transmission electron microscopy (TEM) was mathematically derived based on a three-dimensional (3D) image formation theory. Wave field restoration using this method together with spherical aberration correction was experimentally confirmed in through-focus images of amorphous tungsten thin film, and the resolution of the reconstructed phase image was successfully improved from the Scherzer resolution limit to the information limit. In an application of this method to a crystalline sample, the surface structure of Au(110) was observed in a profile-imaging mode. The processed phase image showed quantitatively the atomic relaxation of the topmost layer.

A quantitative experimental phantom study on MRI image uniformity.

PubMed

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

2018-05-23

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

FT-IR imaging for quantitative determination of liver fat content in non-alcoholic fatty liver.

PubMed

Kochan, K; Maslak, E; Chlopicki, S; Baranska, M

2015-08-07

In this work we apply FT-IR imaging of large areas of liver tissue cross-section samples (∼5 cm × 5 cm) for quantitative assessment of steatosis in murine model of Non-Alcoholic Fatty Liver (NAFLD). We quantified the area of liver tissue occupied by lipid droplets (LDs) by FT-IR imaging and Oil Red O (ORO) staining for comparison. Two alternative FT-IR based approaches are presented. The first, straightforward method, was based on average spectra from tissues and provided values of the fat content by using a PLS regression model and the reference method. The second one – the chemometric-based method – enabled us to determine the values of the fat content, independently of the reference method by means of k-means cluster (KMC) analysis. In summary, FT-IR images of large size liver sections may prove to be useful for quantifying liver steatosis without the need of tissue staining.

Non-invasive quantitative pulmonary V/Q imaging using Fourier decomposition MRI at 1.5T.

PubMed

Kjørstad, Åsmund; Corteville, Dominique M R; Henzler, Thomas; Schmid-Bindert, Gerald; Zöllner, Frank G; Schad, Lothar R

2015-12-01

Techniques for quantitative pulmonary perfusion and ventilation using the Fourier Decomposition method were recently demonstrated. We combine these two techniques and show that ventilation-perfusion (V/Q) imaging is possible using only a single MR acquisition of less than thirty seconds. The Fourier Decomposition method is used in combination with two quantification techniques, which extract baselines from within the images themselves and thus allows quantification. For the perfusion, a region assumed to consist of 100% blood is utilized, while for the ventilation the zero-frequency component is used. V/Q-imaging is then done by dividing the quantified ventilation map with the quantified perfusion map. The techniques were used on ten healthy volunteers and fifteen patients diagnosed with lung cancer. A mean V/Q-ratio of 1.15 ± 0.22 was found for the healthy volunteers and a mean V/Q-ratio of 1.93 ± 0.83 for the non-afflicted lung in the patients. Mean V/Q-ratio in the afflicted (tumor-bearing) lung was found to be 1.61 ± 1.06. Functional defects were clearly visible in many of the patient images, but 5 of 15 patient images had to be excluded due to artifacts or low SNR, indicating a lack of robustness. Non-invasive, quantitative V/Q-imaging is possible using Fourier Decomposition MRI. The method requires only a single acquisition of less than 30 seconds, but robustness in patients remains an issue. Copyright © 2015. Published by Elsevier GmbH.

Development of quantitative analysis method for stereotactic brain image: assessment of reduced accumulation in extent and severity using anatomical segmentation.

PubMed

Mizumura, Sunao; Kumita, Shin-ichiro; Cho, Keiichi; Ishihara, Makiko; Nakajo, Hidenobu; Toba, Masahiro; Kumazaki, Tatsuo

2003-06-01

Through visual assessment by three-dimensional (3D) brain image analysis methods using stereotactic brain coordinates system, such as three-dimensional stereotactic surface projections and statistical parametric mapping, it is difficult to quantitatively assess anatomical information and the range of extent of an abnormal region. In this study, we devised a method to quantitatively assess local abnormal findings by segmenting a brain map according to anatomical structure. Through quantitative local abnormality assessment using this method, we studied the characteristics of distribution of reduced blood flow in cases with dementia of the Alzheimer type (DAT). Using twenty-five cases with DAT (mean age, 68.9 years old), all of whom were diagnosed as probable Alzheimer's disease based on NINCDS-ADRDA, we collected I-123 iodoamphetamine SPECT data. A 3D brain map using the 3D-SSP program was compared with the data of 20 cases in the control group, who age-matched the subject cases. To study local abnormalities on the 3D images, we divided the whole brain into 24 segments based on anatomical classification. We assessed the extent of an abnormal region in each segment (rate of the coordinates with a Z-value that exceeds the threshold value, in all coordinates within a segment), and severity (average Z-value of the coordinates with a Z-value that exceeds the threshold value). This method clarified orientation and expansion of reduced accumulation, through classifying stereotactic brain coordinates according to the anatomical structure. This method was considered useful for quantitatively grasping distribution abnormalities in the brain and changes in abnormality distribution.

Computer simulation of schlieren images of rotationally symmetric plasma systems: a simple method.

PubMed

Noll, R; Haas, C R; Weikl, B; Herziger, G

1986-03-01

Schlieren techniques are commonly used methods for quantitative analysis of cylindrical or spherical index of refraction profiles. Many schlieren objects, however, are characterized by more complex geometries, so we have investigated the more general case of noncylindrical, rotationally symmetric distributions of index of refraction n(r,z). Assuming straight ray paths in the schlieren object we have calculated 2-D beam deviation profiles. It is shown that experimental schlieren images of the noncylindrical plasma generated by a plasma focus device can be simulated with these deviation profiles. The computer simulation allows a quantitative analysis of these schlieren images, which yields, for example, the plasma parameters, electron density, and electron density gradients.

Image analysis and modeling in medical image computing. Recent developments and advances.

PubMed

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

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body. Hence, model-based image computing methods are important tools to improve medical diagnostics and patient treatment in future.

Highly sensitive transient absorption imaging of graphene and graphene oxide in living cells and circulating blood

PubMed Central

Li, Junjie; Zhang, Weixia; Chung, Ting-Fung; Slipchenko, Mikhail N.; Chen, Yong P.; Cheng, Ji-Xin; Yang, Chen

2015-01-01

We report a transient absorption (TA) imaging method for fast visualization and quantitative layer analysis of graphene and GO. Forward and backward imaging of graphene on various substrates under ambient condition was imaged with a speed of 2 μs per pixel. The TA intensity linearly increased with the layer number of graphene. Real-time TA imaging of GO in vitro with capability of quantitative analysis of intracellular concentration and ex vivo in circulating blood were demonstrated. These results suggest that TA microscopy is a valid tool for the study of graphene based materials. PMID:26202216

Computational method for multi-modal microscopy based on transport of intensity equation

NASA Astrophysics Data System (ADS)

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

2017-02-01

In this paper, we develop the requisite theory to describe a hybrid virtual-physical multi-modal imaging system which yields quantitative phase, Zernike phase contrast, differential interference contrast (DIC), and light field moment imaging simultaneously based on transport of intensity equation(TIE). We then give the experimental demonstration of these ideas by time-lapse imaging of live HeLa cell mitosis. Experimental results verify that a tunable lens based TIE system, combined with the appropriate post-processing algorithm, can achieve a variety of promising imaging modalities in parallel with the quantitative phase images for the dynamic study of cellular processes.

ADvanced IMage Algebra (ADIMA): a novel method for depicting multiple sclerosis lesion heterogeneity, as demonstrated by quantitative MRI

PubMed Central

Tozer, Daniel J; Schmierer, Klaus; Chard, Declan T; Anderson, Valerie M; Altmann, Daniel R; Miller, David H; Wheeler-Kingshott, Claudia AM

2013-01-01

Background: There are modest correlations between multiple sclerosis (MS) disability and white matter lesion (WML) volumes, as measured by T2-weighted (T2w) magnetic resonance imaging (MRI) scans (T2-WML). This may partly reflect pathological heterogeneity in WMLs, which is not apparent on T2w scans. Objective: To determine if ADvanced IMage Algebra (ADIMA), a novel MRI post-processing method, can reveal WML heterogeneity from proton-density weighted (PDw) and T2w images. Methods: We obtained conventional PDw and T2w images from 10 patients with relapsing–remitting MS (RRMS) and ADIMA images were calculated from these. We classified all WML into bright (ADIMA-b) and dark (ADIMA-d) sub-regions, which were segmented. We obtained conventional T2-WML and T1-WML volumes for comparison, as well as the following quantitative magnetic resonance parameters: magnetisation transfer ratio (MTR), T1 and T2. Also, we assessed the reproducibility of the segmentation for ADIMA-b, ADIMA-d and T2-WML. Results: Our study’s ADIMA-derived volumes correlated with conventional lesion volumes (p < 0.05). ADIMA-b exhibited higher T1 and T2, and lower MTR than the T2-WML (p < 0.001). Despite the similarity in T1 values between ADIMA-b and T1-WML, these regions were only partly overlapping with each other. ADIMA-d exhibited quantitative characteristics similar to T2-WML; however, they were only partly overlapping. Mean intra- and inter-observer coefficients of variation for ADIMA-b, ADIMA-d and T2-WML volumes were all < 6 % and < 10 %, respectively. Conclusion: ADIMA enabled the simple classification of WML into two groups having different quantitative magnetic resonance properties, which can be reproducibly distinguished. PMID:23037551

Cartilage Repair Surgery: Outcome Evaluation by Using Noninvasive Cartilage Biomarkers Based on Quantitative MRI Techniques?

PubMed Central

Jungmann, Pia M.; Baum, Thomas; Bauer, Jan S.; Karampinos, Dimitrios C.; Link, Thomas M.; Li, Xiaojuan; Trattnig, Siegfried; Rummeny, Ernst J.; Woertler, Klaus; Welsch, Goetz H.

2014-01-01

Background. New quantitative magnetic resonance imaging (MRI) techniques are increasingly applied as outcome measures after cartilage repair. Objective. To review the current literature on the use of quantitative MRI biomarkers for evaluation of cartilage repair at the knee and ankle. Methods. Using PubMed literature research, studies on biochemical, quantitative MR imaging of cartilage repair were identified and reviewed. Results. Quantitative MR biomarkers detect early degeneration of articular cartilage, mainly represented by an increasing water content, collagen disruption, and proteoglycan loss. Recently, feasibility of biochemical MR imaging of cartilage repair tissue and surrounding cartilage was demonstrated. Ultrastructural properties of the tissue after different repair procedures resulted in differences in imaging characteristics. T2 mapping, T1rho mapping, delayed gadolinium-enhanced MRI of cartilage (dGEMRIC), and diffusion weighted imaging (DWI) are applicable on most clinical 1.5 T and 3 T MR scanners. Currently, a standard of reference is difficult to define and knowledge is limited concerning correlation of clinical and MR findings. The lack of histological correlations complicates the identification of the exact tissue composition. Conclusions. A multimodal approach combining several quantitative MRI techniques in addition to morphological and clinical evaluation might be promising. Further investigations are required to demonstrate the potential for outcome evaluation after cartilage repair. PMID:24877139

Targeted Single-Shot Methods for Diffusion-Weighted Imaging in the Kidneys

PubMed Central

Jin, Ning; Deng, Jie; Zhang, Longjiang; Zhang, Zhuoli; Lu, Guangming; Omary, Reed A.; Larson, Andrew C.

2011-01-01

Purpose To investigate the feasibility of combining the inner-volume-imaging (IVI) technique with single-shot diffusion-weighted (DW) spin-echo echo-planar imaging (SE-EPI) and DW-SPLICE (split acquisition of fast spin-echo) sequences for renal DW imaging. Materials and Methods Renal DW imaging was performed in 10 healthy volunteers using single-shot DW-SE-EPI, DW-SPLICE, targeted-DW-SE-EPI and targeted-DW-SPLICE. We compared the quantitative diffusion measurement accuracy and image quality of these targeted-DW-SE-EPI and targeted DW-SPLICE methods with conventional full FOV DW-SE-EPI and DW-SPLICE measurements in phantoms and normal volunteers. Results Compared with full FOV DW-SE-EPI and DW-SPLICE methods, targeted-DW-SE-EPI and targeted-DW-SPLICE approaches produced images of superior overall quality with fewer artifacts, less distortion and reduced spatial blurring in both phantom and volunteer studies. The ADC values measured with each of the four methods were similar and in agreement with previously published data. There were no statistically significant differences between the ADC values and intra-voxel incoherent motion (IVIM) measurements in the kidney cortex and medulla using single-shot DW-SE-EPI, targeted-DW-EPI and targeted-DW-SPLICE (p > 0.05). Conclusion Compared with full-FOV DW imaging methods, targeted-DW-SE-EPI and targeted-DW-SPLICE techniques reduced image distortion and artifacts observed in the single-shot DW-SE-EPI images, reduced blurring in DW-SPLICE images and produced comparable quantitative DW and IVIM measurements to those produced with conventional full-FOV approaches. PMID:21591023

High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

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

Wu, Zhao; Gao, Kun; Chen, Jian

2015-02-15

Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using themore » error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations.« less

Nuclear medicine and imaging research: Quantitative studies in radiopharmaceutical science

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

Copper, M.; Beck, R.N.

1991-06-01

During the past three years the program has undergone a substantial revitalization. There has been no significant change in the scientific direction of this grant, in which emphasis continues to be placed on developing new or improved methods of obtaining quantitative data from radiotracer imaging studies. However, considerable scientific progress has been made in the three areas of interest: Radiochemistry, Quantitative Methodologies, and Experimental Methods and Feasibility Studies, resulting in a sharper focus of perspective and improved integration of the overall scientific effort. Changes in Faculty and staff, including development of new collaborations, have contributed to this, as has acquisitionmore » of additional and new equipment and renovations and expansion of the core facilities. 121 refs., 30 figs., 2 tabs.« less

Quantitative analysis of collagen change between normal and cancerous thyroid tissues based on SHG method

NASA Astrophysics Data System (ADS)

Chen, Xiwen; Huang, Zufang; Xi, Gangqin; Chen, Yongjian; Lin, Duo; Wang, Jing; Li, Zuanfang; Sun, Liqing; Chen, Jianxin; Chen, Rong

2012-03-01

Second-harmonic generation (SHG) is proved to be a high spatial resolution, large penetration depth and non-photobleaching method. In our study, SHG method was used to investigate the normal and cancerous thyroid tissue. For SHG imaging performance, system parameters were adjusted for high-contrast images acquisition. Each x-y image was recorded in pseudo-color, which matches the wavelength range in the visible spectrum. The acquisition time for a 512×512-pixels image was 1.57 sec; each acquired image was averaged four frames to improve the signal-to-noise ratio. Our results indicated that collagen presence as determined by counting the ratio of the SHG pixels over the whole pixels for normal and cancerous thyroid tissues were 0.48+/-0.05, 0.33+/-0.06 respectively. In addition, to quantitatively assess collagen-related changes, we employed GLCM texture analysis to the SHG images. Corresponding results showed that the correlation both fell off with distance in normal and cancerous group. Calculated value of Corr50 (the distance where the correlation crossed 50% of the initial correlation) indicated significant difference. This study demonstrates that SHG method can be used as a complementary tool in thyroid histopathology.

Nonlinear optical microscopy: use of second harmonic generation and two-photon microscopy for automated quantitative liver fibrosis studies.

PubMed

Sun, Wanxin; Chang, Shi; Tai, Dean C S; Tan, Nancy; Xiao, Guangfa; Tang, Huihuan; Yu, Hanry

2008-01-01

Liver fibrosis is associated with an abnormal increase in an extracellular matrix in chronic liver diseases. Quantitative characterization of fibrillar collagen in intact tissue is essential for both fibrosis studies and clinical applications. Commonly used methods, histological staining followed by either semiquantitative or computerized image analysis, have limited sensitivity, accuracy, and operator-dependent variations. The fibrillar collagen in sinusoids of normal livers could be observed through second-harmonic generation (SHG) microscopy. The two-photon excited fluorescence (TPEF) images, recorded simultaneously with SHG, clearly revealed the hepatocyte morphology. We have systematically optimized the parameters for the quantitative SHG/TPEF imaging of liver tissue and developed fully automated image analysis algorithms to extract the information of collagen changes and cell necrosis. Subtle changes in the distribution and amount of collagen and cell morphology are quantitatively characterized in SHG/TPEF images. By comparing to traditional staining, such as Masson's trichrome and Sirius red, SHG/TPEF is a sensitive quantitative tool for automated collagen characterization in liver tissue. Our system allows for enhanced detection and quantification of sinusoidal collagen fibers in fibrosis research and clinical diagnostics.

Quantitative 4D Transcatheter Intraarterial Perfusion MR Imaging as a Method to Standardize Angiographic Chemoembolization Endpoints

PubMed Central

Jin, Brian; Wang, Dingxin; Lewandowski, Robert J.; Ryu, Robert K.; Sato, Kent T.; Larson, Andrew C.; Salem, Riad; Omary, Reed A.

2011-01-01

PURPOSE We aimed to test the hypothesis that subjective angiographic endpoints during transarterial chemoembolization (TACE) of hepatocellular carcinoma (HCC) exhibit consistency and correlate with objective intraprocedural reductions in tumor perfusion as determined by quantitative four dimensional (4D) transcatheter intraarterial perfusion (TRIP) magnetic resonance (MR) imaging. MATERIALS AND METHODS This prospective study was approved by the institutional review board. Eighteen consecutive patients underwent TACE in a combined MR/interventional radiology (MR-IR) suite. Three board-certified interventional radiologists independently graded the angiographic endpoint of each procedure based on a previously described subjective angiographic chemoembolization endpoint (SACE) scale. A consensus SACE rating was established for each patient. Patients underwent quantitative 4D TRIP-MR imaging immediately before and after TACE, from which mean whole tumor perfusion (Fρ) was calculated. Consistency of SACE ratings between observers was evaluated using the intraclass correlation coefficient (ICC). The relationship between SACE ratings and intraprocedural TRIP-MR imaging perfusion changes was evaluated using Spearman’s rank correlation coefficient. RESULTS The SACE rating scale demonstrated very good consistency among all observers (ICC = 0.80). The consensus SACE rating was significantly correlated with both absolute (r = 0.54, P = 0.022) and percent (r = 0.85, P < 0.001) intraprocedural perfusion reduction. CONCLUSION The SACE rating scale demonstrates very good consistency between raters, and significantly correlates with objectively measured intraprocedural perfusion reductions during TACE. These results support the use of the SACE scale as a standardized alternative method to quantitative 4D TRIP-MR imaging to classify patients based on embolic endpoints of TACE. PMID:22021520

Benchmarking the performance of fixed-image receptor digital radiographic systems part 1: a novel method for image quality analysis.

PubMed

Lee, Kam L; Ireland, Timothy A; Bernardo, Michael

2016-06-01

This is the first part of a two-part study in benchmarking the performance of fixed digital radiographic general X-ray systems. This paper concentrates on reporting findings related to quantitative analysis techniques used to establish comparative image quality metrics. A systematic technical comparison of the evaluated systems is presented in part two of this study. A novel quantitative image quality analysis method is presented with technical considerations addressed for peer review. The novel method was applied to seven general radiographic systems with four different makes of radiographic image receptor (12 image receptors in total). For the System Modulation Transfer Function (sMTF), the use of grid was found to reduce veiling glare and decrease roll-off. The major contributor in sMTF degradation was found to be focal spot blurring. For the System Normalised Noise Power Spectrum (sNNPS), it was found that all systems examined had similar sNNPS responses. A mathematical model is presented to explain how the use of stationary grid may cause a difference between horizontal and vertical sNNPS responses.

Computer-aided analysis with Image J for quantitatively assessing psoriatic lesion area.

PubMed

Sun, Z; Wang, Y; Ji, S; Wang, K; Zhao, Y

2015-11-01

Body surface area is important in determining the severity of psoriasis. However, objective, reliable, and practical method is still in need for this purpose. We performed a computer image analysis (CIA) of psoriatic area using the image J freeware to determine whether this method could be used for objective evaluation of psoriatic area. Fifteen psoriasis patients were randomized to be treated with adalimumab or placebo in a clinical trial. At each visit, the psoriasis area of each body site was estimated by two physicians (E-method), and standard photographs were taken. The psoriasis area in the pictures was assessed with CIA using semi-automatic threshold selection (T-method), or manual selection (M-method, gold standard). The results assessed by the three methods were analyzed with reliability and affecting factors evaluated. Both T- and E-method correlated strongly with M-method, and T-method had a slightly stronger correlation with M-method. Both T- and E-methods had a good consistency between the evaluators. All the three methods were able to detect the change in the psoriatic area after treatment, while the E-method tends to overestimate. The CIA with image J freeware is reliable and practicable in quantitatively assessing the lesional of psoriasis area. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

PubMed Central

Bigler, Erin D.

2016-01-01

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

Assessment of calcium scoring performance in cardiac computed tomography.

PubMed

Ulzheimer, Stefan; Kalender, Willi A

2003-03-01

Electron beam tomography (EBT) has been used for cardiac diagnosis and the quantitative assessment of coronary calcium since the late 1980s. The introduction of mechanical multi-slice spiral CT (MSCT) scanners with shorter rotation times opened new possibilities of cardiac imaging with conventional CT scanners. The purpose of this work was to qualitatively and quantitatively evaluate the performance for EBT and MSCT for the task of coronary artery calcium imaging as a function of acquisition protocol, heart rate, spiral reconstruction algorithm (where applicable) and calcium scoring method. A cardiac CT semi-anthropomorphic phantom was designed and manufactured for the investigation of all relevant image quality parameters in cardiac CT. This phantom includes various test objects, some of which can be moved within the anthropomorphic phantom in a manner that mimics realistic heart motion. These tools were used to qualitatively and quantitatively demonstrate the accuracy of coronary calcium imaging using typical protocols for an electron beam (Evolution C-150XP, Imatron, South San Francisco, Calif.) and a 0.5-s four-slice spiral CT scanner (Sensation 4, Siemens, Erlangen, Germany). A special focus was put on the method of quantifying coronary calcium, and three scoring systems were evaluated (Agatston, volume, and mass scoring). Good reproducibility in coronary calcium scoring is always the result of a combination of high temporal and spatial resolution; consequently, thin-slice protocols in combination with retrospective gating on MSCT scanners yielded the best results. The Agatston score was found to be the least reproducible scoring method. The hydroxyapatite mass, being better reproducible and comparable on different scanners and being a physical quantitative measure, appears to be the method of choice for future clinical studies. The hydroxyapatite mass is highly correlated to the Agatston score. The introduced phantoms can be used to quantitatively assess the performance characteristics of, for example, different scanners, reconstruction algorithms, and quantification methods in cardiac CT. This is especially important for quantitative tasks, such as the determination of the amount of calcium in the coronary arteries, to achieve high and constant quality in this field.

Quantitative phase imaging using four interferograms with special phase shifts by dual-wavelength in-line phase-shifting interferometry

NASA Astrophysics Data System (ADS)

Xu, Xiaoqing; Wang, Yawei; Ji, Ying; Xu, Yuanyuan; Xie, Ming; Han, Hao

2018-05-01

A new approach of quantitative phase imaging using four interferograms with special phase shifts in dual-wavelength in-line phase-shifting interferometry is presented. In this method, positive negative 2π phase shifts are employed to easily separate the incoherent addition of two single-wavelength interferograms by combining the phase-shifting technique with the subtraction procedure, then the quantitative phase at one of both wavelengths can be achieved based on two intensities without the corresponding dc terms by the use of the character of the trigonometric function. The quantitative phase of the other wavelength can be retrieved from two dc-term suppressed intensities obtained by employing the two-step phase-shifting technique or the filtering technique in the frequency domain. The proposed method is illustrated with theory, and its effectiveness is demonstrated by simulation experiments of the spherical cap and the HeLa cell, respectively.

Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution.

PubMed

Knowles, David W; Biggin, Mark D

2013-01-01

Animals comprise dynamic three-dimensional arrays of cells that express gene products in intricate spatial and temporal patterns that determine cellular differentiation and morphogenesis. A rigorous understanding of these developmental processes requires automated methods that quantitatively record and analyze complex morphologies and their associated patterns of gene expression at cellular resolution. Here we summarize light microscopy-based approaches to establish permanent, quantitative datasets-atlases-that record this information. We focus on experiments that capture data for whole embryos or large areas of tissue in three dimensions, often at multiple time points. We compare and contrast the advantages and limitations of different methods and highlight some of the discoveries made. We emphasize the need for interdisciplinary collaborations and integrated experimental pipelines that link sample preparation, image acquisition, image analysis, database design, visualization, and quantitative analysis. Copyright © 2013 Wiley Periodicals, Inc.

Retrieving the Quantitative Chemical Information at Nanoscale from Scanning Electron Microscope Energy Dispersive X-ray Measurements by Machine Learning

NASA Astrophysics Data System (ADS)

Jany, B. R.; Janas, A.; Krok, F.

2017-11-01

The quantitative composition of metal alloy nanowires on InSb(001) semiconductor surface and gold nanostructures on germanium surface is determined by blind source separation (BSS) machine learning (ML) method using non negative matrix factorization (NMF) from energy dispersive X-ray spectroscopy (EDX) spectrum image maps measured in a scanning electron microscope (SEM). The BSS method blindly decomposes the collected EDX spectrum image into three source components, which correspond directly to the X-ray signals coming from the supported metal nanostructures, bulk semiconductor signal and carbon background. The recovered quantitative composition is validated by detailed Monte Carlo simulations and is confirmed by separate cross-sectional TEM EDX measurements of the nanostructures. This shows that SEM EDX measurements together with machine learning blind source separation processing could be successfully used for the nanostructures quantitative chemical composition determination.

The Edge Detectors Suitable for Retinal OCT Image Segmentation

PubMed Central

Yang, Jing; Gao, Qian; Zhou, Sheng

2017-01-01

Retinal layer thickness measurement offers important information for reliable diagnosis of retinal diseases and for the evaluation of disease development and medical treatment responses. This task critically depends on the accurate edge detection of the retinal layers in OCT images. Here, we intended to search for the most suitable edge detectors for the retinal OCT image segmentation task. The three most promising edge detection algorithms were identified in the related literature: Canny edge detector, the two-pass method, and the EdgeFlow technique. The quantitative evaluation results show that the two-pass method outperforms consistently the Canny detector and the EdgeFlow technique in delineating the retinal layer boundaries in the OCT images. In addition, the mean localization deviation metrics show that the two-pass method caused the smallest edge shifting problem. These findings suggest that the two-pass method is the best among the three algorithms for detecting retinal layer boundaries. The overall better performance of Canny and two-pass methods over EdgeFlow technique implies that the OCT images contain more intensity gradient information than texture changes along the retinal layer boundaries. The results will guide our future efforts in the quantitative analysis of retinal OCT images for the effective use of OCT technologies in the field of ophthalmology. PMID:29065594

Groping for quantitative digital 3-D image analysis: an approach to quantitative fluorescence in situ hybridization in thick tissue sections of prostate carcinoma.

PubMed

Rodenacker, K; Aubele, M; Hutzler, P; Adiga, P S

1997-01-01

In molecular pathology numerical chromosome aberrations have been found to be decisive for the prognosis of malignancy in tumours. The existence of such aberrations can be detected by interphase fluorescence in situ hybridization (FISH). The gain or loss of certain base sequences in the desoxyribonucleic acid (DNA) can be estimated by counting the number of FISH signals per cell nucleus. The quantitative evaluation of such events is a necessary condition for a prospective use in diagnostic pathology. To avoid occlusions of signals, the cell nucleus has to be analyzed in three dimensions. Confocal laser scanning microscopy is the means to obtain series of optical thin sections from fluorescence stained or marked material to fulfill the conditions mentioned above. A graphical user interface (GUI) to a software package for display, inspection, count and (semi-)automatic analysis of 3-D images for pathologists is outlined including the underlying methods of 3-D image interaction and segmentation developed. The preparative methods are briefly described. Main emphasis is given to the methodical questions of computer-aided analysis of large 3-D image data sets for pathologists. Several automated analysis steps can be performed for segmentation and succeeding quantification. However tumour material is in contrast to isolated or cultured cells even for visual inspection, a difficult material. For the present a fully automated digital image analysis of 3-D data is not in sight. A semi-automatic segmentation method is thus presented here.

Agreement between clinical estimation and a new quantitative analysis by Photoshop software in fundus and angiographic image variables.

PubMed

Ramezani, Alireza; Ahmadieh, Hamid; Azarmina, Mohsen; Soheilian, Masoud; Dehghan, Mohammad H; Mohebbi, Mohammad R

2009-12-01

To evaluate the validity of a new method for the quantitative analysis of fundus or angiographic images using Photoshop 7.0 (Adobe, USA) software by comparing with clinical evaluation. Four hundred and eighteen fundus and angiographic images of diabetic patients were evaluated by three retina specialists and then by computing using Photoshop 7.0 software. Four variables were selected for comparison: amount of hard exudates (HE) on color pictures, amount of HE on red-free pictures, severity of leakage, and the size of the foveal avascular zone (FAZ). The coefficient of agreement (Kappa) between the two methods in the amount of HE on color and red-free photographs were 85% (0.69) and 79% (0.59), respectively. The agreement for severity of leakage was 72% (0.46). In the two methods for the evaluation of the FAZ size using the magic and lasso software tools, the agreement was 54% (0.09) and 89% (0.77), respectively. Agreement in the estimation of the FAZ size by the lasso magnetic tool was excellent and was almost as good in the quantification of HE on color and on red-free images. Considering the agreement of this new technique for the measurement of variables in fundus images using Photoshop software with the clinical evaluation, this method seems to have sufficient validity to be used for the quantitative analysis of HE, leakage, and FAZ size on the angiograms of diabetic patients.

Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons.

PubMed

Obuchowski, Nancy A; Reeves, Anthony P; Huang, Erich P; Wang, Xiao-Feng; Buckler, Andrew J; Kim, Hyun J Grace; Barnhart, Huiman X; Jackson, Edward F; Giger, Maryellen L; Pennello, Gene; Toledano, Alicia Y; Kalpathy-Cramer, Jayashree; Apanasovich, Tatiyana V; Kinahan, Paul E; Myers, Kyle J; Goldgof, Dmitry B; Barboriak, Daniel P; Gillies, Robert J; Schwartz, Lawrence H; Sullivan, Daniel C

2015-02-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

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

[Modeling continuous scaling of NDVI based on fractal theory].

PubMed

Luan, Hai-Jun; Tian, Qing-Jiu; Yu, Tao; Hu, Xin-Li; Huang, Yan; Du, Ling-Tong; Zhao, Li-Min; Wei, Xi; Han, Jie; Zhang, Zhou-Wei; Li, Shao-Peng

2013-07-01

Scale effect was one of the very important scientific problems of remote sensing. The scale effect of quantitative remote sensing can be used to study retrievals' relationship between different-resolution images, and its research became an effective way to confront the challenges, such as validation of quantitative remote sensing products et al. Traditional up-scaling methods cannot describe scale changing features of retrievals on entire series of scales; meanwhile, they are faced with serious parameters correction issues because of imaging parameters' variation of different sensors, such as geometrical correction, spectral correction, etc. Utilizing single sensor image, fractal methodology was utilized to solve these problems. Taking NDVI (computed by land surface radiance) as example and based on Enhanced Thematic Mapper Plus (ETM+) image, a scheme was proposed to model continuous scaling of retrievals. Then the experimental results indicated that: (a) For NDVI, scale effect existed, and it could be described by fractal model of continuous scaling; (2) The fractal method was suitable for validation of NDVI. All of these proved that fractal was an effective methodology of studying scaling of quantitative remote sensing.

Calibration methods influence quantitative material decomposition in photon-counting spectral CT

NASA Astrophysics Data System (ADS)

Curtis, Tyler E.; Roeder, Ryan K.

2017-03-01

Photon-counting detectors and nanoparticle contrast agents can potentially enable molecular imaging and material decomposition in computed tomography (CT). Material decomposition has been investigated using both simulated and acquired data sets. However, the effect of calibration methods on material decomposition has not been systematically investigated. Therefore, the objective of this study was to investigate the influence of the range and number of contrast agent concentrations within a modular calibration phantom on quantitative material decomposition. A commerciallyavailable photon-counting spectral micro-CT (MARS Bioimaging) was used to acquire images with five energy bins selected to normalize photon counts and leverage the contrast agent k-edge. Material basis matrix values were determined using multiple linear regression models and material decomposition was performed using a maximum a posteriori estimator. The accuracy of quantitative material decomposition was evaluated by the root mean squared error (RMSE), specificity, sensitivity, and area under the curve (AUC). An increased maximum concentration (range) in the calibration significantly improved RMSE, specificity and AUC. The effects of an increased number of concentrations in the calibration were not statistically significant for the conditions in this study. The overall results demonstrated that the accuracy of quantitative material decomposition in spectral CT is significantly influenced by calibration methods, which must therefore be carefully considered for the intended diagnostic imaging application.

Imaging and quantitative methods for studying cytoskeletal rearrangements during root development and gravitropism.

PubMed

Jacques, Eveline; Wells, Darren M; Bennett, Malcolm J; Vissenberg, Kris

2015-01-01

High-resolution imaging of cytoskeletal structures paves the way for standardized methods to quantify cytoskeletal organization. Here we provide a detailed description of the analysis performed to determine the microtubule patterns in gravistimulated roots, using the recently developed software tool MicroFilament Analyzer.

4D PET iterative deconvolution with spatiotemporal regularization for quantitative dynamic PET imaging.

PubMed

Reilhac, Anthonin; Charil, Arnaud; Wimberley, Catriona; Angelis, Georgios; Hamze, Hasar; Callaghan, Paul; Garcia, Marie-Paule; Boisson, Frederic; Ryder, Will; Meikle, Steven R; Gregoire, Marie-Claude

2015-09-01

Quantitative measurements in dynamic PET imaging are usually limited by the poor counting statistics particularly in short dynamic frames and by the low spatial resolution of the detection system, resulting in partial volume effects (PVEs). In this work, we present a fast and easy to implement method for the restoration of dynamic PET images that have suffered from both PVE and noise degradation. It is based on a weighted least squares iterative deconvolution approach of the dynamic PET image with spatial and temporal regularization. Using simulated dynamic [(11)C] Raclopride PET data with controlled biological variations in the striata between scans, we showed that the restoration method provides images which exhibit less noise and better contrast between emitting structures than the original images. In addition, the method is able to recover the true time activity curve in the striata region with an error below 3% while it was underestimated by more than 20% without correction. As a result, the method improves the accuracy and reduces the variability of the kinetic parameter estimates calculated from the corrected images. More importantly it increases the accuracy (from less than 66% to more than 95%) of measured biological variations as well as their statistical detectivity. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Cancer Imaging Phenomics Toolkit (CaPTk) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

CaPTk is a software toolkit to facilitate translation of quantitative image analysis methods that help us obtain rich imaging phenotypic signatures of oncologic images and relate them to precision diagnostics and prediction of clinical outcomes, as well as to underlying molecular characteristics of cancer. The stand-alone graphical user interface of CaPTk brings analysis methods from the realm of medical imaging research to the clinic, and will be extended to use web-based services for computationally-demanding pipelines.

Cardiac contraction motion compensation in gated myocardial perfusion SPECT: A comparative study.

PubMed

Salehi, Narges; Rahmim, Arman; Fatemizadeh, Emad; Akbarzadeh, Afshin; Farahani, Mohammad Hossein; Farzanefar, Saeed; Ay, Mohammad Reza

2018-05-01

Cardiac contraction significantly degrades quality and quantitative accuracy of gated myocardial perfusion SPECT (MPS) images. In this study, we aimed to explore different techniques in motion-compensated temporal processing of MPS images and their impact on image quality and quantitative accuracy. 50 patients without known heart condition underwent gated MPS. 3D motion compensation methods using Motion Freezing by Cedars Sinai (MF), Log-domain Diffeomorphic Demons (LDD) and Free-Form Deformation (FFD) were applied to warp all image phases to fit the end-diastolic (ED) phase. Afterwards, myocardial wall thickness, myocardial to blood pool contrast, and image contrast-to noise ratio (CNR) were measured in summed images with no motion compensation (NoMC) and compensated images (MF, LDD and FFD). Total Perfusion Defect (TPD) was derived from Cedars-Sinai software, on the basis of sex-specific normal limits. Left ventricle (LV) lateral wall thickness was reduced after applying motion compensation (p < 0.05). Myocardial to blood pool contrast and CNR in compensated images were greater than NoMC (p < 0.05). TPD_LDD was in good agreement with the corresponding TPD_MF (p = 0.13). All methods have improved image quality and quantitative performance relative to NoMC. LDD and FFD are fully automatic and do not require any manual intervention, while MF is dependent on contour definition. In terms of diagnostic parameters LDD is in good agreement with MF which is a clinically accepted method. Further investigation along with diagnostic reference standards, in order to specify diagnostic value of each technique is recommended. Copyright © 2018 Associazione Italiana di Fisica Medica. All rights reserved.

Using Anatomic Magnetic Resonance Image Information to Enhance Visualization and Interpretation of Functional Images: A Comparison of Methods Applied to Clinical Arterial Spin Labeling Images

PubMed Central

Dai, Weiying; Soman, Salil; Hackney, David B.; Wong, Eric T.; Robson, Philip M.; Alsop, David C.

2017-01-01

Functional imaging provides hemodynamic and metabolic information and is increasingly being incorporated into clinical diagnostic and research studies. Typically functional images have reduced signal-to-noise ratio and spatial resolution compared to other non-functional cross sectional images obtained as part of a routine clinical protocol. We hypothesized that enhancing visualization and interpretation of functional images with anatomic information could provide preferable quality and superior diagnostic value. In this work, we implemented five methods (frequency addition, frequency multiplication, wavelet transform, non-subsampled contourlet transform and intensity-hue-saturation) and a newly proposed ShArpening by Local Similarity with Anatomic images (SALSA) method to enhance the visualization of functional images, while preserving the original functional contrast and quantitative signal intensity characteristics over larger spatial scales. Arterial spin labeling blood flow MR images of the brain were visualization enhanced using anatomic images with multiple contrasts. The algorithms were validated on a numerical phantom and their performance on images of brain tumor patients were assessed by quantitative metrics and neuroradiologist subjective ratings. The frequency multiplication method had the lowest residual error for preserving the original functional image contrast at larger spatial scales (55%–98% of the other methods with simulated data and 64%–86% with experimental data). It was also significantly more highly graded by the radiologists (p<0.005 for clear brain anatomy around the tumor). Compared to other methods, the SALSA provided 11%–133% higher similarity with ground truth images in the simulation and showed just slightly lower neuroradiologist grading score. Most of these monochrome methods do not require any prior knowledge about the functional and anatomic image characteristics, except the acquired resolution. Hence, automatic implementation on clinical images should be readily feasible. PMID:27723582

Real-time quantitative Schlieren imaging by fast Fourier demodulation of a checkered backdrop

NASA Astrophysics Data System (ADS)

Wildeman, Sander

2018-06-01

A quantitative synthetic Schlieren imaging (SSI) method based on fast Fourier demodulation is presented. Instead of a random dot pattern (as usually employed in SSI), a 2D periodic pattern (such as a checkerboard) is used as a backdrop to the refractive object of interest. The range of validity and accuracy of this "Fast Checkerboard Demodulation" (FCD) method are assessed using both synthetic data and experimental recordings of patterns optically distorted by small waves on a water surface. It is found that the FCD method is at least as accurate as sophisticated, multi-stage, digital image correlation (DIC) or optical flow (OF) techniques used with random dot patterns, and it is significantly faster. Efficient, fully vectorized, implementations of both the FCD and DIC/OF schemes developed for this study are made available as open source Matlab scripts.

Hyperspectral and differential CARS microscopy for quantitative chemical imaging in human adipocytes

PubMed Central

Di Napoli, Claudia; Pope, Iestyn; Masia, Francesco; Watson, Peter; Langbein, Wolfgang; Borri, Paola

2014-01-01

In this work, we demonstrate the applicability of coherent anti-Stokes Raman scattering (CARS) micro-spectroscopy for quantitative chemical imaging of saturated and unsaturated lipids in human stem-cell derived adipocytes. We compare dual-frequency/differential CARS (D-CARS), which enables rapid imaging and simple data analysis, with broadband hyperspectral CARS microscopy analyzed using an unsupervised phase-retrieval and factorization method recently developed by us for quantitative chemical image analysis. Measurements were taken in the vibrational fingerprint region (1200–2000/cm) and in the CH stretch region (2600–3300/cm) using a home-built CARS set-up which enables hyperspectral imaging with 10/cm resolution via spectral focussing from a single broadband 5 fs Ti:Sa laser source. Through a ratiometric analysis, both D-CARS and phase-retrieved hyperspectral CARS determine the concentration of unsaturated lipids with comparable accuracy in the fingerprint region, while in the CH stretch region D-CARS provides only a qualitative contrast owing to its non-linear behavior. When analyzing hyperspectral CARS images using the blind factorization into susceptibilities and concentrations of chemical components recently demonstrated by us, we are able to determine vol:vol concentrations of different lipid components and spatially resolve inhomogeneities in lipid composition with superior accuracy compared to state-of-the art ratiometric methods. PMID:24877002

Histological Image Processing Features Induce a Quantitative Characterization of Chronic Tumor Hypoxia

PubMed Central

Grabocka, Elda; Bar-Sagi, Dafna; Mishra, Bud

2016-01-01

Hypoxia in tumors signifies resistance to therapy. Despite a wealth of tumor histology data, including anti-pimonidazole staining, no current methods use these data to induce a quantitative characterization of chronic tumor hypoxia in time and space. We use image-processing algorithms to develop a set of candidate image features that can formulate just such a quantitative description of xenographed colorectal chronic tumor hypoxia. Two features in particular give low-variance measures of chronic hypoxia near a vessel: intensity sampling that extends radially away from approximated blood vessel centroids, and multithresholding to segment tumor tissue into normal, hypoxic, and necrotic regions. From these features we derive a spatiotemporal logical expression whose truth value depends on its predicate clauses that are grounded in this histological evidence. As an alternative to the spatiotemporal logical formulation, we also propose a way to formulate a linear regression function that uses all of the image features to learn what chronic hypoxia looks like, and then gives a quantitative similarity score once it is trained on a set of histology images. PMID:27093539

Quantitative imaging biomarkers: Effect of sample size and bias on confidence interval coverage.

PubMed

Obuchowski, Nancy A; Bullen, Jennifer

2017-01-01

Introduction Quantitative imaging biomarkers (QIBs) are being increasingly used in medical practice and clinical trials. An essential first step in the adoption of a quantitative imaging biomarker is the characterization of its technical performance, i.e. precision and bias, through one or more performance studies. Then, given the technical performance, a confidence interval for a new patient's true biomarker value can be constructed. Estimating bias and precision can be problematic because rarely are both estimated in the same study, precision studies are usually quite small, and bias cannot be measured when there is no reference standard. Methods A Monte Carlo simulation study was conducted to assess factors affecting nominal coverage of confidence intervals for a new patient's quantitative imaging biomarker measurement and for change in the quantitative imaging biomarker over time. Factors considered include sample size for estimating bias and precision, effect of fixed and non-proportional bias, clustered data, and absence of a reference standard. Results Technical performance studies of a quantitative imaging biomarker should include at least 35 test-retest subjects to estimate precision and 65 cases to estimate bias. Confidence intervals for a new patient's quantitative imaging biomarker measurement constructed under the no-bias assumption provide nominal coverage as long as the fixed bias is <12%. For confidence intervals of the true change over time, linearity must hold and the slope of the regression of the measurements vs. true values should be between 0.95 and 1.05. The regression slope can be assessed adequately as long as fixed multiples of the measurand can be generated. Even small non-proportional bias greatly reduces confidence interval coverage. Multiple lesions in the same subject can be treated as independent when estimating precision. Conclusion Technical performance studies of quantitative imaging biomarkers require moderate sample sizes in order to provide robust estimates of bias and precision for constructing confidence intervals for new patients. Assumptions of linearity and non-proportional bias should be assessed thoroughly.

Quantitative subsurface analysis using frequency modulated thermal wave imaging

NASA Astrophysics Data System (ADS)

Subhani, S. K.; Suresh, B.; Ghali, V. S.

2018-01-01

Quantitative depth analysis of the anomaly with an enhanced depth resolution is a challenging task towards the estimation of depth of the subsurface anomaly using thermography. Frequency modulated thermal wave imaging introduced earlier provides a complete depth scanning of the object by stimulating it with a suitable band of frequencies and further analyzing the subsequent thermal response using a suitable post processing approach to resolve subsurface details. But conventional Fourier transform based methods used for post processing unscramble the frequencies with a limited frequency resolution and contribute for a finite depth resolution. Spectral zooming provided by chirp z transform facilitates enhanced frequency resolution which can further improves the depth resolution to axially explore finest subsurface features. Quantitative depth analysis with this augmented depth resolution is proposed to provide a closest estimate to the actual depth of subsurface anomaly. This manuscript experimentally validates this enhanced depth resolution using non stationary thermal wave imaging and offers an ever first and unique solution for quantitative depth estimation in frequency modulated thermal wave imaging.

Active illumination using a digital micromirror device for quantitative phase imaging.

PubMed

Shin, Seungwoo; Kim, Kyoohyun; Yoon, Jonghee; Park, YongKeun

2015-11-15

We present a powerful and cost-effective method for active illumination using a digital micromirror device (DMD) for quantitative phase-imaging techniques. Displaying binary illumination patterns on a DMD with appropriate spatial filtering, plane waves with various illumination angles are generated and impinged onto a sample. Complex optical fields of the sample obtained with various incident angles are then measured via Mach-Zehnder interferometry, from which a high-resolution 2D synthetic aperture phase image and a 3D refractive index tomogram of the sample are reconstructed. We demonstrate the fast and stable illumination-control capability of the proposed method by imaging colloidal spheres and biological cells. The capability of high-speed optical diffraction tomography is also demonstrated by measuring 3D Brownian motion of colloidal particles with the tomogram acquisition rate of 100 Hz.

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

Reproducibility and Prognosis of Quantitative Features Extracted from CT Images12

PubMed Central

Balagurunathan, Yoganand; Gu, Yuhua; Wang, Hua; Kumar, Virendra; Grove, Olya; Hawkins, Sam; Kim, Jongphil; Goldgof, Dmitry B; Hall, Lawrence O; Gatenby, Robert A; Gillies, Robert J

2014-01-01

We study the reproducibility of quantitative imaging features that are used to describe tumor shape, size, and texture from computed tomography (CT) scans of non-small cell lung cancer (NSCLC). CT images are dependent on various scanning factors. We focus on characterizing image features that are reproducible in the presence of variations due to patient factors and segmentation methods. Thirty-two NSCLC nonenhanced lung CT scans were obtained from the Reference Image Database to Evaluate Response data set. The tumors were segmented using both manual (radiologist expert) and ensemble (software-automated) methods. A set of features (219 three-dimensional and 110 two-dimensional) was computed, and quantitative image features were statistically filtered to identify a subset of reproducible and nonredundant features. The variability in the repeated experiment was measured by the test-retest concordance correlation coefficient (CCCTreT). The natural range in the features, normalized to variance, was measured by the dynamic range (DR). In this study, there were 29 features across segmentation methods found with CCCTreT and DR ≥ 0.9 and R2Bet ≥ 0.95. These reproducible features were tested for predicting radiologist prognostic score; some texture features (run-length and Laws kernels) had an area under the curve of 0.9. The representative features were tested for their prognostic capabilities using an independent NSCLC data set (59 lung adenocarcinomas), where one of the texture features, run-length gray-level nonuniformity, was statistically significant in separating the samples into survival groups (P ≤ .046). PMID:24772210

High temporal resolution dynamic contrast-enhanced MRI using compressed sensing-combined sequence in quantitative renal perfusion measurement.

PubMed

Chen, Bin; Zhao, Kai; Li, Bo; Cai, Wenchao; Wang, Xiaoying; Zhang, Jue; Fang, Jing

2015-10-01

To demonstrate the feasibility of the improved temporal resolution by using compressed sensing (CS) combined imaging sequence in dynamic contrast-enhanced MRI (DCE-MRI) of kidney, and investigate its quantitative effects on renal perfusion measurements. Ten rabbits were included in the accelerated scans with a CS-combined 3D pulse sequence. To evaluate the image quality, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between the proposed CS strategy and the conventional full sampling method. Moreover, renal perfusion was estimated by using the separable compartmental model in both CS simulation and realistic CS acquisitions. The CS method showed DCE-MRI images with improved temporal resolution and acceptable image contrast, while presenting significantly higher SNR than the fully sampled images (p<.01) at 2-, 3- and 4-X acceleration. In quantitative measurements, renal perfusion results were in good agreement with the fully sampled one (concordance correlation coefficient=0.95, 0.91, 0.88) at 2-, 3- and 4-X acceleration in CS simulation. Moreover, in realistic acquisitions, the estimated perfusion by the separable compartmental model exhibited no significant differences (p>.05) between each CS-accelerated acquisition and the full sampling method. The CS-combined 3D sequence could improve the temporal resolution for DCE-MRI in kidney while yielding diagnostically acceptable image quality, and it could provide effective measurements of renal perfusion. Copyright © 2015 Elsevier Inc. All rights reserved.

Computation of mass-density images from x-ray refraction-angle images.

PubMed

Wernick, Miles N; Yang, Yongyi; Mondal, Indrasis; Chapman, Dean; Hasnah, Moumen; Parham, Christopher; Pisano, Etta; Zhong, Zhong

2006-04-07

In this paper, we investigate the possibility of computing quantitatively accurate images of mass density variations in soft tissue. This is a challenging task, because density variations in soft tissue, such as the breast, can be very subtle. Beginning from an image of refraction angle created by either diffraction-enhanced imaging (DEI) or multiple-image radiography (MIR), we estimate the mass-density image using a constrained least squares (CLS) method. The CLS algorithm yields accurate density estimates while effectively suppressing noise. Our method improves on an analytical method proposed by Hasnah et al (2005 Med. Phys. 32 549-52), which can produce significant artefacts when even a modest level of noise is present. We present a quantitative evaluation study to determine the accuracy with which mass density can be determined in the presence of noise. Based on computer simulations, we find that the mass-density estimation error can be as low as a few per cent for typical density variations found in the breast. Example images computed from less-noisy real data are also shown to illustrate the feasibility of the technique. We anticipate that density imaging may have application in assessment of water content of cartilage resulting from osteoarthritis, in evaluation of bone density, and in mammographic interpretation.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Colour measurements of pigmented rice grain using flatbed scanning and image analysis

NASA Astrophysics Data System (ADS)

Kaisaat, Khotchakorn; Keawdonree, Nuttapong; Chomkokard, Sakchai; Jinuntuya, Noparit; Pattanasiri, Busara

2017-09-01

Recently, the National Bureau of Agricultural Commodity and Food Standards (ACFS) have drafted a manual of Thai colour rice standards. However, there are no quantitative descriptions of rice colour and its measurement method. These drawbacks might lead to misunderstanding for people who use the manual. In this work, we proposed an inexpensive method, using flatbed scanning together with image analysis, to quantitatively measure rice colour and colour uniformity. To demonstrate its general applicability for colour differentiation of rice, we applied it to different kinds of pigmented rice, including Riceberry rice with and without uniform colour and Chinese black rice.

Quantitative endoscopy: initial accuracy measurements.

PubMed

Truitt, T O; Adelman, R A; Kelly, D H; Willging, J P

2000-02-01

The geometric optics of an endoscope can be used to determine the absolute size of an object in an endoscopic field without knowing the actual distance from the object. This study explores the accuracy of a technique that estimates absolute object size from endoscopic images. Quantitative endoscopy involves calibrating a rigid endoscope to produce size estimates from 2 images taken with a known traveled distance between the images. The heights of 12 samples, ranging in size from 0.78 to 11.80 mm, were estimated with this calibrated endoscope. Backup distances of 5 mm and 10 mm were used for comparison. The mean percent error for all estimated measurements when compared with the actual object sizes was 1.12%. The mean errors for 5-mm and 10-mm backup distances were 0.76% and 1.65%, respectively. The mean errors for objects <2 mm and > or =2 mm were 0.94% and 1.18%, respectively. Quantitative endoscopy estimates endoscopic image size to within 5% of the actual object size. This method remains promising for quantitatively evaluating object size from endoscopic images. It does not require knowledge of the absolute distance of the endoscope from the object, rather, only the distance traveled by the endoscope between images.

Quantitative validation of a nonlinear histology-MRI coregistration method using Generalized Q-sampling Imaging in complex human cortical white matter

PubMed Central

Gangolli, Mihika; Holleran, Laurena; Kim, Joong Hee; Stein, Thor D.; Alvarez, Victor; McKee, Ann C.; Brody, David L.

2017-01-01

Advanced diffusion MRI methods have recently been proposed for detection of pathologies such as traumatic axonal injury and chronic traumatic encephalopathy which commonly affect complex cortical brain regions. However, radiological-pathological correlations in human brain tissue that detail the relationship between the multi-component diffusion signal and underlying pathology are lacking. We present a nonlinear voxel based two dimensional coregistration method that is useful for matching diffusion signals to quantitative metrics of high resolution histological images. When validated in ex vivo human cortical tissue at a 250 × 250 × 500 micron spatial resolution, the method proved robust in correlations between generalized q-sampling imaging and histologically based white matter fiber orientations, with r = 0.94 for the primary fiber direction and r = 0.88 for secondary fiber direction in each voxel. Importantly, however, the correlation was substantially worse with reduced spatial resolution or with fiber orientations derived using a diffusion tensor model. Furthermore, we have detailed a quantitative histological metric of white matter fiber integrity termed power coherence capable of distinguishing between architecturally complex but intact white matter from disrupted white matter regions. These methods may allow for more sensitive and specific radiological-pathological correlations of neurodegenerative diseases affecting complex gray and white matter. PMID:28365421

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

PubMed

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

2017-02-15

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

Sensitive elemental detection using microwave-assisted laser-induced breakdown imaging

NASA Astrophysics Data System (ADS)

Iqbal, Adeel; Sun, Zhiwei; Wall, Matthew; Alwahabi, Zeyad T.

2017-10-01

This study reports a sensitive spectroscopic method for quantitative elemental detection by manipulating the temporal and spatial parameters of laser-induced plasma. The method was tested for indium detection in solid samples, in which laser ablation was used to generate a tiny plasma. The lifetime of the laser-induced plasma can be extended to hundreds of microseconds using microwave injection to remobilize the electrons. In this novel method, temporal integrated signal of indium emission was significantly enhanced. Meanwhile, the projected detectable area of the excited indium atoms was also significantly improved using an interference-, instead of diffraction-, based technique, achieved by directly imaging microwave-enhanced plasma through a novel narrow-bandpass filter, exactly centered at the indium emission line. Quantitative laser-induce breakdown spectroscopy was also recorded simultaneously with the new imaging method. The intensities recorded from both methods exhibit very good mutual linear relationship. The detection intensity was improved to 14-folds because of the combined improvements in the plasma lifetime and the area of detection.

New approaches for the analysis of confluent cell layers with quantitative phase digital holographic microscopy

NASA Astrophysics Data System (ADS)

Pohl, L.; Kaiser, M.; Ketelhut, S.; Pereira, S.; Goycoolea, F.; Kemper, Björn

2016-03-01

Digital holographic microscopy (DHM) enables high resolution non-destructive inspection of technical surfaces and minimally-invasive label-free live cell imaging. However, the analysis of confluent cell layers represents a challenge as quantitative DHM phase images in this case do not provide sufficient information for image segmentation, determination of the cellular dry mass or calculation of the cell thickness. We present novel strategies for the analysis of confluent cell layers with quantitative DHM phase contrast utilizing a histogram based-evaluation procedure. The applicability of our approach is illustrated by quantification of drug induced cell morphology changes and it is shown that the method is capable to quantify reliable global morphology changes of confluent cell layers.

Image dehazing based on non-local saturation

NASA Astrophysics Data System (ADS)

Wang, Linlin; Zhang, Qian; Yang, Deyun; Hou, Yingkun; He, Xiaoting

2018-04-01

In this paper, a method based on non-local saturation algorithm is proposed to avoid block and halo effect for single image dehazing with dark channel prior. First we convert original image from RGB color space into HSV color space with the idea of non-local method. Image saturation is weighted equally by the size of fixed window according to image resolution. Second we utilize the saturation to estimate the atmospheric light value and transmission rate. Then through the function of saturation and transmission, the haze-free image is obtained based on the atmospheric scattering model. Comparing the results of existing methods, our method can restore image color and enhance contrast. We guarantee the proposed method with quantitative and qualitative evaluation respectively. Experiments show the better visual effect with high efficiency.

Quantitative X-ray mapping, scatter diagrams and the generation of correction maps to obtain more information about your material

NASA Astrophysics Data System (ADS)

Wuhrer, R.; Moran, K.

2014-03-01

Quantitative X-ray mapping with silicon drift detectors and multi-EDS detector systems have become an invaluable analysis technique and one of the most useful methods of X-ray microanalysis today. The time to perform an X-ray map has reduced considerably with the ability to map minor and trace elements very accurately due to the larger detector area and higher count rate detectors. Live X-ray imaging can now be performed with a significant amount of data collected in a matter of minutes. A great deal of information can be obtained from X-ray maps. This includes; elemental relationship or scatter diagram creation, elemental ratio mapping, chemical phase mapping (CPM) and quantitative X-ray maps. In obtaining quantitative x-ray maps, we are able to easily generate atomic number (Z), absorption (A), fluorescence (F), theoretical back scatter coefficient (η), and quantitative total maps from each pixel in the image. This allows us to generate an image corresponding to each factor (for each element present). These images allow the user to predict and verify where they are likely to have problems in our images, and are especially helpful to look at possible interface artefacts. The post-processing techniques to improve the quantitation of X-ray map data and the development of post processing techniques for improved characterisation are covered in this paper.

Quantitative Chemical Imaging and Unsupervised Analysis Using Hyperspectral Coherent Anti-Stokes Raman Scattering Microscopy

PubMed Central

2013-01-01

In this work, we report a method to acquire and analyze hyperspectral coherent anti-Stokes Raman scattering (CARS) microscopy images of organic materials and biological samples resulting in an unbiased quantitative chemical analysis. The method employs singular value decomposition on the square root of the CARS intensity, providing an automatic determination of the components above noise, which are retained. Complex CARS susceptibility spectra, which are linear in the chemical composition, are retrieved from the CARS intensity spectra using the causality of the susceptibility by two methods, and their performance is evaluated by comparison with Raman spectra. We use non-negative matrix factorization applied to the imaginary part and the nonresonant real part of the susceptibility with an additional concentration constraint to obtain absolute susceptibility spectra of independently varying chemical components and their absolute concentration. We demonstrate the ability of the method to provide quantitative chemical analysis on known lipid mixtures. We then show the relevance of the method by imaging lipid-rich stem-cell-derived mouse adipocytes as well as differentiated embryonic stem cells with a low density of lipids. We retrieve and visualize the most significant chemical components with spectra given by water, lipid, and proteins segmenting the image into the cell surrounding, lipid droplets, cytosol, and the nucleus, and we reveal the chemical structure of the cells, with details visualized by the projection of the chemical contrast into a few relevant channels. PMID:24099603

Fully automatic multi-atlas segmentation of CTA for partial volume correction in cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Liu, Qingyi; Mohy-ud-Din, Hassan; Boutagy, Nabil E.; Jiang, Mingyan; Ren, Silin; Stendahl, John C.; Sinusas, Albert J.; Liu, Chi

2017-05-01

Anatomical-based partial volume correction (PVC) has been shown to improve image quality and quantitative accuracy in cardiac SPECT/CT. However, this method requires manual segmentation of various organs from contrast-enhanced computed tomography angiography (CTA) data. In order to achieve fully automatic CTA segmentation for clinical translation, we investigated the most common multi-atlas segmentation methods. We also modified the multi-atlas segmentation method by introducing a novel label fusion algorithm for multiple organ segmentation to eliminate overlap and gap voxels. To evaluate our proposed automatic segmentation, eight canine 99mTc-labeled red blood cell SPECT/CT datasets that incorporated PVC were analyzed, using the leave-one-out approach. The Dice similarity coefficient of each organ was computed. Compared to the conventional label fusion method, our proposed label fusion method effectively eliminated gaps and overlaps and improved the CTA segmentation accuracy. The anatomical-based PVC of cardiac SPECT images with automatic multi-atlas segmentation provided consistent image quality and quantitative estimation of intramyocardial blood volume, as compared to those derived using manual segmentation. In conclusion, our proposed automatic multi-atlas segmentation method of CTAs is feasible, practical, and facilitates anatomical-based PVC of cardiac SPECT/CT images.

Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy

PubMed Central

Young, Jonathan W; Locke, James C W; Altinok, Alphan; Rosenfeld, Nitzan; Bacarian, Tigran; Swain, Peter S; Mjolsness, Eric; Elowitz, Michael B

2014-01-01

Quantitative single-cell time-lapse microscopy is a powerful method for analyzing gene circuit dynamics and heterogeneous cell behavior. We describe the application of this method to imaging bacteria by using an automated microscopy system. This protocol has been used to analyze sporulation and competence differentiation in Bacillus subtilis, and to quantify gene regulation and its fluctuations in individual Escherichia coli cells. The protocol involves seeding and growing bacteria on small agarose pads and imaging the resulting microcolonies. Images are then reviewed and analyzed using our laboratory's custom MATLAB analysis code, which segments and tracks cells in a frame-to-frame method. This process yields quantitative expression data on cell lineages, which can illustrate dynamic expression profiles and facilitate mathematical models of gene circuits. With fast-growing bacteria, such as E. coli or B. subtilis, image acquisition can be completed in 1 d, with an additional 1–2 d for progressing through the analysis procedure. PMID:22179594

Quantitative live-cell imaging of human immunodeficiency virus (HIV-1) assembly.

PubMed

Baumgärtel, Viola; Müller, Barbara; Lamb, Don C

2012-05-01

Advances in fluorescence methodologies make it possible to investigate biological systems in unprecedented detail. Over the last few years, quantitative live-cell imaging has increasingly been used to study the dynamic interactions of viruses with cells and is expected to become even more indispensable in the future. Here, we describe different fluorescence labeling strategies that have been used to label HIV-1 for live cell imaging and the fluorescence based methods used to visualize individual aspects of virus-cell interactions. This review presents an overview of experimental methods and recent experiments that have employed quantitative microscopy in order to elucidate the dynamics of late stages in the HIV-1 replication cycle. This includes cytosolic interactions of the main structural protein, Gag, with itself and the viral RNA genome, the recruitment of Gag and RNA to the plasma membrane, virion assembly at the membrane and the recruitment of cellular proteins involved in HIV-1 release to the nascent budding site.

Smartphone based hand-held quantitative phase microscope using the transport of intensity equation method.

PubMed

Meng, Xin; Huang, Huachuan; Yan, Keding; Tian, Xiaolin; Yu, Wei; Cui, Haoyang; Kong, Yan; Xue, Liang; Liu, Cheng; Wang, Shouyu

2016-12-20

In order to realize high contrast imaging with portable devices for potential mobile healthcare, we demonstrate a hand-held smartphone based quantitative phase microscope using the transport of intensity equation method. With a cost-effective illumination source and compact microscope system, multi-focal images of samples can be captured by the smartphone's camera via manual focusing. Phase retrieval is performed using a self-developed Android application, which calculates sample phases from multi-plane intensities via solving the Poisson equation. We test the portable microscope using a random phase plate with known phases, and to further demonstrate its performance, a red blood cell smear, a Pap smear and monocot root and broad bean epidermis sections are also successfully imaged. Considering its advantages as an accurate, high-contrast, cost-effective and field-portable device, the smartphone based hand-held quantitative phase microscope is a promising tool which can be adopted in the future in remote healthcare and medical diagnosis.

Pansharpening on the Narrow Vnir and SWIR Spectral Bands of SENTINEL-2

NASA Astrophysics Data System (ADS)

Vaiopoulos, A. D.; Karantzalos, K.

2016-06-01

In this paper results from the evaluation of several state-of-the-art pansharpening techniques are presented for the VNIR and SWIR bands of Sentinel-2. A procedure for the pansharpening is also proposed which aims at respecting the closest spectral similarities between the higher and lower resolution bands. The evaluation included 21 different fusion algorithms and three evaluation frameworks based both on standard quantitative image similarity indexes and qualitative evaluation from remote sensing experts. The overall analysis of the evaluation results indicated that remote sensing experts disagreed with the outcomes and method ranking from the quantitative assessment. The employed image quality similarity indexes and quantitative evaluation framework based on both high and reduced resolution data from the literature didn't manage to highlight/evaluate mainly the spatial information that was injected to the lower resolution images. Regarding the SWIR bands none of the methods managed to deliver significantly better results than a standard bicubic interpolation on the original low resolution bands.

Quantitative Live-Cell Imaging of Human Immunodeficiency Virus (HIV-1) Assembly

PubMed Central

Baumgärtel, Viola; Müller, Barbara; Lamb, Don C.

2012-01-01

Advances in fluorescence methodologies make it possible to investigate biological systems in unprecedented detail. Over the last few years, quantitative live-cell imaging has increasingly been used to study the dynamic interactions of viruses with cells and is expected to become even more indispensable in the future. Here, we describe different fluorescence labeling strategies that have been used to label HIV-1 for live cell imaging and the fluorescence based methods used to visualize individual aspects of virus-cell interactions. This review presents an overview of experimental methods and recent experiments that have employed quantitative microscopy in order to elucidate the dynamics of late stages in the HIV-1 replication cycle. This includes cytosolic interactions of the main structural protein, Gag, with itself and the viral RNA genome, the recruitment of Gag and RNA to the plasma membrane, virion assembly at the membrane and the recruitment of cellular proteins involved in HIV-1 release to the nascent budding site. PMID:22754649

I Vivo Quantitative Ultrasound Imaging and Scatter Assessments.

NASA Astrophysics Data System (ADS)

Lu, Zheng Feng

There is evidence that "instrument independent" measurements of ultrasonic scattering properties would provide useful diagnostic information that is not available with conventional ultrasound imaging. This dissertation is a continuing effort to test the above hypothesis and to incorporate quantitative ultrasound methods into clinical examinations for early detection of diffuse liver disease. A well-established reference phantom method was employed to construct quantitative ultrasound images of tissue in vivo. The method was verified by extensive phantom tests. A new method was developed to measure the effective attenuation coefficient of the body wall. The method relates the slope of the difference between the echo signal power spectrum from a uniform region distal to the body wall and the echo signal power spectrum from a reference phantom to the body wall attenuation. The accuracy obtained from phantom tests suggests further studies with animal experiments. Clinically, thirty-five healthy subjects and sixteen patients with diffuse liver disease were studied by these quantitative ultrasound methods. The average attenuation coefficient in normals agreed with previous investigators' results; in vivo backscatter coefficients agreed with the results from normals measured by O'Donnell. Strong discriminating power (p < 0.001) was found for both attenuation and backscatter coefficients between fatty livers and normals; a significant difference (p < 0.01) was observed in the backscatter coefficient but not in the attenuation coefficient between cirrhotic livers and normals. An in vivo animal model of steroid hepatopathy was used to investigate the system sensitivity in detecting early changes in canine liver resulting from corticosteroid administration. The average attenuation coefficient slope increased from 0.7 dB/cm/MHz in controls to 0.82 dB/cm/MHz (at 6 MHz) in treated animals on day 14 into the treatment, and the backscatter coefficient was 26times 10^{ -4}cm^{-1}sr^{-1} in controls compared with 74times 10^{-4}cm^{-1}sr^ {-1} (at 6 MHz) in treated animals. A simplified quantitative approach using video image signals was developed. Results derived both from the r.f. signal analysis and from the video signal analysis are sensitive to the changes in the liver in this animal model.

Chemoenzymatic method for glycomics: isolation, identification, and quantitation

PubMed Central

Yang, Shuang; Rubin, Abigail; Eshghi, Shadi Toghi; Zhang, Hui

2015-01-01

Over the past decade, considerable progress has been made with respect to the analytical methods for analysis of glycans from biological sources. Regardless of the specific methods that are used, glycan analysis includes isolation, identification, and quantitation. Derivatization is indispensable to increase their identification. Derivatization of glycans can be performed by permethylation or carbodiimide coupling / esterification. By introducing a fluorophore or chromophore at their reducing end, glycans can be separated by electrophoresis or chromatography. The fluorogenically labeled glycans can be quantitated using fluorescent detection. The recently developed approaches using solid-phase such as glycoprotein immobilization for glycan extraction and on-tissue glycan mass spectrometry imaging demonstrate advantages over methods performed in solution. Derivatization of sialic acids is favorably implemented on the solid support using carbodiimide coupling, and the released glycans can be further modified at the reducing end or permethylated for quantitative analysis. In this review, methods for glycan isolation, identification, and quantitation are discussed. PMID:26390280

Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction

PubMed Central

Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib

2016-01-01

Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate Ki as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting Ki images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit Ki bias of sPatlak analysis at regions with non-negligible 18F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source Software for Tomographic Image Reconstruction (STIR) platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published 18F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced Ki target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D vs. the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10–20 sub-iterations. Moreover, systematic reduction in Ki % bias and improved TBR were observed for gPatlak vs. sPatlak. Finally, validation on clinical WB dynamic data demonstrated the clinical feasibility and superior Ki CNR performance for the proposed 4D framework compared to indirect Patlak and SUV imaging. PMID:27383991

Whole-body direct 4D parametric PET imaging employing nested generalized Patlak expectation-maximization reconstruction

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Casey, Michael E.; Lodge, Martin A.; Rahmim, Arman; Zaidi, Habib

2016-08-01

Whole-body (WB) dynamic PET has recently demonstrated its potential in translating the quantitative benefits of parametric imaging to the clinic. Post-reconstruction standard Patlak (sPatlak) WB graphical analysis utilizes multi-bed multi-pass PET acquisition to produce quantitative WB images of the tracer influx rate K i as a complimentary metric to the semi-quantitative standardized uptake value (SUV). The resulting K i images may suffer from high noise due to the need for short acquisition frames. Meanwhile, a generalized Patlak (gPatlak) WB post-reconstruction method had been suggested to limit K i bias of sPatlak analysis at regions with non-negligible 18F-FDG uptake reversibility; however, gPatlak analysis is non-linear and thus can further amplify noise. In the present study, we implemented, within the open-source software for tomographic image reconstruction platform, a clinically adoptable 4D WB reconstruction framework enabling efficient estimation of sPatlak and gPatlak images directly from dynamic multi-bed PET raw data with substantial noise reduction. Furthermore, we employed the optimization transfer methodology to accelerate 4D expectation-maximization (EM) convergence by nesting the fast image-based estimation of Patlak parameters within each iteration cycle of the slower projection-based estimation of dynamic PET images. The novel gPatlak 4D method was initialized from an optimized set of sPatlak ML-EM iterations to facilitate EM convergence. Initially, realistic simulations were conducted utilizing published 18F-FDG kinetic parameters coupled with the XCAT phantom. Quantitative analyses illustrated enhanced K i target-to-background ratio (TBR) and especially contrast-to-noise ratio (CNR) performance for the 4D versus the indirect methods and static SUV. Furthermore, considerable convergence acceleration was observed for the nested algorithms involving 10-20 sub-iterations. Moreover, systematic reduction in K i % bias and improved TBR were observed for gPatlak versus sPatlak. Finally, validation on clinical WB dynamic data demonstrated the clinical feasibility and superior K i CNR performance for the proposed 4D framework compared to indirect Patlak and SUV imaging.

TH-AB-209-09: Quantitative Imaging of Electrical Conductivity by VHF-Induced Thermoacoustics

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

Patch, S; Hull, D; See, W

Purpose: To demonstrate that very high frequency (VHF) induced thermoacoustics has the potential to provide quantitative images of electrical conductivity in Siemens/meter, much as shear wave elastography provides tissue stiffness in kPa. Quantitatively imaging a large organ requires exciting thermoacoustic pulses throughout the volume and broadband detection of those pulses because tomographic image reconstruction preserves frequency content. Applying the half-wavelength limit to a 200-micron inclusion inside a 7.5 cm diameter organ requires measurement sensitivity to frequencies ranging from 4 MHz down to 10 kHz, respectively. VHF irradiation provides superior depth penetration over near infrared used in photoacoustics. Additionally, VHF signalmore » production is proportional to electrical conductivity, and prostate cancer is known to suppress electrical conductivity of prostatic fluid. Methods: A dual-transducer system utilizing a P4-1 array connected to a Verasonics V1 system augmented by a lower frequency focused single element transducer was developed. Simultaneous acquisition of VHF-induced thermoacoustic pulses by both transducers enabled comparison of transducer performance. Data from the clinical array generated a stack of 96-images with separation of 0.3 mm, whereas the single element transducer imaged only in a single plane. In-plane resolution and quantitative accuracy were measured at isocenter. Results: The array provided volumetric imaging capability with superior resolution whereas the single element transducer provided superior quantitative accuracy. Combining axial images from both transducers preserved resolution of the P4-1 array and improved image contrast. Neither transducer was sensitive to frequencies below 50 kHz, resulting in a DC offset and low-frequency shading over fields of view exceeding 15 mm. Fresh human prostates were imaged ex vivo and volumetric reconstructions reveal structures rarely seen in diagnostic images. Conclusion: Quantitative whole-organ thermoacoustic tomography will be feasible by sparsely interspersing transducer elements sensitive to the low end of the ultrasonic range.« less

Informatics in radiology: automated structured reporting of imaging findings using the AIM standard and XML.

PubMed

Zimmerman, Stefan L; Kim, Woojin; Boonn, William W

2011-01-01

Quantitative and descriptive imaging data are a vital component of the radiology report and are frequently of paramount importance to the ordering physician. Unfortunately, current methods of recording these data in the report are both inefficient and error prone. In addition, the free-text, unstructured format of a radiology report makes aggregate analysis of data from multiple reports difficult or even impossible without manual intervention. A structured reporting work flow has been developed that allows quantitative data created at an advanced imaging workstation to be seamlessly integrated into the radiology report with minimal radiologist intervention. As an intermediary step between the workstation and the reporting software, quantitative and descriptive data are converted into an extensible markup language (XML) file in a standardized format specified by the Annotation and Image Markup (AIM) project of the National Institutes of Health Cancer Biomedical Informatics Grid. The AIM standard was created to allow image annotation data to be stored in a uniform machine-readable format. These XML files containing imaging data can also be stored on a local database for data mining and analysis. This structured work flow solution has the potential to improve radiologist efficiency, reduce errors, and facilitate storage of quantitative and descriptive imaging data for research. Copyright © RSNA, 2011.

QIN. Early experiences in establishing a regional quantitative imaging network for PET/CT clinical trials

PubMed Central

Doot, Robert K.; Thompson, Tove; Greer, Benjamin E.; Allberg, Keith C.; Linden, Hannah M.; Mankoff, David A.; Kinahan, Paul E.

2012-01-01

The Seattle Cancer Care Alliance (SCCA) is a Pacific Northwest regional network that enables patients from community cancer centers to participate in multicenter oncology clinical trials where patients can receive some trial-related procedures at their local center. Results of positron emission tomography (PET) scans performed at community cancer centers are not currently used in SCCA Network trials since clinical trials customarily accept results from only trial-accredited PET imaging centers located at academic and large hospitals. Oncologists would prefer the option of using standard clinical PET scans from Network sites in multicenter clinical trials to increase accrual of patients for whom additional travel requirements for imaging is a barrier to recruitment. In an effort to increase accrual of rural and other underserved populations to Network trials, researchers and clinicians at the University of Washington, SCCA and its Network are assessing feasibility of using PET scans from all Network sites in their oncology clinical trials. A feasibility study is required because the reproducibility of multicenter PET measurements ranges from approximately 3% to 40% at national academic centers. Early experiences from both national and local PET phantom imaging trials are discussed and next steps are proposed for including patient PET scans from the emerging regional quantitative imaging network in clinical trials. There are feasible methods to determine and characterize PET quantitation errors and improve data quality by either prospective scanner calibration or retrospective post hoc corrections. These methods should be developed and implemented in multicenter clinical trials employing quantitative PET imaging of patients. PMID:22795929

Early experiences in establishing a regional quantitative imaging network for PET/CT clinical trials.

PubMed

Doot, Robert K; Thompson, Tove; Greer, Benjamin E; Allberg, Keith C; Linden, Hannah M; Mankoff, David A; Kinahan, Paul E

2012-11-01

The Seattle Cancer Care Alliance (SCCA) is a Pacific Northwest regional network that enables patients from community cancer centers to participate in multicenter oncology clinical trials where patients can receive some trial-related procedures at their local center. Results of positron emission tomography (PET) scans performed at community cancer centers are not currently used in SCCA Network trials since clinical trials customarily accept results from only trial-accredited PET imaging centers located at academic and large hospitals. Oncologists would prefer the option of using standard clinical PET scans from Network sites in multicenter clinical trials to increase accrual of patients for whom additional travel requirements for imaging are a barrier to recruitment. In an effort to increase accrual of rural and other underserved populations to Network trials, researchers and clinicians at the University of Washington, SCCA and its Network are assessing the feasibility of using PET scans from all Network sites in their oncology clinical trials. A feasibility study is required because the reproducibility of multicenter PET measurements ranges from approximately 3% to 40% at national academic centers. Early experiences from both national and local PET phantom imaging trials are discussed, and next steps are proposed for including patient PET scans from the emerging regional quantitative imaging network in clinical trials. There are feasible methods to determine and characterize PET quantitation errors and improve data quality by either prospective scanner calibration or retrospective post hoc corrections. These methods should be developed and implemented in multicenter clinical trials employing quantitative PET imaging of patients. Copyright © 2012 Elsevier Inc. All rights reserved.

Radiation exposure in X-ray-based imaging techniques used in osteoporosis

PubMed Central

Adams, Judith E.; Guglielmi, Giuseppe; Link, Thomas M.

2010-01-01

Recent advances in medical X-ray imaging have enabled the development of new techniques capable of assessing not only bone quantity but also structure. This article provides (a) a brief review of the current X-ray methods used for quantitative assessment of the skeleton, (b) data on the levels of radiation exposure associated with these methods and (c) information about radiation safety issues. Radiation doses associated with dual-energy X-ray absorptiometry are very low. However, as with any X-ray imaging technique, each particular examination must always be clinically justified. When an examination is justified, the emphasis must be on dose optimisation of imaging protocols. Dose optimisation is more important for paediatric examinations because children are more vulnerable to radiation than adults. Methods based on multi-detector CT (MDCT) are associated with higher radiation doses. New 3D volumetric hip and spine quantitative computed tomography (QCT) techniques and high-resolution MDCT for evaluation of bone structure deliver doses to patients from 1 to 3 mSv. Low-dose protocols are needed to reduce radiation exposure from these methods and minimise associated health risks. PMID:20559834

A three-image algorithm for hard x-ray grating interferometry.

PubMed

Pelliccia, Daniele; Rigon, Luigi; Arfelli, Fulvia; Menk, Ralf-Hendrik; Bukreeva, Inna; Cedola, Alessia

2013-08-12

A three-image method to extract absorption, refraction and scattering information for hard x-ray grating interferometry is presented. The method comprises a post-processing approach alternative to the conventional phase stepping procedure and is inspired by a similar three-image technique developed for analyzer-based x-ray imaging. Results obtained with this algorithm are quantitatively comparable with phase-stepping. This method can be further extended to samples with negligible scattering, where only two images are needed to separate absorption and refraction signal. Thanks to the limited number of images required, this technique is a viable route to bio-compatible imaging with x-ray grating interferometer. In addition our method elucidates and strengthens the formal and practical analogies between grating interferometry and the (non-interferometric) diffraction enhanced imaging technique.

Segmentation-based retrospective shading correction in fluorescence microscopy E. coli images for quantitative analysis

NASA Astrophysics Data System (ADS)

Mai, Fei; Chang, Chunqi; Liu, Wenqing; Xu, Weichao; Hung, Yeung S.

2009-10-01

Due to the inherent imperfections in the imaging process, fluorescence microscopy images often suffer from spurious intensity variations, which is usually referred to as intensity inhomogeneity, intensity non uniformity, shading or bias field. In this paper, a retrospective shading correction method for fluorescence microscopy Escherichia coli (E. Coli) images is proposed based on segmentation result. Segmentation and shading correction are coupled together, so we iteratively correct the shading effects based on segmentation result and refine the segmentation by segmenting the image after shading correction. A fluorescence microscopy E. Coli image can be segmented (based on its intensity value) into two classes: the background and the cells, where the intensity variation within each class is close to zero if there is no shading. Therefore, we make use of this characteristics to correct the shading in each iteration. Shading is mathematically modeled as a multiplicative component and an additive noise component. The additive component is removed by a denoising process, and the multiplicative component is estimated using a fast algorithm to minimize the intra-class intensity variation. We tested our method on synthetic images and real fluorescence E.coli images. It works well not only for visual inspection, but also for numerical evaluation. Our proposed method should be useful for further quantitative analysis especially for protein expression value comparison.

Quantitative assessment on coronary computed tomography angiography (CCTA) image quality: comparisons between genders and different tube voltage settings

PubMed Central

Chian, Teo Chee; Nassir, Norziana Mat; Ibrahim, Mohd Izuan; Yusof, Ahmad Khairuddin Md

2017-01-01

Background This study was carried out to quantify and compare the quantitative image quality of coronary computed tomography angiography (CCTA) between genders as well as between different tube voltages scan protocols. Methods Fifty-five cases of CCTA were collected retrospectively and all images including reformatted axial images at systolic and diastolic phases as well as images with curved multi planar reformation (cMPR) were obtained. Quantitative image quality including signal intensity, image noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of right coronary artery (RCA), left anterior descending artery (LAD), left circumflex artery (LCx) and left main artery (LM) were quantified using Analyze 12.0 software. Results Six hundred and fifty-seven coronary arteries were evaluated. There were no significant differences in any quantitative image quality parameters between genders. 100 kilovoltage peak (kVp) scanning protocol produced images with significantly higher signal intensity compared to 120 kVp scanning protocol (P<0.001) in all coronary arteries in all types of images. Higher SNR was also observed in 100 kVp scan protocol in all coronary arteries except in LCx where 120 kVp showed better SNR than 100 kVp. Conclusions There were no significant differences in image quality of CCTA between genders and different tube voltages. Lower tube voltage (100 kVp) scanning protocol is recommended in clinical practice to reduce the radiation dose to patient. PMID:28275559

Movement Correction Method for Human Brain PET Images: Application to Quantitative Analysis of Dynamic [18F]-FDDNP Scans

PubMed Central

Wardak, Mirwais; Wong, Koon-Pong; Shao, Weber; Dahlbom, Magnus; Kepe, Vladimir; Satyamurthy, Nagichettiar; Small, Gary W.; Barrio, Jorge R.; Huang, Sung-Cheng

2010-01-01

Head movement during a PET scan (especially, dynamic scan) can affect both the qualitative and quantitative aspects of an image, making it difficult to accurately interpret the results. The primary objective of this study was to develop a retrospective image-based movement correction (MC) method and evaluate its implementation on dynamic [18F]-FDDNP PET images of cognitively intact controls and patients with Alzheimer’s disease (AD). Methods Dynamic [18F]-FDDNP PET images, used for in vivo imaging of beta-amyloid plaques and neurofibrillary tangles, were obtained from 12 AD and 9 age-matched controls. For each study, a transmission scan was first acquired for attenuation correction. An accurate retrospective MC method that corrected for transmission-emission misalignment as well as emission-emission misalignment was applied to all studies. No restriction was assumed for zero movement between the transmission scan and first emission scan. Logan analysis with cerebellum as the reference region was used to estimate various regional distribution volume ratio (DVR) values in the brain before and after MC. Discriminant analysis was used to build a predictive model for group membership, using data with and without MC. Results MC improved the image quality and quantitative values in [18F]-FDDNP PET images. In this subject population, medial temporal (MTL) did not show a significant difference between controls and AD before MC. However, after MC, significant differences in DVR values were seen in frontal, parietal, posterior cingulate (PCG), MTL, lateral temporal (LTL), and global between the two groups (P < 0.05). In controls and AD, the variability of regional DVR values (as measured by the coefficient of variation) decreased on average by >18% after MC. Mean DVR separation between controls and ADs was higher in frontal, MTL, LTL and global after MC. Group classification by discriminant analysis based on [18F]-FDDNP DVR values was markedly improved after MC. Conclusion The streamlined and easy to use MC method presented in this work significantly improves the image quality and the measured tracer kinetics of [18F]-FDDNP PET images. The proposed MC method has the potential to be applied to PET studies on patients having other disorders (e.g., Down syndrome and Parkinson’s disease) and to brain PET scans with other molecular imaging probes. PMID:20080894

Radiologic-Pathologic Analysis of Contrast-enhanced and Diffusion-weighted MR Imaging in Patients with HCC after TACE: Diagnostic Accuracy of 3D Quantitative Image Analysis

PubMed Central

Chapiro, Julius; Wood, Laura D.; Lin, MingDe; Duran, Rafael; Cornish, Toby; Lesage, David; Charu, Vivek; Schernthaner, Rüdiger; Wang, Zhijun; Tacher, Vania; Savic, Lynn Jeanette; Kamel, Ihab R.

2014-01-01

Purpose To evaluate the diagnostic performance of three-dimensional (3Dthree-dimensional) quantitative enhancement-based and diffusion-weighted volumetric magnetic resonance (MR) imaging assessment of hepatocellular carcinoma (HCChepatocellular carcinoma) lesions in determining the extent of pathologic tumor necrosis after transarterial chemoembolization (TACEtransarterial chemoembolization). Materials and Methods This institutional review board–approved retrospective study included 17 patients with HCChepatocellular carcinoma who underwent TACEtransarterial chemoembolization before surgery. Semiautomatic 3Dthree-dimensional volumetric segmentation of target lesions was performed at the last MR examination before orthotopic liver transplantation or surgical resection. The amount of necrotic tumor tissue on contrast material–enhanced arterial phase MR images and the amount of diffusion-restricted tumor tissue on apparent diffusion coefficient (ADCapparent diffusion coefficient) maps were expressed as a percentage of the total tumor volume. Visual assessment of the extent of tumor necrosis and tumor response according to European Association for the Study of the Liver (EASLEuropean Association for the Study of the Liver) criteria was performed. Pathologic tumor necrosis was quantified by using slide-by-slide segmentation. Correlation analysis was performed to evaluate the predictive values of the radiologic techniques. Results At histopathologic examination, the mean percentage of tumor necrosis was 70% (range, 10%–100%). Both 3Dthree-dimensional quantitative techniques demonstrated a strong correlation with tumor necrosis at pathologic examination (R2 = 0.9657 and R2 = 0.9662 for quantitative EASLEuropean Association for the Study of the Liver and quantitative ADCapparent diffusion coefficient, respectively) and a strong intermethod agreement (R2 = 0.9585). Both methods showed a significantly lower discrepancy with pathologically measured necrosis (residual standard error [RSEresidual standard error] = 6.38 and 6.33 for quantitative EASLEuropean Association for the Study of the Liver and quantitative ADCapparent diffusion coefficient, respectively), when compared with non-3Dthree-dimensional techniques (RSEresidual standard error = 12.18 for visual assessment). Conclusion This radiologic-pathologic correlation study demonstrates the diagnostic accuracy of 3Dthree-dimensional quantitative MR imaging techniques in identifying pathologically measured tumor necrosis in HCChepatocellular carcinoma lesions treated with TACEtransarterial chemoembolization. © RSNA, 2014 Online supplemental material is available for this article. PMID:25028783

A new quantitative evaluation method for age-related changes of individual pigmented spots in facial skin.

PubMed

Kikuchi, K; Masuda, Y; Yamashita, T; Sato, K; Katagiri, C; Hirao, T; Mizokami, Y; Yaguchi, H

2016-08-01

Facial skin pigmentation is one of the most prominent visible features of skin aging and often affects perception of health and beauty. To date, facial pigmentation has been evaluated using various image analysis methods developed for the cosmetic and esthetic fields. However, existing methods cannot provide precise information on pigmented spots, such as variations in size, color shade, and distribution pattern. The purpose of this study is the development of image evaluation methods to analyze individual pigmented spots and acquire detailed information on their age-related changes. To characterize the individual pigmented spots within a cheek image, we established a simple object-counting algorithm. First, we captured cheek images using an original imaging system equipped with an illumination unit and a high-resolution digital camera. The acquired images were converted into melanin concentration images using compensation formulae. Next, the melanin images were converted into binary images. The binary images were then subjected to noise reduction. Finally, we calculated parameters such as the melanin concentration, quantity, and size of individual pigmented spots using a connected-components labeling algorithm, which assigns a unique label to each separate group of connected pixels. The cheek image analysis was evaluated on 643 female Japanese subjects. We confirmed that the proposed method was sufficiently sensitive to measure the melanin concentration, and the numbers and sizes of individual pigmented spots through manual evaluation of the cheek images. The image analysis results for the 643 Japanese women indicated clear relationships between age and the changes in the pigmented spots. We developed a new quantitative evaluation method for individual pigmented spots in facial skin. This method facilitates the analysis of the characteristics of various pigmented facial spots and is directly applicable to the fields of dermatology, pharmacology, and esthetic cosmetology. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Measurement of smaller colon polyp in CT colonography images using morphological image processing.

PubMed

Manjunath, K N; Siddalingaswamy, P C; Prabhu, G K

2017-11-01

Automated measurement of the size and shape of colon polyps is one of the challenges in Computed tomography colonography (CTC). The objective of this retrospective study was to improve the sensitivity and specificity of smaller polyp measurement in CTC using image processing techniques. A domain knowledge-based method has been implemented with hybrid method of colon segmentation, morphological image processing operators for detecting the colonic structures, and the decision-making system for delineating the smaller polyp-based on a priori knowledge. The method was applied on 45 CTC dataset. The key finding was that the smaller polyps were accurately measured. In addition to 6-9 mm range, polyps of even <5 mm were also detected. The results were validated qualitatively and quantitatively using both 2D MPR and 3D view. Implementation was done on a high-performance computer with parallel processing. It takes [Formula: see text] min for measuring the smaller polyp in a dataset of 500 CTC images. With this method, [Formula: see text] and [Formula: see text] were achieved. The domain-based approach with morphological image processing has given good results. The smaller polyps were measured accurately which helps in making right clinical decisions. Qualitatively and quantitatively the results were acceptable when compared to the ground truth at [Formula: see text].

Comparison of methods for quantitative evaluation of endoscopic distortion

NASA Astrophysics Data System (ADS)

Wang, Quanzeng; Castro, Kurt; Desai, Viraj N.; Cheng, Wei-Chung; Pfefer, Joshua

2015-03-01

Endoscopy is a well-established paradigm in medical imaging, and emerging endoscopic technologies such as high resolution, capsule and disposable endoscopes promise significant improvements in effectiveness, as well as patient safety and acceptance of endoscopy. However, the field lacks practical standardized test methods to evaluate key optical performance characteristics (OPCs), in particular the geometric distortion caused by fisheye lens effects in clinical endoscopic systems. As a result, it has been difficult to evaluate an endoscope's image quality or assess its changes over time. The goal of this work was to identify optimal techniques for objective, quantitative characterization of distortion that are effective and not burdensome. Specifically, distortion measurements from a commercially available distortion evaluation/correction software package were compared with a custom algorithm based on a local magnification (ML) approach. Measurements were performed using a clinical gastroscope to image square grid targets. Recorded images were analyzed with the ML approach and the commercial software where the results were used to obtain corrected images. Corrected images based on the ML approach and the software were compared. The study showed that the ML method could assess distortion patterns more accurately than the commercial software. Overall, the development of standardized test methods for characterizing distortion and other OPCs will facilitate development, clinical translation, manufacturing quality and assurance of performance during clinical use of endoscopic technologies.

Quantitative Ultrasound Imaging Using Acoustic Backscatter Coefficients.

NASA Astrophysics Data System (ADS)

Boote, Evan Jeffery

Current clinical ultrasound scanners render images which have brightness levels related to the degree of backscattered energy from the tissue being imaged. These images offer the interpreter a qualitative impression of the scattering characteristics of the tissue being examined, but due to the complex factors which affect the amplitude and character of the echoed acoustic energy, it is difficult to make quantitative assessments of scattering nature of the tissue, and thus, difficult to make precise diagnosis when subtle disease effects are present. In this dissertation, a method of data reduction for determining acoustic backscatter coefficients is adapted for use in forming quantitative ultrasound images of this parameter. In these images, the brightness level of an individual pixel corresponds to the backscatter coefficient determined for the spatial position represented by that pixel. The data reduction method utilized rigorously accounts for extraneous factors which affect the scattered echo waveform and has been demonstrated to accurately determine backscatter coefficients under a wide range of conditions. The algorithms and procedures used to form backscatter coefficient images are described. These were tested using tissue-mimicking phantoms which have regions of varying scattering levels. Another phantom has a fat-mimicking layer for testing these techniques under more clinically relevant conditions. Backscatter coefficient images were also formed of in vitro human liver tissue. A clinical ultrasound scanner has been adapted for use as a backscatter coefficient imaging platform. The digital interface between the scanner and the computer used for data reduction are described. Initial tests, using phantoms are presented. A study of backscatter coefficient imaging of in vivo liver was performed using several normal, healthy human subjects.

A comparison of quantitative methods for clinical imaging with hyperpolarized (13)C-pyruvate.

PubMed

Daniels, Charlie J; McLean, Mary A; Schulte, Rolf F; Robb, Fraser J; Gill, Andrew B; McGlashan, Nicholas; Graves, Martin J; Schwaiger, Markus; Lomas, David J; Brindle, Kevin M; Gallagher, Ferdia A

2016-04-01

Dissolution dynamic nuclear polarization (DNP) enables the metabolism of hyperpolarized (13)C-labelled molecules, such as the conversion of [1-(13)C]pyruvate to [1-(13)C]lactate, to be dynamically and non-invasively imaged in tissue. Imaging of this exchange reaction in animal models has been shown to detect early treatment response and correlate with tumour grade. The first human DNP study has recently been completed, and, for widespread clinical translation, simple and reliable methods are necessary to accurately probe the reaction in patients. However, there is currently no consensus on the most appropriate method to quantify this exchange reaction. In this study, an in vitro system was used to compare several kinetic models, as well as simple model-free methods. Experiments were performed using a clinical hyperpolarizer, a human 3 T MR system, and spectroscopic imaging sequences. The quantitative methods were compared in vivo by using subcutaneous breast tumours in rats to examine the effect of pyruvate inflow. The two-way kinetic model was the most accurate method for characterizing the exchange reaction in vitro, and the incorporation of a Heaviside step inflow profile was best able to describe the in vivo data. The lactate time-to-peak and the lactate-to-pyruvate area under the curve ratio were simple model-free approaches that accurately represented the full reaction, with the time-to-peak method performing indistinguishably from the best kinetic model. Finally, extracting data from a single pixel was a robust and reliable surrogate of the whole region of interest. This work has identified appropriate quantitative methods for future work in the analysis of human hyperpolarized (13)C data. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.

A Novel Feature-Tracking Echocardiographic Method for the Quantitation of Regional Myocardial Function

PubMed Central

Pirat, Bahar; Khoury, Dirar S.; Hartley, Craig J.; Tiller, Les; Rao, Liyun; Schulz, Daryl G.; Nagueh, Sherif F.; Zoghbi, William A.

2012-01-01

Objectives The aim of this study was to validate a novel, angle-independent, feature-tracking method for the echocardiographic quantitation of regional function. Background A new echocardiographic method, Velocity Vector Imaging (VVI) (syngo Velocity Vector Imaging technology, Siemens Medical Solutions, Ultrasound Division, Mountain View, California), has been introduced, based on feature tracking—incorporating speckle and endocardial border tracking, that allows the quantitation of endocardial strain, strain rate (SR), and velocity. Methods Seven dogs were studied during baseline, and various interventions causing alterations in regional function: dobutamine, 5-min coronary occlusion with reperfusion up to 1 h, followed by dobutamine and esmolol infusions. Echocardiographic images were acquired from short- and long-axis views of the left ventricle. Segment-length sonomicrometry crystals were used as the reference method. Results Changes in systolic strain in ischemic segments were tracked well with VVI during the different states of regional function. There was a good correlation between circumferential and longitudinal systolic strain by VVI and sonomicrometry (r = 0.88 and r = 0.83, respectively, p < 0.001). Strain measurements in the nonischemic basal segments also demonstrated a significant correlation between the 2 methods (r = 0.65, p < 0.001). Similarly, a significant relation was observed for circumferential and longitudinal SR between the 2 methods (r = 0.94, p < 0.001 and r = 0.90, p < 0.001, respectively). The endocardial velocity relation to changes in strain by sonomicrometry was weaker owing to significant cardiac translation. Conclusions Velocity Vector Imaging, a new feature-tracking method, can accurately assess regional myocardial function at the endocardial level and is a promising clinical tool for the simultaneous quantification of regional and global myocardial function. PMID:18261685

Detection of Prostate Cancer: Quantitative Multiparametric MR Imaging Models Developed Using Registered Correlative Histopathology.

PubMed

Metzger, Gregory J; Kalavagunta, Chaitanya; Spilseth, Benjamin; Bolan, Patrick J; Li, Xiufeng; Hutter, Diane; Nam, Jung W; Johnson, Andrew D; Henriksen, Jonathan C; Moench, Laura; Konety, Badrinath; Warlick, Christopher A; Schmechel, Stephen C; Koopmeiners, Joseph S

2016-06-01

Purpose To develop multiparametric magnetic resonance (MR) imaging models to generate a quantitative, user-independent, voxel-wise composite biomarker score (CBS) for detection of prostate cancer by using coregistered correlative histopathologic results, and to compare performance of CBS-based detection with that of single quantitative MR imaging parameters. Materials and Methods Institutional review board approval and informed consent were obtained. Patients with a diagnosis of prostate cancer underwent multiparametric MR imaging before surgery for treatment. All MR imaging voxels in the prostate were classified as cancer or noncancer on the basis of coregistered histopathologic data. Predictive models were developed by using more than one quantitative MR imaging parameter to generate CBS maps. Model development and evaluation of quantitative MR imaging parameters and CBS were performed separately for the peripheral zone and the whole gland. Model accuracy was evaluated by using the area under the receiver operating characteristic curve (AUC), and confidence intervals were calculated with the bootstrap procedure. The improvement in classification accuracy was evaluated by comparing the AUC for the multiparametric model and the single best-performing quantitative MR imaging parameter at the individual level and in aggregate. Results Quantitative T2, apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), reflux rate constant (kep), and area under the gadolinium concentration curve at 90 seconds (AUGC90) were significantly different between cancer and noncancer voxels (P < .001), with ADC showing the best accuracy (peripheral zone AUC, 0.82; whole gland AUC, 0.74). Four-parameter models demonstrated the best performance in both the peripheral zone (AUC, 0.85; P = .010 vs ADC alone) and whole gland (AUC, 0.77; P = .043 vs ADC alone). Individual-level analysis showed statistically significant improvement in AUC in 82% (23 of 28) and 71% (24 of 34) of patients with peripheral-zone and whole-gland models, respectively, compared with ADC alone. Model-based CBS maps for cancer detection showed improved visualization of cancer location and extent. Conclusion Quantitative multiparametric MR imaging models developed by using coregistered correlative histopathologic data yielded a voxel-wise CBS that outperformed single quantitative MR imaging parameters for detection of prostate cancer, especially when the models were assessed at the individual level. (©) RSNA, 2016 Online supplemental material is available for this article.

Precisely detecting atomic position of atomic intensity images.

PubMed

Wang, Zhijun; Guo, Yaolin; Tang, Sai; Li, Junjie; Wang, Jincheng; Zhou, Yaohe

2015-03-01

We proposed a quantitative method to detect atomic position in atomic intensity images from experiments such as high-resolution transmission electron microscopy, atomic force microscopy, and simulation such as phase field crystal modeling. The evaluation of detection accuracy proves the excellent performance of the method. This method provides a chance to precisely determine atomic interactions based on the detected atomic positions from the atomic intensity image, and hence to investigate the related physical, chemical and electrical properties. Copyright © 2014 Elsevier B.V. All rights reserved.

Modeling of optical quadrature microscopy for imaging mouse embryos

NASA Astrophysics Data System (ADS)

Warger, William C., II; DiMarzio, Charles A.

2008-02-01

Optical quadrature microscopy (OQM) has been shown to provide the optical path difference through a mouse embryo, and has led to a novel method to count the total number of cells further into development than current non-toxic imaging techniques used in the clinic. The cell counting method has the potential to provide an additional quantitative viability marker for blastocyst transfer during in vitro fertilization. OQM uses a 633 nm laser within a modified Mach-Zehnder interferometer configuration to measure the amplitude and phase of the signal beam that travels through the embryo. Four cameras preceded by multiple beamsplitters record the four interferograms that are used within a reconstruction algorithm to produce an image of the complex electric field amplitude. Here we present a model for the electric field through the primary optical components in the imaging configuration and the reconstruction algorithm to calculate the signal to noise ratio when imaging mouse embryos. The model includes magnitude and phase errors in the individual reference and sample paths, fixed pattern noise, and noise within the laser and detectors. This analysis provides the foundation for determining the imaging limitations of OQM and the basis to optimize the cell counting method in order to introduce additional quantitative viability markers.

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

PubMed

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

2016-05-01

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

Usefulness of the automatic quantitative estimation tool for cerebral blood flow: clinical assessment of the application software tool AQCEL.

PubMed

Momose, Mitsuhiro; Takaki, Akihiro; Matsushita, Tsuyoshi; Yanagisawa, Shin; Yano, Kesato; Miyasaka, Tadashi; Ogura, Yuka; Kadoya, Masumi

2011-01-01

AQCEL enables automatic reconstruction of single-photon emission computed tomogram (SPECT) without image degradation and quantitative analysis of cerebral blood flow (CBF) after the input of simple parameters. We ascertained the usefulness and quality of images obtained by the application software AQCEL in clinical practice. Twelve patients underwent brain perfusion SPECT using technetium-99m ethyl cysteinate dimer at rest and after acetazolamide (ACZ) loading. Images reconstructed using AQCEL were compared with those reconstructed using conventional filtered back projection (FBP) method for qualitative estimation. Two experienced nuclear medicine physicians interpreted the image quality using the following visual scores: 0, same; 1, slightly superior; 2, superior. For quantitative estimation, the mean CBF values of the normal hemisphere of the 12 patients using ACZ calculated by the AQCEL method were compared with those calculated by the conventional method. The CBF values of the 24 regions of the 3-dimensional stereotaxic region of interest template (3DSRT) calculated by the AQCEL method at rest and after ACZ loading were compared to those calculated by the conventional method. No significant qualitative difference was observed between the AQCEL and conventional FBP methods in the rest study. The average score by the AQCEL method was 0.25 ± 0.45 and that by the conventional method was 0.17 ± 0.39 (P = 0.34). There was a significant qualitative difference between the AQCEL and conventional methods in the ACZ loading study. The average score for AQCEL was 0.83 ± 0.58 and that for the conventional method was 0.08 ± 0.29 (P = 0.003). During quantitative estimation using ACZ, the mean CBF values of 12 patients calculated by the AQCEL method were 3-8% higher than those calculated by the conventional method. The square of the correlation coefficient between these methods was 0.995. While comparing the 24 3DSRT regions of 12 patients, the squares of the correlation coefficient between AQCEL and conventional methods were 0.973 and 0.986 for the normal and affected sides at rest, respectively, and 0.977 and 0.984 for the normal and affected sides after ACZ loading, respectively. The quality of images reconstructed using the application software AQCEL were superior to that obtained using conventional method after ACZ loading, and high correlations were shown in quantity at rest and after ACZ loading. This software can be applied to clinical practice and is a useful tool for improvement of reproducibility and throughput.

Photon-counting-based diffraction phase microscopy combined with single-pixel imaging

NASA Astrophysics Data System (ADS)

Shibuya, Kyuki; Araki, Hiroyuki; Iwata, Tetsuo

2018-04-01

We propose a photon-counting (PC)-based quantitative-phase imaging (QPI) method for use in diffraction phase microscopy (DPM) that is combined with a single-pixel imaging (SPI) scheme (PC-SPI-DPM). This combination of DPM with the SPI scheme overcomes a low optical throughput problem that has occasionally prevented us from obtaining quantitative-phase images in DPM through use of a high-sensitivity single-channel photodetector such as a photomultiplier tube (PMT). The introduction of a PMT allowed us to perform PC with ease and thus solved a dynamic range problem that was inherent to SPI. As a proof-of-principle experiment, we performed a comparison study of analogue-based SPI-DPM and PC-SPI-DPM for a 125-nm-thick indium tin oxide (ITO) layer coated on a silica glass substrate. We discuss the basic performance of the method and potential future modifications of the proposed system.

Combinational pixel-by-pixel and object-level classifying, segmenting, and agglomerating in performing quantitative image analysis that distinguishes between healthy non-cancerous and cancerous cell nuclei and delineates nuclear, cytoplasm, and stromal material objects from stained biological tissue materials

DOEpatents

Boucheron, Laura E

2013-07-16

Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.

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

NASA Astrophysics Data System (ADS)

Pi, Shiqiang; Liu, Wenzhong; Jiang, Tao

2018-03-01

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

Novel Imaging Method of Continuous Shear Wave by Ultrasonic Color Flow Mapping

NASA Astrophysics Data System (ADS)

Yamakoshi, Yoshiki; Yamamoto, Atsushi; Yuminaka, Yasushi

Shear wave velocity measurement is a promising method in evaluation of tissue stiffness. Several methods have been developed to measure the shear wave velocity, however, it is difficult to obtain quantitative shear wave image in real-time by low cost system. In this paper, a novel shear wave imaging method for continuous shear wave is proposed. This method uses a color flow imaging which is used in ultrasonic imaging system to obtain shear wave's wavefront map. Two conditions, shear wave frequency condition and shear wave displacement amplitude condition, are required, however, these conditions are not severe restrictions in most applications. Using the proposed method, shear wave velocity of trapezius muscle is measured. The result is consistent with the velocity which is calculated from shear elastic modulus measured by ARFI method.

Single frequency thermal wave radar: A next-generation dynamic thermography for quantitative non-destructive imaging over wide modulation frequency ranges.

PubMed

Melnikov, Alexander; Chen, Liangjie; Ramirez Venegas, Diego; Sivagurunathan, Koneswaran; Sun, Qiming; Mandelis, Andreas; Rodriguez, Ignacio Rojas

2018-04-01

Single-Frequency Thermal Wave Radar Imaging (SF-TWRI) was introduced and used to obtain quantitative thickness images of coatings on an aluminum block and on polyetherketone, and to image blind subsurface holes in a steel block. In SF-TWR, the starting and ending frequencies of a linear frequency modulation sweep are chosen to coincide. Using the highest available camera frame rate, SF-TWRI leads to a higher number of sampled points along the modulation waveform than conventional lock-in thermography imaging because it is not limited by conventional undersampling at high frequencies due to camera frame-rate limitations. This property leads to large reduction in measurement time, better quality of images, and higher signal-noise-ratio across wide frequency ranges. For quantitative thin-coating imaging applications, a two-layer photothermal model with lumped parameters was used to reconstruct the layer thickness from multi-frequency SF-TWR images. SF-TWRI represents a next-generation thermography method with superior features for imaging important classes of thin layers, materials, and components that require high-frequency thermal-wave probing well above today's available infrared camera technology frame rates.

Single frequency thermal wave radar: A next-generation dynamic thermography for quantitative non-destructive imaging over wide modulation frequency ranges

NASA Astrophysics Data System (ADS)

Melnikov, Alexander; Chen, Liangjie; Ramirez Venegas, Diego; Sivagurunathan, Koneswaran; Sun, Qiming; Mandelis, Andreas; Rodriguez, Ignacio Rojas

2018-04-01

Single-Frequency Thermal Wave Radar Imaging (SF-TWRI) was introduced and used to obtain quantitative thickness images of coatings on an aluminum block and on polyetherketone, and to image blind subsurface holes in a steel block. In SF-TWR, the starting and ending frequencies of a linear frequency modulation sweep are chosen to coincide. Using the highest available camera frame rate, SF-TWRI leads to a higher number of sampled points along the modulation waveform than conventional lock-in thermography imaging because it is not limited by conventional undersampling at high frequencies due to camera frame-rate limitations. This property leads to large reduction in measurement time, better quality of images, and higher signal-noise-ratio across wide frequency ranges. For quantitative thin-coating imaging applications, a two-layer photothermal model with lumped parameters was used to reconstruct the layer thickness from multi-frequency SF-TWR images. SF-TWRI represents a next-generation thermography method with superior features for imaging important classes of thin layers, materials, and components that require high-frequency thermal-wave probing well above today's available infrared camera technology frame rates.

Quantitative analysis of tympanic membrane perforation: a simple and reliable method.

PubMed

Ibekwe, T S; Adeosun, A A; Nwaorgu, O G

2009-01-01

Accurate assessment of the features of tympanic membrane perforation, especially size, site, duration and aetiology, is important, as it enables optimum management. To describe a simple, cheap and effective method of quantitatively analysing tympanic membrane perforations. The system described comprises a video-otoscope (capable of generating still and video images of the tympanic membrane), adapted via a universal serial bus box to a computer screen, with images analysed using the Image J geometrical analysis software package. The reproducibility of results and their correlation with conventional otoscopic methods of estimation were tested statistically with the paired t-test and correlational tests, using the Statistical Package for the Social Sciences version 11 software. The following equation was generated: P/T x 100 per cent = percentage perforation, where P is the area (in pixels2) of the tympanic membrane perforation and T is the total area (in pixels2) for the entire tympanic membrane (including the perforation). Illustrations are shown. Comparison of blinded data on tympanic membrane perforation area obtained independently from assessments by two trained otologists, of comparative years of experience, using the video-otoscopy system described, showed similar findings, with strong correlations devoid of inter-observer error (p = 0.000, r = 1). Comparison with conventional otoscopic assessment also indicated significant correlation, comparing results for two trained otologists, but some inter-observer variation was present (p = 0.000, r = 0.896). Correlation between the two methods for each of the otologists was also highly significant (p = 0.000). A computer-adapted video-otoscope, with images analysed by Image J software, represents a cheap, reliable, technology-driven, clinical method of quantitative analysis of tympanic membrane perforations and injuries.

Fuzzy object models for newborn brain MR image segmentation

NASA Astrophysics Data System (ADS)

Kobashi, Syoji; Udupa, Jayaram K.

2013-03-01

Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

Box-Counting Method of 2D Neuronal Image: Method Modification and Quantitative Analysis Demonstrated on Images from the Monkey and Human Brain.

PubMed

Rajković, Nemanja; Krstonošić, Bojana; Milošević, Nebojša

2017-01-01

This study calls attention to the difference between traditional box-counting method and its modification. The appropriate scaling factor, influence on image size and resolution, and image rotation, as well as different image presentation, are showed on the sample of asymmetrical neurons from the monkey dentate nucleus. The standard BC method and its modification were evaluated on the sample of 2D neuronal images from the human neostriatum. In addition, three box dimensions (which estimate the space-filling property, the shape, complexity, and the irregularity of dendritic tree) were used to evaluate differences in the morphology of type III aspiny neurons between two parts of the neostriatum.

High resolution quantitative phase imaging of live cells with constrained optimization approach

NASA Astrophysics Data System (ADS)

Pandiyan, Vimal Prabhu; Khare, Kedar; John, Renu

2016-03-01

Quantitative phase imaging (QPI) aims at studying weakly scattering and absorbing biological specimens with subwavelength accuracy without any external staining mechanisms. Use of a reference beam at an angle is one of the necessary criteria for recording of high resolution holograms in most of the interferometric methods used for quantitative phase imaging. The spatial separation of the dc and twin images is decided by the reference beam angle and Fourier-filtered reconstructed image will have a very poor resolution if hologram is recorded below a minimum reference angle condition. However, it is always inconvenient to have a large reference beam angle while performing high resolution microscopy of live cells and biological specimens with nanometric features. In this paper, we treat reconstruction of digital holographic microscopy images as a constrained optimization problem with smoothness constraint in order to recover only complex object field in hologram plane even with overlapping dc and twin image terms. We solve this optimization problem by gradient descent approach iteratively and the smoothness constraint is implemented by spatial averaging with appropriate size. This approach will give excellent high resolution image recovery compared to Fourier filtering while keeping a very small reference angle. We demonstrate this approach on digital holographic microscopy of live cells by recovering the quantitative phase of live cells from a hologram recorded with nearly zero reference angle.

Impact of reconstruction parameters on quantitative I-131 SPECT

NASA Astrophysics Data System (ADS)

van Gils, C. A. J.; Beijst, C.; van Rooij, R.; de Jong, H. W. A. M.

2016-07-01

Radioiodine therapy using I-131 is widely used for treatment of thyroid disease or neuroendocrine tumors. Monitoring treatment by accurate dosimetry requires quantitative imaging. The high energy photons however render quantitative SPECT reconstruction challenging, potentially requiring accurate correction for scatter and collimator effects. The goal of this work is to assess the effectiveness of various correction methods on these effects using phantom studies. A SPECT/CT acquisition of the NEMA IEC body phantom was performed. Images were reconstructed using the following parameters: (1) without scatter correction, (2) with triple energy window (TEW) scatter correction and (3) with Monte Carlo-based scatter correction. For modelling the collimator-detector response (CDR), both (a) geometric Gaussian CDRs as well as (b) Monte Carlo simulated CDRs were compared. Quantitative accuracy, contrast to noise ratios and recovery coefficients were calculated, as well as the background variability and the residual count error in the lung insert. The Monte Carlo scatter corrected reconstruction method was shown to be intrinsically quantitative, requiring no experimentally acquired calibration factor. It resulted in a more accurate quantification of the background compartment activity density compared with TEW or no scatter correction. The quantification error relative to a dose calibrator derived measurement was found to be  <1%,-26% and 33%, respectively. The adverse effects of partial volume were significantly smaller with the Monte Carlo simulated CDR correction compared with geometric Gaussian or no CDR modelling. Scatter correction showed a small effect on quantification of small volumes. When using a weighting factor, TEW correction was comparable to Monte Carlo reconstruction in all measured parameters, although this approach is clinically impractical since this factor may be patient dependent. Monte Carlo based scatter correction including accurately simulated CDR modelling is the most robust and reliable method to reconstruct accurate quantitative iodine-131 SPECT images.

Automatic correspondence detection in mammogram and breast tomosynthesis images

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Krüger, Julia; Bischof, Arpad; Barkhausen, Jörg; Handels, Heinz

2012-02-01

Two-dimensional mammography is the major imaging modality in breast cancer detection. A disadvantage of mammography is the projective nature of this imaging technique. Tomosynthesis is an attractive modality with the potential to combine the high contrast and high resolution of digital mammography with the advantages of 3D imaging. In order to facilitate diagnostics and treatment in the current clinical work-flow, correspondences between tomosynthesis images and previous mammographic exams of the same women have to be determined. In this paper, we propose a method to detect correspondences in 2D mammograms and 3D tomosynthesis images automatically. In general, this 2D/3D correspondence problem is ill-posed, because a point in the 2D mammogram corresponds to a line in the 3D tomosynthesis image. The goal of our method is to detect the "most probable" 3D position in the tomosynthesis images corresponding to a selected point in the 2D mammogram. We present two alternative approaches to solve this 2D/3D correspondence problem: a 2D/3D registration method and a 2D/2D mapping between mammogram and tomosynthesis projection images with a following back projection. The advantages and limitations of both approaches are discussed and the performance of the methods is evaluated qualitatively and quantitatively using a software phantom and clinical breast image data. Although the proposed 2D/3D registration method can compensate for moderate breast deformations caused by different breast compressions, this approach is not suitable for clinical tomosynthesis data due to the limited resolution and blurring effects perpendicular to the direction of projection. The quantitative results show that the proposed 2D/2D mapping method is capable of detecting corresponding positions in mammograms and tomosynthesis images automatically for 61 out of 65 landmarks. The proposed method can facilitate diagnosis, visual inspection and comparison of 2D mammograms and 3D tomosynthesis images for the physician.

Reproducibility of dynamically represented acoustic lung images from healthy individuals

PubMed Central

Maher, T M; Gat, M; Allen, D; Devaraj, A; Wells, A U; Geddes, D M

2008-01-01

Background and aim: Acoustic lung imaging offers a unique method for visualising the lung. This study was designed to demonstrate reproducibility of acoustic lung images recorded from healthy individuals at different time points and to assess intra- and inter-rater agreement in the assessment of dynamically represented acoustic lung images. Methods: Recordings from 29 healthy volunteers were made on three separate occasions using vibration response imaging. Reproducibility was measured using quantitative, computerised assessment of vibration energy. Dynamically represented acoustic lung images were scored by six blinded raters. Results: Quantitative measurement of acoustic recordings was highly reproducible with an intraclass correlation score of 0.86 (very good agreement). Intraclass correlations for inter-rater agreement and reproducibility were 0.61 (good agreement) and 0.86 (very good agreement), respectively. There was no significant difference found between the six raters at any time point. Raters ranged from 88% to 95% in their ability to identically evaluate the different features of the same image presented to them blinded on two separate occasions. Conclusion: Acoustic lung imaging is reproducible in healthy individuals. Graphic representation of lung images can be interpreted with a high degree of accuracy by the same and by different reviewers. PMID:18024534

SU-F-J-112: Clinical Feasibility Test of An RF Pulse-Based MRI Method for the Quantitative Fat-Water Segmentation

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

Yee, S; Wloch, J; Pirkola, M

Purpose: Quantitative fat-water segmentation is important not only because of the clinical utility of fat-suppressed MRI images in better detecting lesions of clinical significance (in the midst of bright fat signal) but also because of the possible physical need, in which CT-like images based on the materials’ photon attenuation properties may have to be generated from MR images; particularly, as in the case of MR-only radiation oncology environment to obtain radiation dose calculation or as in the case of hybrid PET/MR modality to obtain attenuation correction map for the quantitative PET reconstruction. The majority of such fat-water quantitative segmentations havemore » been performed by utilizing the Dixon’s method and its variations, which have to enforce the proper settings (often predefined) of echo time (TE) in the pulse sequences. Therefore, such methods have been unable to be directly combined with those ultrashort TE (UTE) sequences that, taking the advantage of very low TE values (∼ 10’s microsecond), might be beneficial to directly detect bones. Recently, an RF pulse-based method (http://dx.doi.org/10.1016/j.mri.2015.11.006), termed as PROD pulse method, was introduced as a method of quantitative fat-water segmentation that does not have to depend on predefined TE settings. Here, the clinical feasibility of this method is verified in brain tumor patients by combining the PROD pulse with several sequences. Methods: In a clinical 3T MRI, the PROD pulse was combined with turbo spin echo (e.g. TR=1500, TE=16 or 60, ETL=15) or turbo field echo (e.g. TR=5.6, TE=2.8, ETL=12) sequences without specifying TE values. Results: The fat-water segmentation was possible without having to set specific TE values. Conclusion: The PROD pulse method is clinically feasible. Although not yet combined with UTE sequences in our laboratory, the method is potentially compatible with UTE sequences, and thus, might be useful to directly segment fat, water, bone and air.« less

Qualification of a Quantitative Laryngeal Imaging System Using Videostroboscopy and Videokymography

PubMed Central

Popolo, Peter S.; Titze, Ingo R.

2008-01-01

Objectives: We sought to determine whether full-cycle glottal width measurements could be obtained with a quantitative laryngeal imaging system using videostroboscopy, and whether glottal width and vocal fold length measurements were repeatable and reliable. Methods: Synthetic vocal folds were phonated on a laboratory bench, and dynamic images were obtained in repeated trials by use of videostroboscopy and videokymography (VKG) with an imaging system equipped with a 2-point laser projection device for measuring absolute dimensions. Video images were also obtained with an industrial videoscope system with a built-in laser measurement capability. Maximum glottal width and vocal fold length were compared among these 3 methods. Results: The average variation in maximum glottal width measurements between stroboscopic data and VKG data was 3.10%. The average variations in width measurements between the clinical system and the industrial system were 1.93% (stroboscopy) and 3.49% (VKG). The variations in vocal fold length were similarly small. The standard deviations across trials were 0.29 mm for width and 0.48 mm for length (stroboscopy), 0.18 mm for width (VKG), and 0.25 mm for width and 0.84 mm for length (industrial). Conclusions: For stable, periodic vibration, the full extent of the glottal width can be reliably measured with the quantitative videostroboscopy system. PMID:18646436

Estimating background-subtracted fluorescence transients in calcium imaging experiments: a quantitative approach.

PubMed

Joucla, Sébastien; Franconville, Romain; Pippow, Andreas; Kloppenburg, Peter; Pouzat, Christophe

2013-08-01

Calcium imaging has become a routine technique in neuroscience for subcellular to network level investigations. The fast progresses in the development of new indicators and imaging techniques call for dedicated reliable analysis methods. In particular, efficient and quantitative background fluorescence subtraction routines would be beneficial to most of the calcium imaging research field. A background-subtracted fluorescence transients estimation method that does not require any independent background measurement is therefore developed. This method is based on a fluorescence model fitted to single-trial data using a classical nonlinear regression approach. The model includes an appropriate probabilistic description of the acquisition system's noise leading to accurate confidence intervals on all quantities of interest (background fluorescence, normalized background-subtracted fluorescence time course) when background fluorescence is homogeneous. An automatic procedure detecting background inhomogeneities inside the region of interest is also developed and is shown to be efficient on simulated data. The implementation and performances of the proposed method on experimental recordings from the mouse hypothalamus are presented in details. This method, which applies to both single-cell and bulk-stained tissues recordings, should help improving the statistical comparison of fluorescence calcium signals between experiments and studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Quantitative differential phase contrast imaging at high resolution with radially asymmetric illumination.

PubMed

Lin, Yu-Zi; Huang, Kuang-Yuh; Luo, Yuan

2018-06-15

Half-circle illumination-based differential phase contrast (DPC) microscopy has been utilized to recover phase images through a pair of images along multiple axes. Recently, the half-circle based DPC using 12-axis measurements significantly provides a circularly symmetric phase transfer function to improve accuracy for more stable phase recovery. Instead of using half-circle-based DPC, we propose a new scheme of DPC under radially asymmetric illumination to achieve circularly symmetric phase transfer function and enhance the accuracy of phase recovery in a more stable and efficient fashion. We present the design, implementation, and experimental image data demonstrating the ability of our method to obtain quantitative phase images of microspheres, as well as live fibroblast cell samples.

Three-dimensional characterization of pigment dispersion in dried paint films using focused ion beam-scanning electron microscopy.

PubMed

Lin, Jui-Ching; Heeschen, William; Reffner, John; Hook, John

2012-04-01

The combination of integrated focused ion beam-scanning electron microscope (FIB-SEM) serial sectioning and imaging techniques with image analysis provided quantitative characterization of three-dimensional (3D) pigment dispersion in dried paint films. The focused ion beam in a FIB-SEM dual beam system enables great control in slicing paints, and the sectioning process can be synchronized with SEM imaging providing high quality serial cross-section images for 3D reconstruction. Application of Euclidean distance map and ultimate eroded points image analysis methods can provide quantitative characterization of 3D particle distribution. It is concluded that 3D measurement of binder distribution in paints is effective to characterize the order of pigment dispersion in dried paint films.

Quantitative breast MRI radiomics for cancer risk assessment and the monitoring of high-risk populations

NASA Astrophysics Data System (ADS)

Mendel, Kayla R.; Li, Hui; Giger, Maryellen L.

2016-03-01

Breast density is routinely assessed qualitatively in screening mammography. However, it is challenging to quantitatively determine a 3D density from a 2D image such as a mammogram. Furthermore, dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used more frequently in the screening of high-risk populations. The purpose of our study is to segment parenchyma and to quantitatively determine volumetric breast density on pre-contrast axial DCE-MRI images (i.e., non-contrast) using a semi-automated quantitative approach. In this study, we retroactively examined 3D DCE-MRI images taken for breast cancer screening of a high-risk population. We analyzed 66 cases with ages between 28 and 76 (mean 48.8, standard deviation 10.8). DCE-MRIs were obtained on a Philips 3.0 T scanner. Our semi-automated DCE-MRI algorithm includes: (a) segmentation of breast tissue from non-breast tissue using fuzzy cmeans clustering (b) separation of dense and fatty tissues using Otsu's method, and (c) calculation of volumetric density as the ratio of dense voxels to total breast voxels. We examined the relationship between pre-contrast DCE-MRI density and clinical BI-RADS density obtained from radiology reports, and obtained a statistically significant correlation [Spearman ρ-value of 0.66 (p < 0.0001)]. Our method within precision medicine may be useful for monitoring high-risk populations.

Clinically Relevant Subregions of Articular Cartilage of the Hip for Analysis and Reporting Quantitative Magnetic Resonance Imaging: A Technical Note.

PubMed

Surowiec, Rachel K; Lucas, Erin P; Wilson, Katharine J; Saroki, Adriana J; Ho, Charles P

2014-01-01

Before quantitative imaging techniques can become clinically valuable, the method, and more specifically, the regions of locating and reporting these values should be standardized toward reproducibility comparisons across centers and longitudinal follow-up of individual patients. The purpose of this technical note is to describe a rigorous and reproducible method of locating, analyzing, and reporting quantitative MRI values in hip articular cartilage with an approach that is consistent with current orthopedic literature. To demonstrate this localization and documentation, 3 patients (age, 23 ± 5.1 years; 2 males, 1 female) who presented with symptomatic mixed-type femoroacetabular impingement (α angle, 63.3° ± 2.1°; center edge angle, 39° ± 4.2°) were evaluated with T2-mapping at 3 T MRI prior to hip arthroscopy. Manual segmentation was performed and cartilage of the acetabulum and femur was divided into 12 subregions adapted from the geographic zone method. Bone landmarks in the acetabulum and femur, identifiable both in arthroscopy and MR images, were manually selected and the coordinates exported for division of cartilage. Mean T2 values in each zone are presented. The current work outlines a standardized system to locate and describe quantitative mapping values that could aid in surgical decision making, planning, and the noninvasive longitudinal follow-up of implemented cartilage preservation and restoration techniques.

A comparison study of image features between FFDM and film mammogram images

PubMed Central

Jing, Hao; Yang, Yongyi; Wernick, Miles N.; Yarusso, Laura M.; Nishikawa, Robert M.

2012-01-01

Purpose: This work is to provide a direct, quantitative comparison of image features measured by film and full-field digital mammography (FFDM). The purpose is to investigate whether there is any systematic difference between film and FFDM in terms of quantitative image features and their influence on the performance of a computer-aided diagnosis (CAD) system. Methods: The authors make use of a set of matched film-FFDM image pairs acquired from cadaver breast specimens with simulated microcalcifications consisting of bone and teeth fragments using both a GE digital mammography system and a screen-film system. To quantify the image features, the authors consider a set of 12 textural features of lesion regions and six image features of individual microcalcifications (MCs). The authors first conduct a direct comparison on these quantitative features extracted from film and FFDM images. The authors then study the performance of a CAD classifier for discriminating between MCs and false positives (FPs) when the classifier is trained on images of different types (film, FFDM, or both). Results: For all the features considered, the quantitative results show a high degree of correlation between features extracted from film and FFDM, with the correlation coefficients ranging from 0.7326 to 0.9602 for the different features. Based on a Fisher sign rank test, there was no significant difference observed between the features extracted from film and those from FFDM. For both MC detection and discrimination of FPs from MCs, FFDM had a slight but statistically significant advantage in performance; however, when the classifiers were trained on different types of images (acquired with FFDM or SFM) for discriminating MCs from FPs, there was little difference. Conclusions: The results indicate good agreement between film and FFDM in quantitative image features. While FFDM images provide better detection performance in MCs, FFDM and film images may be interchangeable for the purposes of training CAD algorithms, and a single CAD algorithm may be applied to either type of images. PMID:22830771

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Live-cell confocal microscopy and quantitative 4D image analysis of anchor cell invasion through the basement membrane in C. elegans

PubMed Central

Kelley, Laura C.; Wang, Zheng; Hagedorn, Elliott J.; Wang, Lin; Shen, Wanqing; Lei, Shijun; Johnson, Sam A.; Sherwood, David R.

2018-01-01

Cell invasion through basement membrane (BM) barriers is crucial during development, leukocyte trafficking, and for the spread of cancer. Despite its importance in normal and diseased states, the mechanisms that direct invasion are poorly understood, in large part because of the inability to visualize dynamic cell-basement membrane interactions in vivo. This protocol describes multi-channel time-lapse confocal imaging of anchor cell invasion in live C. elegans. Methods presented include outline slide preparation and worm growth synchronization (15 min), mounting (20 min), image acquisition (20-180 min), image processing (20 min), and quantitative analysis (variable timing). Images acquired enable direct measurement of invasive dynamics including invadopodia formation, cell membrane protrusions, and BM removal. This protocol can be combined with genetic analysis, molecular activity probes, and optogenetic approaches to uncover molecular mechanisms underlying cell invasion. These methods can also be readily adapted for real-time analysis of cell migration, basement membrane turnover, and cell membrane dynamics by any worm laboratory. PMID:28880279

An Overview of data science uses in bioimage informatics.

PubMed

Chessel, Anatole

2017-02-15

This review aims at providing a practical overview of the use of statistical features and associated data science methods in bioimage informatics. To achieve a quantitative link between images and biological concepts, one typically replaces an object coming from an image (a segmented cell or intracellular object, a pattern of expression or localisation, even a whole image) by a vector of numbers. They range from carefully crafted biologically relevant measurements to features learnt through deep neural networks. This replacement allows for the use of practical algorithms for visualisation, comparison and inference, such as the ones from machine learning or multivariate statistics. While originating mainly, for biology, in high content screening, those methods are integral to the use of data science for the quantitative analysis of microscopy images to gain biological insight, and they are sure to gather more interest as the need to make sense of the increasing amount of acquired imaging data grows more pressing. Copyright © 2017 Elsevier Inc. All rights reserved.

A hyperspectral imaging system for the evaluation of the human iris spectral reflectance

NASA Astrophysics Data System (ADS)

Di Cecilia, Luca; Marazzi, Francesco; Rovati, Luigi

2017-02-01

According to previous studies, the measurement of the human iris pigmentation can be exploited to detect certain eye pathological conditions in their early stage. In this paper, we propose an instrument and a method to perform hyperspectral quantitative measurements of the iris spectral reflectance. The system is based on a simple imaging setup, which includes a monochrome camera mounted on a standard ophthalmic microscope movement controller, a monochromator, and a flashing LED-based slit lamp. To assure quantitative measurements, the system is properly calibrated against a NIST reflectance standard. Iris reflectance images can be obtained in the spectral range 495-795 nm with a resolution of 25 nm. Each image consists of 1280 x 1024 pixels having a spatial resolution of 18 μm. Reflectance spectra can be calculated both from discrete areas of the iris and as the average of the whole iris surface. Preliminary results suggest that hyperspectral imaging of the iris can provide much more morphological and spectral information with respect to conventional qualitative colorimetric methods.

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers.

PubMed

Shu, Ting; Zhang, Bob; Tang, Yuan Yan

2017-01-01

At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

Characterization of Cerebral White Matter Properties Using Quantitative Magnetic Resonance Imaging Stains

PubMed Central

Hurley, Samuel A.; Samsonov, Alexey A.; Adluru, Nagesh; Hosseinbor, Ameer Pasha; Mossahebi, Pouria; Tromp, Do P.M.; Zakszewski, Elizabeth; Field, Aaron S.

2011-01-01

Abstract The image contrast in magnetic resonance imaging (MRI) is highly sensitive to several mechanisms that are modulated by the properties of the tissue environment. The degree and type of contrast weighting may be viewed as image filters that accentuate specific tissue properties. Maps of quantitative measures of these mechanisms, akin to microstructural/environmental-specific tissue stains, may be generated to characterize the MRI and physiological properties of biological tissues. In this article, three quantitative MRI (qMRI) methods for characterizing white matter (WM) microstructural properties are reviewed. All of these measures measure complementary aspects of how water interacts with the tissue environment. Diffusion MRI, including diffusion tensor imaging, characterizes the diffusion of water in the tissues and is sensitive to the microstructural density, spacing, and orientational organization of tissue membranes, including myelin. Magnetization transfer imaging characterizes the amount and degree of magnetization exchange between free water and macromolecules like proteins found in the myelin bilayers. Relaxometry measures the MRI relaxation constants T1 and T2, which in WM have a component associated with the water trapped in the myelin bilayers. The conduction of signals between distant brain regions occurs primarily through myelinated WM tracts; thus, these methods are potential indicators of pathology and structural connectivity in the brain. This article provides an overview of the qMRI stain mechanisms, acquisition and analysis strategies, and applications for these qMRI stains. PMID:22432902

Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue

PubMed Central

Bjornsson, Christopher S; Lin, Gang; Al-Kofahi, Yousef; Narayanaswamy, Arunachalam; Smith, Karen L; Shain, William; Roysam, Badrinath

2009-01-01

Brain structural complexity has confounded prior efforts to extract quantitative image-based measurements. We present a systematic ‘divide and conquer’ methodology for analyzing three-dimensional (3D) multi-parameter images of brain tissue to delineate and classify key structures, and compute quantitative associations among them. To demonstrate the method, thick (~100 μm) slices of rat brain tissue were labeled using 3 – 5 fluorescent signals, and imaged using spectral confocal microscopy and unmixing algorithms. Automated 3D segmentation and tracing algorithms were used to delineate cell nuclei, vasculature, and cell processes. From these segmentations, a set of 23 intrinsic and 8 associative image-based measurements was computed for each cell. These features were used to classify astrocytes, microglia, neurons, and endothelial cells. Associations among cells and between cells and vasculature were computed and represented as graphical networks to enable further analysis. The automated results were validated using a graphical interface that permits investigator inspection and corrective editing of each cell in 3D. Nuclear counting accuracy was >89%, and cell classification accuracy ranged from 81–92% depending on cell type. We present a software system named FARSIGHT implementing our methodology. Its output is a detailed XML file containing measurements that may be used for diverse quantitative hypothesis-driven and exploratory studies of the central nervous system. PMID:18294697

Investigation of Carbon Fiber Architecture in Braided Composites Using X-Ray CT Inspection

NASA Technical Reports Server (NTRS)

Rhoads, Daniel J.; Miller, Sandi G.; Roberts, Gary D.; Rauser, Richard W.; Golovaty, Dmitry; Wilber, J. Patrick; Espanol, Malena I.

2017-01-01

During the fabrication of braided carbon fiber composite materials, process variations occur which affect the fiber architecture. Quantitative measurements of local and global fiber architecture variations are needed to determine the potential effect of process variations on mechanical properties of the cured composite. Although non-destructive inspection via X-ray CT imaging is a promising approach, difficulties in quantitative analysis of the data arise due to the similar densities of the material constituents. In an effort to gain more quantitative information about features related to fiber architecture, methods have been explored to improve the details that can be captured by X-ray CT imaging. Metal-coated fibers and thin veils are used as inserts to extract detailed information about fiber orientations and inter-ply behavior from X-ray CT images.

Single-shot quantitative phase microscopy with color-multiplexed differential phase contrast (cDPC).

PubMed

Phillips, Zachary F; Chen, Michael; Waller, Laura

2017-01-01

We present a new technique for quantitative phase and amplitude microscopy from a single color image with coded illumination. Our system consists of a commercial brightfield microscope with one hardware modification-an inexpensive 3D printed condenser insert. The method, color-multiplexed Differential Phase Contrast (cDPC), is a single-shot variant of Differential Phase Contrast (DPC), which recovers the phase of a sample from images with asymmetric illumination. We employ partially coherent illumination to achieve resolution corresponding to 2× the objective NA. Quantitative phase can then be used to synthesize DIC and phase contrast images or extract shape and density. We demonstrate amplitude and phase recovery at camera-limited frame rates (50 fps) for various in vitro cell samples and c. elegans in a micro-fluidic channel.

Quantitative three-dimensional photoacoustic tomography of the finger joints: an in vivo study

NASA Astrophysics Data System (ADS)

Sun, Yao; Sobel, Eric; Jiang, Huabei

2009-11-01

We present for the first time in vivo full three-dimensional (3-D) photoacoustic tomography (PAT) of the distal interphalangeal joint in a human subject. Both absorbed energy density and absorption coefficient images of the joint are quantitatively obtained using our finite-element-based photoacoustic image reconstruction algorithm coupled with the photon diffusion equation. The results show that major anatomical features in the joint along with the side arteries can be imaged with a 1-MHz transducer in a spherical scanning geometry. In addition, the cartilages associated with the joint can be quantitatively differentiated from the phalanx. This in vivo study suggests that the 3-D PAT method described has the potential to be used for early diagnosis of joint diseases such as osteoarthritis and rheumatoid arthritis.

Trabecular bone class mapping across resolutions: translating methods from HR-pQCT to clinical CT

NASA Astrophysics Data System (ADS)

Valentinitsch, Alexander; Fischer, Lukas; Patsch, Janina M.; Bauer, Jan; Kainberger, Franz; Langs, Georg; DiFranco, Matthew

2015-03-01

Quantitative assessment of 3D bone microarchitecture in high-resolution peripheral quantitative computed tomography (HR-pQCT) has shown promise in fracture risk assessment and biomechanics, but is limited to the distal radius and tibia. Trabecular microarchitecture classes (TMACs), based on voxel-wise clustering texture and structure tensor features in HRpQCT, is extended in this paper to quantify trabecular bone classes in clinical multi-detector CT (MDCT) images. Our comparison of TMACs in 12 cadaver radii imaged using both HRpQCT and MDCT yields a mean Dice score of up to 0.717+/-0.40 and visually concordant bone quality maps. Further work to develop clinically viable bone quantitative imaging using HR-pQCT validation could have a significant impact on overall bone health assessment.

Robust and fast characterization of OCT-based optical attenuation using a novel frequency-domain algorithm for brain cancer detection

NASA Astrophysics Data System (ADS)

Yuan, Wu; Kut, Carmen; Liang, Wenxuan; Li, Xingde

2017-03-01

Cancer is known to alter the local optical properties of tissues. The detection of OCT-based optical attenuation provides a quantitative method to efficiently differentiate cancer from non-cancer tissues. In particular, the intraoperative use of quantitative OCT is able to provide a direct visual guidance in real time for accurate identification of cancer tissues, especially these without any obvious structural layers, such as brain cancer. However, current methods are suboptimal in providing high-speed and accurate OCT attenuation mapping for intraoperative brain cancer detection. In this paper, we report a novel frequency-domain (FD) algorithm to enable robust and fast characterization of optical attenuation as derived from OCT intensity images. The performance of this FD algorithm was compared with traditional fitting methods by analyzing datasets containing images from freshly resected human brain cancer and from a silica phantom acquired by a 1310 nm swept-source OCT (SS-OCT) system. With graphics processing unit (GPU)-based CUDA C/C++ implementation, this new attenuation mapping algorithm can offer robust and accurate quantitative interpretation of OCT images in real time during brain surgery.

A novel feature-tracking echocardiographic method for the quantitation of regional myocardial function: validation in an animal model of ischemia-reperfusion.

PubMed

Pirat, Bahar; Khoury, Dirar S; Hartley, Craig J; Tiller, Les; Rao, Liyun; Schulz, Daryl G; Nagueh, Sherif F; Zoghbi, William A

2008-02-12

The aim of this study was to validate a novel, angle-independent, feature-tracking method for the echocardiographic quantitation of regional function. A new echocardiographic method, Velocity Vector Imaging (VVI) (syngo Velocity Vector Imaging technology, Siemens Medical Solutions, Ultrasound Division, Mountain View, California), has been introduced, based on feature tracking-incorporating speckle and endocardial border tracking, that allows the quantitation of endocardial strain, strain rate (SR), and velocity. Seven dogs were studied during baseline, and various interventions causing alterations in regional function: dobutamine, 5-min coronary occlusion with reperfusion up to 1 h, followed by dobutamine and esmolol infusions. Echocardiographic images were acquired from short- and long-axis views of the left ventricle. Segment-length sonomicrometry crystals were used as the reference method. Changes in systolic strain in ischemic segments were tracked well with VVI during the different states of regional function. There was a good correlation between circumferential and longitudinal systolic strain by VVI and sonomicrometry (r = 0.88 and r = 0.83, respectively, p < 0.001). Strain measurements in the nonischemic basal segments also demonstrated a significant correlation between the 2 methods (r = 0.65, p < 0.001). Similarly, a significant relation was observed for circumferential and longitudinal SR between the 2 methods (r = 0.94, p < 0.001 and r = 0.90, p < 0.001, respectively). The endocardial velocity relation to changes in strain by sonomicrometry was weaker owing to significant cardiac translation. Velocity Vector Imaging, a new feature-tracking method, can accurately assess regional myocardial function at the endocardial level and is a promising clinical tool for the simultaneous quantification of regional and global myocardial function.

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 corresponding histological ground truth for spatial extent of CaP is known, show a marginally higher sensitivity, specificity, and positive predictive value compared to corresponding CAD results with the individual modalities.

Correction of motion artifacts in endoscopic optical coherence tomography and autofluorescence images based on azimuthal en face image registration.

PubMed

Abouei, Elham; Lee, Anthony M D; Pahlevaninezhad, Hamid; Hohert, Geoffrey; Cua, Michelle; Lane, Pierre; Lam, Stephen; MacAulay, Calum

2018-01-01

We present a method for the correction of motion artifacts present in two- and three-dimensional in vivo endoscopic images produced by rotary-pullback catheters. This method can correct for cardiac/breathing-based motion artifacts and catheter-based motion artifacts such as nonuniform rotational distortion (NURD). This method assumes that en face tissue imaging contains slowly varying structures that are roughly parallel to the pullback axis. The method reduces motion artifacts using a dynamic time warping solution through a cost matrix that measures similarities between adjacent frames in en face images. We optimize and demonstrate the suitability of this method using a real and simulated NURD phantom and in vivo endoscopic pulmonary optical coherence tomography and autofluorescence images. Qualitative and quantitative evaluations of the method show an enhancement of the image quality. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Quantitative phase and amplitude imaging using Differential-Interference Contrast (DIC) microscopy

NASA Astrophysics Data System (ADS)

Preza, Chrysanthe; O'Sullivan, Joseph A.

2009-02-01

We present an extension of the development of an alternating minimization (AM) method for the computation of a specimen's complex transmittance function (magnitude and phase) from DIC images. The ability to extract both quantitative phase and amplitude information from two rotationally-diverse DIC images (i.e., acquired by rotating the sample) extends previous efforts in computational DIC microscopy that have focused on quantitative phase imaging only. Simulation results show that the inverse problem at hand is sensitive to noise as well as to the choice of the AM algorithm parameters. The AM framework allows constraints and penalties on the magnitude and phase estimates to be incorporated in a principled manner. Towards this end, Green and De Pierro's "log-cosh" regularization penalty is applied to the magnitude of differences of neighboring values of the complex-valued function of the specimen during the AM iterations. The penalty is shown to be convex in the complex space. A procedure to approximate the penalty within the iterations is presented. In addition, a methodology to pre-compute AM parameters that are optimal with respect to the convergence rate of the AM algorithm is also presented. Both extensions of the AM method are investigated with simulations.

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.

Acoustic Radiation Force Elasticity Imaging in Diagnostic Ultrasound

PubMed Central

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

2013-01-01

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

Acoustic radiation force elasticity imaging in diagnostic ultrasound.

PubMed

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

2013-04-01

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

Nuclear medicine and quantitative imaging research (instrumentation and quantitative methods of evaluation)

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

Beck, R.N.; Cooper, M.D.

1990-09-01

This report summarizes goals and accomplishments of the research program supported under DOE Grant No. FG02-86ER60418 entitled Instrumentation and Quantitative Methods of Evaluation, with R. Beck, P. I. and M. Cooper, Co-P.I. during the period January 15, 1990 through September 1, 1990. This program addresses the problems involving the basic science and technology underlying the physical and conceptual tools of radioactive tracer methodology as they relate to the measurement of structural and functional parameters of physiologic importance in health and disease. The principal tool is quantitative radionuclide imaging. The overall objective of this program is to further the development andmore » transfer of radiotracer methodology from basic theory to routine clinical practice in order that individual patients and society as a whole will receive the maximum net benefit from the new knowledge gained. The focus of the research is on the development of new instruments and radiopharmaceuticals, and the evaluation of these through the phase of clinical feasibility. 7 figs.« less

Magnetic Interactions and the Method of Images: A Wealth of Educational Suggestions

ERIC Educational Resources Information Center

Bonanno, A.; Camarca, M.; Sapia, P.

2011-01-01

Under some conditions, the method of images (well known in electrostatics) may be implemented in magnetostatic problems too, giving an excellent example of the usefulness of formal analogies in the description of physical systems. In this paper, we develop a quantitative model for the magnetic interactions underlying the so-called Geomag[TM]…

An Image Analysis Method for the Precise Selection and Quantitation of Fluorescently Labeled Cellular Constituents

PubMed Central

Agley, Chibeza C.; Velloso, Cristiana P.; Lazarus, Norman R.

2012-01-01

The accurate measurement of the morphological characteristics of cells with nonuniform conformations presents difficulties. We report here a straightforward method using immunofluorescent staining and the commercially available imaging program Adobe Photoshop, which allows objective and precise information to be gathered on irregularly shaped cells. We have applied this measurement technique to the analysis of human muscle cells and their immunologically marked intracellular constituents, as these cells are prone to adopting a highly branched phenotype in culture. Use of this method can be used to overcome many of the long-standing limitations of conventional approaches for quantifying muscle cell size in vitro. In addition, wider applications of Photoshop as a quantitative and semiquantitative tool in immunocytochemistry are explored. PMID:22511600

Quantitative Method of Measuring Metastatic Activity

NASA Technical Reports Server (NTRS)

Morrison, Dennis R. (Inventor)

1999-01-01

The metastatic potential of tumors can be evaluated by the quantitative detection of urokinase and DNA. The cell sample selected for examination is analyzed for the presence of high levels of urokinase and abnormal DNA using analytical flow cytometry and digital image analysis. Other factors such as membrane associated uroldnase, increased DNA synthesis rates and certain receptors can be used in the method for detection of potentially invasive tumors.

Video-based noncooperative iris image segmentation.

PubMed

Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

2011-02-01

In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

Quantitative and qualitative comparison of MR imaging of the temporomandibular joint at 1.5 and 3.0 T using an optimized high-resolution protocol

PubMed Central

Spinner, Georg; Wyss, Michael; Erni, Stefan; Ettlin, Dominik A; Nanz, Daniel; Ulbrich, Erika J; Gallo, Luigi M; Andreisek, Gustav

2016-01-01

Objectives: To quantitatively and qualitatively compare MRI of the temporomandibular joint (TMJ) using an optimized high-resolution protocol at 3.0 T and a clinical standard protocol at 1.5 T. Methods: A phantom and 12 asymptomatic volunteers were MR imaged using a 2-channel surface coil (standard TMJ coil) at 1.5 and 3.0 T (Philips Achieva and Philips Ingenia, respectively; Philips Healthcare, Best, Netherlands). Imaging protocol consisted of coronal and oblique sagittal proton density-weighted turbo spin echo sequences. For quantitative evaluation, a spherical phantom was imaged. Signal-to-noise ratio (SNR) maps were calculated on a voxelwise basis. For qualitative evaluation, all volunteers underwent MRI of the TMJ with the jaw in closed position. Two readers independently assessed visibility and delineation of anatomical structures of the TMJ and overall image quality on a 5-point Likert scale. Quantitative and qualitative measurements were compared between field strengths. Results: The quantitative analysis showed similar SNR for the high-resolution protocol at 3.0 T compared with the clinical protocol at 1.5 T. The qualitative analysis showed significantly better visibility and delineation of clinically relevant anatomical structures of the TMJ, including the TMJ disc and pterygoid muscle as well as better overall image quality at 3.0 T than at 1.5 T. Conclusions: The presented results indicate that expected gains in SNR at 3.0 T can be used to increase the spatial resolution when imaging the TMJ, which translates into increased visibility and delineation of anatomical structures of the TMJ. Therefore, imaging at 3.0 T should be preferred over 1.5 T for imaging the TMJ. PMID:26371077

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

PubMed

Chen, Xinyuan; Dai, Jianrong

2018-05-01

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

Noninvasive quantitative documentation of cutaneous inflammation in vivo using spectral imaging

NASA Astrophysics Data System (ADS)

Stamatas, Georgios N.; Kollias, Nikiforos

2006-02-01

Skin inflammation is often accompanied by edema and erythema. While erythema is the result of capillary dilation and subsequent local increase of oxygenated hemoglobin (oxy-Hb) concentration, edema is characterized by an increase in extracellular fluid in the dermis leading to local tissue swelling. Edema and erythema are typically graded visually. In this work we tested the potential of spectral imaging as a non-invasive method for quantitative documentation of both the erythema and the edema reactions. As examples of dermatological conditions that exhibit skin inflammation we imaged patients suffering from acne, herpes zoster, and poison ivy rashes using a hyperspectral-imaging camera. Spectral images were acquired in the visible and near infrared part of the spectrum, where oxy-Hb and water demonstrate absorption bands. The values of apparent concentrations of oxy-Hb and water were calculated based on an algorithm that takes into account spectral contributions of deoxy-hemoglobin, melanin, and scattering. In each case examined concentration maps of oxy-Hb and water can be constructed that represent quantitative visualizations of the intensity and extent of erythema and edema correspondingly. In summary, we demonstrate that spectral imaging can be used in dermatology to quantitatively document parameters relating to skin inflammation. Applications may include monitoring of disease progression as well as efficacy of treatments.

Quantitative evaluation methods of skin condition based on texture feature parameters.

PubMed

Pang, Hui; Chen, Tianhua; Wang, Xiaoyi; Chang, Zhineng; Shao, Siqi; Zhao, Jing

2017-03-01

In order to quantitatively evaluate the improvement of the skin condition after using skin care products and beauty, a quantitative evaluation method for skin surface state and texture is presented, which is convenient, fast and non-destructive. Human skin images were collected by image sensors. Firstly, the median filter of the 3 × 3 window is used and then the location of the hairy pixels on the skin is accurately detected according to the gray mean value and color information. The bilinear interpolation is used to modify the gray value of the hairy pixels in order to eliminate the negative effect of noise and tiny hairs on the texture. After the above pretreatment, the gray level co-occurrence matrix (GLCM) is calculated. On the basis of this, the four characteristic parameters, including the second moment, contrast, entropy and correlation, and their mean value are calculated at 45 ° intervals. The quantitative evaluation model of skin texture based on GLCM is established, which can calculate the comprehensive parameters of skin condition. Experiments show that using this method evaluates the skin condition, both based on biochemical indicators of skin evaluation methods in line, but also fully consistent with the human visual experience. This method overcomes the shortcomings of the biochemical evaluation method of skin damage and long waiting time, also the subjectivity and fuzziness of the visual evaluation, which achieves the non-destructive, rapid and quantitative evaluation of skin condition. It can be used for health assessment or classification of the skin condition, also can quantitatively evaluate the subtle improvement of skin condition after using skin care products or stage beauty.

CT-SPECT fusion plus conjugate views for determining dosimetry in iodine-131-monoclonal antibody therapy of lymphoma patients

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

Koral, K.F.; Zasadny, K.R.; Kessler, M.L.

A method of performing {sup 131}I quantitative SPECT imaging is described which uses the superimposition of markers placed on the skin to accomplish fusion of computed tomography (CT) and SPECT image sets. To calculate mean absorbed dose after administration of one of two {sup 131}I-labeled monoclonal antibodies (Mabs), the shape of the time-activity curve is measured by daily diagnostic conjugate views, the y-axis of that curve is normalized by a quantitative SPECT measurement (usually intra-therapy), and the tumor mass is deduced from a concurrent CT volume measurement. The method is applied to six B-cell non-Hodgkin`s lymphoma patients. For four tumorsmore » in three patients treated with the MB1 Mab, a correlation appears to be present between resulting mean absorbed dose and disease response. Including all dosimetric estimates for both antibodies, the range for the specific absorbed dose is within that found by others in treating B-cell lymphoma patients. Excluding a retreated anti-B1 patient, the tumor-specific absorbed dose during anti-B1 therapy is from 1.4 to 1.7 mGy/MBq. For the one anti-B1 patient, where quantitative SPECT and conjugate-view imaging was carried out back to back , the quantitative SPECT-measured activity was somewhat less for the spleen and much less for the tumor than that from conjugate views. The quantitative SPECT plus conjugate views method may be of general utility for macro-dosimetry of {sup 131}If therapies. 18 refs., 3 figs., 5 tabs.« less

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.

Practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in positron emission tomography

PubMed Central

Jha, Abhinav K.; Mena, Esther; Caffo, Brian; Ashrafinia, Saeed; Rahmim, Arman; Frey, Eric; Subramaniam, Rathan M.

2017-01-01

Abstract. Recently, a class of no-gold-standard (NGS) techniques have been proposed to evaluate quantitative imaging methods using patient data. These techniques provide figures of merit (FoMs) quantifying the precision of the estimated quantitative value without requiring repeated measurements and without requiring a gold standard. However, applying these techniques to patient data presents several practical difficulties including assessing the underlying assumptions, accounting for patient-sampling-related uncertainty, and assessing the reliability of the estimated FoMs. To address these issues, we propose statistical tests that provide confidence in the underlying assumptions and in the reliability of the estimated FoMs. Furthermore, the NGS technique is integrated within a bootstrap-based methodology to account for patient-sampling-related uncertainty. The developed NGS framework was applied to evaluate four methods for segmenting lesions from F-Fluoro-2-deoxyglucose positron emission tomography images of patients with head-and-neck cancer on the task of precisely measuring the metabolic tumor volume. The NGS technique consistently predicted the same segmentation method as the most precise method. The proposed framework provided confidence in these results, even when gold-standard data were not available. The bootstrap-based methodology indicated improved performance of the NGS technique with larger numbers of patient studies, as was expected, and yielded consistent results as long as data from more than 80 lesions were available for the analysis. PMID:28331883

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

PubMed

Takamura, Ayari; Watanabe, Ken; Akutsu, Tomoko

2017-07-01

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

High-resolution dynamic imaging and quantitative analysis of lung cancer xenografts in nude mice using clinical PET/CT

PubMed Central

Wang, Ying Yi; Wang, Kai; Xu, Zuo Yu; Song, Yan; Wang, Chu Nan; Zhang, Chong Qing; Sun, Xi Lin; Shen, Bao Zhong

2017-01-01

Considering the general application of dedicated small-animal positron emission tomography/computed tomography is limited, an acceptable alternative in many situations might be clinical PET/CT. To estimate the feasibility of using clinical PET/CT with [F-18]-fluoro-2-deoxy-D-glucose for high-resolution dynamic imaging and quantitative analysis of cancer xenografts in nude mice. Dynamic clinical PET/CT scans were performed on xenografts for 60 min after injection with [F-18]-fluoro-2-deoxy-D-glucose. Scans were reconstructed with or without SharpIR method in two phases. And mice were sacrificed to extracting major organs and tumors, using ex vivo γ-counting as a reference. Strikingly, we observed that the image quality and the correlation between the all quantitive data from clinical PET/CT and the ex vivo counting was better with the SharpIR reconstructions than without. Our data demonstrate that clinical PET/CT scanner with SharpIR reconstruction is a valuable tool for imaging small animals in preclinical cancer research, offering dynamic imaging parameters, good image quality and accurate data quatification. PMID:28881772

High-resolution dynamic imaging and quantitative analysis of lung cancer xenografts in nude mice using clinical PET/CT.

PubMed

Wang, Ying Yi; Wang, Kai; Xu, Zuo Yu; Song, Yan; Wang, Chu Nan; Zhang, Chong Qing; Sun, Xi Lin; Shen, Bao Zhong

2017-08-08

Considering the general application of dedicated small-animal positron emission tomography/computed tomography is limited, an acceptable alternative in many situations might be clinical PET/CT. To estimate the feasibility of using clinical PET/CT with [F-18]-fluoro-2-deoxy-D-glucose for high-resolution dynamic imaging and quantitative analysis of cancer xenografts in nude mice. Dynamic clinical PET/CT scans were performed on xenografts for 60 min after injection with [F-18]-fluoro-2-deoxy-D-glucose. Scans were reconstructed with or without SharpIR method in two phases. And mice were sacrificed to extracting major organs and tumors, using ex vivo γ-counting as a reference. Strikingly, we observed that the image quality and the correlation between the all quantitive data from clinical PET/CT and the ex vivo counting was better with the SharpIR reconstructions than without. Our data demonstrate that clinical PET/CT scanner with SharpIR reconstruction is a valuable tool for imaging small animals in preclinical cancer research, offering dynamic imaging parameters, good image quality and accurate data quatification.

T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model.

PubMed

Whittaker, Heather T; Zhu, Shenghua; Di Curzio, Domenico L; Buist, Richard; Li, Xin-Min; Noy, Suzanna; Wiseman, Frances K; Thiessen, Jonathan D; Martin, Melanie

2018-07-01

Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T 1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T 1 -weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD. Copyright © 2018. Published by Elsevier Inc.

Quantitative detection of benzoyl peroxide in wheat flour by line-scan macro-scale Raman chemical imaging

USDA-ARS?s Scientific Manuscript database

A high-throughput Raman chemical imaging method was developed for direct inspection of benzoyl peroxide (BPO) mixed in wheat flour. A 5 W 785 nm line laser (240 mm long and 1 mm wide) was used as a Raman excitation source in a push-broom Raman imaging system. Hyperspectral Raman images were collecte...

Image database for digital hand atlas

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente; Dey, Partha S.; Gertych, Arkadiusz; Pospiech-Kurkowska, Sywia

2003-05-01

Bone age assessment is a procedure frequently performed in pediatric patients to evaluate their growth disorder. A commonly used method is atlas matching by a visual comparison of a hand radiograph with a small reference set of old Greulich-Pyle atlas. We have developed a new digital hand atlas with a large set of clinically normal hand images of diverse ethnic groups. In this paper, we will present our system design and implementation of the digital atlas database to support the computer-aided atlas matching for bone age assessment. The system consists of a hand atlas image database, a computer-aided diagnostic (CAD) software module for image processing and atlas matching, and a Web user interface. Users can use a Web browser to push DICOM images, directly or indirectly from PACS, to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, are then extracted and compared with patterns from the atlas image database to assess the bone age. The digital atlas method built on a large image database and current Internet technology provides an alternative to supplement or replace the traditional one for a quantitative, accurate and cost-effective assessment of bone age.

Single image super-resolution via an iterative reproducing kernel Hilbert space method.

PubMed

Deng, Liang-Jian; Guo, Weihong; Huang, Ting-Zhu

2016-11-01

Image super-resolution, a process to enhance image resolution, has important applications in satellite imaging, high definition television, medical imaging, etc. Many existing approaches use multiple low-resolution images to recover one high-resolution image. In this paper, we present an iterative scheme to solve single image super-resolution problems. It recovers a high quality high-resolution image from solely one low-resolution image without using a training data set. We solve the problem from image intensity function estimation perspective and assume the image contains smooth and edge components. We model the smooth components of an image using a thin-plate reproducing kernel Hilbert space (RKHS) and the edges using approximated Heaviside functions. The proposed method is applied to image patches, aiming to reduce computation and storage. Visual and quantitative comparisons with some competitive approaches show the effectiveness of the proposed method.

Quantitative Image Recovery From Measured Blind Backscattered Data Using a Globally Convergent Inverse Method

DTIC Science & Technology

2012-01-01

research interests include in- 794 verse problems related to superresolution imaging and metamaterial design. 795 Dr. Fiddy is a Fellow of the Optical...verse problems related to superresolution imaging and metamaterial design. 795 Dr. Fiddy is a Fellow of the Optical Society of America, the IOP, and The

Quantitative cardiac SPECT reconstruction with reduced image degradation due to patient anatomy

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

Tsui, B.M.W.; Zhao, X.D.; Gregoriou, G.K.

1994-12-01

Patient anatomy has complicated effects on cardiac SPECT images. The authors investigated reconstruction methods which substantially reduced these effects for improved image quality. A 3D mathematical cardiac-torso (MCAT) phantom which models the anatomical structures in the thorax region were used in the study. The phantom was modified to simulate variations in patient anatomy including regions of natural thinning along the myocardium, body size, diaphragmatic shape, gender, and size and shape of breasts for female patients. Distributions of attenuation coefficients and Tl-201 uptake in different organs in a normal patient were also simulated. Emission projection data were generated from the phantomsmore » including effects of attenuation and detector response. The authors have observed the attenuation-induced artifacts caused by patient anatomy in the conventional FBP reconstructed images. Accurate attenuation compensation using iterative reconstruction algorithms and attenuation maps substantially reduced the image artifacts and improved quantitative accuracy. They conclude that reconstruction methods which accurately compensate for non-uniform attenuation can substantially reduce image degradation caused by variations in patient anatomy in cardiac SPECT.« less

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis

PubMed Central

Kim, David M.; Zhang, Hairong; Zhou, Haiying; Du, Tommy; Wu, Qian; Mockler, Todd C.; Berezin, Mikhail Y.

2015-01-01

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health. PMID:26531782

A benchmark for comparison of dental radiography analysis algorithms.

PubMed

Wang, Ching-Wei; Huang, Cheng-Ta; Lee, Jia-Hong; Li, Chung-Hsing; Chang, Sheng-Wei; Siao, Ming-Jhih; Lai, Tat-Ming; Ibragimov, Bulat; Vrtovec, Tomaž; Ronneberger, Olaf; Fischer, Philipp; Cootes, Tim F; Lindner, Claudia

2016-07-01

Dental radiography plays an important role in clinical diagnosis, treatment and surgery. In recent years, efforts have been made on developing computerized dental X-ray image analysis systems for clinical usages. A novel framework for objective evaluation of automatic dental radiography analysis algorithms has been established under the auspices of the IEEE International Symposium on Biomedical Imaging 2015 Bitewing Radiography Caries Detection Challenge and Cephalometric X-ray Image Analysis Challenge. In this article, we present the datasets, methods and results of the challenge and lay down the principles for future uses of this benchmark. The main contributions of the challenge include the creation of the dental anatomy data repository of bitewing radiographs, the creation of the anatomical abnormality classification data repository of cephalometric radiographs, and the definition of objective quantitative evaluation for comparison and ranking of the algorithms. With this benchmark, seven automatic methods for analysing cephalometric X-ray image and two automatic methods for detecting bitewing radiography caries have been compared, and detailed quantitative evaluation results are presented in this paper. Based on the quantitative evaluation results, we believe automatic dental radiography analysis is still a challenging and unsolved problem. The datasets and the evaluation software will be made available to the research community, further encouraging future developments in this field. (http://www-o.ntust.edu.tw/~cweiwang/ISBI2015/). Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

ADvanced IMage Algebra (ADIMA): a novel method for depicting multiple sclerosis lesion heterogeneity, as demonstrated by quantitative MRI.

PubMed

Yiannakas, Marios C; Tozer, Daniel J; Schmierer, Klaus; Chard, Declan T; Anderson, Valerie M; Altmann, Daniel R; Miller, David H; Wheeler-Kingshott, Claudia A M

2013-05-01

There are modest correlations between multiple sclerosis (MS) disability and white matter lesion (WML) volumes, as measured by T2-weighted (T2w) magnetic resonance imaging (MRI) scans (T2-WML). This may partly reflect pathological heterogeneity in WMLs, which is not apparent on T2w scans. To determine if ADvanced IMage Algebra (ADIMA), a novel MRI post-processing method, can reveal WML heterogeneity from proton-density weighted (PDw) and T2w images. We obtained conventional PDw and T2w images from 10 patients with relapsing-remitting MS (RRMS) and ADIMA images were calculated from these. We classified all WML into bright (ADIMA-b) and dark (ADIMA-d) sub-regions, which were segmented. We obtained conventional T2-WML and T1-WML volumes for comparison, as well as the following quantitative magnetic resonance parameters: magnetisation transfer ratio (MTR), T1 and T2. Also, we assessed the reproducibility of the segmentation for ADIMA-b, ADIMA-d and T2-WML. Our study's ADIMA-derived volumes correlated with conventional lesion volumes (p < 0.05). ADIMA-b exhibited higher T1 and T2, and lower MTR than the T2-WML (p < 0.001). Despite the similarity in T1 values between ADIMA-b and T1-WML, these regions were only partly overlapping with each other. ADIMA-d exhibited quantitative characteristics similar to T2-WML; however, they were only partly overlapping. Mean intra- and inter-observer coefficients of variation for ADIMA-b, ADIMA-d and T2-WML volumes were all < 6 % and < 10 %, respectively. ADIMA enabled the simple classification of WML into two groups having different quantitative magnetic resonance properties, which can be reproducibly distinguished.

Development of the local magnification method for quantitative evaluation of endoscope geometric distortion

NASA Astrophysics Data System (ADS)

Wang, Quanzeng; Cheng, Wei-Chung; Suresh, Nitin; Hua, Hong

2016-05-01

With improved diagnostic capabilities and complex optical designs, endoscopic technologies are advancing. As one of the several important optical performance characteristics, geometric distortion can negatively affect size estimation and feature identification related diagnosis. Therefore, a quantitative and simple distortion evaluation method is imperative for both the endoscopic industry and the medical device regulatory agent. However, no such method is available yet. While the image correction techniques are rather mature, they heavily depend on computational power to process multidimensional image data based on complex mathematical model, i.e., difficult to understand. Some commonly used distortion evaluation methods, such as the picture height distortion (DPH) or radial distortion (DRAD), are either too simple to accurately describe the distortion or subject to the error of deriving a reference image. We developed the basic local magnification (ML) method to evaluate endoscope distortion. Based on the method, we also developed ways to calculate DPH and DRAD. The method overcomes the aforementioned limitations, has clear physical meaning in the whole field of view, and can facilitate lesion size estimation during diagnosis. Most importantly, the method can facilitate endoscopic technology to market and potentially be adopted in an international endoscope standard.

Quantitative evaluation method of the threshold adjustment and the flat field correction performances of hybrid photon counting pixel detectors

NASA Astrophysics Data System (ADS)

Medjoubi, K.; Dawiec, A.

2017-12-01

A simple method is proposed in this work for quantitative evaluation of the quality of the threshold adjustment and the flat-field correction of Hybrid Photon Counting pixel (HPC) detectors. This approach is based on the Photon Transfer Curve (PTC) corresponding to the measurement of the standard deviation of the signal in flat field images. Fixed pattern noise (FPN), easily identifiable in the curve, is linked to the residual threshold dispersion, sensor inhomogeneity and the remnant errors in flat fielding techniques. The analytical expression of the signal to noise ratio curve is developed for HPC and successfully used as a fit function applied to experimental data obtained with the XPAD detector. The quantitative evaluation of the FPN, described by the photon response non-uniformity (PRNU), is measured for different configurations (threshold adjustment method and flat fielding technique) and is demonstrated to be used in order to evaluate the best setting for having the best image quality from a commercial or a R&D detector.

Clinical and mathematical introduction to computer processing of scintigraphic images

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

Goris, M.L.; Briandet, P.A.

The authors state in their preface:''...we believe that there is no book yet available in which computing in nuclear medicine has been approached in a reasonable manner. This book is our attempt to correct the situation.'' The book is divided into four sections: (1) Clinical Applications of Quantitative Scintigraphic Analysis; (2) Mathematical Derivations; (3) Processing Methods of Scintigraphic Images; and (4) The (Computer) System. Section 1 has chapters on quantitative approaches to congenital and acquired heart diseases, nephrology and urology, and pulmonary medicine.

Retrieving the hydrous minerals on Mars by sparse unmixing and the Hapke model using MRO/CRISM data

NASA Astrophysics Data System (ADS)

Lin, Honglei; Zhang, Xia

2017-05-01

The hydrous minerals on Mars preserve records of potential past aqueous activity. Quantitative information regarding mineralogical composition would enable a better understanding of the formation processes of these hydrous minerals, and provide unique insights into ancient habitable environments and the geological evolution of Mars. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) has the advantage of both a high spatial and spectral resolution, which makes it suitable for the quantitative analysis of minerals on Mars. However, few studies have attempted to quantitatively retrieve the mineralogical composition of hydrous minerals on Mars using visible-infrared (VISIR) hyperspectral data due to their distribution characteristics (relatively low concentrations, located primarily in Noachian terrain, and unclear or unknown background minerals) and limitations of the spectral unmixing algorithms. In this study, we developed a modified sparse unmixing (MSU) method, combining the Hapke model with sparse unmixing. The MSU method considers the nonlinear mixed effects of minerals and avoids the difficulty of determining the spectra and number of endmembers from the image. The proposed method was tested successfully using laboratory mixture spectra and an Airborne Visible Infrared Imaging Spectrometer (AVIRIS) image of the Cuprite site (Nevada, USA). Then it was applied to CRISM hyperspectral images over Gale crater. Areas of hydrous mineral distribution were first identified by spectral features of water and hydroxyl absorption. The MSU method was performed on these areas, and the abundances were retrieved. The results indicated that the hydrous minerals consisted mostly of hydrous silicates, with abundances of up to 35%, as well as hydrous sulfates, with abundances ≤10%. Several main subclasses of hydrous minerals (e.g., Fe/Mg phyllosilicate, prehnite, and kieserite) were retrieved. Among these, Fe/Mg- phyllosilicate was the most abundant, with abundances ranging up to almost 30%, followed by prehnite and kieserite, with abundances lower than 15%. Our results are consistent with related research and in situ analyses of data from the rover Curiosity; thus, our method has the potential to be widely used for quantitative mineralogical mapping at the global scale of the surface of Mars.

Image-derived and arterial blood sampled input functions for quantitative PET imaging of the angiotensin II subtype 1 receptor in the kidney

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

Feng, Tao; Tsui, Benjamin M. W.; Li, Xin

Purpose: The radioligand {sup 11}C-KR31173 has been introduced for positron emission tomography (PET) imaging of the angiotensin II subtype 1 receptor in the kidney in vivo. To study the biokinetics of {sup 11}C-KR31173 with a compartmental model, the input function is needed. Collection and analysis of arterial blood samples are the established approach to obtain the input function but they are not feasible in patients with renal diseases. The goal of this study was to develop a quantitative technique that can provide an accurate image-derived input function (ID-IF) to replace the conventional invasive arterial sampling and test the method inmore » pigs with the goal of translation into human studies. Methods: The experimental animals were injected with [{sup 11}C]KR31173 and scanned up to 90 min with dynamic PET. Arterial blood samples were collected for the artery derived input function (AD-IF) and used as a gold standard for ID-IF. Before PET, magnetic resonance angiography of the kidneys was obtained to provide the anatomical information required for derivation of the recovery coefficients in the abdominal aorta, a requirement for partial volume correction of the ID-IF. Different image reconstruction methods, filtered back projection (FBP) and ordered subset expectation maximization (OS-EM), were investigated for the best trade-off between bias and variance of the ID-IF. The effects of kidney uptakes on the quantitative accuracy of ID-IF were also studied. Biological variables such as red blood cell binding and radioligand metabolism were also taken into consideration. A single blood sample was used for calibration in the later phase of the input function. Results: In the first 2 min after injection, the OS-EM based ID-IF was found to be biased, and the bias was found to be induced by the kidney uptake. No such bias was found with the FBP based image reconstruction method. However, the OS-EM based image reconstruction was found to reduce variance in the subsequent phase of the ID-IF. The combined use of FBP and OS-EM resulted in reduced bias and noise. After performing all the necessary corrections, the areas under the curves (AUCs) of the AD-IF were close to that of the AD-IF (average AUC ratio =1 ± 0.08) during the early phase. When applied in a two-tissue-compartmental kinetic model, the average difference between the estimated model parameters from ID-IF and AD-IF was 10% which was within the error of the estimation method. Conclusions: The bias of radioligand concentration in the aorta from the OS-EM image reconstruction is significantly affected by radioligand uptake in the adjacent kidney and cannot be neglected for quantitative evaluation. With careful calibrations and corrections, the ID-IF derived from quantitative dynamic PET images can be used as the input function of the compartmental model to quantify the renal kinetics of {sup 11}C-KR31173 in experimental animals and the authors intend to evaluate this method in future human studies.« less

Cardiovascular magnetic resonance of myocardial edema using a short inversion time inversion recovery (STIR) black-blood technique: Diagnostic accuracy of visual and semi-quantitative assessment

PubMed Central

2012-01-01

Background The short inversion time inversion recovery (STIR) black-blood technique has been used to visualize myocardial edema, and thus to differentiate acute from chronic myocardial lesions. However, some cardiovascular magnetic resonance (CMR) groups have reported variable image quality, and hence the diagnostic value of STIR in routine clinical practice has been put into question. The aim of our study was to analyze image quality and diagnostic performance of STIR using a set of pulse sequence parameters dedicated to edema detection, and to discuss possible factors that influence image quality. We hypothesized that STIR imaging is an accurate and robust way of detecting myocardial edema in non-selected patients with acute myocardial infarction. Methods Forty-six consecutive patients with acute myocardial infarction underwent CMR (day 4.5, +/- 1.6) including STIR for the assessment of myocardial edema and late gadolinium enhancement (LGE) for quantification of myocardial necrosis. Thirty of these patients underwent a follow-up CMR at approximately six months (195 +/- 39 days). Both STIR and LGE images were evaluated separately on a segmental basis for image quality as well as for presence and extent of myocardial hyper-intensity, with both visual and semi-quantitative (threshold-based) analysis. LGE was used as a reference standard for localization and extent of myocardial necrosis (acute) or scar (chronic). Results Image quality of STIR images was rated as diagnostic in 99.5% of cases. At the acute stage, the sensitivity and specificity of STIR to detect infarcted segments on visual assessment was 95% and 78% respectively, and on semi-quantitative assessment was 99% and 83%, respectively. STIR differentiated acutely from chronically infarcted segments with a sensitivity of 95% by both methods and with a specificity of 99% by visual assessment and 97% by semi-quantitative assessment. The extent of hyper-intense areas on acute STIR images was 85% larger than those on LGE images, with a larger myocardial salvage index in reperfused than in non-reperfused infarcts (p = 0.035). Conclusions STIR with appropriate pulse sequence settings is accurate in detecting acute myocardial infarction (MI) and distinguishing acute from chronic MI with both visual and semi-quantitative analysis. Due to its unique technical characteristics, STIR should be regarded as an edema-weighted rather than a purely T2-weighted technique. PMID:22455461

Quantitative imaging of protein targets in the human brain with PET

NASA Astrophysics Data System (ADS)

Gunn, Roger N.; Slifstein, Mark; Searle, Graham E.; Price, Julie C.

2015-11-01

PET imaging of proteins in the human brain with high affinity radiolabelled molecules has a history stretching back over 30 years. During this period the portfolio of protein targets that can be imaged has increased significantly through successes in radioligand discovery and development. This portfolio now spans six major categories of proteins; G-protein coupled receptors, membrane transporters, ligand gated ion channels, enzymes, misfolded proteins and tryptophan-rich sensory proteins. In parallel to these achievements in radiochemical sciences there have also been significant advances in the quantitative analysis and interpretation of the imaging data including the development of methods for image registration, image segmentation, tracer compartmental modeling, reference tissue kinetic analysis and partial volume correction. In this review, we analyze the activity of the field around each of the protein targets in order to give a perspective on the historical focus and the possible future trajectory of the field. The important neurobiology and pharmacology is introduced for each of the six protein classes and we present established radioligands for each that have successfully transitioned to quantitative imaging in humans. We present a standard quantitative analysis workflow for these radioligands which takes the dynamic PET data, associated blood and anatomical MRI data as the inputs to a series of image processing and bio-mathematical modeling steps before outputting the outcome measure of interest on either a regional or parametric image basis. The quantitative outcome measures are then used in a range of different imaging studies including tracer discovery and development studies, cross sectional studies, classification studies, intervention studies and longitudinal studies. Finally we consider some of the confounds, challenges and subtleties that arise in practice when trying to quantify and interpret PET neuroimaging data including motion artifacts, partial volume effects, age effects, image registration and normalization, input functions and metabolites, parametric imaging, receptor internalization and genetic factors.

Atherosclerosis imaging using 3D black blood TSE SPACE vs 2D TSE

PubMed Central

Wong, Stephanie K; Mobolaji-Iawal, Motunrayo; Arama, Leron; Cambe, Joy; Biso, Sylvia; Alie, Nadia; Fayad, Zahi A; Mani, Venkatesh

2014-01-01

AIM: To compare 3D Black Blood turbo spin echo (TSE) sampling perfection with application-optimized contrast using different flip angle evolution (SPACE) vs 2D TSE in evaluating atherosclerotic plaques in multiple vascular territories. METHODS: The carotid, aortic, and femoral arterial walls of 16 patients at risk for cardiovascular or atherosclerotic disease were studied using both 3D black blood magnetic resonance imaging SPACE and conventional 2D multi-contrast TSE sequences using a consolidated imaging approach in the same imaging session. Qualitative and quantitative analyses were performed on the images. Agreement of morphometric measurements between the two imaging sequences was assessed using a two-sample t-test, calculation of the intra-class correlation coefficient and by the method of linear regression and Bland-Altman analyses. RESULTS: No statistically significant qualitative differences were found between the 3D SPACE and 2D TSE techniques for images of the carotids and aorta. For images of the femoral arteries, however, there were statistically significant differences in all four qualitative scores between the two techniques. Using the current approach, 3D SPACE is suboptimal for femoral imaging. However, this may be due to coils not being optimized for femoral imaging. Quantitatively, in our study, higher mean total vessel area measurements for the 3D SPACE technique across all three vascular beds were observed. No significant differences in lumen area for both the right and left carotids were observed between the two techniques. Overall, a significant-correlation existed between measures obtained between the two approaches. CONCLUSION: Qualitative and quantitative measurements between 3D SPACE and 2D TSE techniques are comparable. 3D-SPACE may be a feasible approach in the evaluation of cardiovascular patients. PMID:24876923

Intraoperative laser speckle contrast imaging with retrospective motion correction for quantitative assessment of cerebral blood flow

PubMed Central

Richards, Lisa M.; Towle, Erica L.; Fox, Douglas J.; Dunn, Andrew K.

2014-01-01

Abstract. Although multiple intraoperative cerebral blood flow (CBF) monitoring techniques are currently available, a quantitative method that allows for continuous monitoring and that can be easily integrated into the surgical workflow is still needed. Laser speckle contrast imaging (LSCI) is an optical imaging technique with a high spatiotemporal resolution that has been recently demonstrated as feasible and effective for intraoperative monitoring of CBF during neurosurgical procedures. This study demonstrates the impact of retrospective motion correction on the quantitative analysis of intraoperatively acquired LSCI images. LSCI images were acquired through a surgical microscope during brain tumor resection procedures from 10 patients under baseline conditions and after a cortical stimulation in three of those patients. The patient’s electrocardiogram (ECG) was recorded during acquisition for postprocess correction of pulsatile artifacts. Automatic image registration was retrospectively performed to correct for tissue motion artifacts, and the performance of rigid and nonrigid transformations was compared. In baseline cases, the original images had 25%±27% noise across 16 regions of interest (ROIs). ECG filtering moderately reduced the noise to 20%±21%, while image registration resulted in a further noise reduction of 15%±4%. Combined ECG filtering and image registration significantly reduced the noise to 6.2%±2.6% (p<0.05). Using the combined motion correction, accuracy and sensitivity to small changes in CBF were improved in cortical stimulation cases. There was also excellent agreement between rigid and nonrigid registration methods (15/16 ROIs with <3% difference). Results from this study demonstrate the importance of motion correction for improved visualization of CBF changes in clinical LSCI images. PMID:26157974

Low-dose, high-resolution and high-efficiency ptychography at STXM beamline of SSRF

NASA Astrophysics Data System (ADS)

Xu, Zijian; Wang, Chunpeng; Liu, Haigang; Tao, Xulei; Tai, Renzhong

2017-06-01

Ptychography is a diffraction-based X-ray microscopy method that can image extended samples quantitatively while remove the resolution limit imposed by image-forming optical elements. As a natural extension of scanning transmission X-ray microscopy (STXM) imaging method, we developed soft X-ray ptychographic coherent diffraction imaging (PCDI) method at the STXM endstation of BL08U beamline of Shanghai Synchrotron Radiation Facility. Compared to the traditional STXM imaging, the new PCDI method has resulted in significantly lower dose, higher resolution and higher efficiency imaging in our platform. In the demonstration experiments shown here, a spatial resolution of sub-10 nm was obtained for a gold nanowires sample, which is much better than the limit resolution 30 nm of the STXM method, while the radiation dose is only 1/12 of STXM.

A custom-built PET phantom design for quantitative imaging of printed distributions.

PubMed

Markiewicz, P J; Angelis, G I; Kotasidis, F; Green, M; Lionheart, W R; Reader, A J; Matthews, J C

2011-11-07

This note presents a practical approach to a custom-made design of PET phantoms enabling the use of digital radioactive distributions with high quantitative accuracy and spatial resolution. The phantom design allows planar sources of any radioactivity distribution to be imaged in transaxial and axial (sagittal or coronal) planes. Although the design presented here is specially adapted to the high-resolution research tomograph (HRRT), the presented methods can be adapted to almost any PET scanner. Although the presented phantom design has many advantages, a number of practical issues had to be overcome such as positioning of the printed source, calibration, uniformity and reproducibility of printing. A well counter (WC) was used in the calibration procedure to find the nonlinear relationship between digital voxel intensities and the actual measured radioactive concentrations. Repeated printing together with WC measurements and computed radiography (CR) using phosphor imaging plates (IP) were used to evaluate the reproducibility and uniformity of such printing. Results show satisfactory printing uniformity and reproducibility; however, calibration is dependent on the printing mode and the physical state of the cartridge. As a demonstration of the utility of using printed phantoms, the image resolution and quantitative accuracy of reconstructed HRRT images are assessed. There is very good quantitative agreement in the calibration procedure between HRRT, CR and WC measurements. However, the high resolution of CR and its quantitative accuracy supported by WC measurements made it possible to show the degraded resolution of HRRT brain images caused by the partial-volume effect and the limits of iterative image reconstruction.

Automatic vertebral bodies detection of x-ray images using invariant multiscale template matching

NASA Astrophysics Data System (ADS)

Sharifi Sarabi, Mona; Villaroman, Diane; Beckett, Joel; Attiah, Mark; Marcus, Logan; Ahn, Christine; Babayan, Diana; Gaonkar, Bilwaj; Macyszyn, Luke; Raghavendra, Cauligi

2017-03-01

Lower back pain and pathologies related to it are one of the most common results for a referral to a neurosurgical clinic in the developed and the developing world. Quantitative evaluation of these pathologies is a challenge. Image based measurements of angles/vertebral heights and disks could provide a potential quantitative biomarker for tracking and measuring these pathologies. Detection of vertebral bodies is a key element and is the focus of the current work. From the variety of medical imaging techniques, MRI and CT scans have been typically used for developing image segmentation methods. However, CT scans are known to give a large dose of x-rays, increasing cancer risk [8]. MRI can be substituted for CTs when the risk is high [8] but are difficult to obtain in smaller facilities due to cost and lack of expertise in the field [2]. X-rays provide another option with its ability to control the x-ray dosage, especially for young people, and its accessibility for smaller facilities. Hence, the ability to create quantitative biomarkers from x-ray data is especially valuable. Here, we develop a multiscale template matching, inspired by [9], to detect centers of vertebral bodies from x-ray data. The immediate application of such detection lies in developing quantitative biomarkers and in querying similar images in a database. Previously, shape similarity classification methods have been used to address this problem, but these are challenging to use in the presence of variation due to gross pathology and even subtle effects [1].

Preprocessing film-copied MRI for studying morphological brain changes.

PubMed

Pham, Tuan D; Eisenblätter, Uwe; Baune, Bernhard T; Berger, Klaus

2009-06-15

The magnetic resonance imaging (MRI) of the brain is one of the important data items for studying memory and morbidity in elderly as these images can provide useful information through the quantitative measures of various regions of interest of the brain. As an effort to fully automate the biomedical analysis of the brain that can be combined with the genetic data of the same human population and where the records of the original MRI data are missing, this paper presents two effective methods for addressing this imaging problem. The first method handles the restoration of the film-copied MRI. The second method involves the segmentation of the image data. Experimental results and comparisons with other methods suggest the usefulness of the proposed image analysis methodology.

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

PubMed

Johnson, Heath E; Haugh, Jason M

2013-12-02

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

A quantitative method to measure biofilm removal efficiency from complex biomaterial surfaces using SEM and image analysis

NASA Astrophysics Data System (ADS)

Vyas, N.; Sammons, R. L.; Addison, O.; Dehghani, H.; Walmsley, A. D.

2016-09-01

Biofilm accumulation on biomaterial surfaces is a major health concern and significant research efforts are directed towards producing biofilm resistant surfaces and developing biofilm removal techniques. To accurately evaluate biofilm growth and disruption on surfaces, accurate methods which give quantitative information on biofilm area are needed, as current methods are indirect and inaccurate. We demonstrate the use of machine learning algorithms to segment biofilm from scanning electron microscopy images. A case study showing disruption of biofilm from rough dental implant surfaces using cavitation bubbles from an ultrasonic scaler is used to validate the imaging and analysis protocol developed. Streptococcus mutans biofilm was disrupted from sandblasted, acid etched (SLA) Ti discs and polished Ti discs. Significant biofilm removal occurred due to cavitation from ultrasonic scaling (p < 0.001). The mean sensitivity and specificity values for segmentation of the SLA surface images were 0.80 ± 0.18 and 0.62 ± 0.20 respectively and 0.74 ± 0.13 and 0.86 ± 0.09 respectively for polished surfaces. Cavitation has potential to be used as a novel way to clean dental implants. This imaging and analysis method will be of value to other researchers and manufacturers wishing to study biofilm growth and removal.

Scatter Correction with Combined Single-Scatter Simulation and Monte Carlo Simulation Scaling Improved the Visual Artifacts and Quantification in 3-Dimensional Brain PET/CT Imaging with 15O-Gas Inhalation.

PubMed

Magota, Keiichi; Shiga, Tohru; Asano, Yukari; Shinyama, Daiki; Ye, Jinghan; Perkins, Amy E; Maniawski, Piotr J; Toyonaga, Takuya; Kobayashi, Kentaro; Hirata, Kenji; Katoh, Chietsugu; Hattori, Naoya; Tamaki, Nagara

2017-12-01

In 3-dimensional PET/CT imaging of the brain with 15 O-gas inhalation, high radioactivity in the face mask creates cold artifacts and affects the quantitative accuracy when scatter is corrected by conventional methods (e.g., single-scatter simulation [SSS] with tail-fitting scaling [TFS-SSS]). Here we examined the validity of a newly developed scatter-correction method that combines SSS with a scaling factor calculated by Monte Carlo simulation (MCS-SSS). Methods: We performed phantom experiments and patient studies. In the phantom experiments, a plastic bottle simulating a face mask was attached to a cylindric phantom simulating the brain. The cylindric phantom was filled with 18 F-FDG solution (3.8-7.0 kBq/mL). The bottle was filled with nonradioactive air or various levels of 18 F-FDG (0-170 kBq/mL). Images were corrected either by TFS-SSS or MCS-SSS using the CT data of the bottle filled with nonradioactive air. We compared the image activity concentration in the cylindric phantom with the true activity concentration. We also performed 15 O-gas brain PET based on the steady-state method on patients with cerebrovascular disease to obtain quantitative images of cerebral blood flow and oxygen metabolism. Results: In the phantom experiments, a cold artifact was observed immediately next to the bottle on TFS-SSS images, where the image activity concentrations in the cylindric phantom were underestimated by 18%, 36%, and 70% at the bottle radioactivity levels of 2.4, 5.1, and 9.7 kBq/mL, respectively. At higher bottle radioactivity, the image activity concentrations in the cylindric phantom were greater than 98% underestimated. For the MCS-SSS, in contrast, the error was within 5% at each bottle radioactivity level, although the image generated slight high-activity artifacts around the bottle when the bottle contained significantly high radioactivity. In the patient imaging with 15 O 2 and C 15 O 2 inhalation, cold artifacts were observed on TFS-SSS images, whereas no artifacts were observed on any of the MCS-SSS images. Conclusion: MCS-SSS accurately corrected the scatters in 15 O-gas brain PET when the 3-dimensional acquisition mode was used, preventing the generation of cold artifacts, which were observed immediately next to a face mask on TFS-SSS images. The MCS-SSS method will contribute to accurate quantitative assessments. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Quantitative correlational study of microbubble-enhanced ultrasound imaging and magnetic resonance imaging of glioma and early response to radiotherapy in a rat model

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

Yang, Chen; Lee, Dong-Hoon; Zhang, Kai

Purpose: Radiotherapy remains a major treatment method for malignant tumors. Magnetic resonance imaging (MRI) is the standard modality for assessing glioma treatment response in the clinic. Compared to MRI, ultrasound imaging is low-cost and portable and can be used during intraoperative procedures. The purpose of this study was to quantitatively compare contrast-enhanced ultrasound (CEUS) imaging and MRI of irradiated gliomas in rats and to determine which quantitative ultrasound imaging parameters can be used for the assessment of early response to radiation in glioma. Methods: Thirteen nude rats with U87 glioma were used. A small thinned skull window preparation was performedmore » to facilitate ultrasound imaging and mimic intraoperative procedures. Both CEUS and MRI with structural, functional, and molecular imaging parameters were performed at preradiation and at 1 day and 4 days postradiation. Statistical analysis was performed to determine the correlations between MRI and CEUS parameters and the changes between pre- and postradiation imaging. Results: Area under the curve (AUC) in CEUS showed significant difference between preradiation and 4 days postradiation, along with four MRI parameters, T{sub 2}, apparent diffusion coefficient, cerebral blood flow, and amide proton transfer-weighted (APTw) (all p < 0.05). The APTw signal was correlated with three CEUS parameters, rise time (r = − 0.527, p < 0.05), time to peak (r = − 0.501, p < 0.05), and perfusion index (r = 458, p < 0.05). Cerebral blood flow was correlated with rise time (r = − 0.589, p < 0.01) and time to peak (r = − 0.543, p < 0.05). Conclusions: MRI can be used for the assessment of radiotherapy treatment response and CEUS with AUC as a new technique and can also be one of the assessment methods for early response to radiation in glioma.« less

Novel Contrast Mechanisms at 3 Tesla and 7 Tesla

PubMed Central

Regatte, Ravinder R.; Schweitzer, Mark E.

2013-01-01

Osteoarthritis (OA) is the most common musculoskeletal degenerative disease, affecting millions of people. Although OA has been considered primarily a cartilage disorder associated with focal cartilage degeneration, it is accompanied by well-known changes in subchondral and trabecular bone, including sclerosis and osteophyte formation. The exact cause of OA initiation and progression remains under debate, but OA typically first affects weightbearing joints such as the knee. Magnetic resonance imaging (MRI) has been recognized as a potential tool for quantitative assessment of cartilage abnormalities due to its excellent soft tissue contrast. Over the last two decades, several new MR biochemical imaging methods have been developed to characterize the disease process and possibly predict the progression of knee OA. These new MR biochemical methods play an important role not only for diagnosis of disease at an early stage, but also for their potential use in monitoring outcome of various drug therapies (success or failure). Recent advances in multicoil radiofrequency technology and high field systems (3 T and above) significantly improve the sensitivity and specificity of imaging studies for the diagnosis of musculoskeletal disorders. The current state-of-the-art MR imaging methods are briefly reviewed for the quantitative biochemical and functional imaging assessment of musculoskeletal systems. PMID:18850506

Synthesis method from low-coherence digital holograms for improvement of image quality in holographic display.

PubMed

Mori, Yutaka; Nomura, Takanori

2013-06-01

In holographic displays, it is undesirable to observe the speckle noises with the reconstructed images. A method for improvement of reconstructed image quality by synthesizing low-coherence digital holograms is proposed. It is possible to obtain speckleless reconstruction of holograms due to low-coherence digital holography. An image sensor records low-coherence digital holograms, and the holograms are synthesized by computational calculation. Two approaches, the threshold-processing and the picking-a-peak methods, are proposed in order to reduce random noise of low-coherence digital holograms. The reconstructed image quality by the proposed methods is compared with the case of high-coherence digital holography. Quantitative evaluation is given to confirm the proposed methods. In addition, the visual evaluation by 15 people is also shown.

Quantitative segmentation of fluorescence microscopy images of heterogeneous tissue: Approach for tuning algorithm parameters

NASA Astrophysics Data System (ADS)

Mueller, Jenna L.; Harmany, Zachary T.; Mito, Jeffrey K.; Kennedy, Stephanie A.; Kim, Yongbaek; Dodd, Leslie; Geradts, Joseph; Kirsch, David G.; Willett, Rebecca M.; Brown, J. Quincy; Ramanujam, Nimmi

2013-02-01

The combination of fluorescent contrast agents with microscopy is a powerful technique to obtain real time images of tissue histology without the need for fixing, sectioning, and staining. The potential of this technology lies in the identification of robust methods for image segmentation and quantitation, particularly in heterogeneous tissues. Our solution is to apply sparse decomposition (SD) to monochrome images of fluorescently-stained microanatomy to segment and quantify distinct tissue types. The clinical utility of our approach is demonstrated by imaging excised margins in a cohort of mice after surgical resection of a sarcoma. Representative images of excised margins were used to optimize the formulation of SD and tune parameters associated with the algorithm. Our results demonstrate that SD is a robust solution that can advance vital fluorescence microscopy as a clinically significant technology.

Evaluation of Deblur Methods for Radiography

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

Wood, William M.

2014-03-31

Radiography is used as a primary diagnostic for dynamic experiments, providing timeresolved radiographic measurements of areal mass density along a line of sight through the experiment. It is well known that the finite spot extent of the radiographic source, as well as scattering, are sources of blurring of the radiographic images. This blurring interferes with quantitative measurement of the areal mass density. In order to improve the quantitative utility of this diagnostic, it is necessary to deblur or “restore” the radiographs to recover the “true” areal mass density from a radiographic transmission measurement. Towards this end, I am evaluating threemore » separate methods currently in use for deblurring radiographs. I begin by briefly describing the problems associated with image restoration, and outlining the three methods. Next, I illustrate how blurring affects the quantitative measurements using radiographs. I then present the results of the various deblur methods, evaluating each according to several criteria. After I have summarized the results of the evaluation, I give a detailed account of how the restoration process is actually implemented.« less

Flow-gated radial phase-contrast imaging in the presence of weak flow.

PubMed

Peng, Hsu-Hsia; Huang, Teng-Yi; Wang, Fu-Nien; Chung, Hsiao-Wen

2013-01-01

To implement a flow-gating method to acquire phase-contrast (PC) images of carotid arteries without use of an electrocardiography (ECG) signal to synchronize the acquisition of imaging data with pulsatile arterial flow. The flow-gating method was realized through radial scanning and sophisticated post-processing methods including downsampling, complex difference, and correlation analysis to improve the evaluation of flow-gating times in radial phase-contrast scans. Quantitatively comparable results (R = 0.92-0.96, n = 9) of flow-related parameters, including mean velocity, mean flow rate, and flow volume, with conventional ECG-gated imaging demonstrated that the proposed method is highly feasible. The radial flow-gating PC imaging method is applicable in carotid arteries. The proposed flow-gating method can potentially avoid the setting up of ECG-related equipment for brain imaging. This technique has potential use in patients with arrhythmia or weak ECG signals.

Three-dimensional cardiac architecture determined by two-photon microtomy

NASA Astrophysics Data System (ADS)

Huang, Hayden; MacGillivray, Catherine; Kwon, Hyuk-Sang; Lammerding, Jan; Robbins, Jeffrey; Lee, Richard T.; So, Peter

2009-07-01

Cardiac architecture is inherently three-dimensional, yet most characterizations rely on two-dimensional histological slices or dissociated cells, which remove the native geometry of the heart. We previously developed a method for labeling intact heart sections without dissociation and imaging large volumes while preserving their three-dimensional structure. We further refine this method to permit quantitative analysis of imaged sections. After data acquisition, these sections are assembled using image-processing tools, and qualitative and quantitative information is extracted. By examining the reconstructed cardiac blocks, one can observe end-to-end adjacent cardiac myocytes (cardiac strands) changing cross-sectional geometries, merging and separating from other strands. Quantitatively, representative cross-sectional areas typically used for determining hypertrophy omit the three-dimensional component; we show that taking orientation into account can significantly alter the analysis. Using fast-Fourier transform analysis, we analyze the gross organization of cardiac strands in three dimensions. By characterizing cardiac structure in three dimensions, we are able to determine that the α crystallin mutation leads to hypertrophy with cross-sectional area increases, but not necessarily via changes in fiber orientation distribution.

Advances in Imaging Approaches to Fracture Risk Evaluation

PubMed Central

Manhard, Mary Kate; Nyman, Jeffry S.; Does, Mark D.

2016-01-01

Fragility fractures are a growing problem worldwide, and current methods for diagnosing osteoporosis do not always identify individuals who require treatment to prevent a fracture and may misidentify those not a risk. Traditionally, fracture risk is assessed using dual-energy X-ray absorptiometry, which provides measurements of areal bone mineral density (BMD) at sites prone to fracture. Recent advances in imaging show promise in adding new information that could improve the prediction of fracture risk in the clinic. As reviewed herein, advances in quantitative computed tomography (QCT) predict hip and vertebral body strength; high resolution HR-peripheral QCT (HR-pQCT) and micro-magnetic resonance imaging (μMRI) assess the micro-architecture of trabecular bone; quantitative ultrasound (QUS) measures the modulus or tissue stiffness of cortical bone; and quantitative ultra-short echo time MRI methods quantify the concentrations of bound water and pore water in cortical bone, which reflect a variety of mechanical properties of bone. Each of these technologies provides unique characteristics of bone and may improve fracture risk diagnoses and reduce prevalence of fractures by helping to guide treatment decisions. PMID:27816505

Quantitative tomographic imaging of intermolecular FRET in small animals

PubMed Central

Venugopal, Vivek; Chen, Jin; Barroso, Margarida; Intes, Xavier

2012-01-01

Forster resonance energy transfer (FRET) is a nonradiative transfer of energy between two fluorescent molecules (a donor and an acceptor) in nanometer range proximity. FRET imaging methods have been applied to proteomic studies and drug discovery applications based on intermolecular FRET efficiency measurements and stoichiometric measurements of FRET interaction as quantitative parameters of interest. Importantly, FRET provides information about biomolecular interactions at a molecular level, well beyond the diffraction limits of standard microscopy techniques. The application of FRET to small animal imaging will allow biomedical researchers to investigate physiological processes occurring at nanometer range in vivo as well as in situ. In this work a new method for the quantitative reconstruction of FRET measurements in small animals, incorporating a full-field tomographic acquisition system with a Monte Carlo based hierarchical reconstruction scheme, is described and validated in murine models. Our main objective is to estimate the relative concentration of two forms of donor species, i.e., a donor molecule involved in FRETing to an acceptor close by and a nonFRETing donor molecule. PMID:23243567

Research on assessment and improvement method of remote sensing image reconstruction

NASA Astrophysics Data System (ADS)

Sun, Li; Hua, Nian; Yu, Yanbo; Zhao, Zhanping

2018-01-01

Remote sensing image quality assessment and improvement is an important part of image processing. Generally, the use of compressive sampling theory in remote sensing imaging system can compress images while sampling which can improve efficiency. A method of two-dimensional principal component analysis (2DPCA) is proposed to reconstruct the remote sensing image to improve the quality of the compressed image in this paper, which contain the useful information of image and can restrain the noise. Then, remote sensing image quality influence factors are analyzed, and the evaluation parameters for quantitative evaluation are introduced. On this basis, the quality of the reconstructed images is evaluated and the different factors influence on the reconstruction is analyzed, providing meaningful referential data for enhancing the quality of remote sensing images. The experiment results show that evaluation results fit human visual feature, and the method proposed have good application value in the field of remote sensing image processing.

3.0T MR imaging of the ankle: Axial traction for morphological cartilage evaluation, quantitative T2 mapping and cartilage diffusion imaging-A preliminary study.

PubMed

Jungmann, Pia M; Baum, Thomas; Schaeffeler, Christoph; Sauerschnig, Martin; Brucker, Peter U; Mann, Alexander; Ganter, Carl; Bieri, Oliver; Rummeny, Ernst J; Woertler, Klaus; Bauer, Jan S

2015-08-01

To determine the impact of axial traction during high resolution 3.0T MR imaging of the ankle on morphological assessment of articular cartilage and quantitative cartilage imaging parameters. MR images of n=25 asymptomatic ankles were acquired with and without axial traction (6kg). Coronal and sagittal T1-weighted (w) turbo spin echo (TSE) sequences with a driven equilibrium pulse and sagittal fat-saturated intermediate-w (IMfs) TSE sequences were acquired for morphological evaluation on a four-point scale (1=best, 4=worst). For quantitative assessment of cartilage degradation segmentation was performed on 2D multislice-multiecho (MSME) SE T2, steady-state free-precession (SSFP; n=8) T2 and SSFP diffusion-weighted imaging (DWI; n=8) images. Wilcoxon-tests and paired t-tests were used for statistical analysis. With axial traction, joint space width increased significantly and delineation of cartilage surfaces was rated superior (P<0.05). Cartilage surfaces were best visualized on coronal T1-w images (P<0.05). Differences for cartilage matrix evaluation were smaller. Subchondral bone evaluation, motion artifacts and image quality were not significantly different between the acquisition methods (P>0.05). T2 values were lower at the tibia than at the talus (P<0.001). Reproducibility was better for images with axial traction. Axial traction increased the joint space width, allowed for better visualization of cartilage surfaces and improved compartment discrimination and reproducibility of quantitative cartilage parameters. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

MO-DE-303-03: Session on quantitative imaging for assessment of tumor response to radiation therapy

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

Bowen, S.

This session will focus on quantitative imaging for assessment of tumor response to radiation therapy. This is a technically challenging method to translate to practice in radiation therapy. In the new era of precision medicine, however, delivering the right treatment, to the right patient, and at the right time, can positively impact treatment choices and patient outcomes. Quantitative imaging provides the spatial sensitivity required by radiation therapy for precision medicine that is not available by other means. In this Joint ESTRO -AAPM Symposium, three leading-edge investigators will present specific motivations for quantitative imaging biomarkers in radiation therapy of esophageal, headmore » and neck, locally advanced non-small cell lung cancer, and hepatocellular carcinoma. Experiences with the use of dynamic contrast enhanced (DCE) MRI, diffusion- weighted (DW) MRI, PET/CT, and SPECT/CT will be presented. Issues covered will include: response prediction, dose-painting, timing between therapy and imaging, within-therapy biomarkers, confounding effects, normal tissue sparing, dose-response modeling, and association with clinical biomarkers and outcomes. Current information will be presented from investigational studies and clinical practice. Learning Objectives: Learn motivations for the use of quantitative imaging biomarkers for assessment of response to radiation therapy Review the potential areas of application in cancer therapy Examine the challenges for translation, including imaging confounds and paucity of evidence to date Compare exemplary examples of the current state of the art in DCE-MRI, DW-MRI, PET/CT and SPECT/CT imaging for assessment of response to radiation therapy Van der Heide: Research grants from the Dutch Cancer Society and the European Union (FP7) Bowen: RSNA Scholar grant.« less

General Staining and Segmentation Procedures for High Content Imaging and Analysis.

PubMed

Chambers, Kevin M; Mandavilli, Bhaskar S; Dolman, Nick J; Janes, Michael S

2018-01-01

Automated quantitative fluorescence microscopy, also known as high content imaging (HCI), is a rapidly growing analytical approach in cell biology. Because automated image analysis relies heavily on robust demarcation of cells and subcellular regions, reliable methods for labeling cells is a critical component of the HCI workflow. Labeling of cells for image segmentation is typically performed with fluorescent probes that bind DNA for nuclear-based cell demarcation or with those which react with proteins for image analysis based on whole cell staining. These reagents, along with instrument and software settings, play an important role in the successful segmentation of cells in a population for automated and quantitative image analysis. In this chapter, we describe standard procedures for labeling and image segmentation in both live and fixed cell samples. The chapter will also provide troubleshooting guidelines for some of the common problems associated with these aspects of HCI.

Quantitative method of measuring cancer cell urokinase and metastatic potential

NASA Technical Reports Server (NTRS)

Morrison, Dennis R. (Inventor)

1993-01-01

The metastatic potential of tumors can be evaluated by the quantitative detection of urokinase and DNA. The cell sample selected for examination is analyzed for the presence of high levels of urokinase and abnormal DNA using analytical flow cytometry and digital image analysis. Other factors such as membrane associated urokinase, increased DNA synthesis rates and certain receptors can be used in the method for detection of potentially invasive tumors.

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.

MR Morphology of Triangular Fibrocartilage Complex: Correlation with Quantitative MR and Biomechanical Properties

PubMed Central

Bae, Won C.; Ruangchaijatuporn, Thumanoon; Chang, Eric Y; Biswas, Reni; Du, Jiang; Statum, Sheronda

2016-01-01

Objective To evaluate pathology of the triangular fibrocartilage complex (TFCC) using high resolution morphologic magnetic resonance (MR) imaging, and compare with quantitative MR and biomechanical properties. Materials and Methods Five cadaveric wrists (22 to 70 yrs) were imaged at 3T using morphologic (proton density weighted spin echo, PD FS, and 3D spoiled gradient echo, 3D SPGR) and quantitative MR sequences to determine T2 and T1rho properties. In eight geographic regions, morphology of TFC disc and laminae were evaluated for pathology and quantitative MR values. Samples were disarticulated and biomechanical indentation testing was performed on the distal surface of the TFC disc. Results On morphologic PD SE images, TFC disc pathology included degeneration and tears, while that of the laminae included degeneration, degeneration with superimposed tear, mucinous transformation, and globular calcification. Punctate calcifications were highly visible on 3D SPGR images and found only in pathologic regions. Disc pathology occurred more frequently in proximal regions of the disc than distal regions. Quantitative MR values were lowest in normal samples, and generally higher in pathologic regions. Biomechanical testing demonstrated an inverse relationship, with indentation modulus being high in normal regions with low MR values. The laminae studied were mostly pathologic, and additional normal samples are needed to discern quantitative changes. Conclusion These results show technical feasibility of morphologic MR, quantitative MR, and biomechanical techniques to characterize pathology of the TFCC. Quantitative MRI may be a suitable surrogate marker of soft tissue mechanical properties, and a useful adjunct to conventional morphologic MR techniques. PMID:26691643

Light sheet theta microscopy for rapid high-resolution imaging of large biological samples.

PubMed

Migliori, Bianca; Datta, Malika S; Dupre, Christophe; Apak, Mehmet C; Asano, Shoh; Gao, Ruixuan; Boyden, Edward S; Hermanson, Ola; Yuste, Rafael; Tomer, Raju

2018-05-29

Advances in tissue clearing and molecular labeling methods are enabling unprecedented optical access to large intact biological systems. These developments fuel the need for high-speed microscopy approaches to image large samples quantitatively and at high resolution. While light sheet microscopy (LSM), with its high planar imaging speed and low photo-bleaching, can be effective, scaling up to larger imaging volumes has been hindered by the use of orthogonal light sheet illumination. To address this fundamental limitation, we have developed light sheet theta microscopy (LSTM), which uniformly illuminates samples from the same side as the detection objective, thereby eliminating limits on lateral dimensions without sacrificing the imaging resolution, depth, and speed. We present a detailed characterization of LSTM, and demonstrate its complementary advantages over LSM for rapid high-resolution quantitative imaging of large intact samples with high uniform quality. The reported LSTM approach is a significant step for the rapid high-resolution quantitative mapping of the structure and function of very large biological systems, such as a clarified thick coronal slab of human brain and uniformly expanded tissues, and also for rapid volumetric calcium imaging of highly motile animals, such as Hydra, undergoing non-isomorphic body shape changes.

A Checklist for Successful Quantitative Live Cell Imaging in Systems Biology

PubMed Central

Sung, Myong-Hee

2013-01-01

Mathematical modeling of signaling and gene regulatory networks has provided unique insights about systems behaviors for many cell biological problems of medical importance. Quantitative single cell monitoring has a crucial role in advancing systems modeling of molecular networks. However, due to the multidisciplinary techniques that are necessary for adaptation of such systems biology approaches, dissemination to a wide research community has been relatively slow. In this essay, I focus on some technical aspects that are often under-appreciated, yet critical in harnessing live cell imaging methods to achieve single-cell-level understanding and quantitative modeling of molecular networks. The importance of these technical considerations will be elaborated with examples of successes and shortcomings. Future efforts will benefit by avoiding some pitfalls and by utilizing the lessons collectively learned from recent applications of imaging in systems biology. PMID:24709701

Single-shot quantitative phase microscopy with color-multiplexed differential phase contrast (cDPC)

PubMed Central

2017-01-01

We present a new technique for quantitative phase and amplitude microscopy from a single color image with coded illumination. Our system consists of a commercial brightfield microscope with one hardware modification—an inexpensive 3D printed condenser insert. The method, color-multiplexed Differential Phase Contrast (cDPC), is a single-shot variant of Differential Phase Contrast (DPC), which recovers the phase of a sample from images with asymmetric illumination. We employ partially coherent illumination to achieve resolution corresponding to 2× the objective NA. Quantitative phase can then be used to synthesize DIC and phase contrast images or extract shape and density. We demonstrate amplitude and phase recovery at camera-limited frame rates (50 fps) for various in vitro cell samples and c. elegans in a micro-fluidic channel. PMID:28152023

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

NASA Astrophysics Data System (ADS)

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

2012-02-01

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

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology

NASA Astrophysics Data System (ADS)

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-01

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology.

PubMed

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-13

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a temporal regularization in the reconstruction process of the PET dynamic series led to substantial quantitative improvements and motion artifact reduction. Future work will include the integration of a linear FDG kinetic model, in order to directly reconstruct parametric images.

Enhancement of dynamic myocardial perfusion PET images based on low-rank plus sparse decomposition.

PubMed

Lu, Lijun; Ma, Xiaomian; Mohy-Ud-Din, Hassan; Ma, Jianhua; Feng, Qianjin; Rahmim, Arman; Chen, Wufan

2018-02-01

The absolute quantification of dynamic myocardial perfusion (MP) PET imaging is challenged by the limited spatial resolution of individual frame images due to division of the data into shorter frames. This study aims to develop a method for restoration and enhancement of dynamic PET images. We propose that the image restoration model should be based on multiple constraints rather than a single constraint, given the fact that the image characteristic is hardly described by a single constraint alone. At the same time, it may be possible, but not optimal, to regularize the image with multiple constraints simultaneously. Fortunately, MP PET images can be decomposed into a superposition of background vs. dynamic components via low-rank plus sparse (L + S) decomposition. Thus, we propose an L + S decomposition based MP PET image restoration model and express it as a convex optimization problem. An iterative soft thresholding algorithm was developed to solve the problem. Using realistic dynamic 82 Rb MP PET scan data, we optimized and compared its performance with other restoration methods. The proposed method resulted in substantial visual as well as quantitative accuracy improvements in terms of noise versus bias performance, as demonstrated in extensive 82 Rb MP PET simulations. In particular, the myocardium defect in the MP PET images had improved visual as well as contrast versus noise tradeoff. The proposed algorithm was also applied on an 8-min clinical cardiac 82 Rb MP PET study performed on the GE Discovery PET/CT, and demonstrated improved quantitative accuracy (CNR and SNR) compared to other algorithms. The proposed method is effective for restoration and enhancement of dynamic PET images. Copyright © 2017 Elsevier B.V. All rights reserved.

TH-AB-207A-05: A Fully-Automated Pipeline for Generating CT Images Across a Range of Doses and Reconstruction Methods

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

Young, S; Lo, P; Hoffman, J

Purpose: To evaluate the robustness of CAD or Quantitative Imaging methods, they should be tested on a variety of cases and under a variety of image acquisition and reconstruction conditions that represent the heterogeneity encountered in clinical practice. The purpose of this work was to develop a fully-automated pipeline for generating CT images that represent a wide range of dose and reconstruction conditions. Methods: The pipeline consists of three main modules: reduced-dose simulation, image reconstruction, and quantitative analysis. The first two modules of the pipeline can be operated in a completely automated fashion, using configuration files and running the modulesmore » in a batch queue. The input to the pipeline is raw projection CT data; this data is used to simulate different levels of dose reduction using a previously-published algorithm. Filtered-backprojection reconstructions are then performed using FreeCT-wFBP, a freely-available reconstruction software for helical CT. We also added support for an in-house, model-based iterative reconstruction algorithm using iterative coordinate-descent optimization, which may be run in tandem with the more conventional recon methods. The reduced-dose simulations and image reconstructions are controlled automatically by a single script, and they can be run in parallel on our research cluster. The pipeline was tested on phantom and lung screening datasets from a clinical scanner (Definition AS, Siemens Healthcare). Results: The images generated from our test datasets appeared to represent a realistic range of acquisition and reconstruction conditions that we would expect to find clinically. The time to generate images was approximately 30 minutes per dose/reconstruction combination on a hybrid CPU/GPU architecture. Conclusion: The automated research pipeline promises to be a useful tool for either training or evaluating performance of quantitative imaging software such as classifiers and CAD algorithms across the range of acquisition and reconstruction parameters present in the clinical environment. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.« less

Quantitative evaluation of lipid concentration in atherosclerotic plaque phantom by near-infrared multispectral angioscope at wavelengths around 1200 nm

NASA Astrophysics Data System (ADS)

Matsui, Daichi; Ishii, Katsunori; Awazu, Kunio

2015-07-01

Atherosclerosis is a primary cause of critical ischemic diseases like heart infarction or stroke. A method that can provide detailed information about the stability of atherosclerotic plaques is required. We focused on spectroscopic techniques that could evaluate the chemical composition of lipid in plaques. A novel angioscope using multispectral imaging at wavelengths around 1200 nm for quantitative evaluation of atherosclerotic plaques was developed. The angioscope consists of a halogen lamp, an indium gallium arsenide (InGaAs) camera, 3 optical band pass filters transmitting wavelengths of 1150, 1200, and 1300 nm, an image fiber having 0.7 mm outer diameter, and an irradiation fiber which consists of 7 multimode fibers. Atherosclerotic plaque phantoms with 100, 60, 20 vol.% of lipid were prepared and measured by the multispectral angioscope. The acquired datasets were processed by spectral angle mapper (SAM) method. As a result, simulated plaque areas in atherosclerotic plaque phantoms that could not be detected by an angioscopic visible image could be clearly enhanced. In addition, quantitative evaluation of atherosclerotic plaque phantoms based on the lipid volume fractions was performed up to 20 vol.%. These results show the potential of a multispectral angioscope at wavelengths around 1200 nm for quantitative evaluation of the stability of atherosclerotic plaques.

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

PubMed

Ripoll, Jorge; Ntziachristos, Vasilis

2011-01-01

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

Combined self-learning based single-image super-resolution and dual-tree complex wavelet transform denoising for medical images

NASA Astrophysics Data System (ADS)

Yang, Guang; Ye, Xujiong; Slabaugh, Greg; Keegan, Jennifer; Mohiaddin, Raad; Firmin, David

2016-03-01

In this paper, we propose a novel self-learning based single-image super-resolution (SR) method, which is coupled with dual-tree complex wavelet transform (DTCWT) based denoising to better recover high-resolution (HR) medical images. Unlike previous methods, this self-learning based SR approach enables us to reconstruct HR medical images from a single low-resolution (LR) image without extra training on HR image datasets in advance. The relationships between the given image and its scaled down versions are modeled using support vector regression with sparse coding and dictionary learning, without explicitly assuming reoccurrence or self-similarity across image scales. In addition, we perform DTCWT based denoising to initialize the HR images at each scale instead of simple bicubic interpolation. We evaluate our method on a variety of medical images. Both quantitative and qualitative results show that the proposed approach outperforms bicubic interpolation and state-of-the-art single-image SR methods while effectively removing noise.

Coherent diffraction imaging of non-isolated object with apodized illumination.

PubMed

Khakurel, Krishna P; Kimura, Takashi; Joti, Yasumasa; Matsuyama, Satoshi; Yamauchi, Kazuto; Nishino, Yoshinori

2015-11-02

Coherent diffraction imaging (CDI) is an established lensless imaging method widely used at the x-ray regime applicable to the imaging of non-periodic materials. Conventional CDI can practically image isolated objects only, which hinders the broader application of the method. We present the imaging of non-isolated objects by employing recently proposed "non-scanning" apodized-illumination CDI at an optical wavelength. We realized isolated apodized illumination with a specially designed optical configuration and succeeded in imaging phase objects as well as amplitude objects. The non-scanning nature of the method is important particularly in imaging live cells and tissues, where fast imaging is required for non-isolated objects, and is an advantage over ptychography. We believe that our result of phase contrast imaging at an optical wavelength can be extended to the quantitative phase imaging of cells and tissues. The method also provides the feasibility of the lensless single-shot imaging of extended objects with x-ray free-electron lasers.

Quantitative analysis of ex vivo colorectal epithelium using an automated feature extraction algorithm for microendoscopy image data

PubMed Central

Prieto, Sandra P.; Lai, Keith K.; Laryea, Jonathan A.; Mizell, Jason S.; Muldoon, Timothy J.

2016-01-01

Abstract. Qualitative screening for colorectal polyps via fiber bundle microendoscopy imaging has shown promising results, with studies reporting high rates of sensitivity and specificity, as well as low interobserver variability with trained clinicians. A quantitative image quality control and image feature extraction algorithm (QFEA) was designed to lessen the burden of training and provide objective data for improved clinical efficacy of this method. After a quantitative image quality control step, QFEA extracts field-of-view area, crypt area, crypt circularity, and crypt number per image. To develop and validate this QFEA, a training set of microendoscopy images was collected from freshly resected porcine colon epithelium. The algorithm was then further validated on ex vivo image data collected from eight human subjects, selected from clinically normal appearing regions distant from grossly visible tumor in surgically resected colorectal tissue. QFEA has proven flexible in application to both mosaics and individual images, and its automated crypt detection sensitivity ranges from 71 to 94% despite intensity and contrast variation within the field of view. It also demonstrates the ability to detect and quantify differences in grossly normal regions among different subjects, suggesting the potential efficacy of this approach in detecting occult regions of dysplasia. PMID:27335893

Determining open cluster membership. A Bayesian framework for quantitative member classification

NASA Astrophysics Data System (ADS)

Stott, Jonathan J.

2018-01-01

Aims: My goal is to develop a quantitative algorithm for assessing open cluster membership probabilities. The algorithm is designed to work with single-epoch observations. In its simplest form, only one set of program images and one set of reference images are required. Methods: The algorithm is based on a two-stage joint astrometric and photometric assessment of cluster membership probabilities. The probabilities were computed within a Bayesian framework using any available prior information. Where possible, the algorithm emphasizes simplicity over mathematical sophistication. Results: The algorithm was implemented and tested against three observational fields using published survey data. M 67 and NGC 654 were selected as cluster examples while a third, cluster-free, field was used for the final test data set. The algorithm shows good quantitative agreement with the existing surveys and has a false-positive rate significantly lower than the astrometric or photometric methods used individually.

Quantitative imaging of aggregated emulsions.

PubMed

Penfold, Robert; Watson, Andrew D; Mackie, Alan R; Hibberd, David J

2006-02-28

Noise reduction, restoration, and segmentation methods are developed for the quantitative structural analysis in three dimensions of aggregated oil-in-water emulsion systems imaged by fluorescence confocal laser scanning microscopy. Mindful of typical industrial formulations, the methods are demonstrated for concentrated (30% volume fraction) and polydisperse emulsions. Following a regularized deconvolution step using an analytic optical transfer function and appropriate binary thresholding, novel application of the Euclidean distance map provides effective discrimination of closely clustered emulsion droplets with size variation over at least 1 order of magnitude. The a priori assumption of spherical nonintersecting objects provides crucial information to combat the ill-posed inverse problem presented by locating individual particles. Position coordinates and size estimates are recovered with sufficient precision to permit quantitative study of static geometrical features. In particular, aggregate morphology is characterized by a novel void distribution measure based on the generalized Apollonius problem. This is also compared with conventional Voronoi/Delauney analysis.

Influence of sample preparation and reliability of automated numerical refocusing in stain-free analysis of dissected tissues with quantitative phase digital holographic microscopy

NASA Astrophysics Data System (ADS)

Kemper, Björn; Lenz, Philipp; Bettenworth, Dominik; Krausewitz, Philipp; Domagk, Dirk; Ketelhut, Steffi

2015-05-01

Digital holographic microscopy (DHM) has been demonstrated to be a versatile tool for high resolution non-destructive quantitative phase imaging of surfaces and multi-modal minimally-invasive monitoring of living cell cultures in-vitro. DHM provides quantitative monitoring of physiological processes through functional imaging and structural analysis which, for example, gives new insight into signalling of cellular water permeability and cell morphology changes due to toxins and infections. Also the analysis of dissected tissues quantitative DHM phase contrast prospects application fields by stain-free imaging and the quantification of tissue density changes. We show that DHM allows imaging of different tissue layers with high contrast in unstained tissue sections. As the investigation of fixed samples represents a very important application field in pathology, we also analyzed the influence of the sample preparation. The retrieved data demonstrate that the quality of quantitative DHM phase images of dissected tissues depends strongly on the fixing method and common staining agents. As in DHM the reconstruction is performed numerically, multi-focus imaging is achieved from a single digital hologram. Thus, we evaluated the automated refocussing feature of DHM for application on different types of dissected tissues and revealed that on moderately stained samples highly reproducible holographic autofocussing can be achieved. Finally, it is demonstrated that alterations of the spatial refractive index distribution in murine and human tissue samples represent a reliable absolute parameter that is related of different degrees of inflammation in experimental colitis and Crohn's disease. This paves the way towards the usage of DHM in digital pathology for automated histological examinations and further studies to elucidate the translational potential of quantitative phase microscopy for the clinical management of patients, e.g., with inflammatory bowel disease.

Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging

NASA Astrophysics Data System (ADS)

Chung, Hyunkoo; Lu, Guolan; Tian, Zhiqiang; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2016-03-01

Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two dimensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and obtains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.

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

PubMed

Heidelberger, Lindsay; Smith, Chery

2018-03-03

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

A Review on Segmentation of Positron Emission Tomography Images

PubMed Central

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

2014-01-01

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

Analysis of chronic aortic regurgitation by 2D and 3D echocardiography and cardiac MRI

PubMed Central

Stoebe, Stephan; Metze, Michael; Jurisch, Daniel; Tayal, Bhupendar; Solty, Kilian; Laufs, Ulrich; Pfeiffer, Dietrich; Hagendorff, Andreas

2018-01-01

Purpose The study compares the feasibility of the quantitative volumetric and semi-quantitative approach for quantification of chronic aortic regurgitation (AR) using different imaging modalities. Methods Left ventricular (LV) volumes, regurgitant volumes (RVol) and regurgitant fractions (RF) were assessed retrospectively by 2D, 3D echocardiography and cMRI in 55 chronic AR patients. Semi-quantitative parameters were assessed by 2D echocardiography. Results 22 (40%) patients had mild, 25 (46%) moderate and 8 (14%) severe AR. The quantitative volumetric approach was feasible using 2D, 3D echocardiography and cMRI, whereas the feasibility of semi-quantitative parameters varied considerably. LV volume (LVEDV, LVESV, SVtot) analyses showed good correlations between the different imaging modalities, although significantly increased LV volumes were assessed by cMRI. RVol was significantly different between 2D/3D echocardiography and 2D echocardiography/cMRI but was not significantly different between 3D echocardiography/cMRI. RF was not statistically different between 2D echocardiography/cMRI and 3D echocardiography/cMRI showing poor correlations (r < 0.5) between the different imaging modalities. For AR grading by RF, moderate agreement was observed between 2D/3D echocardiography and 2D echocardiography/cMRI and good agreement was observed between 3D echocardiography/cMRI. Conclusion Semi-quantitative parameters are difficult to determine by 2D echocardiography in clinical routine. The quantitative volumetric RF assessment seems to be feasible and can be discussed as an alternative approach in chronic AR. However, RVol and RF did not correlate well between the different imaging modalities. The best agreement for grading of AR severity by RF was observed between 3D echocardiography and cMRI. LV volumes can be verified by different approaches and different imaging modalities. PMID:29519957

Quantitative correlational study of microbubble-enhanced ultrasound imaging and magnetic resonance imaging of glioma and early response to radiotherapy in a rat model.

PubMed

Yang, Chen; Lee, Dong-Hoon; Mangraviti, Antonella; Su, Lin; Zhang, Kai; Zhang, Yin; Zhang, Bin; Li, Wenxiao; Tyler, Betty; Wong, John; Wang, Ken Kang-Hsin; Velarde, Esteban; Zhou, Jinyuan; Ding, Kai

2015-08-01

Radiotherapy remains a major treatment method for malignant tumors. Magnetic resonance imaging (MRI) is the standard modality for assessing glioma treatment response in the clinic. Compared to MRI, ultrasound imaging is low-cost and portable and can be used during intraoperative procedures. The purpose of this study was to quantitatively compare contrast-enhanced ultrasound (CEUS) imaging and MRI of irradiated gliomas in rats and to determine which quantitative ultrasound imaging parameters can be used for the assessment of early response to radiation in glioma. Thirteen nude rats with U87 glioma were used. A small thinned skull window preparation was performed to facilitate ultrasound imaging and mimic intraoperative procedures. Both CEUS and MRI with structural, functional, and molecular imaging parameters were performed at preradiation and at 1 day and 4 days postradiation. Statistical analysis was performed to determine the correlations between MRI and CEUS parameters and the changes between pre- and postradiation imaging. Area under the curve (AUC) in CEUS showed significant difference between preradiation and 4 days postradiation, along with four MRI parameters, T2, apparent diffusion coefficient, cerebral blood flow, and amide proton transfer-weighted (APTw) (all p < 0.05). The APTw signal was correlated with three CEUS parameters, rise time (r = - 0.527, p < 0.05), time to peak (r = - 0.501, p < 0.05), and perfusion index (r = 458, p < 0.05). Cerebral blood flow was correlated with rise time (r = - 0.589, p < 0.01) and time to peak (r = - 0.543, p < 0.05). MRI can be used for the assessment of radiotherapy treatment response and CEUS with AUC as a new technique and can also be one of the assessment methods for early response to radiation in glioma.

Fluorescence imaging of tryptophan and collagen cross-links to evaluate wound closure ex vivo

NASA Astrophysics Data System (ADS)

Wang, Ying; Ortega-Martinez, Antonio; Farinelli, Bill; Anderson, R. R.; Franco, Walfre

2016-02-01

Wound size is a key parameter in monitoring healing. Current methods to measure wound size are often subjective, time-consuming and marginally invasive. Recently, we developed a non-invasive, non-contact, fast and simple but robust fluorescence imaging (u-FEI) method to monitor the healing of skin wounds. This method exploits the fluorescence of native molecules to tissue as functional and structural markers. The objective of the present study is to demonstrate the feasibility of using variations in the fluorescence intensity of tryptophan and cross-links of collagen to evaluate proliferation of keratinocyte cells and quantitate size of wound during healing, respectively. Circular dermal wounds were created in ex vivo human skin and cultured in different media. Two serial fluorescence images of tryptophan and collagen cross-links were acquired every two days. Histology and immunohistology were used to validate correlation between fluorescence and epithelialization. Images of collagen cross-links show fluorescence of the exposed dermis and, hence, are a measure of wound area. Images of tryptophan show higher fluorescence intensity of proliferating keratinocytes forming new epithelium, as compared to surrounding keratinocytes not involved in epithelialization. These images are complementary since collagen cross-links report on structure while tryptophan reports on function. HE and immunohistology show that tryptophan fluorescence correlates with newly formed epidermis. We have established a fluorescence imaging method for studying epithelialization processes during wound healing in a skin organ culture model, our approach has the potential to provide a non-invasive, non-contact, quick, objective and direct method for quantitative measurements in wound healing in vivo.

Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images

PubMed Central

Khansari, Maziyar M; O’Neill, William; Penn, Richard; Chau, Felix; Blair, Norman P; Shahidi, Mahnaz

2016-01-01

The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method’s discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring. PMID:27446692

A comparative study of qualitative and quantitative methods for the assessment of adhesive remnant after bracket debonding.

PubMed

Cehreli, S Burcak; Polat-Ozsoy, Omur; Sar, Cagla; Cubukcu, H Evren; Cehreli, Zafer C

2012-04-01

The amount of the residual adhesive after bracket debonding is frequently assessed in a qualitative manner, utilizing the adhesive remnant index (ARI). This study aimed to investigate whether quantitative assessment of the adhesive remnant yields more precise results compared to qualitative methods utilizing the 4- and 5-point ARI scales. Twenty debonded brackets were selected. Evaluation and scoring of the adhesive remnant on bracket bases were made consecutively using: 1. qualitative assessment (visual scoring) and 2. quantitative measurement (image analysis) on digital photographs. Image analysis was made on scanning electron micrographs (SEM) and high-precision elemental maps of the adhesive remnant as determined by energy dispersed X-ray spectrometry. Evaluations were made in accordance with the original 4-point and the modified 5-point ARI scales. Intra-class correlation coefficients (ICCs) were calculated, and the data were evaluated using Friedman test followed by Wilcoxon signed ranks test with Bonferroni correction. ICC statistics indicated high levels of agreement for qualitative visual scoring among examiners. The 4-point ARI scale was compliant with the SEM assessments but indicated significantly less adhesive remnant compared to the results of quantitative elemental mapping. When the 5-point scale was used, both quantitative techniques yielded similar results with those obtained qualitatively. These results indicate that qualitative visual scoring using the ARI is capable of generating similar results with those assessed by quantitative image analysis techniques. In particular, visual scoring with the 5-point ARI scale can yield similar results with both the SEM analysis and elemental mapping.

3D quantitative phase imaging of neural networks using WDT

NASA Astrophysics Data System (ADS)

Kim, Taewoo; Liu, S. C.; Iyer, Raj; Gillette, Martha U.; Popescu, Gabriel

2015-03-01

White-light diffraction tomography (WDT) is a recently developed 3D imaging technique based on a quantitative phase imaging system called spatial light interference microscopy (SLIM). The technique has achieved a sub-micron resolution in all three directions with high sensitivity granted by the low-coherence of a white-light source. Demonstrations of the technique on single cell imaging have been presented previously; however, imaging on any larger sample, including a cluster of cells, has not been demonstrated using the technique. Neurons in an animal body form a highly complex and spatially organized 3D structure, which can be characterized by neuronal networks or circuits. Currently, the most common method of studying the 3D structure of neuron networks is by using a confocal fluorescence microscope, which requires fluorescence tagging with either transient membrane dyes or after fixation of the cells. Therefore, studies on neurons are often limited to samples that are chemically treated and/or dead. WDT presents a solution for imaging live neuron networks with a high spatial and temporal resolution, because it is a 3D imaging method that is label-free and non-invasive. Using this method, a mouse or rat hippocampal neuron culture and a mouse dorsal root ganglion (DRG) neuron culture have been imaged in order to see the extension of processes between the cells in 3D. Furthermore, the tomogram is compared with a confocal fluorescence image in order to investigate the 3D structure at synapses.

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging.

PubMed

Liu, Fang; Zhou, Zhaoye; Jang, Hyungseok; Samsonov, Alexey; Zhao, Gengyan; Kijowski, Richard

2018-04-01

To describe and evaluate a new fully automated musculoskeletal tissue segmentation method using deep convolutional neural network (CNN) and three-dimensional (3D) simplex deformable modeling to improve the accuracy and efficiency of cartilage and bone segmentation within the knee joint. A fully automated segmentation pipeline was built by combining a semantic segmentation CNN and 3D simplex deformable modeling. A CNN technique called SegNet was applied as the core of the segmentation method to perform high resolution pixel-wise multi-class tissue classification. The 3D simplex deformable modeling refined the output from SegNet to preserve the overall shape and maintain a desirable smooth surface for musculoskeletal structure. The fully automated segmentation method was tested using a publicly available knee image data set to compare with currently used state-of-the-art segmentation methods. The fully automated method was also evaluated on two different data sets, which include morphological and quantitative MR images with different tissue contrasts. The proposed fully automated segmentation method provided good segmentation performance with segmentation accuracy superior to most of state-of-the-art methods in the publicly available knee image data set. The method also demonstrated versatile segmentation performance on both morphological and quantitative musculoskeletal MR images with different tissue contrasts and spatial resolutions. The study demonstrates that the combined CNN and 3D deformable modeling approach is useful for performing rapid and accurate cartilage and bone segmentation within the knee joint. The CNN has promising potential applications in musculoskeletal imaging. Magn Reson Med 79:2379-2391, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

[Assessment of skin aging grading based on computer vision].

PubMed

Li, Lingyu; Xue, Jinxia; He, Xiangqian; Zhang, Sheng; Fan, Chu

2017-06-01

Skin aging is the most intuitive and obvious sign of the human aging processes. Qualitative and quantitative determination of skin aging is of particular importance for the evaluation of human aging and anti-aging treatment effects. To solve the problem of subjectivity of conventional skin aging grading methods, the self-organizing map (SOM) network was used to explore an automatic method for skin aging grading. First, the ventral forearm skin images were obtained by a portable digital microscope and two texture parameters, i.e. , mean width of skin furrows and the number of intersections were extracted by image processing algorithm. Then, the values of texture parameters were taken as inputs of SOM network to train the network. The experimental results showed that the network achieved an overall accuracy of 80.8%, compared with the aging grading results by human graders. The designed method appeared to be rapid and objective, which can be used for quantitative analysis of skin images, and automatic assessment of skin aging grading.

Assessment of imaging quality in magnified phase CT of human bone tissue at the nanoscale

NASA Astrophysics Data System (ADS)

Yu, Boliang; Langer, Max; Pacureanu, Alexandra; Gauthier, Remy; Follet, Helene; Mitton, David; Olivier, Cecile; Cloetens, Peter; Peyrin, Francoise

2017-10-01

Bone properties at all length scales have a major impact on the fracture risk in disease such as osteoporosis. However, quantitative 3D data on bone tissue at the cellular scale are still rare. Here we propose to use magnified X-ray phase nano-CT to quantify bone ultra-structure in human bone, on the new setup developed on the beamline ID16A at the ESRF, Grenoble. Obtaining 3D images requires the application of phase retrieval prior to tomographic reconstruction. Phase retrieval is an ill-posed problem for which various approaches have been developed. Since image quality has a strong impact on the further quantification of bone tissue, our aim here is to evaluate different phase retrieval methods for imaging bone samples at the cellular scale. Samples from femurs of female donors were scanned using magnified phase nano-CT at voxel sizes of 120 and 30 nm with an energy of 33 keV. Four CT scans at varying sample-to-detector distances were acquired for each sample. We evaluated three phase retrieval methods adapted to these conditions: Paganin's method at single distance, Paganin's method extended to multiple distances, and the contrast transfer function (CTF) approach for pure phase objects. These methods were used as initialization to an iterative refinement step. Our results based on visual and quantitative assessment show that the use of several distances (as opposed to single one) clearly improves image quality and the two multi-distance phase retrieval methods give similar results. First results on the segmentation of osteocyte lacunae and canaliculi from such images are presented.

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.

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.

Comparison of two laboratory-based systems for evaluation of halos in intraocular lenses

PubMed Central

Alexander, Elsinore; Wei, Xin; Lee, Shinwook

2018-01-01

Purpose Multifocal intraocular lenses (IOLs) can be associated with unwanted visual phenomena, including halos. Predicting potential for halos is desirable when designing new multifocal IOLs. Halo images from 6 IOL models were compared using the Optikos modulation transfer function bench system and a new high dynamic range (HDR) system. Materials and methods One monofocal, 1 extended depth of focus, and 4 multifocal IOLs were evaluated. An off-the-shelf optical bench was used to simulate a distant (>50 m) car headlight and record images. A custom HDR system was constructed using an imaging photometer to simulate headlight images and to measure quantitative halo luminance data. A metric was developed to characterize halo luminance properties. Clinical relevance was investigated by correlating halo measurements to visual outcomes questionnaire data. Results The Optikos system produced halo images useful for visual comparisons; however, measurements were relative and not quantitative. The HDR halo system provided objective and quantitative measurements used to create a metric from the area under the curve (AUC) of the logarithmic normalized halo profile. This proposed metric differentiated between IOL models, and linear regression analysis found strong correlations between AUC and subjective clinical ratings of halos. Conclusion The HDR system produced quantitative, preclinical metrics that correlated to patients’ subjective perception of halos. PMID:29503526

Quantitative Live-Cell Confocal Imaging of 3D Spheroids in a High-Throughput Format.

PubMed

Leary, Elizabeth; Rhee, Claire; Wilks, Benjamin T; Morgan, Jeffrey R

2018-06-01

Accurately predicting the human response to new compounds is critical to a wide variety of industries. Standard screening pipelines (including both in vitro and in vivo models) often lack predictive power. Three-dimensional (3D) culture systems of human cells, a more physiologically relevant platform, could provide a high-throughput, automated means to test the efficacy and/or toxicity of novel substances. However, the challenge of obtaining high-magnification, confocal z stacks of 3D spheroids and understanding their respective quantitative limitations must be overcome first. To address this challenge, we developed a method to form spheroids of reproducible size at precise spatial locations across a 96-well plate. Spheroids of variable radii were labeled with four different fluorescent dyes and imaged with a high-throughput confocal microscope. 3D renderings of the spheroid had a complex bowl-like appearance. We systematically analyzed these confocal z stacks to determine the depth of imaging and the effect of spheroid size and dyes on quantitation. Furthermore, we have shown that this loss of fluorescence can be addressed through the use of ratio imaging. Overall, understanding both the limitations of confocal imaging and the tools to correct for these limits is critical for developing accurate quantitative assays using 3D spheroids.

Surface-Enhanced Raman Scattering Active Plasmonic Nanoparticles with Ultrasmall Interior Nanogap for Multiplex Quantitative Detection and Cancer Cell Imaging.

PubMed

Li, Jiuxing; Zhu, Zhi; Zhu, Bingqing; Ma, Yanli; Lin, Bingqian; Liu, Rudi; Song, Yanling; Lin, Hui; Tu, Song; Yang, Chaoyong

2016-08-02

Due to its large enhancement effect, nanostructure-based surface-enhanced Raman scattering (SERS) technology had been widely applied for bioanalysis and cell imaging. However, most SERS nanostructures suffer from poor signal reproducibility, which hinders the application of SERS nanostructures in quantitative detection. We report an etching-assisted approach to synthesize SERS-active plasmonic nanoparticles with 1 nm interior nanogap for multiplex quantitative detection and cancer cell imaging. Raman dyes and methoxy poly(ethylene glycol) thiol (mPEG-SH) were attached to gold nanoparticles (AuNPs) to prepare gold cores. Next, Ag atoms were deposited on gold cores in the presence of Pluronic F127 to form a Ag shell. HAuCl4 was used to etch the Ag shell and form an interior nanogap in Au@AgAuNPs, leading to increased Raman intensity of dyes. SERS intensity distribution of Au@AgAuNPs was found to be more uniform than that of aggregated AuNPs. Finally, Au@AgAuNPs were used for multiplex quantitative detection and cancer cell imaging. With the advantages of simple and rapid preparation of Au@AgAuNPs with highly uniform, stable, and reproducible Raman intensity, the method reported here will widen the applications of SERS-active nanoparticles in diagnostics and imaging.

Automated measurement of stent strut coverage in intravascular optical coherence tomography

NASA Astrophysics Data System (ADS)

Ahn, Chi Young; Kim, Byeong-Keuk; Hong, Myeong-Ki; Jang, Yangsoo; Heo, Jung; Joo, Chulmin; Seo, Jin Keun

2015-02-01

Optical coherence tomography (OCT) is a non-invasive, cross-sectional imaging modality that has become a prominent imaging method in percutaneous intracoronary intervention. We present an automated detection algorithm for stent strut coordinates and coverage in OCT images. The algorithm for stent strut detection is composed of a coordinate transformation from the polar to the Cartesian domains and application of second derivative operators in the radial and the circumferential directions. Local region-based active contouring was employed to detect lumen boundaries. We applied the method to the OCT pullback images acquired from human patients in vivo to quantitatively measure stent strut coverage. The validation studies against manual expert assessments demonstrated high Pearson's coefficients ( R = 0.99) in terms of the stent strut coordinates, with no significant bias. An averaged Hausdorff distance of < 120 μm was obtained for vessel border detection. Quantitative comparison in stent strut to vessel wall distance found a bias of < 12.3 μm and a 95% confidence of < 110 μm.

A novel 3D imaging system for strawberry phenotyping.

PubMed

He, Joe Q; Harrison, Richard J; Li, Bo

2017-01-01

Accurate and quantitative phenotypic data in plant breeding programmes is vital in breeding to assess the performance of genotypes and to make selections. Traditional strawberry phenotyping relies on the human eye to assess most external fruit quality attributes, which is time-consuming and subjective. 3D imaging is a promising high-throughput technique that allows multiple external fruit quality attributes to be measured simultaneously. A low cost multi-view stereo (MVS) imaging system was developed, which captured data from 360° around a target strawberry fruit. A 3D point cloud of the sample was derived and analysed with custom-developed software to estimate berry height, length, width, volume, calyx size, colour and achene number. Analysis of these traits in 100 fruits showed good concordance with manual assessment methods. This study demonstrates the feasibility of an MVS based 3D imaging system for the rapid and quantitative phenotyping of seven agronomically important external strawberry traits. With further improvement, this method could be applied in strawberry breeding programmes as a cost effective phenotyping technique.

Super-resolved linear fluorescence localization microscopy using photostable fluorophores: A virtual microscopy study

NASA Astrophysics Data System (ADS)

Birk, Udo; Szczurek, Aleksander; Cremer, Christoph

2017-12-01

Current approaches to overcome the conventional limit of the resolution potential of light microscopy (of about 200 nm for visible light), often suffer from non-linear effects, which render the quantification of the image intensities in the reconstructions difficult, and also affect the quantification of the biological structure under investigation. As an attempt to face these difficulties, we discuss a particular method of localization microscopy which is based on photostable fluorescent dyes. The proposed method can potentially be implemented as a fast alternative for quantitative localization microscopy, circumventing the need for the acquisition of thousands of image frames and complex, highly dye-specific imaging buffers. Although the need for calibration remains in order to extract quantitative data (such as the number of emitters), multispectral approaches are largely facilitated due to the much less stringent requirements on imaging buffers. Furthermore, multispectral acquisitions can be readily obtained using commercial instrumentation such as e.g. the conventional confocal laser scanning microscope.

Quantitative 3D imaging of yeast by hard X-ray tomography.

PubMed

Zheng, Ting; Li, Wenjie; Guan, Yong; Song, Xiangxia; Xiong, Ying; Liu, Gang; Tian, Yangchao

2012-05-01

Full-field hard X-ray tomography could be used to obtain three-dimensional (3D) nanoscale structures of biological samples. The image of the fission yeast, Schizosaccharomyces pombe, was clearly visualized based on Zernike phase contrast imaging technique and heavy metal staining method at a spatial resolution better than 50 nm at the energy of 8 keV. The distributions and shapes of the organelles during the cell cycle were clearly visualized and two types of organelle were distinguished. The results for cells during various phases were compared and the ratios of organelle volume to cell volume can be analyzed quantitatively. It showed that the ratios remained constant between growth and division phase and increased strongly in stationary phase, following the shape and size of two types of organelles changes. Our results demonstrated that hard X-ray microscopy was a complementary method for imaging and revealing structural information for biological samples. Copyright © 2011 Wiley Periodicals, Inc.

Introduction to Modern Methods in Light Microscopy.

PubMed

Ryan, Joel; Gerhold, Abby R; Boudreau, Vincent; Smith, Lydia; Maddox, Paul S

2017-01-01

For centuries, light microscopy has been a key method in biological research, from the early work of Robert Hooke describing biological organisms as cells, to the latest in live-cell and single-molecule systems. Here, we introduce some of the key concepts related to the development and implementation of modern microscopy techniques. We briefly discuss the basics of optics in the microscope, super-resolution imaging, quantitative image analysis, live-cell imaging, and provide an outlook on active research areas pertaining to light microscopy.

Can use of adaptive statistical iterative reconstruction reduce radiation dose in unenhanced head CT? An analysis of qualitative and quantitative image quality

PubMed Central

Heggen, Kristin Livelten; Pedersen, Hans Kristian; Andersen, Hilde Kjernlie; Martinsen, Anne Catrine T

2016-01-01

Background Iterative reconstruction can reduce image noise and thereby facilitate dose reduction. Purpose To evaluate qualitative and quantitative image quality for full dose and dose reduced head computed tomography (CT) protocols reconstructed using filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASIR). Material and Methods Fourteen patients undergoing follow-up head CT were included. All patients underwent full dose (FD) exam and subsequent 15% dose reduced (DR) exam, reconstructed using FBP and 30% ASIR. Qualitative image quality was assessed using visual grading characteristics. Quantitative image quality was assessed using ROI measurements in cerebrospinal fluid (CSF), white matter, peripheral and central gray matter. Additionally, quantitative image quality was measured in Catphan and vendor’s water phantom. Results There was no significant difference in qualitative image quality between FD FBP and DR ASIR. Comparing same scan FBP versus ASIR, a noise reduction of 28.6% in CSF and between −3.7 and 3.5% in brain parenchyma was observed. Comparing FD FBP versus DR ASIR, a noise reduction of 25.7% in CSF, and −7.5 and 6.3% in brain parenchyma was observed. Image contrast increased in ASIR reconstructions. Contrast-to-noise ratio was improved in DR ASIR compared to FD FBP. In phantoms, noise reduction was in the range of 3 to 28% with image content. Conclusion There was no significant difference in qualitative image quality between full dose FBP and dose reduced ASIR. CNR improved in DR ASIR compared to FD FBP mostly due to increased contrast, not reduced noise. Therefore, we recommend using caution if reducing dose and applying ASIR to maintain image quality. PMID:27583169

Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review.

PubMed

Pascual-Marqui, R D; Esslen, M; Kochi, K; Lehmann, D

2002-01-01

This paper reviews several recent publications that have successfully used the functional brain imaging method known as LORETA. Emphasis is placed on the electrophysiological and neuroanatomical basis of the method, on the localization properties of the method, and on the validation of the method in real experimental human data. Papers that criticize LORETA are briefly discussed. LORETA publications in the 1994-1997 period based localization inference on images of raw electric neuronal activity. In 1998, a series of papers appeared that based localization inference on the statistical parametric mapping methodology applied to high-time resolution LORETA images. Starting in 1999, quantitative neuroanatomy was added to the methodology, based on the digitized Talairach atlas provided by the Brain Imaging Centre, Montreal Neurological Institute. The combination of these methodological developments has placed LORETA at a level that compares favorably to the more classical functional imaging methods, such as PET and fMRI.

Simulation of realistic abnormal SPECT brain perfusion images: application in semi-quantitative analysis

NASA Astrophysics Data System (ADS)

Ward, T.; Fleming, J. S.; Hoffmann, S. M. A.; Kemp, P. M.

2005-11-01

Simulation is useful in the validation of functional image analysis methods, particularly when considering the number of analysis techniques currently available lacking thorough validation. Problems exist with current simulation methods due to long run times or unrealistic results making it problematic to generate complete datasets. A method is presented for simulating known abnormalities within normal brain SPECT images using a measured point spread function (PSF), and incorporating a stereotactic atlas of the brain for anatomical positioning. This allows for the simulation of realistic images through the use of prior information regarding disease progression. SPECT images of cerebral perfusion have been generated consisting of a control database and a group of simulated abnormal subjects that are to be used in a UK audit of analysis methods. The abnormality is defined in the stereotactic space, then transformed to the individual subject space, convolved with a measured PSF and removed from the normal subject image. The dataset was analysed using SPM99 (Wellcome Department of Imaging Neuroscience, University College, London) and the MarsBaR volume of interest (VOI) analysis toolbox. The results were evaluated by comparison with the known ground truth. The analysis showed improvement when using a smoothing kernel equal to system resolution over the slightly larger kernel used routinely. Significant correlation was found between effective volume of a simulated abnormality and the detected size using SPM99. Improvements in VOI analysis sensitivity were found when using the region median over the region mean. The method and dataset provide an efficient methodology for use in the comparison and cross validation of semi-quantitative analysis methods in brain SPECT, and allow the optimization of analysis parameters.

Confidence estimation for quantitative photoacoustic imaging

NASA Astrophysics Data System (ADS)

Gröhl, Janek; Kirchner, Thomas; Maier-Hein, Lena

2018-02-01

Quantification of photoacoustic (PA) images is one of the major challenges currently being addressed in PA research. Tissue properties can be quantified by correcting the recorded PA signal with an estimation of the corresponding fluence. Fluence estimation itself, however, is an ill-posed inverse problem which usually needs simplifying assumptions to be solved with state-of-the-art methods. These simplifications, as well as noise and artifacts in PA images reduce the accuracy of quantitative PA imaging (PAI). This reduction in accuracy is often localized to image regions where the assumptions do not hold true. This impedes the reconstruction of functional parameters when averaging over entire regions of interest (ROI). Averaging over a subset of voxels with a high accuracy would lead to an improved estimation of such parameters. To achieve this, we propose a novel approach to the local estimation of confidence in quantitative reconstructions of PA images. It makes use of conditional probability densities to estimate confidence intervals alongside the actual quantification. It encapsulates an estimation of the errors introduced by fluence estimation as well as signal noise. We validate the approach using Monte Carlo generated data in combination with a recently introduced machine learning-based approach to quantitative PAI. Our experiments show at least a two-fold improvement in quantification accuracy when evaluating on voxels with high confidence instead of thresholding signal intensity.

Hybrid quantitative MRI using chemical shift displacement and recovery-based simultaneous water and lipid imaging: A preliminary study.

PubMed

Ohno, Naoki; Miyati, Tosiaki; Suzuki, Shuto; Kan, Hirohito; Aoki, Toshitaka; Nakamura, Yoshitaka; Hiramatsu, Yuki; Kobayashi, Satoshi; Gabata, Toshifumi

2018-07-01

To suppress olefinic signals and enable simultaneous and quantitative estimation of multiple functional parameters associated with water and lipid, we investigated a modified method using chemical shift displacement and recovery-based separation of lipid tissue (SPLIT) involving acquisitions with different inversion times (TIs), echo times (TEs), and b-values. Single-shot diffusion echo-planar imaging (SSD-EPI) with multiple b-values (0-3000 s/mm 2 ) was performed without fat suppression to separate water and lipid images using the chemical shift displacement of lipid signals in the phase-encoding direction. An inversion pulse (TI = 292 ms) was applied to SSD-EPI to remove olefinic signals. Consecutively, SSD-EPI (b = 0 s/mm 2 ) was performed with TI = 0 ms and TE = 31.8 ms for T 1 and T 2 measurements, respectively. Under these conditions, transverse water and lipid images at the maximum diameter of the right calf were obtained in six healthy subjects. T 1 , T 2 , and the apparent diffusion coefficients (ADC) were then calculated for the tibialis anterior (TA), gastrocnemius (GM), and soleus (SL) muscles, tibialis bone marrow (TB), and subcutaneous fat (SF). Perfusion-related (D*) and restricted diffusion coefficients (D) were calculated for the muscles. Lastly, the lipid fractions (LF) of the muscles were determined after T 1 and T 2 corrections. The modified SPLIT method facilitated sufficient separation of water and lipid images of the calf, and the inversion pulse with TI of 292 ms effectively suppressed olefinic signals. All quantitative parameters obtained with the modified SPLIT method were found to be in general agreement with those previously reported in the literature. The modified SPLIT technique enabled sufficient suppression of olefinic signals and simultaneous acquisition of quantitative parameters including diffusion, perfusion, T 1 and T 2 relaxation times, and LF. Copyright © 2018. Published by Elsevier Inc.

Analytical validation of quantitative immunohistochemical assays of tumor infiltrating lymphocyte biomarkers.

PubMed

Singh, U; Cui, Y; Dimaano, N; Mehta, S; Pruitt, S K; Yearley, J; Laterza, O F; Juco, J W; Dogdas, B

2018-06-04

Tumor infiltrating lymphocytes (TIL), especially T-cells, have both prognostic and therapeutic applications. The presence of CD8+ effector T-cells and the ratio of CD8+ cells to FOXP3+ regulatory T-cells have been used as biomarkers of disease prognosis to predict response to various immunotherapies. Blocking the interaction between inhibitory receptors on T-cells and their ligands with therapeutic antibodies including atezolizumab, nivolumab, pembrolizumab and tremelimumab increases the immune response against cancer cells and has shown significant improvement in clinical benefits and survival in several different tumor types. The improved clinical outcome is presumed to be associated with a higher tumor infiltration; therefore, it is thought that more accurate methods for measuring the amount of TIL could assist prognosis and predict treatment response. We have developed and validated quantitative immunohistochemistry (IHC) assays for CD3, CD8 and FOXP3 for immunophenotyping T-lymphocytes in tumor tissue. Various types of formalin fixed, paraffin embedded (FFPE) tumor tissues were immunolabeled with anti-CD3, anti-CD8 and anti-FOXP3 antibodies using an IHC autostainer. The tumor area of stained tissues, including the invasive margin of the tumor, was scored by a pathologist (visual scoring) and by computer-based quantitative image analysis. Two image analysis scores were obtained for the staining of each biomarker: the percent positive cells in the tumor area and positive cells/mm 2 tumor area. Comparison of visual vs. image analysis scoring methods using regression analysis showed high correlation and indicated that quantitative image analysis can be used to score the number of positive cells in IHC stained slides. To demonstrate that the IHC assays produce consistent results in normal daily testing, we evaluated the specificity, sensitivity and reproducibility of the IHC assays using both visual and image analysis scoring methods. We found that CD3, CD8 and FOXP3 IHC assays met the fit-for-purpose analytical acceptance validation criteria and that they can be used to support clinical studies.

Quantitative Comparison of Minimum Inductance and Minimum Power Algorithms for the Design of Shim Coils for Small Animal Imaging

PubMed Central

HUDSON, PARISA; HUDSON, STEPHEN D.; HANDLER, WILLIAM B.; SCHOLL, TIMOTHY J.; CHRONIK, BLAINE A.

2010-01-01

High-performance shim coils are required for high-field magnetic resonance imaging and spectroscopy. Complete sets of high-power and high-performance shim coils were designed using two different methods: the minimum inductance and the minimum power target field methods. A quantitative comparison of shim performance in terms of merit of inductance (ML) and merit of resistance (MR) was made for shim coils designed using the minimum inductance and the minimum power design algorithms. In each design case, the difference in ML and the difference in MR given by the two design methods was <15%. Comparison of wire patterns obtained using the two design algorithms show that minimum inductance designs tend to feature oscillations within the current density; while minimum power designs tend to feature less rapidly varying current densities and lower power dissipation. Overall, the differences in coil performance obtained by the two methods are relatively small. For the specific case of shim systems customized for small animal imaging, the reduced power dissipation obtained when using the minimum power method is judged to be more significant than the improvements in switching speed obtained from the minimum inductance method. PMID:20411157

Improving the Performance of the Prony Method Using a Wavelet Domain Filter for MRI Denoising

PubMed Central

Lentini, Marianela; Paluszny, Marco

2014-01-01

The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T 2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek's algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T 2 MR images, and the filter is applied to each image before using the variant of the Prony method. PMID:24834108

Improving the performance of the prony method using a wavelet domain filter for MRI denoising.

PubMed

Jaramillo, Rodney; Lentini, Marianela; Paluszny, Marco

2014-01-01

The Prony methods are used for exponential fitting. We use a variant of the Prony method for abnormal brain tissue detection in sequences of T 2 weighted magnetic resonance images. Here, MR images are considered to be affected only by Rician noise, and a new wavelet domain bilateral filtering process is implemented to reduce the noise in the images. This filter is a modification of Kazubek's algorithm and we use synthetic images to show the ability of the new procedure to suppress noise and compare its performance with respect to the original filter, using quantitative and qualitative criteria. The tissue classification process is illustrated using a real sequence of T 2 MR images, and the filter is applied to each image before using the variant of the Prony method.

Y-90 SPECT ML image reconstruction with a new model for tissue-dependent bremsstrahlung production using CT information: a proof-of-concept study

NASA Astrophysics Data System (ADS)

Lim, Hongki; Fessler, Jeffrey A.; Wilderman, Scott J.; Brooks, Allen F.; Dewaraja, Yuni K.

2018-06-01

While the yield of positrons used in Y-90 PET is independent of tissue media, Y-90 SPECT imaging is complicated by the tissue dependence of bremsstrahlung photon generation. The probability of bremsstrahlung production is proportional to the square of the atomic number of the medium. Hence, the same amount of activity in different tissue regions of the body will produce different numbers of bremsstrahlung photons. Existing reconstruction methods disregard this tissue-dependency, potentially impacting both qualitative and quantitative imaging of heterogeneous regions of the body such as bone with marrow cavities. In this proof-of-concept study, we propose a new maximum-likelihood method that incorporates bremsstrahlung generation probabilities into the system matrix, enabling images of the desired Y-90 distribution to be reconstructed instead of the ‘bremsstrahlung distribution’ that is obtained with existing methods. The tissue-dependent probabilities are generated by Monte Carlo simulation while bone volume fractions for each SPECT voxel are obtained from co-registered CT. First, we demonstrate the tissue dependency in a SPECT/CT imaging experiment with Y-90 in bone equivalent solution and water. Visually, the proposed reconstruction approach better matched the true image and the Y-90 PET image than the standard bremsstrahlung reconstruction approach. An XCAT phantom simulation including bone and marrow regions also demonstrated better agreement with the true image using the proposed reconstruction method. Quantitatively, compared with the standard reconstruction, the new method improved estimation of the liquid bone:water activity concentration ratio by 40% in the SPECT measurement and the cortical bone:marrow activity concentration ratio by 58% in the XCAT simulation.

Anatomical-based partial volume correction for low-dose dedicated cardiac SPECT/CT

NASA Astrophysics Data System (ADS)

Liu, Hui; Chan, Chung; Grobshtein, Yariv; Ma, Tianyu; Liu, Yaqiang; Wang, Shi; Stacy, Mitchel R.; Sinusas, Albert J.; Liu, Chi

2015-09-01

Due to the limited spatial resolution, partial volume effect has been a major degrading factor on quantitative accuracy in emission tomography systems. This study aims to investigate the performance of several anatomical-based partial volume correction (PVC) methods for a dedicated cardiac SPECT/CT system (GE Discovery NM/CT 570c) with focused field-of-view over a clinically relevant range of high and low count levels for two different radiotracer distributions. These PVC methods include perturbation geometry transfer matrix (pGTM), pGTM followed by multi-target correction (MTC), pGTM with known concentration in blood pool, the former followed by MTC and our newly proposed methods, which perform the MTC method iteratively, where the mean values in all regions are estimated and updated by the MTC-corrected images each time in the iterative process. The NCAT phantom was simulated for cardiovascular imaging with 99mTc-tetrofosmin, a myocardial perfusion agent, and 99mTc-red blood cell (RBC), a pure intravascular imaging agent. Images were acquired at six different count levels to investigate the performance of PVC methods in both high and low count levels for low-dose applications. We performed two large animal in vivo cardiac imaging experiments following injection of 99mTc-RBC for evaluation of intramyocardial blood volume (IMBV). The simulation results showed our proposed iterative methods provide superior performance than other existing PVC methods in terms of image quality, quantitative accuracy, and reproducibility (standard deviation), particularly for low-count data. The iterative approaches are robust for both 99mTc-tetrofosmin perfusion imaging and 99mTc-RBC imaging of IMBV and blood pool activity even at low count levels. The animal study results indicated the effectiveness of PVC to correct the overestimation of IMBV due to blood pool contamination. In conclusion, the iterative PVC methods can achieve more accurate quantification, particularly for low count cardiac SPECT studies, typically obtained from low-dose protocols, gated studies, and dynamic applications.

Automated image analysis for quantitative fluorescence in situ hybridization with environmental samples.

PubMed

Zhou, Zhi; Pons, Marie Noëlle; Raskin, Lutgarde; Zilles, Julie L

2007-05-01

When fluorescence in situ hybridization (FISH) analyses are performed with complex environmental samples, difficulties related to the presence of microbial cell aggregates and nonuniform background fluorescence are often encountered. The objective of this study was to develop a robust and automated quantitative FISH method for complex environmental samples, such as manure and soil. The method and duration of sample dispersion were optimized to reduce the interference of cell aggregates. An automated image analysis program that detects cells from 4',6'-diamidino-2-phenylindole (DAPI) micrographs and extracts the maximum and mean fluorescence intensities for each cell from corresponding FISH images was developed with the software Visilog. Intensity thresholds were not consistent even for duplicate analyses, so alternative ways of classifying signals were investigated. In the resulting method, the intensity data were divided into clusters using fuzzy c-means clustering, and the resulting clusters were classified as target (positive) or nontarget (negative). A manual quality control confirmed this classification. With this method, 50.4, 72.1, and 64.9% of the cells in two swine manure samples and one soil sample, respectively, were positive as determined with a 16S rRNA-targeted bacterial probe (S-D-Bact-0338-a-A-18). Manual counting resulted in corresponding values of 52.3, 70.6, and 61.5%, respectively. In two swine manure samples and one soil sample 21.6, 12.3, and 2.5% of the cells were positive with an archaeal probe (S-D-Arch-0915-a-A-20), respectively. Manual counting resulted in corresponding values of 22.4, 14.0, and 2.9%, respectively. This automated method should facilitate quantitative analysis of FISH images for a variety of complex environmental samples.

Hybrid model based unified scheme for endoscopic Cerenkov and radio-luminescence tomography: Simulation demonstration

NASA Astrophysics Data System (ADS)

Wang, Lin; Cao, Xin; Ren, Qingyun; Chen, Xueli; He, Xiaowei

2018-05-01

Cerenkov luminescence imaging (CLI) is an imaging method that uses an optical imaging scheme to probe a radioactive tracer. Application of CLI with clinically approved radioactive tracers has opened an opportunity for translating optical imaging from preclinical to clinical applications. Such translation was further improved by developing an endoscopic CLI system. However, two-dimensional endoscopic imaging cannot identify accurate depth and obtain quantitative information. Here, we present an imaging scheme to retrieve the depth and quantitative information from endoscopic Cerenkov luminescence tomography, which can also be applied for endoscopic radio-luminescence tomography. In the scheme, we first constructed a physical model for image collection, and then a mathematical model for characterizing the luminescent light propagation from tracer to the endoscopic detector. The mathematical model is a hybrid light transport model combined with the 3rd order simplified spherical harmonics approximation, diffusion, and radiosity equations to warrant accuracy and speed. The mathematical model integrates finite element discretization, regularization, and primal-dual interior-point optimization to retrieve the depth and the quantitative information of the tracer. A heterogeneous-geometry-based numerical simulation was used to explore the feasibility of the unified scheme, which demonstrated that it can provide a satisfactory balance between imaging accuracy and computational burden.

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

PubMed Central

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

2014-01-01

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

Single underwater image enhancement based on color cast removal and visibility restoration

NASA Astrophysics Data System (ADS)

Li, Chongyi; Guo, Jichang; Wang, Bo; Cong, Runmin; Zhang, Yan; Wang, Jian

2016-05-01

Images taken under underwater condition usually have color cast and serious loss of contrast and visibility. Degraded underwater images are inconvenient for observation and analysis. In order to address these problems, an underwater image-enhancement method is proposed. A simple yet effective underwater image color cast removal algorithm is first presented based on the optimization theory. Then, based on the minimum information loss principle and inherent relationship of medium transmission maps of three color channels in an underwater image, an effective visibility restoration algorithm is proposed to recover visibility, contrast, and natural appearance of degraded underwater images. To evaluate the performance of the proposed method, qualitative comparison, quantitative comparison, and color accuracy test are conducted. Experimental results demonstrate that the proposed method can effectively remove color cast, improve contrast and visibility, and recover natural appearance of degraded underwater images. Additionally, the proposed method is comparable to and even better than several state-of-the-art methods.

Basic investigation on acoustic velocity change imaging method for quantitative assessment of fat content in human liver

NASA Astrophysics Data System (ADS)

Mano, Kazune; Tanigawa, Shohei; Hori, Makoto; Yokota, Daiki; Wada, Kenji; Matsunaka, Toshiyuki; Morikawa, Hiroyasu; Horinaka, Hiromichi

2016-07-01

Fatty liver is a disease caused by the excess accumulation of fat in the human liver. The early diagnosis of fatty liver is very important, because fatty liver is the major marker linked to metabolic syndrome. We already proposed the ultrasonic velocity change imaging method to diagnose fatty liver by using the fact that the temperature dependence of ultrasonic velocity is different in water and in fat. For the diagonosis of a fatty liver stage, we attempted a feasibility study of the quantitative assessment of the fat content in the human liver using our ultrasonic velocity change imaging method. Experimental results showed that the fat content in the tissue mimic phantom containing lard was determined by its ultrasonic velocity change in the flat temperature region formed by a circular warming ultrasonic transducer with an acoustic lens having an appropriate focal length. By considering the results of our simulation using a thermal diffusion equation, we determined whether this method could be applied to fatty liver assessment under the condition that the tissue had the thermal relaxation effect caused by blood flow.

A gradient method for the quantitative analysis of cell movement and tissue flow and its application to the analysis of multicellular Dictyostelium development.

PubMed

Siegert, F; Weijer, C J; Nomura, A; Miike, H

1994-01-01

We describe the application of a novel image processing method, which allows quantitative analysis of cell and tissue movement in a series of digitized video images. The result is a vector velocity field showing average direction and velocity of movement for every pixel in the frame. We apply this method to the analysis of cell movement during different stages of the Dictyostelium developmental cycle. We analysed time-lapse video recordings of cell movement in single cells, mounds and slugs. The program can correctly assess the speed and direction of movement of either unlabelled or labelled cells in a time series of video images depending on the illumination conditions. Our analysis of cell movement during multicellular development shows that the entire morphogenesis of Dictyostelium is characterized by rotational cell movement. The analysis of cell and tissue movement by the velocity field method should be applicable to the analysis of morphogenetic processes in other systems such as gastrulation and neurulation in vertebrate embryos.

Patient-dependent count-rate adaptive normalization for PET detector efficiency with delayed-window coincidence events

NASA Astrophysics Data System (ADS)

Niu, Xiaofeng; Ye, Hongwei; Xia, Ting; Asma, Evren; Winkler, Mark; Gagnon, Daniel; Wang, Wenli

2015-07-01

Quantitative PET imaging is widely used in clinical diagnosis in oncology and neuroimaging. Accurate normalization correction for the efficiency of each line-of- response is essential for accurate quantitative PET image reconstruction. In this paper, we propose a normalization calibration method by using the delayed-window coincidence events from the scanning phantom or patient. The proposed method could dramatically reduce the ‘ring’ artifacts caused by mismatched system count-rates between the calibration and phantom/patient datasets. Moreover, a modified algorithm for mean detector efficiency estimation is proposed, which could generate crystal efficiency maps with more uniform variance. Both phantom and real patient datasets are used for evaluation. The results show that the proposed method could lead to better uniformity in reconstructed images by removing ring artifacts, and more uniform axial variance profiles, especially around the axial edge slices of the scanner. The proposed method also has the potential benefit to simplify the normalization calibration procedure, since the calibration can be performed using the on-the-fly acquired delayed-window dataset.

Multimodal imaging of cutaneous wound tissue

NASA Astrophysics Data System (ADS)

Zhang, Shiwu; Gnyawali, Surya; Huang, Jiwei; Ren, Wenqi; Gordillo, Gayle; Sen, Chandan K.; Xu, Ronald

2015-01-01

Quantitative assessment of wound tissue ischemia, perfusion, and inflammation provides critical information for appropriate detection, staging, and treatment of chronic wounds. However, few methods are available for simultaneous assessment of these tissue parameters in a noninvasive and quantitative fashion. We integrated hyperspectral, laser speckle, and thermographic imaging modalities in a single-experimental setup for multimodal assessment of tissue oxygenation, perfusion, and inflammation characteristics. Algorithms were developed for appropriate coregistration between wound images acquired by different imaging modalities at different times. The multimodal wound imaging system was validated in an occlusion experiment, where oxygenation and perfusion maps of a healthy subject's upper extremity were continuously monitored during a postocclusive reactive hyperemia procedure and compared with standard measurements. The system was also tested in a clinical trial where a wound of three millimeters in diameter was introduced on a healthy subject's lower extremity and the healing process was continuously monitored. Our in vivo experiments demonstrated the clinical feasibility of multimodal cutaneous wound imaging.

Breast cancer diagnosis using spatial light interference microscopy

NASA Astrophysics Data System (ADS)

Majeed, Hassaan; Kandel, Mikhail E.; Han, Kevin; Luo, Zelun; Macias, Virgilia; Tangella, Krishnarao; Balla, Andre; Popescu, Gabriel

2015-11-01

The standard practice in histopathology of breast cancers is to examine a hematoxylin and eosin (H&E) stained tissue biopsy under a microscope to diagnose whether a lesion is benign or malignant. This determination is made based on a manual, qualitative inspection, making it subject to investigator bias and resulting in low throughput. Hence, a quantitative, label-free, and high-throughput diagnosis method is highly desirable. We present here preliminary results showing the potential of quantitative phase imaging for breast cancer screening and help with differential diagnosis. We generated phase maps of unstained breast tissue biopsies using spatial light interference microscopy (SLIM). As a first step toward quantitative diagnosis based on SLIM, we carried out a qualitative evaluation of our label-free images. These images were shown to two pathologists who classified each case as either benign or malignant. This diagnosis was then compared against the diagnosis of the two pathologists on corresponding H&E stained tissue images and the number of agreements were counted. The agreement between SLIM and H&E based diagnosis was 88% for the first pathologist and 87% for the second. Our results demonstrate the potential and promise of SLIM for quantitative, label-free, and high-throughput diagnosis.

High PRF ultrafast sliding compound doppler imaging: fully qualitative and quantitative analysis of blood flow

NASA Astrophysics Data System (ADS)

Kang, Jinbum; Jang, Won Seuk; Yoo, Yangmo

2018-02-01

Ultrafast compound Doppler imaging based on plane-wave excitation (UCDI) can be used to evaluate cardiovascular diseases using high frame rates. In particular, it provides a fully quantifiable flow analysis over a large region of interest with high spatio-temporal resolution. However, the pulse-repetition frequency (PRF) in the UCDI method is limited for high-velocity flow imaging since it has a tradeoff between the number of plane-wave angles (N) and acquisition time. In this paper, we present high PRF ultrafast sliding compound Doppler imaging method (HUSDI) to improve quantitative flow analysis. With the HUSDI method, full scanline images (i.e. each tilted plane wave data) in a Doppler frame buffer are consecutively summed using a sliding window to create high-quality ensemble data so that there is no reduction in frame rate and flow sensitivity. In addition, by updating a new compounding set with a certain time difference (i.e. sliding window step size or L), the HUSDI method allows various Doppler PRFs with the same acquisition data to enable a fully qualitative, retrospective flow assessment. To evaluate the performance of the proposed HUSDI method, simulation, in vitro and in vivo studies were conducted under diverse flow circumstances. In the simulation and in vitro studies, the HUSDI method showed improved hemodynamic representations without reducing either temporal resolution or sensitivity compared to the UCDI method. For the quantitative analysis, the root mean squared velocity error (RMSVE) was measured using 9 angles (-12° to 12°) with L of 1-9, and the results were found to be comparable to those of the UCDI method (L  =  N  =  9), i.e.  ⩽0.24 cm s-1, for all L values. For the in vivo study, the flow data acquired from a full cardiac cycle of the femoral vessels of a healthy volunteer were analyzed using a PW spectrogram, and arterial and venous flows were successfully assessed with high Doppler PRF (e.g. 5 kHz at L  =  4). These results indicate that the proposed HUSDI method can improve flow visualization and quantification with a higher frame rate, PRF and flow sensitivity in cardiovascular imaging.

High PRF ultrafast sliding compound doppler imaging: fully qualitative and quantitative analysis of blood flow.

PubMed

Kang, Jinbum; Jang, Won Seuk; Yoo, Yangmo

2018-02-09

Ultrafast compound Doppler imaging based on plane-wave excitation (UCDI) can be used to evaluate cardiovascular diseases using high frame rates. In particular, it provides a fully quantifiable flow analysis over a large region of interest with high spatio-temporal resolution. However, the pulse-repetition frequency (PRF) in the UCDI method is limited for high-velocity flow imaging since it has a tradeoff between the number of plane-wave angles (N) and acquisition time. In this paper, we present high PRF ultrafast sliding compound Doppler imaging method (HUSDI) to improve quantitative flow analysis. With the HUSDI method, full scanline images (i.e. each tilted plane wave data) in a Doppler frame buffer are consecutively summed using a sliding window to create high-quality ensemble data so that there is no reduction in frame rate and flow sensitivity. In addition, by updating a new compounding set with a certain time difference (i.e. sliding window step size or L), the HUSDI method allows various Doppler PRFs with the same acquisition data to enable a fully qualitative, retrospective flow assessment. To evaluate the performance of the proposed HUSDI method, simulation, in vitro and in vivo studies were conducted under diverse flow circumstances. In the simulation and in vitro studies, the HUSDI method showed improved hemodynamic representations without reducing either temporal resolution or sensitivity compared to the UCDI method. For the quantitative analysis, the root mean squared velocity error (RMSVE) was measured using 9 angles (-12° to 12°) with L of 1-9, and the results were found to be comparable to those of the UCDI method (L  =  N  =  9), i.e.  ⩽0.24 cm s -1 , for all L values. For the in vivo study, the flow data acquired from a full cardiac cycle of the femoral vessels of a healthy volunteer were analyzed using a PW spectrogram, and arterial and venous flows were successfully assessed with high Doppler PRF (e.g. 5 kHz at L  =  4). These results indicate that the proposed HUSDI method can improve flow visualization and quantification with a higher frame rate, PRF and flow sensitivity in cardiovascular imaging.

Generalized whole-body Patlak parametric imaging for enhanced quantification in clinical PET.

PubMed

Karakatsanis, Nicolas A; Zhou, Yun; Lodge, Martin A; Casey, Michael E; Wahl, Richard L; Zaidi, Habib; Rahmim, Arman

2015-11-21

We recently developed a dynamic multi-bed PET data acquisition framework to translate the quantitative benefits of Patlak voxel-wise analysis to the domain of routine clinical whole-body (WB) imaging. The standard Patlak (sPatlak) linear graphical analysis assumes irreversible PET tracer uptake, ignoring the effect of FDG dephosphorylation, which has been suggested by a number of PET studies. In this work: (i) a non-linear generalized Patlak (gPatlak) model is utilized, including a net efflux rate constant kloss, and (ii) a hybrid (s/g)Patlak (hPatlak) imaging technique is introduced to enhance contrast to noise ratios (CNRs) of uptake rate Ki images. Representative set of kinetic parameter values and the XCAT phantom were employed to generate realistic 4D simulation PET data, and the proposed methods were additionally evaluated on 11 WB dynamic PET patient studies. Quantitative analysis on the simulated Ki images over 2 groups of regions-of-interest (ROIs), with low (ROI A) or high (ROI B) true kloss relative to Ki, suggested superior accuracy for gPatlak. Bias of sPatlak was found to be 16-18% and 20-40% poorer than gPatlak for ROIs A and B, respectively. By contrast, gPatlak exhibited, on average, 10% higher noise than sPatlak. Meanwhile, the bias and noise levels for hPatlak always ranged between the other two methods. In general, hPatlak was seen to outperform all methods in terms of target-to-background ratio (TBR) and CNR for all ROIs. Validation on patient datasets demonstrated clinical feasibility for all Patlak methods, while TBR and CNR evaluations confirmed our simulation findings, and suggested presence of non-negligible kloss reversibility in clinical data. As such, we recommend gPatlak for highly quantitative imaging tasks, while, for tasks emphasizing lesion detectability (e.g. TBR, CNR) over quantification, or for high levels of noise, hPatlak is instead preferred. Finally, gPatlak and hPatlak CNR was systematically higher compared to routine SUV values.

Generalized whole-body Patlak parametric imaging for enhanced quantification in clinical PET

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Zhou, Yun; Lodge, Martin A.; Casey, Michael E.; Wahl, Richard L.; Zaidi, Habib; Rahmim, Arman

2015-11-01

We recently developed a dynamic multi-bed PET data acquisition framework to translate the quantitative benefits of Patlak voxel-wise analysis to the domain of routine clinical whole-body (WB) imaging. The standard Patlak (sPatlak) linear graphical analysis assumes irreversible PET tracer uptake, ignoring the effect of FDG dephosphorylation, which has been suggested by a number of PET studies. In this work: (i) a non-linear generalized Patlak (gPatlak) model is utilized, including a net efflux rate constant kloss, and (ii) a hybrid (s/g)Patlak (hPatlak) imaging technique is introduced to enhance contrast to noise ratios (CNRs) of uptake rate Ki images. Representative set of kinetic parameter values and the XCAT phantom were employed to generate realistic 4D simulation PET data, and the proposed methods were additionally evaluated on 11 WB dynamic PET patient studies. Quantitative analysis on the simulated Ki images over 2 groups of regions-of-interest (ROIs), with low (ROI A) or high (ROI B) true kloss relative to Ki, suggested superior accuracy for gPatlak. Bias of sPatlak was found to be 16-18% and 20-40% poorer than gPatlak for ROIs A and B, respectively. By contrast, gPatlak exhibited, on average, 10% higher noise than sPatlak. Meanwhile, the bias and noise levels for hPatlak always ranged between the other two methods. In general, hPatlak was seen to outperform all methods in terms of target-to-background ratio (TBR) and CNR for all ROIs. Validation on patient datasets demonstrated clinical feasibility for all Patlak methods, while TBR and CNR evaluations confirmed our simulation findings, and suggested presence of non-negligible kloss reversibility in clinical data. As such, we recommend gPatlak for highly quantitative imaging tasks, while, for tasks emphasizing lesion detectability (e.g. TBR, CNR) over quantification, or for high levels of noise, hPatlak is instead preferred. Finally, gPatlak and hPatlak CNR was systematically higher compared to routine SUV values.

Evaluation of chemotherapy response in ovarian cancer treatment using quantitative CT image biomarkers: a preliminary study

NASA Astrophysics Data System (ADS)

Qiu, Yuchen; Tan, Maxine; McMeekin, Scott; Thai, Theresa; Moore, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2015-03-01

The purpose of this study is to identify and apply quantitative image biomarkers for early prediction of the tumor response to the chemotherapy among the ovarian cancer patients participated in the clinical trials of testing new drugs. In the experiment, we retrospectively selected 30 cases from the patients who participated in Phase I clinical trials of new drug or drug agents for ovarian cancer treatment. Each case is composed of two sets of CT images acquired pre- and post-treatment (4-6 weeks after starting treatment). A computer-aided detection (CAD) scheme was developed to extract and analyze the quantitative image features of the metastatic tumors previously tracked by the radiologists using the standard Response Evaluation Criteria in Solid Tumors (RECIST) guideline. The CAD scheme first segmented 3-D tumor volumes from the background using a hybrid tumor segmentation scheme. Then, for each segmented tumor, CAD computed three quantitative image features including the change of tumor volume, tumor CT number (density) and density variance. The feature changes were calculated between the matched tumors tracked on the CT images acquired pre- and post-treatments. Finally, CAD predicted patient's 6-month progression-free survival (PFS) using a decision-tree based classifier. The performance of the CAD scheme was compared with the RECIST category. The result shows that the CAD scheme achieved a prediction accuracy of 76.7% (23/30 cases) with a Kappa coefficient of 0.493, which is significantly higher than the performance of RECIST prediction with a prediction accuracy and Kappa coefficient of 60% (17/30) and 0.062, respectively. This study demonstrated the feasibility of analyzing quantitative image features to improve the early predicting accuracy of the tumor response to the new testing drugs or therapeutic methods for the ovarian cancer patients.

A brain MRI bias field correction method created in the Gaussian multi-scale space

NASA Astrophysics Data System (ADS)

Chen, Mingsheng; Qin, Mingxin

2017-07-01

A pre-processing step is needed to correct for the bias field signal before submitting corrupted MR images to such image-processing algorithms. This study presents a new bias field correction method. The method creates a Gaussian multi-scale space by the convolution of the inhomogeneous MR image with a two-dimensional Gaussian function. In the multi-Gaussian space, the method retrieves the image details from the differentiation of the original image and convolution image. Then, it obtains an image whose inhomogeneity is eliminated by the weighted sum of image details in each layer in the space. Next, the bias field-corrected MR image is retrieved after the Υ correction, which enhances the contrast and brightness of the inhomogeneity-eliminated MR image. We have tested the approach on T1 MRI and T2 MRI with varying bias field levels and have achieved satisfactory results. Comparison experiments with popular software have demonstrated superior performance of the proposed method in terms of quantitative indices, especially an improvement in subsequent image segmentation.

Carr-Purcell-Meiboom-Gill imaging of prostate cancer: quantitative T2 values for cancer discrimination.

PubMed

Roebuck, Joseph R; Haker, Steven J; Mitsouras, Dimitris; Rybicki, Frank J; Tempany, Clare M; Mulkern, Robert V

2009-05-01

Quantitative, apparent T(2) values of suspected prostate cancer and healthy peripheral zone tissue in men with prostate cancer were measured using a Carr-Purcell-Meiboom-Gill (CPMG) imaging sequence in order to assess the cancer discrimination potential of tissue T(2) values. The CPMG imaging sequence was used to image the prostates of 18 men with biopsy-proven prostate cancer. Whole gland coverage with nominal voxel volumes of 0.54 x 1.1 x 4 mm(3) was obtained in 10.7 min, resulting in data sets suitable for generating high-quality images with variable T(2)-weighting and for evaluating quantitative T(2) values on a pixel-by-pixel basis. Region-of-interest analysis of suspected healthy peripheral zone tissue and suspected cancer, identified on the basis of both T(1)- and T(2)-weighted signal intensities and available histopathology reports, yielded significantly (P<.0001) longer apparent T(2) values in suspected healthy tissue (193+/-49 ms) vs. suspected cancer (100+/-26 ms), suggesting potential utility of this method as a tissue specific discrimination index for prostate cancer. We conclude that CPMG imaging of the prostate can be performed in reasonable scan times and can provide advantages over T(2)-weighted fast spin echo (FSE) imaging alone, including quantitative T(2) values for cancer discrimination as well as proton density maps without the point spread function degradation associated with short effective echo time FSE sequences.

Carr-Purcell-Meiboom-Gill (CPMG) Imaging of Prostate Cancer: Quantitative T2 Values for Cancer Discrimination

PubMed Central

Roebuck, Joseph R.; Haker, Steven J.; Mitsouras, Dimitris; Rybicki, Frank J.; Tempany, Clare M.; Mulkern, Robert V.

2009-01-01

Quantitative, apparent T2 values of suspected prostate cancer and healthy peripheral zone tissue in men with prostate cancer were measured using a Carr-Purcell-Meiboom-Gill (CPMG) imaging sequence in order to assess the cancer discrimination potential of tissue T2 values. The CPMG imaging sequence was used to image the prostates of 18 men with biopsy proven prostate cancer. Whole gland coverage with nominal voxel volumes of 0.54 × 1.1 × 4 mm3 was obtained in 10.7 minutes, resulting in data sets suitable for generating high quality images with variable T2-weighting and for evaluating quantitative T2 values on a pixel-by-pixel basis. Region-of-interest analysis of suspected healthy peripheral zone tissue and suspected cancer, identified on the basis of both T1- and T2-weighted signal intensities and available histopathology reports, yielded significantly (p < 0.0001) longer apparent T2 values in suspected healthy tissue (193 ± 49 ms) vs. suspected cancer (100 ± 26 ms), suggesting potential utility of this method as a tissue specific discrimination index for prostate cancer. We conclude that CPMG imaging of the prostate can be performed in reasonable scan times and can provide advantages over T2-weighted fast spin echo imaging alone, including quantitative T2 values for cancer discrimination as well as proton density maps without the point spread function degradation associated with short effective echo time fast spin echo (FSE) sequences. PMID:18823731

A comparison of phase imaging and quantitative susceptibility mapping in the imaging of multiple sclerosis lesions at ultrahigh field.

PubMed

Cronin, Matthew John; Wharton, Samuel; Al-Radaideh, Ali; Constantinescu, Cris; Evangelou, Nikos; Bowtell, Richard; Gowland, Penny Anne

2016-06-01

The aim of this study was to compare the use of high-resolution phase and QSM images acquired at ultra-high field in the investigation of multiple sclerosis (MS) lesions with peripheral rings, and to discuss their usefulness for drawing inferences about underlying tissue composition. Thirty-nine Subjects were scanned at 7 T, using 3D T 2*-weighted and T 1-weighted sequences. Phase images were then unwrapped and filtered, and quantitative susceptibility maps were generated using a thresholded k-space division method. Lesions were compared visually and using a 1D profiling algorithm. Lesions displaying peripheral rings in the phase images were identified in 10 of the 39 subjects. Dipolar projections were apparent in the phase images outside of the extent of several of these lesions; however, QSM images showed peripheral rings without such projections. These projections appeared ring-like in a small number of phase images where no ring was observed in QSM. 1D profiles of six well-isolated example lesions showed that QSM contrast corresponds more closely to the magnitude images than phase contrast. Phase images contain dipolar projections, which confounds their use in the investigation of tissue composition in MS lesions. Quantitative susceptibility maps correct these projections, providing insight into the composition of MS lesions showing peripheral rings.

Evaluation of coronary stenosis with the aid of quantitative image analysis in histological cross sections.

PubMed

Dulohery, Kate; Papavdi, Asteria; Michalodimitrakis, Manolis; Kranioti, Elena F

2012-11-01

Coronary artery atherosclerosis is a hugely prevalent condition in the Western World and is often encountered during autopsy. Atherosclerotic plaques can cause luminal stenosis: which, if over a significant level (75%), is said to contribute to cause of death. Estimation of stenosis can be macroscopically performed by the forensic pathologists at the time of autopsy or by microscopic examination. This study compares macroscopic estimation with quantitative microscopic image analysis with a particular focus on the assessment of significant stenosis (>75%). A total of 131 individuals were analysed. The sample consists of an atherosclerotic group (n=122) and a control group (n=9). The results of the two methods were significantly different from each other (p=0.001) and the macroscopic method gave a greater percentage stenosis by an average of 3.5%. Also, histological examination of coronary artery stenosis yielded a difference in significant stenosis in 11.5% of cases. The differences were attributed to either histological quantitative image analysis underestimation; gross examination overestimation; or, a combination of both. The underestimation may have come from tissue shrinkage during tissue processing for histological specimen. The overestimation from the macroscopic assessment can be attributed to the lumen shape, to the examiner observer error or to a possible bias to diagnose coronary disease when no other cause of death is apparent. The results indicate that the macroscopic estimation is open to more biases and that histological quantitative image analysis only gives a precise assessment of stenosis ex vivo. Once tissue shrinkage, if any, is accounted for then histological quantitative image analysis will yield a more accurate assessment of in vivo stenosis. It may then be considered a complementary tool for the examination of coronary stenosis. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Intravital microscopy of biosensor activities and intrinsic metabolic states

PubMed Central

Winfree, Seth; Hato, Takashi; Day, Richard N.

2018-01-01

Intravital microscopy (IVM) is an imaging tool that is capable of detecting subcellular signaling or metabolic events as they occur in tissues in the living animal. Imaging in highly scattering biological tissues, however, is challenging because of the attenuation of signal in images acquired at increasing depths. Depth-dependent signal attenuation is the major impediment to IVM, limiting the depth from which significant data can be obtained. Therefore, making quantitative measurements by IVM requires methods that use internal calibration, or alternatively, a completely different way of evaluating the signals. Here, we describe how ratiometric imaging of genetically encoded biosensor probes can be used to make quantitative measurements of changes in the activity of cell signaling pathways. Then, we describe how fluorescence lifetime imaging can be used for label-free measurements of the metabolic states of cells within the living animal. PMID:28434902

The dynamic micro computed tomography at SSRF

NASA Astrophysics Data System (ADS)

Chen, R.; Xu, L.; Du, G.; Deng, B.; Xie, H.; Xiao, T.

2018-05-01

Synchrotron radiation micro-computed tomography (SR-μCT) is a critical technique for quantitative characterizing the 3D internal structure of samples, recently the dynamic SR-μCT has been attracting vast attention since it can evaluate the three-dimensional structure evolution of a sample. A dynamic μCT method, which is based on monochromatic beam, was developed at the X-ray Imaging and Biomedical Application Beamline at Shanghai Synchrotron Radiation Facility, by combining the compressed sensing based CT reconstruction algorithm and hardware upgrade. The monochromatic beam based method can achieve quantitative information, and lower dose than the white beam base method in which the lower energy beam is absorbed by the sample rather than contribute to the final imaging signal. The developed method is successfully used to investigate the compression of the air sac during respiration in a bell cricket, providing new knowledge for further research on the insect respiratory system.

Quantitative super-resolution localization microscopy of DNA in situ using Vybrant® DyeCycle™ Violet fluorescent probe.

PubMed

Żurek-Biesiada, Dominika; Szczurek, Aleksander T; Prakash, Kirti; Best, Gerrit; Mohana, Giriram K; Lee, Hyun-Keun; Roignant, Jean-Yves; Dobrucki, Jurek W; Cremer, Christoph; Birk, Udo

2016-06-01

Single Molecule Localization Microscopy (SMLM) is a recently emerged optical imaging method that was shown to achieve a resolution in the order of tens of nanometers in intact cells. Novel high resolution imaging methods might be crucial for understanding of how the chromatin, a complex of DNA and proteins, is arranged in the eukaryotic cell nucleus. Such an approach utilizing switching of a fluorescent, DNA-binding dye Vybrant® DyeCycle™ Violet has been previously demonstrated by us (Żurek-Biesiada et al., 2015) [1]. Here we provide quantitative information on the influence of the chemical environment on the behavior of the dye, discuss the variability in the DNA-associated signal density, and demonstrate direct proof of enhanced structural resolution. Furthermore, we compare different visualization approaches. Finally, we describe various opportunities of multicolor DNA/SMLM imaging in eukaryotic cell nuclei.

Quantitative super-resolution localization microscopy of DNA in situ using Vybrant® DyeCycle™ Violet fluorescent probe

PubMed Central

Żurek-Biesiada, Dominika; Szczurek, Aleksander T.; Prakash, Kirti; Best, Gerrit; Mohana, Giriram K.; Lee, Hyun-Keun; Roignant, Jean-Yves; Dobrucki, Jurek W.; Cremer, Christoph; Birk, Udo

2016-01-01

Single Molecule Localization Microscopy (SMLM) is a recently emerged optical imaging method that was shown to achieve a resolution in the order of tens of nanometers in intact cells. Novel high resolution imaging methods might be crucial for understanding of how the chromatin, a complex of DNA and proteins, is arranged in the eukaryotic cell nucleus. Such an approach utilizing switching of a fluorescent, DNA-binding dye Vybrant® DyeCycle™ Violet has been previously demonstrated by us (Żurek-Biesiada et al., 2015) [1]. Here we provide quantitative information on the influence of the chemical environment on the behavior of the dye, discuss the variability in the DNA-associated signal density, and demonstrate direct proof of enhanced structural resolution. Furthermore, we compare different visualization approaches. Finally, we describe various opportunities of multicolor DNA/SMLM imaging in eukaryotic cell nuclei. PMID:27054149

Quantitative fluorescence imaging of protein diffusion and interaction in living cells.

PubMed

Capoulade, Jérémie; Wachsmuth, Malte; Hufnagel, Lars; Knop, Michael

2011-08-07

Diffusion processes and local dynamic equilibria inside cells lead to nonuniform spatial distributions of molecules, which are essential for processes such as nuclear organization and signaling in cell division, differentiation and migration. To understand these mechanisms, spatially resolved quantitative measurements of protein abundance, mobilities and interactions are needed, but current methods have limited capabilities to study dynamic parameters. Here we describe a microscope based on light-sheet illumination that allows massively parallel fluorescence correlation spectroscopy (FCS) measurements and use it to visualize the diffusion and interactions of proteins in mammalian cells and in isolated fly tissue. Imaging the mobility of heterochromatin protein HP1α (ref. 4) in cell nuclei we could provide high-resolution diffusion maps that reveal euchromatin areas with heterochromatin-like HP1α-chromatin interactions. We expect that FCS imaging will become a useful method for the precise characterization of cellular reaction-diffusion processes.

Quantitative mouse brain phenotyping based on single and multispectral MR protocols

PubMed Central

Badea, Alexandra; Gewalt, Sally; Avants, Brian B.; Cook, James J.; Johnson, G. Allan

2013-01-01

Sophisticated image analysis methods have been developed for the human brain, but such tools still need to be adapted and optimized for quantitative small animal imaging. We propose a framework for quantitative anatomical phenotyping in mouse models of neurological and psychiatric conditions. The framework encompasses an atlas space, image acquisition protocols, and software tools to register images into this space. We show that a suite of segmentation tools (Avants, Epstein et al., 2008) designed for human neuroimaging can be incorporated into a pipeline for segmenting mouse brain images acquired with multispectral magnetic resonance imaging (MR) protocols. We present a flexible approach for segmenting such hyperimages, optimizing registration, and identifying optimal combinations of image channels for particular structures. Brain imaging with T1, T2* and T2 contrasts yielded accuracy in the range of 83% for hippocampus and caudate putamen (Hc and CPu), but only 54% in white matter tracts, and 44% for the ventricles. The addition of diffusion tensor parameter images improved accuracy for large gray matter structures (by >5%), white matter (10%), and ventricles (15%). The use of Markov random field segmentation further improved overall accuracy in the C57BL/6 strain by 6%; so Dice coefficients for Hc and CPu reached 93%, for white matter 79%, for ventricles 68%, and for substantia nigra 80%. We demonstrate the segmentation pipeline for the widely used C57BL/6 strain, and two test strains (BXD29, APP/TTA). This approach appears promising for characterizing temporal changes in mouse models of human neurological and psychiatric conditions, and may provide anatomical constraints for other preclinical imaging, e.g. fMRI and molecular imaging. This is the first demonstration that multiple MR imaging modalities combined with multivariate segmentation methods lead to significant improvements in anatomical segmentation in the mouse brain. PMID:22836174

Multi-spectral digital holographic microscopy for enhanced quantitative phase imaging of living cells

NASA Astrophysics Data System (ADS)

Kemper, Björn; Kastl, Lena; Schnekenburger, Jürgen; Ketelhut, Steffi

2018-02-01

Main restrictions of using laser light in digital holographic microscopy (DHM) are coherence induced noise and parasitic reflections in the experimental setup which limit resolution and measurement accuracy. We explored, if coherence properties of partial coherent light sources can be generated synthetically utilizing spectrally tunable lasers. The concept of the method is demonstrated by label-free quantitative phase imaging of living pancreatic tumor cells and utilizing an experimental configuration including a commercial microscope and a laser source with a broad tunable spectral range of more than 200 nm.

Variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction

NASA Astrophysics Data System (ADS)

Li, Shuo; Wang, Hui; Wang, Liyong; Yu, Xiangzhou; Yang, Le

2018-01-01

The uneven illumination phenomenon reduces the quality of remote sensing image and causes interference in the subsequent processing and applications. A variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction is proposed. The L1 norm and the L2 norm are adopted to constrain the textures and details of reflectance image and the smoothness of the illumination image, respectively. The problem of separating the illumination image from the reflectance image is transformed into the optimal solution of the variational model. In order to accelerate the solution, the split Bregman method is used to decompose the variational model into three subproblems, which are calculated by alternate iteration. Two groups of experiments are implemented on two synthetic images and three real remote sensing images. Compared with the variational Retinex method with single-norm constraint and the Mask method, the proposed method performs better in both visual evaluation and quantitative measurements. The proposed method can effectively eliminate the uneven illumination while maintaining the textures and details of the remote sensing image. Moreover, the proposed method using split Bregman method is more than 10 times faster than the method with the steepest descent method.

Technical Note: Rod phantom analysis for comparison of PET detector sampling and reconstruction methods.

PubMed

Wollenweber, Scott D; Kemp, Brad J

2016-11-01

This investigation aimed to develop a scanner quantification performance methodology and compare multiple metrics between two scanners under different imaging conditions. Most PET scanners are designed to work over a wide dynamic range of patient imaging conditions. Clinical constraints, however, often impact the realization of the entitlement performance for a particular scanner design. Using less injected dose and imaging for a shorter time are often key considerations, all while maintaining "acceptable" image quality and quantitative capability. A dual phantom measurement including resolution inserts was used to measure the effects of in-plane (x, y) and axial (z) system resolution between two PET/CT systems with different block detector crystal dimensions. One of the scanners had significantly thinner slices. Several quantitative measures, including feature contrast recovery, max/min value, and feature profile accuracy were derived from the resulting data and compared between the two scanners and multiple phantoms and alignments. At the clinically relevant count levels used, the scanner with thinner slices had improved performance of approximately 2%, averaged over phantom alignments, measures, and reconstruction methods, for the head-sized phantom, mainly demonstrated with the rods aligned perpendicular to the scanner axis. That same scanner had a slightly decreased performance of -1% for the larger body-size phantom, mostly due to an apparent noise increase in the images. Most of the differences in the metrics between the two scanners were less than 10%. Using the proposed scanner performance methodology, it was shown that smaller detector elements and a larger number of image voxels require higher count density in order to demonstrate improved image quality and quantitation. In a body imaging scenario under typical clinical conditions, the potential advantages of the design must overcome increases in noise due to lower count density.

Portable smartphone based quantitative phase microscope

NASA Astrophysics Data System (ADS)

Meng, Xin; Tian, Xiaolin; Yu, Wei; Kong, Yan; Jiang, Zhilong; Liu, Fei; Xue, Liang; Liu, Cheng; Wang, Shouyu

2018-01-01

To realize portable device with high contrast imaging capability, we designed a quantitative phase microscope using transport of intensity equation method based on a smartphone. The whole system employs an objective and an eyepiece as imaging system and a cost-effective LED as illumination source. A 3-D printed cradle is used to align these components. Images of different focal planes are captured by manual focusing, followed by calculation of sample phase via a self-developed Android application. To validate its accuracy, we first tested the device by measuring a random phase plate with known phases, and then red blood cell smear, Pap smear, broad bean epidermis sections and monocot root were also measured to show its performance. Owing to its advantages as accuracy, high-contrast, cost-effective and portability, the portable smartphone based quantitative phase microscope is a promising tool which can be future adopted in remote healthcare and medical diagnosis.

Localization-based super-resolution imaging meets high-content screening.

PubMed

Beghin, Anne; Kechkar, Adel; Butler, Corey; Levet, Florian; Cabillic, Marine; Rossier, Olivier; Giannone, Gregory; Galland, Rémi; Choquet, Daniel; Sibarita, Jean-Baptiste

2017-12-01

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

The Evolution of 3D Microimaging Techniques in Geosciences

NASA Astrophysics Data System (ADS)

Sahagian, D.; Proussevitch, A.

2009-05-01

In the analysis of geomaterials, it is essential to be able to analyze internal structures on a quantitative basis. Techniques have evolved from rough qualitative methods to highly accurate quantitative methods coupled with 3-D numerical analysis. The earliest primitive method for "seeing'" what was inside a rock was multiple sectioning to produce a series of image slices. This technique typically completely destroyed the sample being analyzed. Another destructive method was developed to give more detailed quantitative information by forming plastic casts of internal voids in sedimentary and volcanic rocks. For this, void were filled with plastic and the rock dissolved away with HF to reveal plastic casts of internal vesicles. Later, new approaches to stereology were developed to extract 3D information from 2D cross-sectional images. This has long been possible for spheres because the probability distribution for cutting a sphere along any small circle is known analytically (greatest probability is near the equator). However, large numbers of objects are required for statistical validity, and geomaterials are seldom spherical, so crystals, vesicles, and other inclusions would need a more sophisticated approach. Consequently, probability distributions were developed using numerical techniques for rectangular solids and various ellipsoids so that stereological techniques could be applied to these. The "holy grail" has always been to obtain 3D quantitative images non-destructively. A key method is Computed X-ray Tomography (CXT), in which attenuation of X-rays is recorded as a function of angular position in a cylindrical sample, providing a 2D "slice" of the interior. When a series of these "slices" is stacked (in increments equivalent with the resolution of the X-ray to make cubic voxels), a 3D image results with quantitative information regarding internal structure, particle/void volumes, nearest neighbors, coordination numbers, preferred orientations, etc. CXT can be done at three basic levels of resolution, with "normal" x-rays providing tens of microns resolution, synchrotron sources providing single to few microns, and emerging XuM techniques providing a practical 300 nm and theoretical 60 nm. The main challenges in CXT imaging have been in segmentation, which delineates material boundaries, and object recognition (registration), in which the individual objects within a material are identified. The former is critical in quantifying object volume, while the latter is essential for preventing the false appearance of individual objects as a continuous structure. Additional, new techniques are now being developed to enhance resolution and provide more detailed analysis without the complex infrastructure needed for CXT. One such method is Laser Scanning Confocal Microscopy, in which a laser is reflected from individual interior surfaces of a fluorescing material, providing a series of sharp images of internal slices with quantitative information available, just as in x-ray tomography, after "z-stacking" of planes of pixels. Another novel approach is the use of Stereo Scanning Electron Microscopy to create digital elevation models of 3D surficial features such as partial bubble margins on the surfaces of fine volcanic ash particles. As other novel techniques emerge, new opportunities will be presented to the geological research community to obtain ever more detailed and accurate information regarding the interior structure of geomaterials.

Standardizing Evaluation of pQCT Image Quality in the Presence of Subject Movement: Qualitative vs. Quantitative Assessment

PubMed Central

Blew, Robert M.; Lee, Vinson R.; Farr, Joshua N.; Schiferl, Daniel J.; Going, Scott B.

2013-01-01

Purpose Peripheral quantitative computed tomography (pQCT) is an essential tool for assessing bone parameters of the limbs, but subject movement and its impact on image quality remains a challenge to manage. The current approach to determine image viability is by visual inspection, but pQCT lacks a quantitative evaluation. Therefore, the aims of this study were to (1) examine the reliability of a qualitative visual inspection scale, and (2) establish a quantitative motion assessment methodology. Methods Scans were performed on 506 healthy girls (9–13yr) at diaphyseal regions of the femur and tibia. Scans were rated for movement independently by three technicians using a linear, nominal scale. Quantitatively, a ratio of movement to limb size (%Move) provided a measure of movement artifact. A repeat-scan subsample (n=46) was examined to determine %Move’s impact on bone parameters. Results Agreement between measurers was strong (ICC = .732 for tibia, .812 for femur), but greater variability was observed in scans rated 3 or 4, the delineation between repeat or no repeat. The quantitative approach found ≥95% of subjects had %Move <25%. Comparison of initial and repeat scans by groups above and below 25% initial movement, showed significant differences in the >25% grouping. Conclusions A pQCT visual inspection scale can be a reliable metric of image quality but technicians may periodically mischaracterize subject motion. The presented quantitative methodology yields more consistent movement assessment and could unify procedure across laboratories. Data suggest a delineation of 25% movement for determining whether a diaphyseal scan is viable or requires repeat. PMID:24077875

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

Quantitative digital image analysis of chromogenic assays for high throughput screening of alpha-amylase mutant libraries.

PubMed

Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy

2009-08-01

An image analysis-based method for high throughput screening of an alpha-amylase mutant library using chromogenic assays was developed. Assays were performed in microplates and high resolution images of the assay plates were read using the Virtual Microplate Reader (VMR) script to quantify the concentration of the chromogen. This method is fast and sensitive in quantifying 0.025-0.3 mg starch/ml as well as 0.05-0.75 mg glucose/ml. It was also an effective screening method for improved alpha-amylase activity with a coefficient of variance of 18%.

An approach for quantitative image quality analysis for CT

NASA Astrophysics Data System (ADS)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders

PubMed Central

Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J.

2014-01-01

Abstract. Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed. PMID:26157976

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders.

PubMed

Marquet, Pierre; Depeursinge, Christian; Magistretti, Pierre J

2014-10-01

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.

Analyser-based phase contrast image reconstruction using geometrical optics.

PubMed

Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A

2007-07-21

Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (<100 microm), whilst quantitative phase and attenuation information can be extracted using just two images when the approximations of geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser.

An interactive method based on the live wire for segmentation of the breast in mammography images.

PubMed

Zewei, Zhang; Tianyue, Wang; Li, Guo; Tingting, Wang; Lu, Xu

2014-01-01

In order to improve accuracy of computer-aided diagnosis of breast lumps, the authors introduce an improved interactive segmentation method based on Live Wire. This paper presents the Gabor filters and FCM clustering algorithm is introduced to the Live Wire cost function definition. According to the image FCM analysis for image edge enhancement, we eliminate the interference of weak edge and access external features clear segmentation results of breast lumps through improving Live Wire on two cases of breast segmentation data. Compared with the traditional method of image segmentation, experimental results show that the method achieves more accurate segmentation of breast lumps and provides more accurate objective basis on quantitative and qualitative analysis of breast lumps.

Accurate sparse-projection image reconstruction via nonlocal TV regularization.

PubMed

Zhang, Yi; Zhang, Weihua; Zhou, Jiliu

2014-01-01

Sparse-projection image reconstruction is a useful approach to lower the radiation dose; however, the incompleteness of projection data will cause degeneration of imaging quality. As a typical compressive sensing method, total variation has obtained great attention on this problem. Suffering from the theoretical imperfection, total variation will produce blocky effect on smooth regions and blur edges. To overcome this problem, in this paper, we introduce the nonlocal total variation into sparse-projection image reconstruction and formulate the minimization problem with new nonlocal total variation norm. The qualitative and quantitative analyses of numerical as well as clinical results demonstrate the validity of the proposed method. Comparing to other existing methods, our method more efficiently suppresses artifacts caused by low-rank reconstruction and reserves structure information better.

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

PubMed

Jenkins, Micah H; Gaylord, Thomas K

2015-10-01

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

Automatic motion correction for in vivo human skin optical coherence tomography angiography through combined rigid and nonrigid registration

NASA Astrophysics Data System (ADS)

Wei, David Wei; Deegan, Anthony J.; Wang, Ruikang K.

2017-06-01

When using optical coherence tomography angiography (OCTA), the development of artifacts due to involuntary movements can severely compromise the visualization and subsequent quantitation of tissue microvasculatures. To correct such an occurrence, we propose a motion compensation method to eliminate artifacts from human skin OCTA by means of step-by-step rigid affine registration, rigid subpixel registration, and nonrigid B-spline registration. To accommodate this remedial process, OCTA is conducted using two matching all-depth volume scans. Affine transformation is first performed on the large vessels of the deep reticular dermis, and then the resulting affine parameters are applied to all-depth vasculatures with a further subpixel registration to refine the alignment between superficial smaller vessels. Finally, the coregistration of both volumes is carried out to result in the final artifact-free composite image via an algorithm based upon cubic B-spline free-form deformation. We demonstrate that the proposed method can provide a considerable improvement to the final en face OCTA images with substantial artifact removal. In addition, the correlation coefficients and peak signal-to-noise ratios of the corrected images are evaluated and compared with those of the original images, further validating the effectiveness of the proposed method. We expect that the proposed method can be useful in improving qualitative and quantitative assessment of the OCTA images of scanned tissue beds.

Automatic motion correction for in vivo human skin optical coherence tomography angiography through combined rigid and nonrigid registration.

PubMed

Wei, David Wei; Deegan, Anthony J; Wang, Ruikang K

2017-06-01

When using optical coherence tomography angiography (OCTA), the development of artifacts due to involuntary movements can severely compromise the visualization and subsequent quantitation of tissue microvasculatures. To correct such an occurrence, we propose a motion compensation method to eliminate artifacts from human skin OCTA by means of step-by-step rigid affine registration, rigid subpixel registration, and nonrigid B-spline registration. To accommodate this remedial process, OCTA is conducted using two matching all-depth volume scans. Affine transformation is first performed on the large vessels of the deep reticular dermis, and then the resulting affine parameters are applied to all-depth vasculatures with a further subpixel registration to refine the alignment between superficial smaller vessels. Finally, the coregistration of both volumes is carried out to result in the final artifact-free composite image via an algorithm based upon cubic B-spline free-form deformation. We demonstrate that the proposed method can provide a considerable improvement to the final en face OCTA images with substantial artifact removal. In addition, the correlation coefficients and peak signal-to-noise ratios of the corrected images are evaluated and compared with those of the original images, further validating the effectiveness of the proposed method. We expect that the proposed method can be useful in improving qualitative and quantitative assessment of the OCTA images of scanned tissue beds.

An endoscopic diffuse optical tomographic method with high resolution based on the improved FOCUSS method

NASA Astrophysics Data System (ADS)

Qin, Zhuanping; Ma, Wenjuan; Ren, Shuyan; Geng, Liqing; Li, Jing; Yang, Ying; Qin, Yingmei

2017-02-01

Endoscopic DOT has the potential to apply to cancer-related imaging in tubular organs. Although the DOT has relatively large tissue penetration depth, the endoscopic DOT is limited by the narrow space of the internal tubular tissue, so as to the relatively small penetration depth. Because some adenocarcinomas including cervical adenocarcinoma are located in deep canal, it is necessary to improve the imaging resolution under the limited measurement condition. To improve the resolution, a new FOCUSS algorithm along with the image reconstruction algorithm based on the effective detection range (EDR) is developed. This algorithm is based on the region of interest (ROI) to reduce the dimensions of the matrix. The shrinking method cuts down the computation burden. To reduce the computational complexity, double conjugate gradient method is used in the matrix inversion. For a typical inner size and optical properties of the cervix-like tubular tissue, reconstructed images from the simulation data demonstrate that the proposed method achieves equivalent image quality to that obtained from the method based on EDR when the target is close the inner boundary of the model, and with higher spatial resolution and quantitative ratio when the targets are far from the inner boundary of the model. The quantitative ratio of reconstructed absorption and reduced scattering coefficient can be up to 70% and 80% under 5mm depth, respectively. Furthermore, the two close targets with different depths can be separated from each other. The proposed method will be useful to the development of endoscopic DOT technologies in tubular organs.

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Automated classification of cell morphology by coherence-controlled holographic microscopy

NASA Astrophysics Data System (ADS)

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity.

Automated classification of cell morphology by coherence-controlled holographic microscopy.

PubMed

Strbkova, Lenka; Zicha, Daniel; Vesely, Pavel; Chmelik, Radim

2017-08-01

In the last few years, classification of cells by machine learning has become frequently used in biology. However, most of the approaches are based on morphometric (MO) features, which are not quantitative in terms of cell mass. This may result in poor classification accuracy. Here, we study the potential contribution of coherence-controlled holographic microscopy enabling quantitative phase imaging for the classification of cell morphologies. We compare our approach with the commonly used method based on MO features. We tested both classification approaches in an experiment with nutritionally deprived cancer tissue cells, while employing several supervised machine learning algorithms. Most of the classifiers provided higher performance when quantitative phase features were employed. Based on the results, it can be concluded that the quantitative phase features played an important role in improving the performance of the classification. The methodology could be valuable help in refining the monitoring of live cells in an automated fashion. We believe that coherence-controlled holographic microscopy, as a tool for quantitative phase imaging, offers all preconditions for the accurate automated analysis of live cell behavior while enabling noninvasive label-free imaging with sufficient contrast and high-spatiotemporal phase sensitivity. (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

A New Approach to Image Fusion Based on Cokriging

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; LeMoigne, Jacqueline; Mount, David M.; Morisette, Jeffrey T.

2005-01-01

We consider the image fusion problem involving remotely sensed data. We introduce cokriging as a method to perform fusion. We investigate the advantages of fusing Hyperion with ALI. The evaluation is performed by comparing the classification of the fused data with that of input images and by calculating well-chosen quantitative fusion quality metrics. We consider the Invasive Species Forecasting System (ISFS) project as our fusion application. The fusion of ALI with Hyperion data is studies using PCA and wavelet-based fusion. We then propose utilizing a geostatistical based interpolation method called cokriging as a new approach for image fusion.

SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

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

Wahi-Anwar, M; Lo, P; Kim, H

Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifiesmore » the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel component to automatically verify image acquisition parameters and automated adherence to specifications. Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics; NIH Grant support from: U01 CA181156.« less

Medical imaging and computers in the diagnosis of breast cancer

NASA Astrophysics Data System (ADS)

Giger, Maryellen L.

2014-09-01

Computer-aided diagnosis (CAD) and quantitative image analysis (QIA) methods (i.e., computerized methods of analyzing digital breast images: mammograms, ultrasound, and magnetic resonance images) can yield novel image-based tumor and parenchyma characteristics (i.e., signatures that may ultimately contribute to the design of patient-specific breast cancer management plans). The role of QIA/CAD has been expanding beyond screening programs towards applications in risk assessment, diagnosis, prognosis, and response to therapy as well as in data mining to discover relationships of image-based lesion characteristics with genomics and other phenotypes; thus, as they apply to disease states. These various computer-based applications are demonstrated through research examples from the Giger Lab.

Advanced imaging of the macrostructure and microstructure of bone

NASA Technical Reports Server (NTRS)

Genant, H. K.; Gordon, C.; Jiang, Y.; Link, T. M.; Hans, D.; Majumdar, S.; Lang, T. F.

2000-01-01

Noninvasive and/or nondestructive techniques are capable of providing more macro- or microstructural information about bone than standard bone densitometry. Although the latter provides important information about osteoporotic fracture risk, numerous studies indicate that bone strength is only partially explained by bone mineral density. Quantitative assessment of macro- and microstructural features may improve our ability to estimate bone strength. The methods available for quantitatively assessing macrostructure include (besides conventional radiographs) quantitative computed tomography (QCT) and volumetric quantitative computed tomography (vQCT). Methods for assessing microstructure of trabecular bone noninvasively and/or nondestructively include high-resolution computed tomography (hrCT), micro-computed tomography (muCT), high-resolution magnetic resonance (hrMR), and micromagnetic resonance (muMR). vQCT, hrCT and hrMR are generally applicable in vivo; muCT and muMR are principally applicable in vitro. Although considerable progress has been made in the noninvasive and/or nondestructive imaging of the macro- and microstructure of bone, considerable challenges and dilemmas remain. From a technical perspective, the balance between spatial resolution versus sampling size, or between signal-to-noise versus radiation dose or acquisition time, needs further consideration, as do the trade-offs between the complexity and expense of equipment and the availability and accessibility of the methods. The relative merits of in vitro imaging and its ultrahigh resolution but invasiveness versus those of in vivo imaging and its modest resolution but noninvasiveness also deserve careful attention. From a clinical perspective, the challenges for bone imaging include balancing the relative advantages of simple bone densitometry against the more complex architectural features of bone or, similarly, the deeper research requirements against the broader clinical needs. The considerable potential biological differences between the peripheral appendicular skeleton and the central axial skeleton have to be addressed further. Finally, the relative merits of these sophisticated imaging techniques have to be weighed with respect to their applications as diagnostic procedures requiring high accuracy or reliability on one hand and their monitoring applications requiring high precision or reproducibility on the other. Copyright 2000 S. Karger AG, Basel.

Performing Quantitative Imaging Acquisition, Analysis and Visualization Using the Best of Open Source and Commercial Software Solutions.

PubMed

Shenoy, Shailesh M

2016-07-01

A challenge in any imaging laboratory, especially one that uses modern techniques, is to achieve a sustainable and productive balance between using open source and commercial software to perform quantitative image acquisition, analysis and visualization. In addition to considering the expense of software licensing, one must consider factors such as the quality and usefulness of the software's support, training and documentation. Also, one must consider the reproducibility with which multiple people generate results using the same software to perform the same analysis, how one may distribute their methods to the community using the software and the potential for achieving automation to improve productivity.

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.

Iron in Multiple Sclerosis and Its Noninvasive Imaging with Quantitative Susceptibility Mapping

PubMed Central

Stüber, Carsten; Pitt, David; Wang, Yi

2016-01-01

Iron is considered to play a key role in the development and progression of Multiple Sclerosis (MS). In particular, iron that accumulates in myeloid cells after the blood-brain barrier (BBB) seals may contribute to chronic inflammation, oxidative stress and eventually neurodegeneration. Magnetic resonance imaging (MRI) is a well-established tool for the non-invasive study of MS. In recent years, an advanced MRI method, quantitative susceptibility mapping (QSM), has made it possible to study brain iron through in vivo imaging. Moreover, immunohistochemical investigations have helped defining the lesional and cellular distribution of iron in MS brain tissue. Imaging studies in MS patients and of brain tissue combined with histological studies have provided important insights into the role of iron in inflammation and neurodegeneration in MS. PMID:26784172

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.

A Semi-Automatic Method for Image Analysis of Edge Dynamics in Living Cells

PubMed Central

Huang, Lawrence; Helmke, Brian P.

2011-01-01

Spatial asymmetry of actin edge ruffling contributes to the process of cell polarization and directional migration, but mechanisms by which external cues control actin polymerization near cell edges remain unclear. We designed a quantitative image analysis strategy to measure the spatiotemporal distribution of actin edge ruffling. Time-lapse images of endothelial cells (ECs) expressing mRFP-actin were segmented using an active contour method. In intensity line profiles oriented normal to the cell edge, peak detection identified the angular distribution of polymerized actin within 1 µm of the cell edge, which was localized to lamellipodia and edge ruffles. Edge features associated with filopodia and peripheral stress fibers were removed. Circular statistical analysis enabled detection of cell polarity, indicated by a unimodal distribution of edge ruffles. To demonstrate the approach, we detected a rapid, nondirectional increase in edge ruffling in serum-stimulated ECs and a change in constitutive ruffling orientation in quiescent, nonpolarized ECs. Error analysis using simulated test images demonstrate robustness of the method to variations in image noise levels, edge ruffle arc length, and edge intensity gradient. These quantitative measurements of edge ruffling dynamics enable investigation at the cellular length scale of the underlying molecular mechanisms regulating actin assembly and cell polarization. PMID:21643526

Image-derived arterial input function for quantitative fluorescence imaging of receptor-drug binding in vivo

PubMed Central

Elliott, Jonathan T.; Samkoe, Kimberley S.; Davis, Scott C.; Gunn, Jason R.; Paulsen, Keith D.; Roberts, David W.; Pogue, Brian W.

2017-01-01

Receptor concentration imaging (RCI) with targeted-untargeted optical dye pairs has enabled in vivo immunohistochemistry analysis in preclinical subcutaneous tumors. Successful application of RCI to fluorescence guided resection (FGR), so that quantitative molecular imaging of tumor-specific receptors could be performed in situ, would have a high impact. However, assumptions of pharmacokinetics, permeability and retention, as well as the lack of a suitable reference region limit the potential for RCI in human neurosurgery. In this study, an arterial input graphic analysis (AIGA) method is presented which is enabled by independent component analysis (ICA). The percent difference in arterial concentration between the image-derived arterial input function (AIFICA) and that obtained by an invasive method (ICACAR) was 2.0 ± 2.7% during the first hour of circulation of a targeted-untargeted dye pair in mice. Estimates of distribution volume and receptor concentration in tumor bearing mice (n = 5) recovered using the AIGA technique did not differ significantly from values obtained using invasive AIF measurements (p=0.12). The AIGA method, enabled by the subject-specific AIFICA, was also applied in a rat orthotopic model of U-251 glioblastoma to obtain the first reported receptor concentration and distribution volume maps during open craniotomy. PMID:26349671

Quantitative detection of the colloidal gold immunochromatographic strip in HSV color space

NASA Astrophysics Data System (ADS)

Wu, Yuanshu; Gao, Yueming; Du, Min

2014-09-01

In this paper, a fast, reliable and accurate quantitative detection method for the colloidal gold immunochromatographic strip(GICA) is presented. An image acquisition device which is mainly composed of annular LED source, zoom ratio lens, and 10bit CMOS image sensors with 54.5dB SNR is designed for the detection. Firstly, the test line is extracted from the strip window through using the H component peak points of the HSV space as the clustering centers via the Fuzzy C-Means(FCM) clustering method. Then, a two dimensional eigenvalue composed with the hue(H) and saturation(S) of HSV space was proposed to improve the accuracy of the quantitative detection. At last, the experiment of human chorionic gonadotropin(HCG) with the concentration range 0-500mIU/mL is carried out. The results show that the linear correlation coefficient between this method and optical density(OD) values measured by the fiber optical sensor reach 96.74%. Meanwhile, the linearity of fitting curve constructed with concentration was greater than 95.00%.

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

PubMed

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

2017-06-01

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

A method for rapid quantitative assessment of biofilms with biomolecular staining and image analysis.

PubMed

Larimer, Curtis; Winder, Eric; Jeters, Robert; Prowant, Matthew; Nettleship, Ian; Addleman, Raymond Shane; Bonheyo, George T

2016-01-01

The accumulation of bacteria in surface-attached biofilms can be detrimental to human health, dental hygiene, and many industrial processes. Natural biofilms are soft and often transparent, and they have heterogeneous biological composition and structure over micro- and macroscales. As a result, it is challenging to quantify the spatial distribution and overall intensity of biofilms. In this work, a new method was developed to enhance the visibility and quantification of bacterial biofilms. First, broad-spectrum biomolecular staining was used to enhance the visibility of the cells, nucleic acids, and proteins that make up biofilms. Then, an image analysis algorithm was developed to objectively and quantitatively measure biofilm accumulation from digital photographs and results were compared to independent measurements of cell density. This new method was used to quantify the growth intensity of Pseudomonas putida biofilms as they grew over time. This method is simple and fast, and can quantify biofilm growth over a large area with approximately the same precision as the more laborious cell counting method. Stained and processed images facilitate assessment of spatial heterogeneity of a biofilm across a surface. This new approach to biofilm analysis could be applied in studies of natural, industrial, and environmental biofilms.

Correlated ion and neutral time of flight technique combined with velocity map imaging: Quantitative measurements for dissociation processes in excited molecular nano-systems

NASA Astrophysics Data System (ADS)

Berthias, F.; Feketeová, L.; Della Negra, R.; Dupasquier, T.; Fillol, R.; Abdoul-Carime, H.; Farizon, B.; Farizon, M.; Märk, T. D.

2018-01-01

The combination of the Dispositif d'Irradiation d'Agrégats Moléculaire with the correlated ion and neutral time of flight-velocity map imaging technique provides a new way to explore processes occurring subsequent to the excitation of charged nano-systems. The present contribution describes in detail the methods developed for the quantitative measurement of branching ratios and cross sections for collision-induced dissociation processes of water cluster nano-systems. These methods are based on measurements of the detection efficiency of neutral fragments produced in these dissociation reactions. Moreover, measured detection efficiencies are used here to extract the number of neutral fragments produced for a given charged fragment.

Quantitative analysis of MRI-guided attenuation correction techniques in time-of-flight brain PET/MRI.

PubMed

Mehranian, Abolfazl; Arabi, Hossein; Zaidi, Habib

2016-04-15

In quantitative PET/MR imaging, attenuation correction (AC) of PET data is markedly challenged by the need of deriving accurate attenuation maps from MR images. A number of strategies have been developed for MRI-guided attenuation correction with different degrees of success. In this work, we compare the quantitative performance of three generic AC methods, including standard 3-class MR segmentation-based, advanced atlas-registration-based and emission-based approaches in the context of brain time-of-flight (TOF) PET/MRI. Fourteen patients referred for diagnostic MRI and (18)F-FDG PET/CT brain scans were included in this comparative study. For each study, PET images were reconstructed using four different attenuation maps derived from CT-based AC (CTAC) serving as reference, standard 3-class MR-segmentation, atlas-registration and emission-based AC methods. To generate 3-class attenuation maps, T1-weighted MRI images were segmented into background air, fat and soft-tissue classes followed by assignment of constant linear attenuation coefficients of 0, 0.0864 and 0.0975 cm(-1) to each class, respectively. A robust atlas-registration based AC method was developed for pseudo-CT generation using local weighted fusion of atlases based on their morphological similarity to target MR images. Our recently proposed MRI-guided maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm was employed to estimate the attenuation map from TOF emission data. The performance of the different AC algorithms in terms of prediction of bones and quantification of PET tracer uptake was objectively evaluated with respect to reference CTAC maps and CTAC-PET images. Qualitative evaluation showed that the MLAA-AC method could sparsely estimate bones and accurately differentiate them from air cavities. It was found that the atlas-AC method can accurately predict bones with variable errors in defining air cavities. Quantitative assessment of bone extraction accuracy based on Dice similarity coefficient (DSC) showed that MLAA-AC and atlas-AC resulted in DSC mean values of 0.79 and 0.92, respectively, in all patients. The MLAA-AC and atlas-AC methods predicted mean linear attenuation coefficients of 0.107 and 0.134 cm(-1), respectively, for the skull compared to reference CTAC mean value of 0.138cm(-1). The evaluation of the relative change in tracer uptake within 32 distinct regions of the brain with respect to CTAC PET images showed that the 3-class MRAC, MLAA-AC and atlas-AC methods resulted in quantification errors of -16.2 ± 3.6%, -13.3 ± 3.3% and 1.0 ± 3.4%, respectively. Linear regression and Bland-Altman concordance plots showed that both 3-class MRAC and MLAA-AC methods result in a significant systematic bias in PET tracer uptake, while the atlas-AC method results in a negligible bias. The standard 3-class MRAC method significantly underestimated cerebral PET tracer uptake. While current state-of-the-art MLAA-AC methods look promising, they were unable to noticeably reduce quantification errors in the context of brain imaging. Conversely, the proposed atlas-AC method provided the most accurate attenuation maps, and thus the lowest quantification bias. Copyright © 2016 Elsevier Inc. All rights reserved.

[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.

Examination of a Method to Determine the Reference Region for Calculating the Specific Binding Ratio in Dopamine Transporter Imaging.

PubMed

Watanabe, Ayumi; Inoue, Yusuke; Asano, Yuji; Kikuchi, Kei; Miyatake, Hiroki; Tokushige, Takanobu

2017-01-01

The specific binding ratio (SBR) was first reported by Tossici-Bolt et al. for quantitative indicators for dopamine transporter (DAT) imaging. It is defined as the ratio of the specific binding concentration of the striatum to the non-specific binding concentration of the whole brain other than the striatum. The non-specific binding concentration is calculated based on the region of interest (ROI), which is set 20 mm inside the outer contour, defined by a threshold technique. Tossici-Bolt et al. used a 50% threshold, but sometimes we couldn't define the ROI of non-specific binding concentration (reference region) and calculate SBR appropriately with a 50% threshold. Therefore, we sought a new method for determining the reference region when calculating SBR. We used data from 20 patients who had undergone DAT imaging in our hospital, to calculate the non-specific binding concentration by the following methods, the threshold to define a reference region was fixed at some specific values (the fixing method) and reference region was visually optimized by an examiner at every examination (the visual optimization method). First, we assessed the reference region of each method visually, and afterward, we quantitatively compared SBR calculated based on each method. In the visual assessment, the scores of the fixing method at 30% and visual optimization method were higher than the scores of the fixing method at other values, with or without scatter correction. In the quantitative assessment, the SBR obtained by visual optimization of the reference region, based on consensus of three radiological technologists, was used as a baseline (the standard method). The values of SBR showed good agreement between the standard method and both the fixing method at 30% and the visual optimization method, with or without scatter correction. Therefore, the fixing method at 30% and the visual optimization method were equally suitable for determining the reference region.

Image processing methods for quantitatively detecting soybean rust from multispectral images

USDA-ARS?s Scientific Manuscript database

Soybean rust, caused by Phakopsora pachyrhizi, is one of the most destructive diseases for soybean production. It often causes significant yield loss and may rapidly spread from field to field through airborne urediniospores. In order to implement timely fungicide treatments for the most effective c...

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

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

Szczykutowicz, T; Rubert, N; Ranallo, F

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specificmore » anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework avoids use of the overall “look” or “feel” to dictate acquisition parameter selection. Equipment grants GE Healthcare.« less

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

PubMed Central

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

2011-01-01

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

Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology.

PubMed

Morawski, Markus; Kirilina, Evgeniya; Scherf, Nico; Jäger, Carsten; Reimann, Katja; Trampel, Robert; Gavriilidis, Filippos; Geyer, Stefan; Biedermann, Bernd; Arendt, Thomas; Weiskopf, Nikolaus

2017-11-28

Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

[Cardiac Synchronization Function Estimation Based on ASM Level Set Segmentation Method].

PubMed

Zhang, Yaonan; Gao, Yuan; Tang, Liang; He, Ying; Zhang, Huie

At present, there is no accurate and quantitative methods for the determination of cardiac mechanical synchronism, and quantitative determination of the synchronization function of the four cardiac cavities with medical images has a great clinical value. This paper uses the whole heart ultrasound image sequence, and segments the left & right atriums and left & right ventricles of each frame. After the segmentation, the number of pixels in each cavity and in each frame is recorded, and the areas of the four cavities of the image sequence are therefore obtained. The area change curves of the four cavities are further extracted, and the synchronous information of the four cavities is obtained. Because of the low SNR of Ultrasound images, the boundary lines of cardiac cavities are vague, so the extraction of cardiac contours is still a challenging problem. Therefore, the ASM model information is added to the traditional level set method to force the curve evolution process. According to the experimental results, the improved method improves the accuracy of the segmentation. Furthermore, based on the ventricular segmentation, the right and left ventricular systolic functions are evaluated, mainly according to the area changes. The synchronization of the four cavities of the heart is estimated based on the area changes and the volume changes.

Thermal image analysis using the serpentine method

NASA Astrophysics Data System (ADS)

Koprowski, Robert; Wilczyński, Sławomir

2018-03-01

Thermal imaging is an increasingly widespread alternative to other imaging methods. As a supplementary method in diagnostics, it can be used both statically and with dynamic temperature changes. The paper proposes a new image analysis method that allows for the acquisition of new diagnostic information as well as object segmentation. The proposed serpentine analysis uses known and new methods of image analysis and processing proposed by the authors. Affine transformations of an image and subsequent Fourier analysis provide a new diagnostic quality. The method is fully repeatable and automatic and independent of inter-individual variability in patients. The segmentation results are by 10% better than those obtained from the watershed method and the hybrid segmentation method based on the Canny detector. The first and second harmonics of serpentine analysis enable to determine the type of temperature changes in the region of interest (gradient, number of heat sources etc.). The presented serpentine method provides new quantitative information on thermal imaging and more. Since it allows for image segmentation and designation of contact points of two and more heat sources (local minimum), it can be used to support medical diagnostics in many areas of medicine.

3D quantitative photoacoustic image reconstruction using Monte Carlo method and linearization

NASA Astrophysics Data System (ADS)

Okawa, Shinpei; Hirasawa, Takeshi; Tsujita, Kazuhiro; Kushibiki, Toshihiro; Ishihara, Miya

2018-02-01

To quantify the functional and structural information of peripheral blood vessels for diagnoses of diseases which affects peripheral blood vessels such as diabetes and peripheral vascular disease, a 3D quantitative photoacoustic tomography (QPAT) reconstructing the optical properties such as the absorption coefficient reflecting microvascular structures and hemoglobin concentration and oxygenation saturation is studied. QPAT image reconstruction algorithms based on radiative transfer equation (RTE) and photon diffusion equation (PDE) have been proposed. However, it is not easy to use RTE in the clinical practice because of the huge computational load and long calculation time. On the other hand, it is always considered problematic to use PDE, because it does not approximate RTE well near the illuminating position. In this study, we developed the 3D QPAT image reconstruction using Monte Carlo (MC) method which approximates RTE better than PDE to reconstruct the optical properties in the region near the illuminating surface. To reduce the calculation time, we applied linearization. The QPAT image reconstruction algorithm with MC method and linearization was examined in numerical simulations and phantom experiment by use of a scanning system with a single probe consisting of P(VDF-TrFE) piezo electric film and optical fiber.

Quantitative reconstruction of refractive index distribution and imaging of glucose concentration by using diffusing light.

PubMed

Liang, Xiaoping; Zhang, Qizhi; Jiang, Huabei

2006-11-10

We show that a two-step reconstruction method can be adapted to improve the quantitative accuracy of the refractive index reconstruction in phase-contrast diffuse optical tomography (PCDOT). We also describe the possibility of imaging tissue glucose concentration with PCDOT. In this two-step method, we first use our existing finite-element reconstruction algorithm to recover the position and shape of a target. We then use the position and size of the target as a priori information to reconstruct a single value of the refractive index within the target and background regions using a region reconstruction method. Due to the extremely low contrast available in the refractive index reconstruction, we incorporate a data normalization scheme into the two-step reconstruction to combat the associated low signal-to-noise ratio. Through a series of phantom experiments we find that this two-step reconstruction method can considerably improve the quantitative accuracy of the refractive index reconstruction. The results show that the relative error of the reconstructed refractive index is reduced from 20% to within 1.5%. We also demonstrate the possibility of PCDOT for recovering glucose concentration using these phantom experiments.

Digital pathology and image analysis for robust high-throughput quantitative assessment of Alzheimer disease neuropathologic changes.

PubMed

Neltner, Janna Hackett; Abner, Erin Lynn; Schmitt, Frederick A; Denison, Stephanie Kay; Anderson, Sonya; Patel, Ela; Nelson, Peter T

2012-12-01

Quantitative neuropathologic methods provide information that is important for both research and clinical applications. The technologic advancement of digital pathology and image analysis offers new solutions to enable valid quantification of pathologic severity that is reproducible between raters regardless of experience. Using an Aperio ScanScope XT and its accompanying image analysis software, we designed algorithms for quantitation of amyloid and tau pathologies on 65 β-amyloid (6F/3D antibody) and 48 phospho-tau (PHF-1)-immunostained sections of human temporal neocortex. Quantitative digital pathologic data were compared with manual pathology counts. There were excellent correlations between manually counted and digitally analyzed neuropathologic parameters (R² = 0.56-0.72). Data were highly reproducible among 3 participants with varying degrees of expertise in neuropathology (intraclass correlation coefficient values, >0.910). Digital quantification also provided additional parameters, including average plaque area, which shows statistically significant differences when samples are stratified according to apolipoprotein E allele status (average plaque area, 380.9 μm² in apolipoprotein E [Latin Small Letter Open E]4 carriers vs 274.4 μm² for noncarriers; p < 0.001). Thus, digital pathology offers a rigorous and reproducible method for quantifying Alzheimer disease neuropathologic changes and may provide additional insights into morphologic characteristics that were previously more challenging to assess because of technical limitations.

Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method.

PubMed

Sun, Hongfu; Ma, Yuhan; MacDonald, M Ethan; Pike, G Bruce

2018-06-15

A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods. Copyright © 2018 Elsevier Inc. All rights reserved.